tangyx/MetaQA_3entities · Datasets at Hugging Face

data_source stringclasses 1 value	prompt stringlengths 1.1k 13.9k	ability stringclasses 1 value	reward_model dict	extra_info dict
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 33637, 1959 35845, 2006 27261, 2009 8198, A PRAIRIE HOME COMPANION 22517, A SERIOUS MAN 6283, CARGO 25011, CHILDREN OF GLORY 40097, DARK COMEDY 24943, ETHAN COEN 21123, FARGO 18223, MINNESOTA 4078, NIGHT OF THE GHOULS 32482, NIGHT TRAIN 38358, OBSERVE AND REPORT 26258, PARIS, JE T'AIME 3942, SALVAGE 38498, TAXIDERMIA src, edge_attr, dst 8198, has_tags, 18223 8198, release_year, 35845 22517, directed_by, 24943 22517, has_tags, 40097 22517, has_tags, 24943 22517, has_tags, 18223 22517, release_year, 27261 22517, written_by, 24943 6283, release_year, 35845 6283, release_year, 27261 25011, release_year, 35845 21123, directed_by, 24943 21123, has_tags, 40097 21123, has_tags, 18223 21123, written_by, 24943 4078, release_year, 33637 32482, release_year, 33637 32482, release_year, 27261 38358, has_tags, 40097 38358, release_year, 27261 26258, directed_by, 24943 26258, release_year, 35845 26258, written_by, 24943 3942, release_year, 35845 3942, release_year, 27261 38498, has_tags, 40097 38498, release_year, 35845 Question: How are A SERIOUS MAN, CHILDREN OF GLORY, and NIGHT OF THE GHOULS related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "A SERIOUS MAN", "CHILDREN OF GLORY", "NIGHT OF THE GHOULS" ], "valid_edges": [ [ "A PRAIRIE HOME COMPANION", "has_tags", "MINNESOTA" ], [ "A PRAIRIE HOME COMPANION", "release_year", "2006" ], [ "A SERIOUS MAN", "directed_by", "ETHAN COEN" ], [ "A SERIOUS MAN", "has_tags", "DARK COMEDY" ], [ "A SERIOUS MAN", "has_tags", "ETHAN COEN" ], [ "A SERIOUS MAN", "has_tags", "MINNESOTA" ], [ "A SERIOUS MAN", "release_year", "2009" ], [ "A SERIOUS MAN", "written_by", "ETHAN COEN" ], [ "CARGO", "release_year", "2006" ], [ "CARGO", "release_year", "2009" ], [ "CHILDREN OF GLORY", "release_year", "2006" ], [ "FARGO", "directed_by", "ETHAN COEN" ], [ "FARGO", "has_tags", "DARK COMEDY" ], [ "FARGO", "has_tags", "MINNESOTA" ], [ "FARGO", "written_by", "ETHAN COEN" ], [ "NIGHT OF THE GHOULS", "release_year", "1959" ], [ "NIGHT TRAIN", "release_year", "1959" ], [ "NIGHT TRAIN", "release_year", "2009" ], [ "OBSERVE AND REPORT", "has_tags", "DARK COMEDY" ], [ "OBSERVE AND REPORT", "release_year", "2009" ], [ "PARIS, JE T'AIME", "directed_by", "ETHAN COEN" ], [ "PARIS, JE T'AIME", "release_year", "2006" ], [ "PARIS, JE T'AIME", "written_by", "ETHAN COEN" ], [ "SALVAGE", "release_year", "2006" ], [ "SALVAGE", "release_year", "2009" ], [ "TAXIDERMIA", "has_tags", "DARK COMEDY" ], [ "TAXIDERMIA", "release_year", "2006" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3384, 1935 38258, BRIGHT LIGHTS 230, CARNIVAL IN FLANDERS 30463, COMEDY 6012, FRENCH 22175, I'M REED FISH 14601, LES MISÉRABLES 11142, LUCREZIA BORGIA 30602, PRINCESSE TAM-TAM 25591, THE TRIPLETS OF BELLEVILLE 19429, TONI 1796, ZACKARY ADLER src, edge_attr, dst 38258, release_year, 3384 230, has_genre, 30463 230, in_language, 6012 230, release_year, 3384 22175, directed_by, 1796 22175, has_genre, 30463 22175, written_by, 1796 14601, in_language, 6012 14601, release_year, 3384 11142, in_language, 6012 11142, release_year, 3384 30602, in_language, 6012 30602, release_year, 3384 25591, has_genre, 30463 25591, has_tags, 6012 25591, in_language, 6012 19429, in_language, 6012 19429, release_year, 3384 Question: In what context are BRIGHT LIGHTS, THE TRIPLETS OF BELLEVILLE, and ZACKARY ADLER connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BRIGHT LIGHTS", "THE TRIPLETS OF BELLEVILLE", "ZACKARY ADLER" ], "valid_edges": [ [ "BRIGHT LIGHTS", "release_year", "1935" ], [ "CARNIVAL IN FLANDERS", "has_genre", "COMEDY" ], [ "CARNIVAL IN FLANDERS", "in_language", "FRENCH" ], [ "CARNIVAL IN FLANDERS", "release_year", "1935" ], [ "I'M REED FISH", "directed_by", "ZACKARY ADLER" ], [ "I'M REED FISH", "has_genre", "COMEDY" ], [ "I'M REED FISH", "written_by", "ZACKARY ADLER" ], [ "LES MISÉRABLES", "in_language", "FRENCH" ], [ "LES MISÉRABLES", "release_year", "1935" ], [ "LUCREZIA BORGIA", "in_language", "FRENCH" ], [ "LUCREZIA BORGIA", "release_year", "1935" ], [ "PRINCESSE TAM-TAM", "in_language", "FRENCH" ], [ "PRINCESSE TAM-TAM", "release_year", "1935" ], [ "THE TRIPLETS OF BELLEVILLE", "has_genre", "COMEDY" ], [ "THE TRIPLETS OF BELLEVILLE", "has_tags", "FRENCH" ], [ "THE TRIPLETS OF BELLEVILLE", "in_language", "FRENCH" ], [ "TONI", "in_language", "FRENCH" ], [ "TONI", "release_year", "1935" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 19721, 300 24716, 40 GUNS TO APACHE PASS 25570, BEAUTY AND THE BEAST 36066, FANTASY 6012, FRENCH 31172, KING 14181, ROGER ALLERS 36026, WESTERN src, edge_attr, dst 19721, has_genre, 36066 19721, has_tags, 31172 24716, has_genre, 36026 25570, has_genre, 36066 25570, has_tags, 36066 25570, in_language, 6012 25570, written_by, 14181 36026, in_language, 6012 Question: For what reason are 40 GUNS TO APACHE PASS, KING, and ROGER ALLERS associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "40 GUNS TO APACHE PASS", "KING", "ROGER ALLERS" ], "valid_edges": [ [ "300", "has_genre", "FANTASY" ], [ "300", "has_tags", "KING" ], [ "40 GUNS TO APACHE PASS", "has_genre", "WESTERN" ], [ "BEAUTY AND THE BEAST", "has_genre", "FANTASY" ], [ "BEAUTY AND THE BEAST", "has_tags", "FANTASY" ], [ "BEAUTY AND THE BEAST", "in_language", "FRENCH" ], [ "BEAUTY AND THE BEAST", "written_by", "ROGER ALLERS" ], [ "WESTERN", "in_language", "FRENCH" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37484, 2004 2043, 9 SONGS 5321, A GOOD WOMAN 38203, A HOLE IN MY HEART 20026, A HOME AT THE END OF THE WORLD 5441, A LOVE SONG FOR BOBBY LONG 11398, A MOMENT TO REMEMBER 20576, A WORLD WITHOUT THIEVES 27020, AGAINST THE ROPES 1698, ALFIE 34789, BAD EDUCATION 18380, BEFORE SUNSET 1815, BEFORE THE FALL 2137, BEING JULIA 20294, BIRTH 2856, BROTHERS 20489, CHANGING TIMES 30885, CLOSER 10272, CONFESSIONS OF A TEENAGE DRAMA QUEEN 32049, CRASH 34180, CRUEL INTENTIONS 3 15696, DAY AND NIGHT 27982, DEAR FRANKIE 16961, DIRTY FILTHY LOVE 15779, DORIAN BLUES 1441, DOWN TO THE BONE 36212, DRAMA 1329, ENVY 5924, EROS 15635, ETHAN MAO 5501, EVERYDAY PEOPLE 32706, FIRST LOVE 15080, FLIGHT OF THE PHOENIX 13263, FREEZE FRAME 3175, FRIDAY NIGHT LIGHTS 21640, GARDEN STATE 16914, GILLES' WIFE 28999, GREG SPOTTISWOOD 17567, HARRY + MAX 9621, HAWAII, OSLO 23477, HAWKING 4840, HEAD IN THE CLOUDS 1044, HOTEL RWANDA 20303, HOUSE OF D 8377, ICE MEN 6753, IMAGINARY HEROES 38426, IRON JAWED ANGELS 21861, JERSEY GIRL 8849, KEANE 34731, KINSEY 926, LADDER 49 30600, LADIES IN LAVENDER 37237, LAND OF PLENTY 5251, LIGHTNING BUG 9188, LIGHTNING STRIKES TWICE 11689, LOOK AT ME 12292, MARIE AND BRUCE 20283, MEAN CREEK 831, MELINDA AND MELINDA 33998, MICKEY 28532, MILLION DOLLAR BABY 13143, MILLIONS 4168, MIRACLE 34674, MY SUMMER OF LOVE 26817, MYSTERIOUS SKIN 20433, NEW POLICE STORY 25709, NOBODY KNOWS 37353, NOEL 4132, OMAGH 11031, OUT OF REACH 13268, OYSTER FARMER 29275, P.S. 28047, PALINDROMES 12683, PRIMER 35167, PRIVATE 28125, RAINCOAT 5693, RAISING HELEN 33617, RED DUST 31114, SAINT RALPH 11313, SAVED! 2135, SAVING FACE 12902, SHE HATE ME 36797, SIDEWAYS 12464, SILVER CITY 32387, SIMON 7717, SPANGLISH 10978, STAGE BEAUTY 8374, STRIP SEARCH 24987, SUMMER STORM 6439, THE AVIATOR 16499, THE BEAUTIFUL COUNTRY 5686, THE BRIDGE OF SAN LUIS REY 33022, THE CHORUS 18130, THE CLEARING 21465, THE DOOR IN THE FLOOR 19685, THE FINAL CUT 15429, THE FORGOTTEN 14807, THE GOODBYE GIRL 38765, THE HOLY GIRL 8435, THE KEYS TO THE HOUSE 11711, THE LIBERTINE 28217, THE LIFE AQUATIC WITH STEVE ZISSOU 36024, THE LIZARD 38433, THE MERCHANT OF VENICE 11555, THE NOTEBOOK 34751, THE PASSION OF THE CHRIST 7537, THE RETURNED 15768, THE TERMINAL 25426, THE WOODSMAN 16413, TROPICAL MALADY 29947, TURTLES CAN FLY 32733, VANITY FAIR 7577, VEER-ZAARA 22949, VERA DRAKE 37859, WE DON'T LIVE HERE ANYMORE 21897, WHEN WILL I BE LOVED 7055, WICKER PARK 18720, WILBY WONDERFUL 32096, WILD SIDE 7208, WINTER SOLSTICE src, edge_attr, dst 2043, has_genre, 36212 2043, release_year, 37484 5321, has_genre, 36212 5321, release_year, 37484 38203, has_genre, 36212 38203, release_year, 37484 20026, has_genre, 36212 20026, release_year, 37484 5441, has_genre, 36212 5441, release_year, 37484 11398, has_genre, 36212 11398, release_year, 37484 20576, has_genre, 36212 20576, release_year, 37484 27020, has_genre, 36212 27020, release_year, 37484 1698, has_genre, 36212 1698, release_year, 37484 34789, has_genre, 36212 34789, has_tags, 36212 34789, release_year, 37484 18380, has_genre, 36212 18380, release_year, 37484 1815, has_genre, 36212 1815, release_year, 37484 2137, has_genre, 36212 2137, release_year, 37484 20294, has_genre, 36212 20294, release_year, 37484 2856, has_genre, 36212 2856, release_year, 37484 20489, has_genre, 36212 20489, release_year, 37484 30885, has_genre, 36212 30885, has_tags, 36212 30885, release_year, 37484 10272, has_tags, 36212 10272, release_year, 37484 32049, has_genre, 36212 32049, release_year, 37484 34180, has_genre, 36212 34180, release_year, 37484 15696, has_genre, 36212 15696, has_tags, 36212 15696, release_year, 37484 27982, has_genre, 36212 27982, release_year, 37484 16961, has_genre, 36212 16961, release_year, 37484 15779, has_genre, 36212 15779, release_year, 37484 1441, has_genre, 36212 1441, release_year, 37484 1329, has_genre, 36212 1329, release_year, 37484 5924, has_genre, 36212 5924, release_year, 37484 15635, has_genre, 36212 15635, release_year, 37484 5501, has_genre, 36212 5501, release_year, 37484 32706, has_genre, 36212 32706, release_year, 37484 15080, has_genre, 36212 15080, release_year, 37484 13263, has_genre, 36212 13263, release_year, 37484 3175, has_genre, 36212 3175, has_tags, 36212 3175, release_year, 37484 21640, has_genre, 36212 21640, release_year, 37484 16914, has_genre, 36212 16914, release_year, 37484 17567, has_genre, 36212 17567, release_year, 37484 9621, has_genre, 36212 9621, release_year, 37484 23477, has_genre, 36212 23477, release_year, 37484 4840, has_genre, 36212 4840, release_year, 37484 1044, has_genre, 36212 1044, has_tags, 36212 1044, release_year, 37484 20303, has_genre, 36212 20303, release_year, 37484 8377, release_year, 37484 8377, starred_actors, 28999 6753, has_genre, 36212 6753, release_year, 37484 38426, has_genre, 36212 38426, release_year, 37484 21861, has_genre, 36212 21861, has_tags, 36212 21861, release_year, 37484 8849, has_genre, 36212 8849, release_year, 37484 34731, has_genre, 36212 34731, release_year, 37484 926, has_genre, 36212 926, release_year, 37484 30600, has_genre, 36212 30600, release_year, 37484 37237, has_genre, 36212 37237, release_year, 37484 5251, has_genre, 36212 5251, release_year, 37484 9188, has_genre, 36212 11689, has_genre, 36212 11689, release_year, 37484 12292, has_genre, 36212 12292, release_year, 37484 20283, has_genre, 36212 20283, has_tags, 36212 20283, release_year, 37484 831, has_genre, 36212 831, release_year, 37484 33998, has_genre, 36212 33998, release_year, 37484 28532, has_genre, 36212 28532, has_tags, 36212 28532, release_year, 37484 13143, has_genre, 36212 13143, release_year, 37484 4168, has_genre, 36212 4168, release_year, 37484 34674, has_genre, 36212 34674, has_tags, 36212 34674, release_year, 37484 26817, has_genre, 36212 26817, release_year, 37484 20433, has_genre, 36212 20433, release_year, 37484 25709, has_genre, 36212 25709, release_year, 37484 37353, has_genre, 36212 37353, has_tags, 36212 37353, release_year, 37484 4132, has_genre, 36212 4132, release_year, 37484 11031, has_genre, 36212 11031, release_year, 37484 13268, has_genre, 36212 13268, release_year, 37484 29275, has_genre, 36212 29275, release_year, 37484 28047, has_genre, 36212 28047, release_year, 37484 12683, has_genre, 36212 12683, release_year, 37484 35167, has_genre, 36212 35167, release_year, 37484 28125, has_genre, 36212 28125, release_year, 37484 5693, has_genre, 36212 5693, release_year, 37484 33617, has_genre, 36212 33617, release_year, 37484 31114, has_genre, 36212 31114, release_year, 37484 11313, has_genre, 36212 11313, release_year, 37484 2135, has_genre, 36212 2135, release_year, 37484 12902, has_genre, 36212 12902, release_year, 37484 36797, has_genre, 36212 36797, release_year, 37484 12464, has_genre, 36212 12464, release_year, 37484 32387, has_genre, 36212 32387, release_year, 37484 7717, has_genre, 36212 7717, release_year, 37484 10978, has_genre, 36212 10978, release_year, 37484 8374, has_genre, 36212 8374, release_year, 37484 24987, has_genre, 36212 24987, release_year, 37484 6439, has_genre, 36212 6439, has_tags, 36212 6439, release_year, 37484 16499, has_genre, 36212 16499, has_tags, 36212 16499, release_year, 37484 5686, has_genre, 36212 5686, release_year, 37484 33022, has_genre, 36212 33022, has_tags, 36212 33022, release_year, 37484 18130, has_genre, 36212 18130, release_year, 37484 21465, has_genre, 36212 21465, has_tags, 36212 21465, release_year, 37484 19685, has_genre, 36212 19685, release_year, 37484 15429, has_genre, 36212 15429, release_year, 37484 14807, has_genre, 36212 14807, release_year, 37484 38765, has_genre, 36212 38765, release_year, 37484 8435, has_genre, 36212 8435, release_year, 37484 11711, has_genre, 36212 11711, release_year, 37484 28217, has_genre, 36212 28217, release_year, 37484 36024, has_genre, 36212 36024, release_year, 37484 38433, has_genre, 36212 38433, release_year, 37484 11555, has_genre, 36212 11555, release_year, 37484 34751, has_genre, 36212 34751, release_year, 37484 7537, has_genre, 36212 7537, release_year, 37484 15768, has_genre, 36212 15768, has_tags, 36212 15768, release_year, 37484 25426, has_genre, 36212 25426, has_tags, 36212 25426, release_year, 37484 16413, has_genre, 36212 16413, release_year, 37484 29947, has_genre, 36212 29947, release_year, 37484 32733, has_genre, 36212 32733, release_year, 37484 7577, has_genre, 36212 7577, release_year, 37484 22949, has_genre, 36212 22949, release_year, 37484 37859, has_genre, 36212 37859, release_year, 37484 21897, has_genre, 36212 21897, release_year, 37484 7055, has_genre, 36212 7055, release_year, 37484 18720, has_genre, 36212 18720, release_year, 37484 32096, has_genre, 36212 32096, release_year, 37484 7208, has_genre, 36212 7208, release_year, 37484 Question: For what reason are EVERYDAY PEOPLE, GREG SPOTTISWOOD, and LIGHTNING STRIKES TWICE associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "EVERYDAY PEOPLE", "GREG SPOTTISWOOD", "LIGHTNING STRIKES TWICE" ], "valid_edges": [ [ "9 SONGS", "has_genre", "DRAMA" ], [ "9 SONGS", "release_year", "2004" ], [ "A GOOD WOMAN", "has_genre", "DRAMA" ], [ "A GOOD WOMAN", "release_year", "2004" ], [ "A HOLE IN MY HEART", "has_genre", "DRAMA" ], [ "A HOLE IN MY HEART", "release_year", "2004" ], [ "A HOME AT THE END OF THE WORLD", "has_genre", "DRAMA" ], [ "A HOME AT THE END OF THE WORLD", "release_year", "2004" ], [ "A LOVE SONG FOR BOBBY LONG", "has_genre", "DRAMA" ], [ "A LOVE SONG FOR BOBBY LONG", "release_year", "2004" ], [ "A MOMENT TO REMEMBER", "has_genre", "DRAMA" ], [ "A MOMENT TO REMEMBER", "release_year", "2004" ], [ "A WORLD WITHOUT THIEVES", "has_genre", "DRAMA" ], [ "A WORLD WITHOUT THIEVES", "release_year", "2004" ], [ "AGAINST THE ROPES", "has_genre", "DRAMA" ], [ "AGAINST THE ROPES", "release_year", "2004" ], [ "ALFIE", "has_genre", "DRAMA" ], [ "ALFIE", "release_year", "2004" ], [ "BAD EDUCATION", "has_genre", "DRAMA" ], [ "BAD EDUCATION", "has_tags", "DRAMA" ], [ "BAD EDUCATION", "release_year", "2004" ], [ "BEFORE SUNSET", "has_genre", "DRAMA" ], [ "BEFORE SUNSET", "release_year", "2004" ], [ "BEFORE THE FALL", "has_genre", "DRAMA" ], [ "BEFORE THE FALL", "release_year", "2004" ], [ "BEING JULIA", "has_genre", "DRAMA" ], [ "BEING JULIA", "release_year", "2004" ], [ "BIRTH", "has_genre", "DRAMA" ], [ "BIRTH", "release_year", "2004" ], [ "BROTHERS", "has_genre", "DRAMA" ], [ "BROTHERS", "release_year", "2004" ], [ "CHANGING TIMES", "has_genre", "DRAMA" ], [ "CHANGING TIMES", "release_year", "2004" ], [ "CLOSER", "has_genre", "DRAMA" ], [ "CLOSER", "has_tags", "DRAMA" ], [ "CLOSER", "release_year", "2004" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_tags", "DRAMA" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "release_year", "2004" ], [ "CRASH", "has_genre", "DRAMA" ], [ "CRASH", "release_year", "2004" ], [ "CRUEL INTENTIONS 3", "has_genre", "DRAMA" ], [ "CRUEL INTENTIONS 3", "release_year", "2004" ], [ "DAY AND NIGHT", "has_genre", "DRAMA" ], [ "DAY AND NIGHT", "has_tags", "DRAMA" ], [ "DAY AND NIGHT", "release_year", "2004" ], [ "DEAR FRANKIE", "has_genre", "DRAMA" ], [ "DEAR FRANKIE", "release_year", "2004" ], [ "DIRTY FILTHY LOVE", "has_genre", "DRAMA" ], [ "DIRTY FILTHY LOVE", "release_year", "2004" ], [ "DORIAN BLUES", "has_genre", "DRAMA" ], [ "DORIAN BLUES", "release_year", "2004" ], [ "DOWN TO THE BONE", "has_genre", "DRAMA" ], [ "DOWN TO THE BONE", "release_year", "2004" ], [ "ENVY", "has_genre", "DRAMA" ], [ "ENVY", "release_year", "2004" ], [ "EROS", "has_genre", "DRAMA" ], [ "EROS", "release_year", "2004" ], [ "ETHAN MAO", "has_genre", "DRAMA" ], [ "ETHAN MAO", "release_year", "2004" ], [ "EVERYDAY PEOPLE", "has_genre", "DRAMA" ], [ "EVERYDAY PEOPLE", "release_year", "2004" ], [ "FIRST LOVE", "has_genre", "DRAMA" ], [ "FIRST LOVE", "release_year", "2004" ], [ "FLIGHT OF THE PHOENIX", "has_genre", "DRAMA" ], [ "FLIGHT OF THE PHOENIX", "release_year", "2004" ], [ "FREEZE FRAME", "has_genre", "DRAMA" ], [ "FREEZE FRAME", "release_year", "2004" ], [ "FRIDAY NIGHT LIGHTS", "has_genre", "DRAMA" ], [ "FRIDAY NIGHT LIGHTS", "has_tags", "DRAMA" ], [ "FRIDAY NIGHT LIGHTS", "release_year", "2004" ], [ "GARDEN STATE", "has_genre", "DRAMA" ], [ "GARDEN STATE", "release_year", "2004" ], [ "GILLES' WIFE", "has_genre", "DRAMA" ], [ "GILLES' WIFE", "release_year", "2004" ], [ "HARRY + MAX", "has_genre", "DRAMA" ], [ "HARRY + MAX", "release_year", "2004" ], [ "HAWAII, OSLO", "has_genre", "DRAMA" ], [ "HAWAII, OSLO", "release_year", "2004" ], [ "HAWKING", "has_genre", "DRAMA" ], [ "HAWKING", "release_year", "2004" ], [ "HEAD IN THE CLOUDS", "has_genre", "DRAMA" ], [ "HEAD IN THE CLOUDS", "release_year", "2004" ], [ "HOTEL RWANDA", "has_genre", "DRAMA" ], [ "HOTEL RWANDA", "has_tags", "DRAMA" ], [ "HOTEL RWANDA", "release_year", "2004" ], [ "HOUSE OF D", "has_genre", "DRAMA" ], [ "HOUSE OF D", "release_year", "2004" ], [ "ICE MEN", "release_year", "2004" ], [ "ICE MEN", "starred_actors", "GREG SPOTTISWOOD" ], [ "IMAGINARY HEROES", "has_genre", "DRAMA" ], [ "IMAGINARY HEROES", "release_year", "2004" ], [ "IRON JAWED ANGELS", "has_genre", "DRAMA" ], [ "IRON JAWED ANGELS", "release_year", "2004" ], [ "JERSEY GIRL", "has_genre", "DRAMA" ], [ "JERSEY GIRL", "has_tags", "DRAMA" ], [ "JERSEY GIRL", "release_year", "2004" ], [ "KEANE", "has_genre", "DRAMA" ], [ "KEANE", "release_year", "2004" ], [ "KINSEY", "has_genre", "DRAMA" ], [ "KINSEY", "release_year", "2004" ], [ "LADDER 49", "has_genre", "DRAMA" ], [ "LADDER 49", "release_year", "2004" ], [ "LADIES IN LAVENDER", "has_genre", "DRAMA" ], [ "LADIES IN LAVENDER", "release_year", "2004" ], [ "LAND OF PLENTY", "has_genre", "DRAMA" ], [ "LAND OF PLENTY", "release_year", "2004" ], [ "LIGHTNING BUG", "has_genre", "DRAMA" ], [ "LIGHTNING BUG", "release_year", "2004" ], [ "LIGHTNING STRIKES TWICE", "has_genre", "DRAMA" ], [ "LOOK AT ME", "has_genre", "DRAMA" ], [ "LOOK AT ME", "release_year", "2004" ], [ "MARIE AND BRUCE", "has_genre", "DRAMA" ], [ "MARIE AND BRUCE", "release_year", "2004" ], [ "MEAN CREEK", "has_genre", "DRAMA" ], [ "MEAN CREEK", "has_tags", "DRAMA" ], [ "MEAN CREEK", "release_year", "2004" ], [ "MELINDA AND MELINDA", "has_genre", "DRAMA" ], [ "MELINDA AND MELINDA", "release_year", "2004" ], [ "MICKEY", "has_genre", "DRAMA" ], [ "MICKEY", "release_year", "2004" ], [ "MILLION DOLLAR BABY", "has_genre", "DRAMA" ], [ "MILLION DOLLAR BABY", "has_tags", "DRAMA" ], [ "MILLION DOLLAR BABY", "release_year", "2004" ], [ "MILLIONS", "has_genre", "DRAMA" ], [ "MILLIONS", "release_year", "2004" ], [ "MIRACLE", "has_genre", "DRAMA" ], [ "MIRACLE", "release_year", "2004" ], [ "MY SUMMER OF LOVE", "has_genre", "DRAMA" ], [ "MY SUMMER OF LOVE", "has_tags", "DRAMA" ], [ "MY SUMMER OF LOVE", "release_year", "2004" ], [ "MYSTERIOUS SKIN", "has_genre", "DRAMA" ], [ "MYSTERIOUS SKIN", "release_year", "2004" ], [ "NEW POLICE STORY", "has_genre", "DRAMA" ], [ "NEW POLICE STORY", "release_year", "2004" ], [ "NOBODY KNOWS", "has_genre", "DRAMA" ], [ "NOBODY KNOWS", "release_year", "2004" ], [ "NOEL", "has_genre", "DRAMA" ], [ "NOEL", "has_tags", "DRAMA" ], [ "NOEL", "release_year", "2004" ], [ "OMAGH", "has_genre", "DRAMA" ], [ "OMAGH", "release_year", "2004" ], [ "OUT OF REACH", "has_genre", "DRAMA" ], [ "OUT OF REACH", "release_year", "2004" ], [ "OYSTER FARMER", "has_genre", "DRAMA" ], [ "OYSTER FARMER", "release_year", "2004" ], [ "P.S.", "has_genre", "DRAMA" ], [ "P.S.", "release_year", "2004" ], [ "PALINDROMES", "has_genre", "DRAMA" ], [ "PALINDROMES", "release_year", "2004" ], [ "PRIMER", "has_genre", "DRAMA" ], [ "PRIMER", "release_year", "2004" ], [ "PRIVATE", "has_genre", "DRAMA" ], [ "PRIVATE", "release_year", "2004" ], [ "RAINCOAT", "has_genre", "DRAMA" ], [ "RAINCOAT", "release_year", "2004" ], [ "RAISING HELEN", "has_genre", "DRAMA" ], [ "RAISING HELEN", "release_year", "2004" ], [ "RED DUST", "has_genre", "DRAMA" ], [ "RED DUST", "release_year", "2004" ], [ "SAINT RALPH", "has_genre", "DRAMA" ], [ "SAINT RALPH", "release_year", "2004" ], [ "SAVED!", "has_genre", "DRAMA" ], [ "SAVED!", "release_year", "2004" ], [ "SAVING FACE", "has_genre", "DRAMA" ], [ "SAVING FACE", "release_year", "2004" ], [ "SHE HATE ME", "has_genre", "DRAMA" ], [ "SHE HATE ME", "release_year", "2004" ], [ "SIDEWAYS", "has_genre", "DRAMA" ], [ "SIDEWAYS", "release_year", "2004" ], [ "SILVER CITY", "has_genre", "DRAMA" ], [ "SILVER CITY", "release_year", "2004" ], [ "SIMON", "has_genre", "DRAMA" ], [ "SIMON", "release_year", "2004" ], [ "SPANGLISH", "has_genre", "DRAMA" ], [ "SPANGLISH", "release_year", "2004" ], [ "STAGE BEAUTY", "has_genre", "DRAMA" ], [ "STAGE BEAUTY", "release_year", "2004" ], [ "STRIP SEARCH", "has_genre", "DRAMA" ], [ "STRIP SEARCH", "release_year", "2004" ], [ "SUMMER STORM", "has_genre", "DRAMA" ], [ "SUMMER STORM", "release_year", "2004" ], [ "THE AVIATOR", "has_genre", "DRAMA" ], [ "THE AVIATOR", "has_tags", "DRAMA" ], [ "THE AVIATOR", "release_year", "2004" ], [ "THE BEAUTIFUL COUNTRY", "has_genre", "DRAMA" ], [ "THE BEAUTIFUL COUNTRY", "has_tags", "DRAMA" ], [ "THE BEAUTIFUL COUNTRY", "release_year", "2004" ], [ "THE BRIDGE OF SAN LUIS REY", "has_genre", "DRAMA" ], [ "THE BRIDGE OF SAN LUIS REY", "release_year", "2004" ], [ "THE CHORUS", "has_genre", "DRAMA" ], [ "THE CHORUS", "has_tags", "DRAMA" ], [ "THE CHORUS", "release_year", "2004" ], [ "THE CLEARING", "has_genre", "DRAMA" ], [ "THE CLEARING", "release_year", "2004" ], [ "THE DOOR IN THE FLOOR", "has_genre", "DRAMA" ], [ "THE DOOR IN THE FLOOR", "has_tags", "DRAMA" ], [ "THE DOOR IN THE FLOOR", "release_year", "2004" ], [ "THE FINAL CUT", "has_genre", "DRAMA" ], [ "THE FINAL CUT", "release_year", "2004" ], [ "THE FORGOTTEN", "has_genre", "DRAMA" ], [ "THE FORGOTTEN", "release_year", "2004" ], [ "THE GOODBYE GIRL", "has_genre", "DRAMA" ], [ "THE GOODBYE GIRL", "release_year", "2004" ], [ "THE HOLY GIRL", "has_genre", "DRAMA" ], [ "THE HOLY GIRL", "release_year", "2004" ], [ "THE KEYS TO THE HOUSE", "has_genre", "DRAMA" ], [ "THE KEYS TO THE HOUSE", "release_year", "2004" ], [ "THE LIBERTINE", "has_genre", "DRAMA" ], [ "THE LIBERTINE", "release_year", "2004" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "has_genre", "DRAMA" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "release_year", "2004" ], [ "THE LIZARD", "has_genre", "DRAMA" ], [ "THE LIZARD", "release_year", "2004" ], [ "THE MERCHANT OF VENICE", "has_genre", "DRAMA" ], [ "THE MERCHANT OF VENICE", "release_year", "2004" ], [ "THE NOTEBOOK", "has_genre", "DRAMA" ], [ "THE NOTEBOOK", "release_year", "2004" ], [ "THE PASSION OF THE CHRIST", "has_genre", "DRAMA" ], [ "THE PASSION OF THE CHRIST", "release_year", "2004" ], [ "THE RETURNED", "has_genre", "DRAMA" ], [ "THE RETURNED", "release_year", "2004" ], [ "THE TERMINAL", "has_genre", "DRAMA" ], [ "THE TERMINAL", "has_tags", "DRAMA" ], [ "THE TERMINAL", "release_year", "2004" ], [ "THE WOODSMAN", "has_genre", "DRAMA" ], [ "THE WOODSMAN", "has_tags", "DRAMA" ], [ "THE WOODSMAN", "release_year", "2004" ], [ "TROPICAL MALADY", "has_genre", "DRAMA" ], [ "TROPICAL MALADY", "release_year", "2004" ], [ "TURTLES CAN FLY", "has_genre", "DRAMA" ], [ "TURTLES CAN FLY", "release_year", "2004" ], [ "VANITY FAIR", "has_genre", "DRAMA" ], [ "VANITY FAIR", "release_year", "2004" ], [ "VEER-ZAARA", "has_genre", "DRAMA" ], [ "VEER-ZAARA", "release_year", "2004" ], [ "VERA DRAKE", "has_genre", "DRAMA" ], [ "VERA DRAKE", "release_year", "2004" ], [ "WE DON'T LIVE HERE ANYMORE", "has_genre", "DRAMA" ], [ "WE DON'T LIVE HERE ANYMORE", "release_year", "2004" ], [ "WHEN WILL I BE LOVED", "has_genre", "DRAMA" ], [ "WHEN WILL I BE LOVED", "release_year", "2004" ], [ "WICKER PARK", "has_genre", "DRAMA" ], [ "WICKER PARK", "release_year", "2004" ], [ "WILBY WONDERFUL", "has_genre", "DRAMA" ], [ "WILBY WONDERFUL", "release_year", "2004" ], [ "WILD SIDE", "has_genre", "DRAMA" ], [ "WILD SIDE", "release_year", "2004" ], [ "WINTER SOLSTICE", "has_genre", "DRAMA" ], [ "WINTER SOLSTICE", "release_year", "2004" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26762, 2008 37549, A CHORUS LINE 4269, A HARD DAY'S NIGHT 8198, A PRAIRIE HOME COMPANION 9152, A STAR IS BORN 27803, AASHIQUI 2 30643, ACROSS THE UNIVERSE 19457, AGING 27061, ALADDIN 6847, ALL THAT JAZZ 26658, ANOTHER CINDERELLA STORY 35145, AUGUST RUSH 39085, BILLY ELLIOT 16023, BLUES BROTHERS 2000 36271, BURLESQUE 24631, CADILLAC RECORDS 21381, CAMP ROCK 5376, CAPE NO. 7 10349, CHICAGO 10327, CHITTY CHITTY BANG BANG 35525, CHRISTMAS ON MARS 39861, CINDERELLA 14657, CSNY/DÉJÀ VU 37267, DREAMGIRLS 16291, EVITA 33716, FAME 409, FARINELLI 5287, FROZEN 14698, GRAFFITI BRIDGE 20263, HAIR 9798, HAIRSPRAY 1292, HEDWIG AND THE ANGRY INCH 10346, HERO WANTED 14375, HIGH SCHOOL MUSICAL 30806, IMAGINAERUM 33279, IN BRUGES 16243, JAILHOUSE ROCK 4492, JESUS CHRIST SUPERSTAR 36940, LABYRINTH 8851, LITTLE SHOP OF HORRORS 5163, MAMMA MIA! 22845, MUSIC 24593, MUSICAL 31661, MY FAIR LADY 29995, NEW YORK, NEW YORK 7019, NORMAN REEDUS 18184, OKLAHOMA! 25899, ONCE 8740, PARIS 36 4806, PETE'S DRAGON 14026, PINOCCHIO 6864, PITCH PERFECT 24736, PROM NIGHT 4005, PURPLE RAIN 3257, RED CANYON 30416, REPO! THE GENETIC OPERA 36575, RHINESTONE 38119, ROUSTABOUT 901, SCHOOL OF ROCK 22068, SOUL MEN 25270, THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT 26008, THE BLUES BROTHERS 888, THE JAZZ SINGER 37562, THE KING AND I 14478, THE LION KING 22217, THE MAMBO KINGS 11189, THE MUPPETS 34124, THE NIGHTMARE BEFORE CHRISTMAS 10721, THE ROCKY HORROR PICTURE SHOW 37901, THE SOUND OF MUSIC 31313, THE WEST POINT STORY 28776, THE WIZARD OF OZ 19447, THE WRESTLER 32562, VICTOR VICTORIA 32589, WERE THE WORLD MINE 4552, WEST SIDE STORY src, edge_attr, dst 37549, has_genre, 22845 37549, has_genre, 24593 4269, has_genre, 22845 4269, has_tags, 22845 4269, has_tags, 24593 8198, has_genre, 22845 8198, has_tags, 24593 9152, has_genre, 22845 9152, has_genre, 24593 9152, has_tags, 24593 27803, has_genre, 22845 27803, has_genre, 24593 30643, has_genre, 24593 30643, has_tags, 22845 30643, has_tags, 24593 27061, has_tags, 22845 27061, has_tags, 24593 6847, has_genre, 22845 6847, has_genre, 24593 6847, has_tags, 24593 26658, has_genre, 24593 26658, release_year, 26762 35145, has_genre, 22845 35145, has_tags, 22845 35145, has_tags, 24593 39085, has_genre, 22845 39085, has_tags, 24593 16023, has_tags, 22845 16023, has_tags, 24593 36271, has_genre, 22845 36271, has_tags, 24593 24631, has_tags, 22845 24631, release_year, 26762 21381, has_genre, 24593 21381, release_year, 26762 5376, has_genre, 22845 5376, release_year, 26762 10349, has_genre, 24593 10349, has_tags, 22845 10349, has_tags, 24593 10327, has_tags, 22845 10327, has_tags, 24593 35525, has_genre, 22845 35525, release_year, 26762 39861, has_genre, 24593 39861, has_tags, 22845 39861, has_tags, 24593 14657, has_genre, 22845 14657, release_year, 26762 37267, has_genre, 22845 37267, has_genre, 24593 37267, has_tags, 24593 16291, has_tags, 22845 16291, has_tags, 24593 33716, has_genre, 22845 33716, has_genre, 24593 33716, has_tags, 22845 409, has_genre, 22845 409, has_tags, 24593 5287, has_tags, 22845 5287, has_tags, 24593 14698, has_genre, 22845 14698, has_genre, 24593 20263, has_genre, 24593 20263, has_tags, 22845 20263, has_tags, 24593 9798, has_genre, 22845 9798, has_genre, 24593 9798, has_tags, 24593 1292, has_genre, 22845 1292, has_tags, 22845 1292, has_tags, 24593 10346, release_year, 26762 10346, starred_actors, 7019 14375, has_tags, 22845 14375, has_tags, 24593 30806, has_genre, 24593 30806, has_tags, 22845 33279, has_tags, 22845 33279, release_year, 26762 16243, has_genre, 22845 16243, has_genre, 24593 4492, has_genre, 22845 4492, has_genre, 24593 4492, has_tags, 24593 36940, has_tags, 22845 36940, has_tags, 24593 8851, has_genre, 24593 8851, has_tags, 22845 8851, has_tags, 24593 5163, has_genre, 24593 5163, has_tags, 24593 5163, release_year, 26762 31661, has_genre, 24593 31661, has_tags, 22845 31661, has_tags, 24593 29995, has_genre, 22845 29995, has_genre, 24593 18184, has_genre, 24593 18184, has_tags, 22845 18184, has_tags, 24593 25899, has_genre, 22845 25899, has_tags, 22845 25899, has_tags, 24593 8740, has_genre, 22845 8740, release_year, 26762 4806, has_tags, 22845 4806, has_tags, 24593 14026, has_tags, 22845 14026, has_tags, 24593 6864, has_genre, 22845 6864, has_tags, 22845 6864, has_tags, 24593 24736, has_tags, 22845 24736, release_year, 26762 4005, has_genre, 22845 4005, has_genre, 24593 3257, release_year, 26762 3257, starred_actors, 7019 30416, has_genre, 24593 30416, has_tags, 24593 30416, release_year, 26762 36575, has_genre, 22845 36575, has_genre, 24593 38119, has_genre, 22845 38119, has_genre, 24593 901, has_genre, 22845 901, has_tags, 22845 901, has_tags, 24593 22068, has_genre, 22845 22068, release_year, 26762 25270, has_genre, 22845 25270, has_tags, 24593 26008, has_tags, 22845 26008, has_tags, 24593 888, has_genre, 22845 888, has_genre, 24593 37562, has_genre, 24593 37562, has_tags, 22845 37562, has_tags, 24593 14478, has_tags, 22845 14478, has_tags, 24593 22217, has_genre, 22845 22217, has_tags, 24593 11189, has_genre, 24593 11189, has_tags, 22845 11189, has_tags, 24593 34124, has_tags, 22845 34124, has_tags, 24593 10721, has_genre, 24593 10721, has_tags, 22845 10721, has_tags, 24593 37901, has_tags, 22845 37901, has_tags, 24593 31313, has_genre, 22845 31313, has_tags, 24593 28776, has_tags, 22845 28776, has_tags, 24593 19447, has_tags, 19457 19447, release_year, 26762 32562, has_genre, 22845 32562, has_genre, 24593 32589, has_tags, 24593 32589, release_year, 26762 4552, has_genre, 24593 4552, has_tags, 22845 4552, has_tags, 24593 Question: For what reason are AGING, HERO WANTED, and NEW YORK, NEW YORK associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "AGING", "HERO WANTED", "NEW YORK, NEW YORK" ], "valid_edges": [ [ "A CHORUS LINE", "has_genre", "MUSIC" ], [ "A CHORUS LINE", "has_genre", "MUSICAL" ], [ "A HARD DAY'S NIGHT", "has_genre", "MUSIC" ], [ "A HARD DAY'S NIGHT", "has_tags", "MUSIC" ], [ "A HARD DAY'S NIGHT", "has_tags", "MUSICAL" ], [ "A PRAIRIE HOME COMPANION", "has_genre", "MUSIC" ], [ "A PRAIRIE HOME COMPANION", "has_tags", "MUSICAL" ], [ "A STAR IS BORN", "has_genre", "MUSIC" ], [ "A STAR IS BORN", "has_genre", "MUSICAL" ], [ "A STAR IS BORN", "has_tags", "MUSICAL" ], [ "AASHIQUI 2", "has_genre", "MUSIC" ], [ "AASHIQUI 2", "has_genre", "MUSICAL" ], [ "ACROSS THE UNIVERSE", "has_genre", "MUSICAL" ], [ "ACROSS THE UNIVERSE", "has_tags", "MUSIC" ], [ "ACROSS THE UNIVERSE", "has_tags", "MUSICAL" ], [ "ALADDIN", "has_tags", "MUSIC" ], [ "ALADDIN", "has_tags", "MUSICAL" ], [ "ALL THAT JAZZ", "has_genre", "MUSIC" ], [ "ALL THAT JAZZ", "has_genre", "MUSICAL" ], [ "ALL THAT JAZZ", "has_tags", "MUSICAL" ], [ "ANOTHER CINDERELLA STORY", "has_genre", "MUSICAL" ], [ "ANOTHER CINDERELLA STORY", "release_year", "2008" ], [ "AUGUST RUSH", "has_genre", "MUSIC" ], [ "AUGUST RUSH", "has_tags", "MUSIC" ], [ "AUGUST RUSH", "has_tags", "MUSICAL" ], [ "BILLY ELLIOT", "has_genre", "MUSIC" ], [ "BILLY ELLIOT", "has_tags", "MUSICAL" ], [ "BLUES BROTHERS 2000", "has_tags", "MUSIC" ], [ "BLUES BROTHERS 2000", "has_tags", "MUSICAL" ], [ "BURLESQUE", "has_genre", "MUSIC" ], [ "BURLESQUE", "has_tags", "MUSICAL" ], [ "CADILLAC RECORDS", "has_tags", "MUSIC" ], [ "CADILLAC RECORDS", "release_year", "2008" ], [ "CAMP ROCK", "has_genre", "MUSICAL" ], [ "CAMP ROCK", "release_year", "2008" ], [ "CAPE NO. 7", "has_genre", "MUSIC" ], [ "CAPE NO. 7", "release_year", "2008" ], [ "CHICAGO", "has_genre", "MUSICAL" ], [ "CHICAGO", "has_tags", "MUSIC" ], [ "CHICAGO", "has_tags", "MUSICAL" ], [ "CHITTY CHITTY BANG BANG", "has_tags", "MUSIC" ], [ "CHITTY CHITTY BANG BANG", "has_tags", "MUSICAL" ], [ "CHRISTMAS ON MARS", "has_genre", "MUSIC" ], [ "CHRISTMAS ON MARS", "release_year", "2008" ], [ "CINDERELLA", "has_genre", "MUSICAL" ], [ "CINDERELLA", "has_tags", "MUSIC" ], [ "CINDERELLA", "has_tags", "MUSICAL" ], [ "CSNY/DÉJÀ VU", "has_genre", "MUSIC" ], [ "CSNY/DÉJÀ VU", "release_year", "2008" ], [ "DREAMGIRLS", "has_genre", "MUSIC" ], [ "DREAMGIRLS", "has_genre", "MUSICAL" ], [ "DREAMGIRLS", "has_tags", "MUSICAL" ], [ "EVITA", "has_tags", "MUSIC" ], [ "EVITA", "has_tags", "MUSICAL" ], [ "FAME", "has_genre", "MUSIC" ], [ "FAME", "has_genre", "MUSICAL" ], [ "FAME", "has_tags", "MUSIC" ], [ "FARINELLI", "has_genre", "MUSIC" ], [ "FARINELLI", "has_tags", "MUSICAL" ], [ "FROZEN", "has_tags", "MUSIC" ], [ "FROZEN", "has_tags", "MUSICAL" ], [ "GRAFFITI BRIDGE", "has_genre", "MUSIC" ], [ "GRAFFITI BRIDGE", "has_genre", "MUSICAL" ], [ "HAIR", "has_genre", "MUSICAL" ], [ "HAIR", "has_tags", "MUSIC" ], [ "HAIR", "has_tags", "MUSICAL" ], [ "HAIRSPRAY", "has_genre", "MUSIC" ], [ "HAIRSPRAY", "has_genre", "MUSICAL" ], [ "HAIRSPRAY", "has_tags", "MUSICAL" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "MUSIC" ], [ "HEDWIG AND THE ANGRY INCH", "has_tags", "MUSIC" ], [ "HEDWIG AND THE ANGRY INCH", "has_tags", "MUSICAL" ], [ "HERO WANTED", "release_year", "2008" ], [ "HERO WANTED", "starred_actors", "NORMAN REEDUS" ], [ "HIGH SCHOOL MUSICAL", "has_tags", "MUSIC" ], [ "HIGH SCHOOL MUSICAL", "has_tags", "MUSICAL" ], [ "IMAGINAERUM", "has_genre", "MUSICAL" ], [ "IMAGINAERUM", "has_tags", "MUSIC" ], [ "IN BRUGES", "has_tags", "MUSIC" ], [ "IN BRUGES", "release_year", "2008" ], [ "JAILHOUSE ROCK", "has_genre", "MUSIC" ], [ "JAILHOUSE ROCK", "has_genre", "MUSICAL" ], [ "JESUS CHRIST SUPERSTAR", "has_genre", "MUSIC" ], [ "JESUS CHRIST SUPERSTAR", "has_genre", "MUSICAL" ], [ "JESUS CHRIST SUPERSTAR", "has_tags", "MUSICAL" ], [ "LABYRINTH", "has_tags", "MUSIC" ], [ "LABYRINTH", "has_tags", "MUSICAL" ], [ "LITTLE SHOP OF HORRORS", "has_genre", "MUSICAL" ], [ "LITTLE SHOP OF HORRORS", "has_tags", "MUSIC" ], [ "LITTLE SHOP OF HORRORS", "has_tags", "MUSICAL" ], [ "MAMMA MIA!", "has_genre", "MUSICAL" ], [ "MAMMA MIA!", "has_tags", "MUSICAL" ], [ "MAMMA MIA!", "release_year", "2008" ], [ "MY FAIR LADY", "has_genre", "MUSICAL" ], [ "MY FAIR LADY", "has_tags", "MUSIC" ], [ "MY FAIR LADY", "has_tags", "MUSICAL" ], [ "NEW YORK, NEW YORK", "has_genre", "MUSIC" ], [ "NEW YORK, NEW YORK", "has_genre", "MUSICAL" ], [ "OKLAHOMA!", "has_genre", "MUSICAL" ], [ "OKLAHOMA!", "has_tags", "MUSIC" ], [ "OKLAHOMA!", "has_tags", "MUSICAL" ], [ "ONCE", "has_genre", "MUSIC" ], [ "ONCE", "has_tags", "MUSIC" ], [ "ONCE", "has_tags", "MUSICAL" ], [ "PARIS 36", "has_genre", "MUSIC" ], [ "PARIS 36", "release_year", "2008" ], [ "PETE'S DRAGON", "has_tags", "MUSIC" ], [ "PETE'S DRAGON", "has_tags", "MUSICAL" ], [ "PINOCCHIO", "has_tags", "MUSIC" ], [ "PINOCCHIO", "has_tags", "MUSICAL" ], [ "PITCH PERFECT", "has_genre", "MUSIC" ], [ "PITCH PERFECT", "has_tags", "MUSIC" ], [ "PITCH PERFECT", "has_tags", "MUSICAL" ], [ "PROM NIGHT", "has_tags", "MUSIC" ], [ "PROM NIGHT", "release_year", "2008" ], [ "PURPLE RAIN", "has_genre", "MUSIC" ], [ "PURPLE RAIN", "has_genre", "MUSICAL" ], [ "RED CANYON", "release_year", "2008" ], [ "RED CANYON", "starred_actors", "NORMAN REEDUS" ], [ "REPO! THE GENETIC OPERA", "has_genre", "MUSICAL" ], [ "REPO! THE GENETIC OPERA", "has_tags", "MUSICAL" ], [ "REPO! THE GENETIC OPERA", "release_year", "2008" ], [ "RHINESTONE", "has_genre", "MUSIC" ], [ "RHINESTONE", "has_genre", "MUSICAL" ], [ "ROUSTABOUT", "has_genre", "MUSIC" ], [ "ROUSTABOUT", "has_genre", "MUSICAL" ], [ "SCHOOL OF ROCK", "has_genre", "MUSIC" ], [ "SCHOOL OF ROCK", "has_tags", "MUSIC" ], [ "SCHOOL OF ROCK", "has_tags", "MUSICAL" ], [ "SOUL MEN", "has_genre", "MUSIC" ], [ "SOUL MEN", "release_year", "2008" ], [ "THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT", "has_genre", "MUSIC" ], [ "THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT", "has_tags", "MUSICAL" ], [ "THE BLUES BROTHERS", "has_tags", "MUSIC" ], [ "THE BLUES BROTHERS", "has_tags", "MUSICAL" ], [ "THE JAZZ SINGER", "has_genre", "MUSIC" ], [ "THE JAZZ SINGER", "has_genre", "MUSICAL" ], [ "THE KING AND I", "has_genre", "MUSICAL" ], [ "THE KING AND I", "has_tags", "MUSIC" ], [ "THE KING AND I", "has_tags", "MUSICAL" ], [ "THE LION KING", "has_tags", "MUSIC" ], [ "THE LION KING", "has_tags", "MUSICAL" ], [ "THE MAMBO KINGS", "has_genre", "MUSIC" ], [ "THE MAMBO KINGS", "has_tags", "MUSICAL" ], [ "THE MUPPETS", "has_genre", "MUSICAL" ], [ "THE MUPPETS", "has_tags", "MUSIC" ], [ "THE MUPPETS", "has_tags", "MUSICAL" ], [ "THE NIGHTMARE BEFORE CHRISTMAS", "has_tags", "MUSIC" ], [ "THE NIGHTMARE BEFORE CHRISTMAS", "has_tags", "MUSICAL" ], [ "THE ROCKY HORROR PICTURE SHOW", "has_genre", "MUSICAL" ], [ "THE ROCKY HORROR PICTURE SHOW", "has_tags", "MUSIC" ], [ "THE ROCKY HORROR PICTURE SHOW", "has_tags", "MUSICAL" ], [ "THE SOUND OF MUSIC", "has_tags", "MUSIC" ], [ "THE SOUND OF MUSIC", "has_tags", "MUSICAL" ], [ "THE WEST POINT STORY", "has_genre", "MUSIC" ], [ "THE WEST POINT STORY", "has_tags", "MUSICAL" ], [ "THE WIZARD OF OZ", "has_tags", "MUSIC" ], [ "THE WIZARD OF OZ", "has_tags", "MUSICAL" ], [ "THE WRESTLER", "has_tags", "AGING" ], [ "THE WRESTLER", "release_year", "2008" ], [ "VICTOR VICTORIA", "has_genre", "MUSIC" ], [ "VICTOR VICTORIA", "has_genre", "MUSICAL" ], [ "WERE THE WORLD MINE", "has_tags", "MUSICAL" ], [ "WERE THE WORLD MINE", "release_year", "2008" ], [ "WEST SIDE STORY", "has_genre", "MUSICAL" ], [ "WEST SIDE STORY", "has_tags", "MUSIC" ], [ "WEST SIDE STORY", "has_tags", "MUSICAL" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26257, 1994 15374, 2005 31413, LASSIE 13383, PRIEST 5181, SHOOTING GALLERY 1374, SLEEP WITH ME 35082, THE EXORCIST 25478, WILLIAM PETER BLATTY src, edge_attr, dst 31413, release_year, 26257 31413, release_year, 15374 13383, release_year, 26257 5181, release_year, 15374 1374, release_year, 26257 35082, has_tags, 13383 35082, written_by, 25478 Question: In what context are SHOOTING GALLERY, SLEEP WITH ME, and WILLIAM PETER BLATTY connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "SHOOTING GALLERY", "SLEEP WITH ME", "WILLIAM PETER BLATTY" ], "valid_edges": [ [ "LASSIE", "release_year", "1994" ], [ "LASSIE", "release_year", "2005" ], [ "PRIEST", "release_year", "1994" ], [ "SHOOTING GALLERY", "release_year", "2005" ], [ "SLEEP WITH ME", "release_year", "1994" ], [ "THE EXORCIST", "has_tags", "PRIEST" ], [ "THE EXORCIST", "written_by", "WILLIAM PETER BLATTY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36169, BEYOND THE LIGHTS 36212, DRAMA 22981, GEORGE MACKAY 35078, HOW I LIVE NOW 1804, POSTCARDS FROM THE EDGE src, edge_attr, dst 36169, has_genre, 36212 35078, has_genre, 36212 35078, starred_actors, 22981 1804, has_genre, 36212 Question: For what reason are BEYOND THE LIGHTS, GEORGE MACKAY, and POSTCARDS FROM THE EDGE associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BEYOND THE LIGHTS", "GEORGE MACKAY", "POSTCARDS FROM THE EDGE" ], "valid_edges": [ [ "BEYOND THE LIGHTS", "has_genre", "DRAMA" ], [ "HOW I LIVE NOW", "has_genre", "DRAMA" ], [ "HOW I LIVE NOW", "starred_actors", "GEORGE MACKAY" ], [ "POSTCARDS FROM THE EDGE", "has_genre", "DRAMA" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17745, DAVID ZELLNER 36212, DRAMA 19701, HOTELL 29887, KUMIKO, THE TREASURE HUNTER 4092, LISA LANGSETH 34040, SKINHEADS 18052, THIS IS ENGLAND src, edge_attr, dst 19701, directed_by, 4092 19701, has_genre, 36212 19701, written_by, 4092 29887, directed_by, 17745 29887, has_genre, 36212 29887, starred_actors, 17745 29887, written_by, 17745 18052, has_genre, 36212 18052, has_tags, 34040 Question: How are DAVID ZELLNER, LISA LANGSETH, and SKINHEADS related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DAVID ZELLNER", "LISA LANGSETH", "SKINHEADS" ], "valid_edges": [ [ "HOTELL", "directed_by", "LISA LANGSETH" ], [ "HOTELL", "has_genre", "DRAMA" ], [ "HOTELL", "written_by", "LISA LANGSETH" ], [ "KUMIKO, THE TREASURE HUNTER", "directed_by", "DAVID ZELLNER" ], [ "KUMIKO, THE TREASURE HUNTER", "has_genre", "DRAMA" ], [ "KUMIKO, THE TREASURE HUNTER", "starred_actors", "DAVID ZELLNER" ], [ "KUMIKO, THE TREASURE HUNTER", "written_by", "DAVID ZELLNER" ], [ "THIS IS ENGLAND", "has_genre", "DRAMA" ], [ "THIS IS ENGLAND", "has_tags", "SKINHEADS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1892, 1932 35845, 2006 6718, A FAREWELL TO ARMS 17182, A GATHERING OF EAGLES 29918, AMAZING GRACE 35616, BROKEN LULLABY 8026, END OF THE GAME 31783, ENGLISH 14294, JEWEL ROBBERY 37928, JOE PANTOLIANO 12018, KAY FRANCIS 26649, KISMET 878, PARLIAMENT 21244, RAFFLES 15198, THE HUNCHBACK OF NOTRE DAME 34860, THIS IS THE NIGHT 10133, UNKNOWN 10474, WILLIAM DIETERLE src, edge_attr, dst 6718, in_language, 31783 6718, release_year, 1892 17182, has_imdb_votes, 10133 17182, in_language, 31783 29918, has_tags, 878 29918, release_year, 35845 35616, in_language, 31783 35616, release_year, 1892 8026, has_imdb_votes, 10133 8026, in_language, 31783 14294, directed_by, 10474 14294, has_tags, 10474 14294, in_language, 31783 14294, release_year, 1892 14294, starred_actors, 12018 26649, directed_by, 10474 26649, in_language, 31783 21244, in_language, 31783 21244, starred_actors, 12018 15198, directed_by, 10474 15198, has_tags, 10474 15198, in_language, 31783 34860, in_language, 31783 34860, release_year, 1892 10133, has_tags, 37928 10133, in_language, 31783 10133, release_year, 35845 10133, starred_actors, 37928 Question: How are JEWEL ROBBERY, JOE PANTOLIANO, and PARLIAMENT related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JEWEL ROBBERY", "JOE PANTOLIANO", "PARLIAMENT" ], "valid_edges": [ [ "A FAREWELL TO ARMS", "in_language", "ENGLISH" ], [ "A FAREWELL TO ARMS", "release_year", "1932" ], [ "A GATHERING OF EAGLES", "has_imdb_votes", "UNKNOWN" ], [ "A GATHERING OF EAGLES", "in_language", "ENGLISH" ], [ "AMAZING GRACE", "has_tags", "PARLIAMENT" ], [ "AMAZING GRACE", "release_year", "2006" ], [ "BROKEN LULLABY", "in_language", "ENGLISH" ], [ "BROKEN LULLABY", "release_year", "1932" ], [ "END OF THE GAME", "has_imdb_votes", "UNKNOWN" ], [ "END OF THE GAME", "in_language", "ENGLISH" ], [ "JEWEL ROBBERY", "directed_by", "WILLIAM DIETERLE" ], [ "JEWEL ROBBERY", "has_tags", "WILLIAM DIETERLE" ], [ "JEWEL ROBBERY", "in_language", "ENGLISH" ], [ "JEWEL ROBBERY", "release_year", "1932" ], [ "JEWEL ROBBERY", "starred_actors", "KAY FRANCIS" ], [ "KISMET", "directed_by", "WILLIAM DIETERLE" ], [ "KISMET", "in_language", "ENGLISH" ], [ "RAFFLES", "in_language", "ENGLISH" ], [ "RAFFLES", "starred_actors", "KAY FRANCIS" ], [ "THE HUNCHBACK OF NOTRE DAME", "directed_by", "WILLIAM DIETERLE" ], [ "THE HUNCHBACK OF NOTRE DAME", "has_tags", "WILLIAM DIETERLE" ], [ "THE HUNCHBACK OF NOTRE DAME", "in_language", "ENGLISH" ], [ "THIS IS THE NIGHT", "in_language", "ENGLISH" ], [ "THIS IS THE NIGHT", "release_year", "1932" ], [ "UNKNOWN", "has_tags", "JOE PANTOLIANO" ], [ "UNKNOWN", "in_language", "ENGLISH" ], [ "UNKNOWN", "release_year", "2006" ], [ "UNKNOWN", "starred_actors", "JOE PANTOLIANO" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 4981, 1965 10997, A HIGH WIND IN JAMAICA 15604, CORN ON THE COP 7516, IRV SPECTOR 19754, JAMES COBURN 4922, JOHANNES WEILAND 29056, MAJOR DUNDEE 36899, SHORT 8748, THE GRUFFALO'S CHILD src, edge_attr, dst 10997, release_year, 4981 10997, starred_actors, 19754 15604, directed_by, 7516 15604, has_genre, 36899 15604, release_year, 4981 29056, release_year, 4981 29056, starred_actors, 19754 8748, directed_by, 4922 8748, has_genre, 36899 Question: For what reason are IRV SPECTOR, JAMES COBURN, and JOHANNES WEILAND associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "IRV SPECTOR", "JAMES COBURN", "JOHANNES WEILAND" ], "valid_edges": [ [ "A HIGH WIND IN JAMAICA", "release_year", "1965" ], [ "A HIGH WIND IN JAMAICA", "starred_actors", "JAMES COBURN" ], [ "CORN ON THE COP", "directed_by", "IRV SPECTOR" ], [ "CORN ON THE COP", "has_genre", "SHORT" ], [ "CORN ON THE COP", "release_year", "1965" ], [ "MAJOR DUNDEE", "release_year", "1965" ], [ "MAJOR DUNDEE", "starred_actors", "JAMES COBURN" ], [ "THE GRUFFALO'S CHILD", "directed_by", "JOHANNES WEILAND" ], [ "THE GRUFFALO'S CHILD", "has_genre", "SHORT" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 658, 2012 9952, BRUNO DUMONT 25148, CHICAGO OVERCOAT 36001, HADEWIJCH 22177, TAYLOR SWIFT 34429, THE LORAX 29084, TWENTYNINE PALMS src, edge_attr, dst 658, release_year, 27261 25148, release_year, 27261 36001, directed_by, 9952 36001, has_tags, 9952 36001, release_year, 27261 36001, written_by, 9952 34429, has_tags, 22177 34429, release_year, 658 34429, starred_actors, 22177 29084, directed_by, 9952 29084, written_by, 9952 Question: For what reason are CHICAGO OVERCOAT, TAYLOR SWIFT, and TWENTYNINE PALMS associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CHICAGO OVERCOAT", "TAYLOR SWIFT", "TWENTYNINE PALMS" ], "valid_edges": [ [ "2012", "release_year", "2009" ], [ "CHICAGO OVERCOAT", "release_year", "2009" ], [ "HADEWIJCH", "directed_by", "BRUNO DUMONT" ], [ "HADEWIJCH", "has_tags", "BRUNO DUMONT" ], [ "HADEWIJCH", "release_year", "2009" ], [ "HADEWIJCH", "written_by", "BRUNO DUMONT" ], [ "THE LORAX", "has_tags", "TAYLOR SWIFT" ], [ "THE LORAX", "release_year", "2012" ], [ "THE LORAX", "starred_actors", "TAYLOR SWIFT" ], [ "TWENTYNINE PALMS", "directed_by", "BRUNO DUMONT" ], [ "TWENTYNINE PALMS", "written_by", "BRUNO DUMONT" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13504, 1963 1421, 2013 25594, BAY OF ANGELS 28488, CLAUDE MANN 36212, DRAMA 17034, FLAMING CREATURES 6012, FRENCH 28996, INDIA SONG 4475, JACK SMITH 27245, LONE SURVIVOR 3214, LOVE AND HONOR 23193, PHANTOM 11124, STALINGRAD 30733, SUBMARINE 19442, THE BOOK THIEF 11555, THE NOTEBOOK 22214, WAR src, edge_attr, dst 25594, in_language, 6012 25594, release_year, 13504 25594, starred_actors, 28488 17034, directed_by, 4475 17034, release_year, 13504 17034, written_by, 4475 28996, has_genre, 36212 28996, in_language, 6012 28996, starred_actors, 28488 27245, has_tags, 22214 27245, release_year, 1421 3214, has_genre, 22214 3214, release_year, 1421 23193, has_genre, 22214 23193, has_tags, 30733 23193, release_year, 1421 11124, has_genre, 22214 11124, release_year, 1421 30733, has_genre, 36212 19442, has_genre, 22214 19442, release_year, 1421 11555, has_genre, 22214 11555, release_year, 1421 Question: How are CLAUDE MANN, JACK SMITH, and PHANTOM related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CLAUDE MANN", "JACK SMITH", "PHANTOM" ], "valid_edges": [ [ "BAY OF ANGELS", "in_language", "FRENCH" ], [ "BAY OF ANGELS", "release_year", "1963" ], [ "BAY OF ANGELS", "starred_actors", "CLAUDE MANN" ], [ "FLAMING CREATURES", "directed_by", "JACK SMITH" ], [ "FLAMING CREATURES", "release_year", "1963" ], [ "FLAMING CREATURES", "written_by", "JACK SMITH" ], [ "INDIA SONG", "has_genre", "DRAMA" ], [ "INDIA SONG", "in_language", "FRENCH" ], [ "INDIA SONG", "starred_actors", "CLAUDE MANN" ], [ "LONE SURVIVOR", "has_tags", "WAR" ], [ "LONE SURVIVOR", "release_year", "2013" ], [ "LOVE AND HONOR", "has_genre", "WAR" ], [ "LOVE AND HONOR", "release_year", "2013" ], [ "PHANTOM", "has_genre", "WAR" ], [ "PHANTOM", "has_tags", "SUBMARINE" ], [ "PHANTOM", "release_year", "2013" ], [ "STALINGRAD", "has_genre", "WAR" ], [ "STALINGRAD", "release_year", "2013" ], [ "SUBMARINE", "has_genre", "DRAMA" ], [ "THE BOOK THIEF", "has_genre", "WAR" ], [ "THE BOOK THIEF", "release_year", "2013" ], [ "THE NOTEBOOK", "has_genre", "WAR" ], [ "THE NOTEBOOK", "release_year", "2013" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6925, 1966 17480, 1988 1097, 2003 4390, A PATCH OF BLUE 29089, DUEL AT DIABLO 10709, ELIZABETH HARTMAN 27719, LITTLE NIKITA 21889, OLD SCHOOL 14030, ROGER SPOTTISWOODE 30426, RUNNING ON EMPTY 11262, SHOOT TO KILL 3239, SIDNEY LUMET 1777, SIDNEY POITIER 23639, SPINNING BORIS 36916, THE GROUP 26382, YOU'RE A BIG BOY NOW src, edge_attr, dst 4390, starred_actors, 10709 4390, starred_actors, 1777 29089, release_year, 6925 29089, starred_actors, 1777 27719, release_year, 17480 27719, starred_actors, 1777 21889, release_year, 1097 30426, directed_by, 3239 30426, has_tags, 3239 30426, release_year, 17480 11262, directed_by, 14030 11262, release_year, 17480 11262, starred_actors, 1777 23639, directed_by, 14030 23639, release_year, 1097 36916, directed_by, 3239 36916, release_year, 6925 36916, starred_actors, 10709 26382, release_year, 6925 26382, starred_actors, 10709 Question: In what context are OLD SCHOOL, SHOOT TO KILL, and THE GROUP connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "OLD SCHOOL", "SHOOT TO KILL", "THE GROUP" ], "valid_edges": [ [ "A PATCH OF BLUE", "starred_actors", "ELIZABETH HARTMAN" ], [ "A PATCH OF BLUE", "starred_actors", "SIDNEY POITIER" ], [ "DUEL AT DIABLO", "release_year", "1966" ], [ "DUEL AT DIABLO", "starred_actors", "SIDNEY POITIER" ], [ "LITTLE NIKITA", "release_year", "1988" ], [ "LITTLE NIKITA", "starred_actors", "SIDNEY POITIER" ], [ "OLD SCHOOL", "release_year", "2003" ], [ "RUNNING ON EMPTY", "directed_by", "SIDNEY LUMET" ], [ "RUNNING ON EMPTY", "has_tags", "SIDNEY LUMET" ], [ "RUNNING ON EMPTY", "release_year", "1988" ], [ "SHOOT TO KILL", "directed_by", "ROGER SPOTTISWOODE" ], [ "SHOOT TO KILL", "release_year", "1988" ], [ "SHOOT TO KILL", "starred_actors", "SIDNEY POITIER" ], [ "SPINNING BORIS", "directed_by", "ROGER SPOTTISWOODE" ], [ "SPINNING BORIS", "release_year", "2003" ], [ "THE GROUP", "directed_by", "SIDNEY LUMET" ], [ "THE GROUP", "release_year", "1966" ], [ "THE GROUP", "starred_actors", "ELIZABETH HARTMAN" ], [ "YOU'RE A BIG BOY NOW", "release_year", "1966" ], [ "YOU'RE A BIG BOY NOW", "starred_actors", "ELIZABETH HARTMAN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29424, 2011 15000, APOLLO 18 25202, BRIAN MILLER 33310, CHESTER ERSKINE 30463, COMEDY 36212, DRAMA 5870, HORROR 11375, THE COBBLER 17991, THE EGG AND I 38108, THE STATION AGENT 28579, THE VISITOR 6617, THOMAS MCCARTHY 36565, WIN WIN src, edge_attr, dst 15000, has_genre, 5870 15000, release_year, 29424 15000, written_by, 25202 11375, directed_by, 6617 11375, has_genre, 30463 11375, has_genre, 36212 11375, written_by, 6617 17991, directed_by, 33310 17991, has_genre, 30463 17991, written_by, 33310 38108, directed_by, 6617 38108, has_genre, 30463 38108, has_genre, 36212 38108, has_tags, 6617 38108, written_by, 6617 28579, directed_by, 6617 28579, has_genre, 36212 28579, has_genre, 5870 28579, has_tags, 6617 28579, written_by, 6617 36565, directed_by, 6617 36565, has_genre, 30463 36565, has_genre, 36212 36565, has_tags, 6617 36565, release_year, 29424 36565, written_by, 6617 Question: In what context are BRIAN MILLER, CHESTER ERSKINE, and THOMAS MCCARTHY connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BRIAN MILLER", "CHESTER ERSKINE", "THOMAS MCCARTHY" ], "valid_edges": [ [ "APOLLO 18", "has_genre", "HORROR" ], [ "APOLLO 18", "release_year", "2011" ], [ "APOLLO 18", "written_by", "BRIAN MILLER" ], [ "THE COBBLER", "directed_by", "THOMAS MCCARTHY" ], [ "THE COBBLER", "has_genre", "COMEDY" ], [ "THE COBBLER", "has_genre", "DRAMA" ], [ "THE COBBLER", "written_by", "THOMAS MCCARTHY" ], [ "THE EGG AND I", "directed_by", "CHESTER ERSKINE" ], [ "THE EGG AND I", "has_genre", "COMEDY" ], [ "THE EGG AND I", "written_by", "CHESTER ERSKINE" ], [ "THE STATION AGENT", "directed_by", "THOMAS MCCARTHY" ], [ "THE STATION AGENT", "has_genre", "COMEDY" ], [ "THE STATION AGENT", "has_genre", "DRAMA" ], [ "THE STATION AGENT", "has_tags", "THOMAS MCCARTHY" ], [ "THE STATION AGENT", "written_by", "THOMAS MCCARTHY" ], [ "THE VISITOR", "directed_by", "THOMAS MCCARTHY" ], [ "THE VISITOR", "has_genre", "DRAMA" ], [ "THE VISITOR", "has_genre", "HORROR" ], [ "THE VISITOR", "has_tags", "THOMAS MCCARTHY" ], [ "THE VISITOR", "written_by", "THOMAS MCCARTHY" ], [ "WIN WIN", "directed_by", "THOMAS MCCARTHY" ], [ "WIN WIN", "has_genre", "COMEDY" ], [ "WIN WIN", "has_genre", "DRAMA" ], [ "WIN WIN", "has_tags", "THOMAS MCCARTHY" ], [ "WIN WIN", "release_year", "2011" ], [ "WIN WIN", "written_by", "THOMAS MCCARTHY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35845, 2006 27261, 2009 658, 2012 12931, ALEX KURTZMAN 17021, BLIND DATING 2020, CARRIERS 27018, CHRIS PINE 20845, EDDIE KAYE THOMAS 24481, FRANCHISE 12209, GENE RODDENBERRY 7986, JUST MY LUCK 22109, LEONARD NIMOY 3352, MIGUEL FERRER 31312, PEOPLE LIKE US 15802, RISE OF THE GUARDIANS 26204, ROBERTO ORCI 12333, SMOKIN' ACES 34989, STAR TREK 23210, STAR TREK INTO DARKNESS 20169, THIS MEANS WAR 33951, WRONG TURN AT TAHOE 30346, ZACHARY QUINTO src, edge_attr, dst 17021, release_year, 35845 17021, starred_actors, 27018 17021, starred_actors, 20845 2020, has_tags, 27018 2020, release_year, 27261 2020, starred_actors, 27018 7986, has_tags, 27018 7986, release_year, 35845 7986, starred_actors, 27018 31312, directed_by, 12931 31312, has_tags, 27018 31312, release_year, 658 31312, starred_actors, 27018 31312, written_by, 12931 31312, written_by, 26204 15802, release_year, 658 15802, starred_actors, 27018 12333, has_tags, 27018 12333, release_year, 35845 34989, has_tags, 27018 34989, has_tags, 24481 34989, has_tags, 22109 34989, has_tags, 34989 34989, has_tags, 30346 34989, release_year, 27261 34989, starred_actors, 27018 34989, starred_actors, 22109 34989, starred_actors, 30346 34989, written_by, 12931 34989, written_by, 12209 34989, written_by, 26204 23210, has_tags, 27018 23210, has_tags, 24481 23210, has_tags, 22109 23210, has_tags, 34989 23210, has_tags, 30346 23210, starred_actors, 27018 23210, starred_actors, 30346 23210, written_by, 12931 23210, written_by, 12209 23210, written_by, 26204 20169, has_tags, 27018 20169, release_year, 658 20169, starred_actors, 27018 33951, release_year, 27261 33951, starred_actors, 3352 Question: In what context are CHRIS PINE, EDDIE KAYE THOMAS, and MIGUEL FERRER connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CHRIS PINE", "EDDIE KAYE THOMAS", "MIGUEL FERRER" ], "valid_edges": [ [ "BLIND DATING", "release_year", "2006" ], [ "BLIND DATING", "starred_actors", "CHRIS PINE" ], [ "BLIND DATING", "starred_actors", "EDDIE KAYE THOMAS" ], [ "CARRIERS", "has_tags", "CHRIS PINE" ], [ "CARRIERS", "release_year", "2009" ], [ "CARRIERS", "starred_actors", "CHRIS PINE" ], [ "JUST MY LUCK", "has_tags", "CHRIS PINE" ], [ "JUST MY LUCK", "release_year", "2006" ], [ "JUST MY LUCK", "starred_actors", "CHRIS PINE" ], [ "PEOPLE LIKE US", "directed_by", "ALEX KURTZMAN" ], [ "PEOPLE LIKE US", "has_tags", "CHRIS PINE" ], [ "PEOPLE LIKE US", "release_year", "2012" ], [ "PEOPLE LIKE US", "starred_actors", "CHRIS PINE" ], [ "PEOPLE LIKE US", "written_by", "ALEX KURTZMAN" ], [ "PEOPLE LIKE US", "written_by", "ROBERTO ORCI" ], [ "RISE OF THE GUARDIANS", "release_year", "2012" ], [ "RISE OF THE GUARDIANS", "starred_actors", "CHRIS PINE" ], [ "SMOKIN' ACES", "has_tags", "CHRIS PINE" ], [ "SMOKIN' ACES", "release_year", "2006" ], [ "STAR TREK", "has_tags", "CHRIS PINE" ], [ "STAR TREK", "has_tags", "FRANCHISE" ], [ "STAR TREK", "has_tags", "LEONARD NIMOY" ], [ "STAR TREK", "has_tags", "STAR TREK" ], [ "STAR TREK", "has_tags", "ZACHARY QUINTO" ], [ "STAR TREK", "release_year", "2009" ], [ "STAR TREK", "starred_actors", "CHRIS PINE" ], [ "STAR TREK", "starred_actors", "LEONARD NIMOY" ], [ "STAR TREK", "starred_actors", "ZACHARY QUINTO" ], [ "STAR TREK", "written_by", "ALEX KURTZMAN" ], [ "STAR TREK", "written_by", "GENE RODDENBERRY" ], [ "STAR TREK", "written_by", "ROBERTO ORCI" ], [ "STAR TREK INTO DARKNESS", "has_tags", "CHRIS PINE" ], [ "STAR TREK INTO DARKNESS", "has_tags", "FRANCHISE" ], [ "STAR TREK INTO DARKNESS", "has_tags", "LEONARD NIMOY" ], [ "STAR TREK INTO DARKNESS", "has_tags", "STAR TREK" ], [ "STAR TREK INTO DARKNESS", "has_tags", "ZACHARY QUINTO" ], [ "STAR TREK INTO DARKNESS", "starred_actors", "CHRIS PINE" ], [ "STAR TREK INTO DARKNESS", "starred_actors", "ZACHARY QUINTO" ], [ "STAR TREK INTO DARKNESS", "written_by", "ALEX KURTZMAN" ], [ "STAR TREK INTO DARKNESS", "written_by", "GENE RODDENBERRY" ], [ "STAR TREK INTO DARKNESS", "written_by", "ROBERTO ORCI" ], [ "THIS MEANS WAR", "has_tags", "CHRIS PINE" ], [ "THIS MEANS WAR", "release_year", "2012" ], [ "THIS MEANS WAR", "starred_actors", "CHRIS PINE" ], [ "WRONG TURN AT TAHOE", "release_year", "2009" ], [ "WRONG TURN AT TAHOE", "starred_actors", "MIGUEL FERRER" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6721, 1972 10825, 1973 39435, 1975 22088, A BRIDGE TOO FAR 21158, A TOUCH OF CLASS 19293, ALL THE PRESIDENT'S MEN 20380, BLUME IN LOVE 35953, BUTCH CASSIDY AND THE SUNDANCE KID 18053, CAPER 24671, DAVID S. WARD 18042, GEORGE ROY HILL 19579, GEORGE SEGAL 10481, GLENDA JACKSON 4680, GROUNDHOG DAY 33571, HAVANA 25768, JEREMIAH JOHNSON 2781, LOST AND FOUND 27102, MELVIN FRANK 37497, NATIONAL FILM REGISTRY 34938, OUT OF AFRICA 2305, PAUL NEWMAN 206, PENNSYLVANIA 34758, ROBERT REDFORD 16146, SNEAKERS 8211, SYDNEY POLLACK 1174, THE CANDIDATE 38254, THE ELECTRIC HORSEMAN 8847, THE GREAT WALDO PEPPER 32636, THE HOT ROCK 7386, THE MILAGRO BEANFIELD WAR 39278, THE STING 32709, THE WAY WE WERE 31876, THIS PROPERTY IS CONDEMNED 25255, THREE DAYS OF THE CONDOR 13447, WILLIAM GOLDMAN src, edge_attr, dst 22088, has_tags, 34758 22088, written_by, 13447 21158, directed_by, 27102 21158, release_year, 10825 21158, starred_actors, 19579 21158, starred_actors, 10481 21158, written_by, 27102 19293, has_tags, 34758 19293, starred_actors, 34758 19293, written_by, 13447 20380, release_year, 10825 20380, starred_actors, 19579 35953, directed_by, 18042 35953, has_tags, 18042 35953, has_tags, 37497 35953, has_tags, 2305 35953, has_tags, 34758 35953, has_tags, 13447 35953, starred_actors, 2305 35953, starred_actors, 34758 35953, written_by, 13447 4680, has_tags, 37497 4680, has_tags, 206 33571, directed_by, 8211 33571, has_tags, 33571 33571, starred_actors, 34758 25768, directed_by, 8211 25768, has_tags, 34758 25768, has_tags, 8211 25768, release_year, 6721 25768, starred_actors, 34758 2781, directed_by, 27102 2781, starred_actors, 19579 2781, starred_actors, 10481 2781, written_by, 27102 34938, directed_by, 8211 34938, has_tags, 34758 34938, has_tags, 8211 34938, starred_actors, 34758 16146, has_tags, 18053 16146, has_tags, 34758 16146, starred_actors, 34758 1174, has_tags, 34758 1174, release_year, 6721 1174, starred_actors, 34758 38254, directed_by, 8211 38254, starred_actors, 34758 8847, directed_by, 18042 8847, release_year, 39435 8847, starred_actors, 34758 8847, written_by, 18042 32636, has_tags, 34758 32636, release_year, 6721 32636, starred_actors, 19579 32636, starred_actors, 34758 32636, written_by, 13447 7386, directed_by, 34758 7386, has_tags, 34758 7386, written_by, 24671 39278, directed_by, 18042 39278, has_tags, 18053 39278, has_tags, 18042 39278, has_tags, 2305 39278, has_tags, 34758 39278, release_year, 10825 39278, starred_actors, 2305 39278, starred_actors, 34758 39278, written_by, 24671 32709, directed_by, 8211 32709, has_tags, 8211 32709, release_year, 10825 32709, starred_actors, 34758 31876, directed_by, 8211 31876, has_tags, 8211 31876, starred_actors, 34758 25255, directed_by, 8211 25255, has_tags, 34758 25255, has_tags, 8211 25255, release_year, 39435 25255, starred_actors, 34758 Question: In what context are A TOUCH OF CLASS, PENNSYLVANIA, and ROBERT REDFORD connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "A TOUCH OF CLASS", "PENNSYLVANIA", "ROBERT REDFORD" ], "valid_edges": [ [ "A BRIDGE TOO FAR", "has_tags", "ROBERT REDFORD" ], [ "A BRIDGE TOO FAR", "written_by", "WILLIAM GOLDMAN" ], [ "A TOUCH OF CLASS", "directed_by", "MELVIN FRANK" ], [ "A TOUCH OF CLASS", "release_year", "1973" ], [ "A TOUCH OF CLASS", "starred_actors", "GEORGE SEGAL" ], [ "A TOUCH OF CLASS", "starred_actors", "GLENDA JACKSON" ], [ "A TOUCH OF CLASS", "written_by", "MELVIN FRANK" ], [ "ALL THE PRESIDENT'S MEN", "has_tags", "ROBERT REDFORD" ], [ "ALL THE PRESIDENT'S MEN", "starred_actors", "ROBERT REDFORD" ], [ "ALL THE PRESIDENT'S MEN", "written_by", "WILLIAM GOLDMAN" ], [ "BLUME IN LOVE", "release_year", "1973" ], [ "BLUME IN LOVE", "starred_actors", "GEORGE SEGAL" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "directed_by", "GEORGE ROY HILL" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "GEORGE ROY HILL" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "PAUL NEWMAN" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "ROBERT REDFORD" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "WILLIAM GOLDMAN" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "starred_actors", "PAUL NEWMAN" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "starred_actors", "ROBERT REDFORD" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "written_by", "WILLIAM GOLDMAN" ], [ "GROUNDHOG DAY", "has_tags", "NATIONAL FILM REGISTRY" ], [ "GROUNDHOG DAY", "has_tags", "PENNSYLVANIA" ], [ "HAVANA", "directed_by", "SYDNEY POLLACK" ], [ "HAVANA", "has_tags", "HAVANA" ], [ "HAVANA", "starred_actors", "ROBERT REDFORD" ], [ "JEREMIAH JOHNSON", "directed_by", "SYDNEY POLLACK" ], [ "JEREMIAH JOHNSON", "has_tags", "ROBERT REDFORD" ], [ "JEREMIAH JOHNSON", "has_tags", "SYDNEY POLLACK" ], [ "JEREMIAH JOHNSON", "release_year", "1972" ], [ "JEREMIAH JOHNSON", "starred_actors", "ROBERT REDFORD" ], [ "LOST AND FOUND", "directed_by", "MELVIN FRANK" ], [ "LOST AND FOUND", "starred_actors", "GEORGE SEGAL" ], [ "LOST AND FOUND", "starred_actors", "GLENDA JACKSON" ], [ "LOST AND FOUND", "written_by", "MELVIN FRANK" ], [ "OUT OF AFRICA", "directed_by", "SYDNEY POLLACK" ], [ "OUT OF AFRICA", "has_tags", "ROBERT REDFORD" ], [ "OUT OF AFRICA", "has_tags", "SYDNEY POLLACK" ], [ "OUT OF AFRICA", "starred_actors", "ROBERT REDFORD" ], [ "SNEAKERS", "has_tags", "CAPER" ], [ "SNEAKERS", "has_tags", "ROBERT REDFORD" ], [ "SNEAKERS", "starred_actors", "ROBERT REDFORD" ], [ "THE CANDIDATE", "has_tags", "ROBERT REDFORD" ], [ "THE CANDIDATE", "release_year", "1972" ], [ "THE CANDIDATE", "starred_actors", "ROBERT REDFORD" ], [ "THE ELECTRIC HORSEMAN", "directed_by", "SYDNEY POLLACK" ], [ "THE ELECTRIC HORSEMAN", "starred_actors", "ROBERT REDFORD" ], [ "THE GREAT WALDO PEPPER", "directed_by", "GEORGE ROY HILL" ], [ "THE GREAT WALDO PEPPER", "release_year", "1975" ], [ "THE GREAT WALDO PEPPER", "starred_actors", "ROBERT REDFORD" ], [ "THE GREAT WALDO PEPPER", "written_by", "GEORGE ROY HILL" ], [ "THE HOT ROCK", "has_tags", "ROBERT REDFORD" ], [ "THE HOT ROCK", "release_year", "1972" ], [ "THE HOT ROCK", "starred_actors", "GEORGE SEGAL" ], [ "THE HOT ROCK", "starred_actors", "ROBERT REDFORD" ], [ "THE HOT ROCK", "written_by", "WILLIAM GOLDMAN" ], [ "THE MILAGRO BEANFIELD WAR", "directed_by", "ROBERT REDFORD" ], [ "THE MILAGRO BEANFIELD WAR", "has_tags", "ROBERT REDFORD" ], [ "THE MILAGRO BEANFIELD WAR", "written_by", "DAVID S. WARD" ], [ "THE STING", "directed_by", "GEORGE ROY HILL" ], [ "THE STING", "has_tags", "CAPER" ], [ "THE STING", "has_tags", "GEORGE ROY HILL" ], [ "THE STING", "has_tags", "PAUL NEWMAN" ], [ "THE STING", "has_tags", "ROBERT REDFORD" ], [ "THE STING", "release_year", "1973" ], [ "THE STING", "starred_actors", "PAUL NEWMAN" ], [ "THE STING", "starred_actors", "ROBERT REDFORD" ], [ "THE STING", "written_by", "DAVID S. WARD" ], [ "THE WAY WE WERE", "directed_by", "SYDNEY POLLACK" ], [ "THE WAY WE WERE", "has_tags", "SYDNEY POLLACK" ], [ "THE WAY WE WERE", "release_year", "1973" ], [ "THE WAY WE WERE", "starred_actors", "ROBERT REDFORD" ], [ "THIS PROPERTY IS CONDEMNED", "directed_by", "SYDNEY POLLACK" ], [ "THIS PROPERTY IS CONDEMNED", "has_tags", "SYDNEY POLLACK" ], [ "THIS PROPERTY IS CONDEMNED", "starred_actors", "ROBERT REDFORD" ], [ "THREE DAYS OF THE CONDOR", "directed_by", "SYDNEY POLLACK" ], [ "THREE DAYS OF THE CONDOR", "has_tags", "ROBERT REDFORD" ], [ "THREE DAYS OF THE CONDOR", "has_tags", "SYDNEY POLLACK" ], [ "THREE DAYS OF THE CONDOR", "release_year", "1975" ], [ "THREE DAYS OF THE CONDOR", "starred_actors", "ROBERT REDFORD" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 31486, 1970 37315, A BRONX TALE 10996, AWAKENINGS 31163, DIRECTORIAL DEBUT 13133, HI, MOM! 2938, JUMPIN' JACK FLASH 21728, MASSACRE 17036, PENNY MARSHALL 17979, ROBERT DE NIRO 20390, SOLDIER BLUE 1797, THE BIRD WITH THE CRYSTAL PLUMAGE src, edge_attr, dst 37315, directed_by, 17979 37315, has_tags, 31163 37315, has_tags, 17979 37315, starred_actors, 17979 10996, directed_by, 17036 10996, has_tags, 17036 10996, has_tags, 17979 10996, starred_actors, 17979 13133, has_tags, 17979 13133, release_year, 31486 13133, starred_actors, 17979 2938, directed_by, 17036 2938, has_tags, 31163 20390, has_tags, 21728 20390, release_year, 31486 1797, has_tags, 31163 1797, release_year, 31486 Question: In what context are HI, MOM!, JUMPIN' JACK FLASH, and MASSACRE connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "HI, MOM!", "JUMPIN' JACK FLASH", "MASSACRE" ], "valid_edges": [ [ "A BRONX TALE", "directed_by", "ROBERT DE NIRO" ], [ "A BRONX TALE", "has_tags", "DIRECTORIAL DEBUT" ], [ "A BRONX TALE", "has_tags", "ROBERT DE NIRO" ], [ "A BRONX TALE", "starred_actors", "ROBERT DE NIRO" ], [ "AWAKENINGS", "directed_by", "PENNY MARSHALL" ], [ "AWAKENINGS", "has_tags", "PENNY MARSHALL" ], [ "AWAKENINGS", "has_tags", "ROBERT DE NIRO" ], [ "AWAKENINGS", "starred_actors", "ROBERT DE NIRO" ], [ "HI, MOM!", "has_tags", "ROBERT DE NIRO" ], [ "HI, MOM!", "release_year", "1970" ], [ "HI, MOM!", "starred_actors", "ROBERT DE NIRO" ], [ "JUMPIN' JACK FLASH", "directed_by", "PENNY MARSHALL" ], [ "JUMPIN' JACK FLASH", "has_tags", "DIRECTORIAL DEBUT" ], [ "SOLDIER BLUE", "has_tags", "MASSACRE" ], [ "SOLDIER BLUE", "release_year", "1970" ], [ "THE BIRD WITH THE CRYSTAL PLUMAGE", "has_tags", "DIRECTORIAL DEBUT" ], [ "THE BIRD WITH THE CRYSTAL PLUMAGE", "release_year", "1970" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13464, 10 THINGS I HATE ABOUT YOU 8486, 1999 5620, 200 CIGARETTES 30146, A CHRISTMAS CAROL 38367, A MAP OF THE WORLD 27672, A ROOM FOR ROMEO BRASS 5152, A SLIPPING-DOWN LIFE 30464, A WALK ON THE MOON 35603, AGNES BROWNE 30284, ALL ABOUT MY MOTHER 17254, AMERICAN BEAUTY 20033, ANGEL 17481, ANGELA'S ASHES 29422, ANNA AND THE KING 17320, ANY GIVEN SUNDAY 25586, ARLINGTON ROAD 7908, AUDITION 9669, AUDREY WELLS 26205, BEING JOHN MALKOVICH 2067, BETWEEN YOUR LEGS 8900, BICENTENNIAL MAN 37569, BOYS DON'T CRY 21035, BRINGING OUT THE DEAD 7918, BROKEDOWN PALACE 3291, CATFISH IN BLACK BEAN SAUCE 30463, COMEDY 23710, CRADLE WILL ROCK 32140, CRAZY IN ALABAMA 27377, CRUEL INTENTIONS 13007, DETERRENCE 36212, DRAMA 12319, DREAMING OF JOSEPH LEES 7568, EAST IS EAST 3893, ED WOOD 34555, FLAWLESS 17478, FOOLISH 9161, FOR LOVE OF THE GAME 5820, FOREVER MINE 131, GINA GERSHON 22532, GIRL, INTERRUPTED 9527, GLEN OR GLENDA 35657, GLORIA 10457, GOYA IN BORDEAUX 19204, GUINEVERE 34201, HERMAN SHUMLIN 27446, IN TOO DEEP 35335, IT ALL STARTS TODAY 4912, JAKOB THE LIAR 14391, JOE THE KING 27249, JUDY BERLIN 21224, KIKUJIRO 22333, KING OF COMEDY 18023, LIBERTY HEIGHTS 7104, LIFE 21197, LIGHT IT UP 4052, LIMBO 28092, MAGNOLIA 37867, MAN ON THE MOON 6649, MANSFIELD PARK 6559, MESSAGE IN A BOTTLE 30008, MISS JULIE 19598, MOLLY 14977, MOLOCH 9235, MR. NOBODY 16428, MUMFORD 3018, MUSIC OF THE HEART 12944, MY LIFE WITHOUT ME 33718, MYSTERY, ALASKA 493, ONE MAN'S HERO 18987, ONEGIN 35341, ORFEU 35054, PLAY IT TO THE BONE 21386, POLA X 10039, PUPS 16964, PUSHING TIN 9963, RANDOM HEARTS 14786, REUBEN, REUBEN 27631, RIDE WITH THE DEVIL 12234, RKO 281 27556, ROGUE TRADER 8379, ROMANCE 30403, RUDOLPH GREY 36349, SARAH POLLEY 15252, SCREWED IN TALLINN 36012, SHOWGIRLS 36167, SOFT FRUIT 1469, SOPHIE'S WORLD 37429, STEPHEN REA 32984, SWEET AND LOWDOWN 18005, TAKE THIS WALTZ 4157, THE BEST MAN 27111, THE BIG KAHUNA 22372, THE CIDER HOUSE RULES 6150, THE CONFESSION 165, THE CRYING GAME 25509, THE DEBT 791, THE DEEP END OF THE OCEAN 8141, THE END OF THE AFFAIR 14220, THE FIVE SENSES 12748, THE GLASS AGENCY 35367, THE GREEN MILE 16209, THE HI-LINE 12439, THE INSIDER 34986, THE JOYRIDERS 37562, THE KING AND I 13703, THE LAW OF ENCLOSURES 9799, THE LOST SON 27045, THE MISSION 5098, THE MOMENT AFTER 37200, THE STORY OF US 9301, THE STRAIGHT STORY 11235, THE SUBURBANS 13405, THE THIRD MIRACLE 12026, THE TIC CODE 12801, THE VIRGIN SUICIDES 39253, THE WAR ZONE 14983, THE WINSLOW BOY 332, TOPSY-TURVY 29271, TOUCH 308, TRUE CRIME 13101, TUMBLEWEEDS 11544, UNDER THE TUSCAN SUN 9202, VARSITY BLUES 30597, WATCH ON THE RHINE 16102, WILDFLOWERS 30288, WISCONSIN DEATH TRIP 6567, WITH FIRE AND SWORD 31862, WONDERLAND src, edge_attr, dst 13464, has_genre, 36212 13464, release_year, 8486 5620, has_genre, 36212 5620, release_year, 8486 30146, has_genre, 36212 30146, release_year, 8486 38367, has_genre, 36212 38367, release_year, 8486 27672, has_genre, 36212 27672, release_year, 8486 5152, has_genre, 36212 5152, release_year, 8486 30464, has_genre, 36212 30464, release_year, 8486 35603, has_genre, 36212 35603, release_year, 8486 30284, has_genre, 36212 30284, release_year, 8486 17254, has_genre, 36212 17254, has_tags, 36212 17254, release_year, 8486 20033, has_genre, 36212 20033, starred_actors, 37429 17481, has_genre, 36212 17481, release_year, 8486 29422, has_genre, 36212 29422, release_year, 8486 17320, has_genre, 36212 17320, release_year, 8486 25586, has_genre, 36212 25586, release_year, 8486 7908, has_genre, 36212 7908, release_year, 8486 26205, has_genre, 36212 26205, has_tags, 36212 26205, release_year, 8486 2067, has_genre, 36212 2067, release_year, 8486 8900, has_genre, 36212 8900, release_year, 8486 37569, has_genre, 36212 37569, has_tags, 36212 37569, release_year, 8486 21035, has_genre, 36212 21035, has_tags, 36212 21035, release_year, 8486 7918, has_genre, 36212 7918, release_year, 8486 3291, has_genre, 36212 3291, release_year, 8486 23710, has_genre, 36212 23710, release_year, 8486 32140, has_genre, 36212 32140, release_year, 8486 27377, has_genre, 36212 27377, release_year, 8486 13007, has_genre, 36212 13007, release_year, 8486 12319, has_genre, 36212 12319, release_year, 8486 7568, has_genre, 36212 7568, release_year, 8486 3893, has_genre, 30463 3893, has_genre, 36212 3893, has_tags, 3893 3893, written_by, 30403 34555, has_genre, 36212 34555, release_year, 8486 17478, has_genre, 36212 17478, release_year, 8486 9161, has_genre, 36212 9161, release_year, 8486 5820, has_genre, 36212 5820, release_year, 8486 22532, has_genre, 36212 22532, has_tags, 36212 22532, release_year, 8486 9527, has_genre, 36212 9527, has_tags, 3893 35657, has_genre, 36212 35657, release_year, 8486 10457, has_genre, 36212 10457, release_year, 8486 19204, directed_by, 9669 19204, has_genre, 36212 19204, release_year, 8486 19204, starred_actors, 131 19204, starred_actors, 36349 19204, starred_actors, 37429 19204, written_by, 9669 27446, has_genre, 36212 27446, release_year, 8486 35335, has_genre, 36212 35335, release_year, 8486 4912, has_genre, 36212 4912, release_year, 8486 14391, has_genre, 36212 14391, release_year, 8486 27249, has_genre, 36212 27249, release_year, 8486 21224, has_genre, 36212 21224, release_year, 8486 22333, has_genre, 36212 22333, release_year, 8486 18023, has_genre, 36212 18023, release_year, 8486 7104, has_genre, 36212 7104, release_year, 8486 21197, has_genre, 36212 21197, release_year, 8486 4052, has_genre, 36212 4052, release_year, 8486 28092, has_genre, 36212 28092, release_year, 8486 37867, has_genre, 36212 37867, release_year, 8486 6649, has_genre, 36212 6649, release_year, 8486 6559, has_genre, 36212 6559, release_year, 8486 30008, has_genre, 36212 30008, release_year, 8486 19598, has_genre, 36212 19598, release_year, 8486 14977, has_genre, 36212 14977, release_year, 8486 9235, has_genre, 36212 9235, has_tags, 36349 9235, starred_actors, 36349 16428, has_genre, 36212 16428, release_year, 8486 3018, has_genre, 36212 3018, release_year, 8486 12944, has_genre, 36212 12944, starred_actors, 36349 33718, has_genre, 36212 33718, release_year, 8486 493, has_genre, 36212 493, release_year, 8486 18987, has_genre, 36212 18987, release_year, 8486 35341, has_genre, 36212 35341, release_year, 8486 35054, has_genre, 36212 35054, release_year, 8486 21386, has_genre, 36212 21386, release_year, 8486 10039, has_genre, 36212 10039, release_year, 8486 16964, has_genre, 36212 16964, release_year, 8486 9963, has_genre, 36212 9963, release_year, 8486 14786, has_genre, 30463 14786, has_genre, 36212 14786, written_by, 34201 27631, has_genre, 36212 27631, release_year, 8486 12234, has_genre, 36212 12234, release_year, 8486 27556, has_genre, 36212 27556, release_year, 8486 8379, has_genre, 36212 8379, release_year, 8486 15252, has_genre, 36212 15252, release_year, 8486 36012, has_genre, 36212 36012, starred_actors, 131 36167, has_genre, 36212 36167, release_year, 8486 1469, has_genre, 36212 1469, release_year, 8486 32984, has_genre, 36212 32984, release_year, 8486 18005, directed_by, 36349 18005, has_genre, 36212 18005, has_tags, 36349 18005, written_by, 36349 4157, has_genre, 36212 4157, release_year, 8486 27111, has_genre, 36212 27111, release_year, 8486 22372, has_genre, 36212 22372, has_tags, 36212 22372, release_year, 8486 6150, has_genre, 36212 6150, release_year, 8486 165, has_genre, 36212 165, has_tags, 37429 165, starred_actors, 37429 25509, has_genre, 36212 25509, release_year, 8486 791, has_genre, 36212 791, release_year, 8486 8141, has_genre, 36212 8141, release_year, 8486 8141, starred_actors, 37429 14220, has_genre, 36212 14220, release_year, 8486 12748, has_genre, 36212 12748, release_year, 8486 35367, has_genre, 36212 35367, has_tags, 36212 35367, release_year, 8486 16209, has_genre, 36212 16209, release_year, 8486 12439, has_genre, 36212 12439, has_tags, 36212 12439, release_year, 8486 34986, has_genre, 36212 34986, release_year, 8486 37562, has_genre, 36212 37562, release_year, 8486 13703, has_genre, 36212 13703, starred_actors, 36349 9799, has_genre, 36212 9799, release_year, 8486 27045, has_genre, 36212 27045, release_year, 8486 5098, has_genre, 36212 5098, release_year, 8486 37200, has_genre, 36212 37200, has_tags, 36212 37200, release_year, 8486 9301, has_genre, 36212 9301, release_year, 8486 11235, has_genre, 36212 11235, release_year, 8486 13405, has_genre, 36212 13405, release_year, 8486 12026, has_genre, 36212 12026, release_year, 8486 12801, has_genre, 36212 12801, release_year, 8486 39253, has_genre, 36212 39253, release_year, 8486 14983, has_genre, 36212 14983, release_year, 8486 332, has_genre, 36212 332, release_year, 8486 29271, has_genre, 36212 29271, starred_actors, 131 308, has_genre, 36212 308, release_year, 8486 13101, has_genre, 36212 13101, release_year, 8486 11544, directed_by, 9669 11544, has_genre, 36212 11544, written_by, 9669 9202, has_genre, 36212 9202, release_year, 8486 30597, directed_by, 34201 30597, has_genre, 36212 16102, has_genre, 36212 16102, release_year, 8486 30288, has_genre, 36212 30288, release_year, 8486 6567, has_genre, 36212 6567, release_year, 8486 31862, has_genre, 36212 31862, release_year, 8486 Question: How are GUINEVERE, HERMAN SHUMLIN, and RUDOLPH GREY related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "GUINEVERE", "HERMAN SHUMLIN", "RUDOLPH GREY" ], "valid_edges": [ [ "10 THINGS I HATE ABOUT YOU", "has_genre", "DRAMA" ], [ "10 THINGS I HATE ABOUT YOU", "release_year", "1999" ], [ "200 CIGARETTES", "has_genre", "DRAMA" ], [ "200 CIGARETTES", "release_year", "1999" ], [ "A CHRISTMAS CAROL", "has_genre", "DRAMA" ], [ "A CHRISTMAS CAROL", "release_year", "1999" ], [ "A MAP OF THE WORLD", "has_genre", "DRAMA" ], [ "A MAP OF THE WORLD", "release_year", "1999" ], [ "A ROOM FOR ROMEO BRASS", "has_genre", "DRAMA" ], [ "A ROOM FOR ROMEO BRASS", "release_year", "1999" ], [ "A SLIPPING-DOWN LIFE", "has_genre", "DRAMA" ], [ "A SLIPPING-DOWN LIFE", "release_year", "1999" ], [ "A WALK ON THE MOON", "has_genre", "DRAMA" ], [ "A WALK ON THE MOON", "release_year", "1999" ], [ "AGNES BROWNE", "has_genre", "DRAMA" ], [ "AGNES BROWNE", "release_year", "1999" ], [ "ALL ABOUT MY MOTHER", "has_genre", "DRAMA" ], [ "ALL ABOUT MY MOTHER", "release_year", "1999" ], [ "AMERICAN BEAUTY", "has_genre", "DRAMA" ], [ "AMERICAN BEAUTY", "has_tags", "DRAMA" ], [ "AMERICAN BEAUTY", "release_year", "1999" ], [ "ANGEL", "has_genre", "DRAMA" ], [ "ANGEL", "starred_actors", "STEPHEN REA" ], [ "ANGELA'S ASHES", "has_genre", "DRAMA" ], [ "ANGELA'S ASHES", "release_year", "1999" ], [ "ANNA AND THE KING", "has_genre", "DRAMA" ], [ "ANNA AND THE KING", "release_year", "1999" ], [ "ANY GIVEN SUNDAY", "has_genre", "DRAMA" ], [ "ANY GIVEN SUNDAY", "release_year", "1999" ], [ "ARLINGTON ROAD", "has_genre", "DRAMA" ], [ "ARLINGTON ROAD", "release_year", "1999" ], [ "AUDITION", "has_genre", "DRAMA" ], [ "AUDITION", "release_year", "1999" ], [ "BEING JOHN MALKOVICH", "has_genre", "DRAMA" ], [ "BEING JOHN MALKOVICH", "has_tags", "DRAMA" ], [ "BEING JOHN MALKOVICH", "release_year", "1999" ], [ "BETWEEN YOUR LEGS", "has_genre", "DRAMA" ], [ "BETWEEN YOUR LEGS", "release_year", "1999" ], [ "BICENTENNIAL MAN", "has_genre", "DRAMA" ], [ "BICENTENNIAL MAN", "release_year", "1999" ], [ "BOYS DON'T CRY", "has_genre", "DRAMA" ], [ "BOYS DON'T CRY", "has_tags", "DRAMA" ], [ "BOYS DON'T CRY", "release_year", "1999" ], [ "BRINGING OUT THE DEAD", "has_genre", "DRAMA" ], [ "BRINGING OUT THE DEAD", "has_tags", "DRAMA" ], [ "BRINGING OUT THE DEAD", "release_year", "1999" ], [ "BROKEDOWN PALACE", "has_genre", "DRAMA" ], [ "BROKEDOWN PALACE", "release_year", "1999" ], [ "CATFISH IN BLACK BEAN SAUCE", "has_genre", "DRAMA" ], [ "CATFISH IN BLACK BEAN SAUCE", "release_year", "1999" ], [ "CRADLE WILL ROCK", "has_genre", "DRAMA" ], [ "CRADLE WILL ROCK", "release_year", "1999" ], [ "CRAZY IN ALABAMA", "has_genre", "DRAMA" ], [ "CRAZY IN ALABAMA", "release_year", "1999" ], [ "CRUEL INTENTIONS", "has_genre", "DRAMA" ], [ "CRUEL INTENTIONS", "release_year", "1999" ], [ "DETERRENCE", "has_genre", "DRAMA" ], [ "DETERRENCE", "release_year", "1999" ], [ "DREAMING OF JOSEPH LEES", "has_genre", "DRAMA" ], [ "DREAMING OF JOSEPH LEES", "release_year", "1999" ], [ "EAST IS EAST", "has_genre", "DRAMA" ], [ "EAST IS EAST", "release_year", "1999" ], [ "ED WOOD", "has_genre", "COMEDY" ], [ "ED WOOD", "has_genre", "DRAMA" ], [ "ED WOOD", "has_tags", "ED WOOD" ], [ "ED WOOD", "written_by", "RUDOLPH GREY" ], [ "FLAWLESS", "has_genre", "DRAMA" ], [ "FLAWLESS", "release_year", "1999" ], [ "FOOLISH", "has_genre", "DRAMA" ], [ "FOOLISH", "release_year", "1999" ], [ "FOR LOVE OF THE GAME", "has_genre", "DRAMA" ], [ "FOR LOVE OF THE GAME", "release_year", "1999" ], [ "FOREVER MINE", "has_genre", "DRAMA" ], [ "FOREVER MINE", "release_year", "1999" ], [ "GIRL, INTERRUPTED", "has_genre", "DRAMA" ], [ "GIRL, INTERRUPTED", "has_tags", "DRAMA" ], [ "GIRL, INTERRUPTED", "release_year", "1999" ], [ "GLEN OR GLENDA", "has_genre", "DRAMA" ], [ "GLEN OR GLENDA", "has_tags", "ED WOOD" ], [ "GLORIA", "has_genre", "DRAMA" ], [ "GLORIA", "release_year", "1999" ], [ "GOYA IN BORDEAUX", "has_genre", "DRAMA" ], [ "GOYA IN BORDEAUX", "release_year", "1999" ], [ "GUINEVERE", "directed_by", "AUDREY WELLS" ], [ "GUINEVERE", "has_genre", "DRAMA" ], [ "GUINEVERE", "release_year", "1999" ], [ "GUINEVERE", "starred_actors", "GINA GERSHON" ], [ "GUINEVERE", "starred_actors", "SARAH POLLEY" ], [ "GUINEVERE", "starred_actors", "STEPHEN REA" ], [ "GUINEVERE", "written_by", "AUDREY WELLS" ], [ "IN TOO DEEP", "has_genre", "DRAMA" ], [ "IN TOO DEEP", "release_year", "1999" ], [ "IT ALL STARTS TODAY", "has_genre", "DRAMA" ], [ "IT ALL STARTS TODAY", "release_year", "1999" ], [ "JAKOB THE LIAR", "has_genre", "DRAMA" ], [ "JAKOB THE LIAR", "release_year", "1999" ], [ "JOE THE KING", "has_genre", "DRAMA" ], [ "JOE THE KING", "release_year", "1999" ], [ "JUDY BERLIN", "has_genre", "DRAMA" ], [ "JUDY BERLIN", "release_year", "1999" ], [ "KIKUJIRO", "has_genre", "DRAMA" ], [ "KIKUJIRO", "release_year", "1999" ], [ "KING OF COMEDY", "has_genre", "DRAMA" ], [ "KING OF COMEDY", "release_year", "1999" ], [ "LIBERTY HEIGHTS", "has_genre", "DRAMA" ], [ "LIBERTY HEIGHTS", "release_year", "1999" ], [ "LIFE", "has_genre", "DRAMA" ], [ "LIFE", "release_year", "1999" ], [ "LIGHT IT UP", "has_genre", "DRAMA" ], [ "LIGHT IT UP", "release_year", "1999" ], [ "LIMBO", "has_genre", "DRAMA" ], [ "LIMBO", "release_year", "1999" ], [ "MAGNOLIA", "has_genre", "DRAMA" ], [ "MAGNOLIA", "release_year", "1999" ], [ "MAN ON THE MOON", "has_genre", "DRAMA" ], [ "MAN ON THE MOON", "release_year", "1999" ], [ "MANSFIELD PARK", "has_genre", "DRAMA" ], [ "MANSFIELD PARK", "release_year", "1999" ], [ "MESSAGE IN A BOTTLE", "has_genre", "DRAMA" ], [ "MESSAGE IN A BOTTLE", "release_year", "1999" ], [ "MISS JULIE", "has_genre", "DRAMA" ], [ "MISS JULIE", "release_year", "1999" ], [ "MOLLY", "has_genre", "DRAMA" ], [ "MOLLY", "release_year", "1999" ], [ "MOLOCH", "has_genre", "DRAMA" ], [ "MOLOCH", "release_year", "1999" ], [ "MR. NOBODY", "has_genre", "DRAMA" ], [ "MR. NOBODY", "has_tags", "SARAH POLLEY" ], [ "MR. NOBODY", "starred_actors", "SARAH POLLEY" ], [ "MUMFORD", "has_genre", "DRAMA" ], [ "MUMFORD", "release_year", "1999" ], [ "MUSIC OF THE HEART", "has_genre", "DRAMA" ], [ "MUSIC OF THE HEART", "release_year", "1999" ], [ "MY LIFE WITHOUT ME", "has_genre", "DRAMA" ], [ "MY LIFE WITHOUT ME", "starred_actors", "SARAH POLLEY" ], [ "MYSTERY, ALASKA", "has_genre", "DRAMA" ], [ "MYSTERY, ALASKA", "release_year", "1999" ], [ "ONE MAN'S HERO", "has_genre", "DRAMA" ], [ "ONE MAN'S HERO", "release_year", "1999" ], [ "ONEGIN", "has_genre", "DRAMA" ], [ "ONEGIN", "release_year", "1999" ], [ "ORFEU", "has_genre", "DRAMA" ], [ "ORFEU", "release_year", "1999" ], [ "PLAY IT TO THE BONE", "has_genre", "DRAMA" ], [ "PLAY IT TO THE BONE", "release_year", "1999" ], [ "POLA X", "has_genre", "DRAMA" ], [ "POLA X", "release_year", "1999" ], [ "PUPS", "has_genre", "DRAMA" ], [ "PUPS", "release_year", "1999" ], [ "PUSHING TIN", "has_genre", "DRAMA" ], [ "PUSHING TIN", "release_year", "1999" ], [ "RANDOM HEARTS", "has_genre", "DRAMA" ], [ "RANDOM HEARTS", "release_year", "1999" ], [ "REUBEN, REUBEN", "has_genre", "COMEDY" ], [ "REUBEN, REUBEN", "has_genre", "DRAMA" ], [ "REUBEN, REUBEN", "written_by", "HERMAN SHUMLIN" ], [ "RIDE WITH THE DEVIL", "has_genre", "DRAMA" ], [ "RIDE WITH THE DEVIL", "release_year", "1999" ], [ "RKO 281", "has_genre", "DRAMA" ], [ "RKO 281", "release_year", "1999" ], [ "ROGUE TRADER", "has_genre", "DRAMA" ], [ "ROGUE TRADER", "release_year", "1999" ], [ "ROMANCE", "has_genre", "DRAMA" ], [ "ROMANCE", "release_year", "1999" ], [ "SCREWED IN TALLINN", "has_genre", "DRAMA" ], [ "SCREWED IN TALLINN", "release_year", "1999" ], [ "SHOWGIRLS", "has_genre", "DRAMA" ], [ "SHOWGIRLS", "starred_actors", "GINA GERSHON" ], [ "SOFT FRUIT", "has_genre", "DRAMA" ], [ "SOFT FRUIT", "release_year", "1999" ], [ "SOPHIE'S WORLD", "has_genre", "DRAMA" ], [ "SOPHIE'S WORLD", "release_year", "1999" ], [ "SWEET AND LOWDOWN", "has_genre", "DRAMA" ], [ "SWEET AND LOWDOWN", "release_year", "1999" ], [ "TAKE THIS WALTZ", "directed_by", "SARAH POLLEY" ], [ "TAKE THIS WALTZ", "has_genre", "DRAMA" ], [ "TAKE THIS WALTZ", "has_tags", "SARAH POLLEY" ], [ "TAKE THIS WALTZ", "written_by", "SARAH POLLEY" ], [ "THE BEST MAN", "has_genre", "DRAMA" ], [ "THE BEST MAN", "release_year", "1999" ], [ "THE BIG KAHUNA", "has_genre", "DRAMA" ], [ "THE BIG KAHUNA", "release_year", "1999" ], [ "THE CIDER HOUSE RULES", "has_genre", "DRAMA" ], [ "THE CIDER HOUSE RULES", "has_tags", "DRAMA" ], [ "THE CIDER HOUSE RULES", "release_year", "1999" ], [ "THE CONFESSION", "has_genre", "DRAMA" ], [ "THE CONFESSION", "release_year", "1999" ], [ "THE CRYING GAME", "has_genre", "DRAMA" ], [ "THE CRYING GAME", "has_tags", "STEPHEN REA" ], [ "THE CRYING GAME", "starred_actors", "STEPHEN REA" ], [ "THE DEBT", "has_genre", "DRAMA" ], [ "THE DEBT", "release_year", "1999" ], [ "THE DEEP END OF THE OCEAN", "has_genre", "DRAMA" ], [ "THE DEEP END OF THE OCEAN", "release_year", "1999" ], [ "THE END OF THE AFFAIR", "has_genre", "DRAMA" ], [ "THE END OF THE AFFAIR", "release_year", "1999" ], [ "THE END OF THE AFFAIR", "starred_actors", "STEPHEN REA" ], [ "THE FIVE SENSES", "has_genre", "DRAMA" ], [ "THE FIVE SENSES", "release_year", "1999" ], [ "THE GLASS AGENCY", "has_genre", "DRAMA" ], [ "THE GLASS AGENCY", "release_year", "1999" ], [ "THE GREEN MILE", "has_genre", "DRAMA" ], [ "THE GREEN MILE", "has_tags", "DRAMA" ], [ "THE GREEN MILE", "release_year", "1999" ], [ "THE HI-LINE", "has_genre", "DRAMA" ], [ "THE HI-LINE", "release_year", "1999" ], [ "THE INSIDER", "has_genre", "DRAMA" ], [ "THE INSIDER", "has_tags", "DRAMA" ], [ "THE INSIDER", "release_year", "1999" ], [ "THE JOYRIDERS", "has_genre", "DRAMA" ], [ "THE JOYRIDERS", "release_year", "1999" ], [ "THE KING AND I", "has_genre", "DRAMA" ], [ "THE KING AND I", "release_year", "1999" ], [ "THE LAW OF ENCLOSURES", "has_genre", "DRAMA" ], [ "THE LAW OF ENCLOSURES", "starred_actors", "SARAH POLLEY" ], [ "THE LOST SON", "has_genre", "DRAMA" ], [ "THE LOST SON", "release_year", "1999" ], [ "THE MISSION", "has_genre", "DRAMA" ], [ "THE MISSION", "release_year", "1999" ], [ "THE MOMENT AFTER", "has_genre", "DRAMA" ], [ "THE MOMENT AFTER", "release_year", "1999" ], [ "THE STORY OF US", "has_genre", "DRAMA" ], [ "THE STORY OF US", "has_tags", "DRAMA" ], [ "THE STORY OF US", "release_year", "1999" ], [ "THE STRAIGHT STORY", "has_genre", "DRAMA" ], [ "THE STRAIGHT STORY", "release_year", "1999" ], [ "THE SUBURBANS", "has_genre", "DRAMA" ], [ "THE SUBURBANS", "release_year", "1999" ], [ "THE THIRD MIRACLE", "has_genre", "DRAMA" ], [ "THE THIRD MIRACLE", "release_year", "1999" ], [ "THE TIC CODE", "has_genre", "DRAMA" ], [ "THE TIC CODE", "release_year", "1999" ], [ "THE VIRGIN SUICIDES", "has_genre", "DRAMA" ], [ "THE VIRGIN SUICIDES", "release_year", "1999" ], [ "THE WAR ZONE", "has_genre", "DRAMA" ], [ "THE WAR ZONE", "release_year", "1999" ], [ "THE WINSLOW BOY", "has_genre", "DRAMA" ], [ "THE WINSLOW BOY", "release_year", "1999" ], [ "TOPSY-TURVY", "has_genre", "DRAMA" ], [ "TOPSY-TURVY", "release_year", "1999" ], [ "TOUCH", "has_genre", "DRAMA" ], [ "TOUCH", "starred_actors", "GINA GERSHON" ], [ "TRUE CRIME", "has_genre", "DRAMA" ], [ "TRUE CRIME", "release_year", "1999" ], [ "TUMBLEWEEDS", "has_genre", "DRAMA" ], [ "TUMBLEWEEDS", "release_year", "1999" ], [ "UNDER THE TUSCAN SUN", "directed_by", "AUDREY WELLS" ], [ "UNDER THE TUSCAN SUN", "has_genre", "DRAMA" ], [ "UNDER THE TUSCAN SUN", "written_by", "AUDREY WELLS" ], [ "VARSITY BLUES", "has_genre", "DRAMA" ], [ "VARSITY BLUES", "release_year", "1999" ], [ "WATCH ON THE RHINE", "directed_by", "HERMAN SHUMLIN" ], [ "WATCH ON THE RHINE", "has_genre", "DRAMA" ], [ "WILDFLOWERS", "has_genre", "DRAMA" ], [ "WILDFLOWERS", "release_year", "1999" ], [ "WISCONSIN DEATH TRIP", "has_genre", "DRAMA" ], [ "WISCONSIN DEATH TRIP", "release_year", "1999" ], [ "WITH FIRE AND SWORD", "has_genre", "DRAMA" ], [ "WITH FIRE AND SWORD", "release_year", "1999" ], [ "WONDERLAND", "has_genre", "DRAMA" ], [ "WONDERLAND", "release_year", "1999" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13408, 2001 13747, 25 WATTS 1543, 61* 30721, A BEAUTIFUL MIND 19865, A.I. ARTIFICIAL INTELLIGENCE 1538, ALIAS BETTY 4141, AN AMERICAN RHAPSODY 22873, ANGEL EYES 462, AUTUMN SPRING 1156, AVALON 5593, BABY BOY 23952, BANDITS 13418, BARTLEBY 11298, BOLIVIA 20912, BRIDE OF THE WIND 26051, BRIDESHEAD REVISITED 7461, BROTHERHOOD OF THE WOLF 17892, CAMOUFLAGE 29794, CHARLOTTE GRAY 10293, CONSPIRACY 23979, CRAZY/BEAUTIFUL 656, CRUSH 1915, DIL CHAHTA HAI 7281, DON'S PLUM 22255, DONNIE DARKO 8704, DR. DOLITTLE 2 36212, DRAMA 27747, DRIVEN 17266, DUST 19194, ENIGMA 24686, FATE 6915, FOCUS 12664, GHOST WORLD 38300, GLITTER 15389, GYPSY 83 21060, HARVARD MAN 19139, HEARTS IN ATLANTIS 1292, HEDWIG AND THE ANGRY INCH 38901, HIGH HEELS AND LOW LIFES 22858, HISTORY IS MADE AT NIGHT 35625, HUMAN NATURE 10714, I AM SAM 20430, IN THE BEDROOM 23380, INVINCIBLE 23526, JACKPOT 12610, JOE SOMEBODY 31226, JULIE JOHNSON 6206, KABHI KHUSHI KABHIE GHAM... 7699, KINGDOM COME 7888, L.I.E. 19121, LAST ORDERS 18370, LEO CARRILLO 39962, LIFE AS A HOUSE 29734, LITTLE SECRETS 22386, LOST AND DELIRIOUS 17728, MAD LOVE 30062, MANIC 33714, MEAN MACHINE 14565, MONSTER'S BALL 24616, MOSTLY MARTHA 10824, O 32514, ONE 2 KA 4 32186, ONE MAN UP 28044, PAULINE AND PAULETTE 234, PEARL HARBOR 28106, PROZAC NATION 8367, RAIN 28182, RARE BIRDS 38381, ROCK STAR 29441, SEX AND LUCIA 2407, SON OF THE BRIDE 7949, STORYTELLING 27762, SWEET NOVEMBER 15887, TAPE 13270, TEXAS RANGERS 2582, THE AFFAIR OF THE NECKLACE 15795, THE ANNIVERSARY PARTY 33436, THE BANK 267, THE BELIEVER 25674, THE BROTHERS 30854, THE CAT'S MEOW 4946, THE CAVEMAN'S VALENTINE 14993, THE INVISIBLE CIRCUS 23268, THE JIMMY SHOW 4143, THE LAST CASTLE 28107, THE LAST KISS 12566, THE MAJESTIC 23940, THE MAN FROM ELYSIAN FIELDS 22538, THE OTHER SIDE OF HEAVEN 27573, THE OTHERS 39469, THE PORNOGRAPHER 18649, THE RIVER 20728, THE ROYAL TENENBAUMS 23798, THE SHIPPING NEWS 27910, THE UNSAID 38275, THIRTEEN CONVERSATIONS ABOUT ONE THING 25783, TIME OUT 27854, TO THE LEFT OF THE FATHER 35988, TORTILLA SOUP 8974, TREED MURRAY 17093, UNFAIR COMPETITION 6655, UPRISING 35443, VIZONTELE 18892, WAKING LIFE 19926, WORLD TRAVELER 25391, Y TU MAMÁ TAMBIÉN src, edge_attr, dst 13747, has_genre, 36212 13747, release_year, 13408 1543, has_genre, 36212 1543, release_year, 13408 30721, has_genre, 36212 30721, has_tags, 36212 30721, release_year, 13408 19865, has_genre, 36212 19865, release_year, 13408 1538, has_genre, 36212 1538, release_year, 13408 4141, has_genre, 36212 4141, release_year, 13408 22873, has_genre, 36212 22873, release_year, 13408 462, has_genre, 36212 462, release_year, 13408 1156, has_genre, 36212 1156, release_year, 13408 5593, has_genre, 36212 5593, release_year, 13408 23952, has_genre, 36212 23952, release_year, 13408 13418, has_genre, 36212 13418, release_year, 13408 11298, has_genre, 36212 11298, release_year, 13408 20912, has_genre, 36212 20912, release_year, 13408 26051, has_genre, 36212 7461, has_genre, 36212 7461, release_year, 13408 17892, has_genre, 36212 17892, release_year, 13408 29794, has_genre, 36212 29794, release_year, 13408 10293, has_genre, 36212 10293, release_year, 13408 23979, has_genre, 36212 23979, release_year, 13408 656, has_genre, 36212 656, release_year, 13408 1915, has_genre, 36212 1915, release_year, 13408 7281, has_genre, 36212 7281, release_year, 13408 22255, has_genre, 36212 22255, release_year, 13408 8704, release_year, 13408 27747, has_genre, 36212 27747, release_year, 13408 17266, has_genre, 36212 17266, release_year, 13408 19194, has_genre, 36212 19194, release_year, 13408 24686, has_genre, 36212 24686, release_year, 13408 6915, has_genre, 36212 6915, release_year, 13408 12664, has_genre, 36212 12664, release_year, 13408 38300, has_genre, 36212 38300, release_year, 13408 15389, has_genre, 36212 15389, release_year, 13408 21060, has_genre, 36212 21060, release_year, 13408 19139, has_genre, 36212 19139, release_year, 13408 1292, has_genre, 36212 1292, release_year, 13408 38901, has_genre, 36212 38901, release_year, 13408 22858, has_genre, 36212 22858, starred_actors, 18370 35625, has_genre, 36212 35625, release_year, 13408 10714, has_genre, 36212 10714, release_year, 13408 20430, has_genre, 36212 20430, has_tags, 36212 20430, release_year, 13408 23380, has_genre, 36212 23380, release_year, 13408 23526, has_genre, 36212 23526, release_year, 13408 12610, has_genre, 36212 12610, release_year, 13408 31226, has_genre, 36212 31226, release_year, 13408 6206, has_genre, 36212 6206, release_year, 13408 7699, has_genre, 36212 7699, release_year, 13408 7888, has_genre, 36212 7888, release_year, 13408 19121, has_genre, 36212 19121, release_year, 13408 39962, has_genre, 36212 39962, release_year, 13408 29734, has_genre, 36212 29734, release_year, 13408 22386, has_genre, 36212 22386, release_year, 13408 17728, has_genre, 36212 17728, release_year, 13408 30062, has_genre, 36212 30062, release_year, 13408 33714, has_genre, 36212 33714, release_year, 13408 14565, has_genre, 36212 14565, release_year, 13408 24616, has_genre, 36212 24616, release_year, 13408 10824, has_genre, 36212 10824, release_year, 13408 32514, has_genre, 36212 32514, release_year, 13408 32186, has_genre, 36212 32186, release_year, 13408 28044, has_genre, 36212 28044, release_year, 13408 234, has_genre, 36212 234, has_tags, 36212 234, release_year, 13408 28106, has_genre, 36212 28106, release_year, 13408 8367, has_genre, 36212 8367, release_year, 13408 28182, has_genre, 36212 28182, release_year, 13408 38381, has_genre, 36212 38381, release_year, 13408 29441, has_genre, 36212 29441, release_year, 13408 2407, has_genre, 36212 2407, release_year, 13408 7949, has_genre, 36212 7949, release_year, 13408 27762, has_genre, 36212 27762, release_year, 13408 15887, has_genre, 36212 15887, release_year, 13408 13270, has_genre, 36212 13270, release_year, 13408 2582, has_genre, 36212 2582, release_year, 13408 15795, has_genre, 36212 15795, release_year, 13408 33436, has_genre, 36212 33436, release_year, 13408 267, has_genre, 36212 267, release_year, 13408 25674, has_genre, 36212 25674, release_year, 13408 30854, has_genre, 36212 30854, release_year, 13408 4946, has_genre, 36212 4946, release_year, 13408 14993, has_genre, 36212 14993, release_year, 13408 23268, has_genre, 36212 23268, release_year, 13408 4143, has_genre, 36212 4143, release_year, 13408 28107, has_genre, 36212 28107, release_year, 13408 12566, has_genre, 36212 12566, release_year, 13408 23940, has_genre, 36212 23940, release_year, 13408 22538, has_genre, 36212 22538, release_year, 13408 27573, has_tags, 36212 27573, release_year, 13408 39469, has_genre, 36212 39469, release_year, 13408 18649, has_genre, 36212 18649, release_year, 13408 20728, has_genre, 36212 20728, release_year, 13408 23798, has_genre, 36212 23798, release_year, 13408 27910, has_genre, 36212 27910, release_year, 13408 38275, has_genre, 36212 38275, release_year, 13408 25783, has_genre, 36212 25783, release_year, 13408 27854, has_genre, 36212 27854, release_year, 13408 35988, has_genre, 36212 35988, release_year, 13408 8974, has_genre, 36212 8974, release_year, 13408 17093, has_genre, 36212 17093, release_year, 13408 6655, has_genre, 36212 6655, release_year, 13408 35443, has_genre, 36212 35443, release_year, 13408 18892, has_genre, 36212 18892, release_year, 13408 19926, has_genre, 36212 19926, release_year, 13408 25391, has_genre, 36212 25391, has_tags, 36212 25391, release_year, 13408 Question: How are BRIDESHEAD REVISITED, DR. DOLITTLE 2, and LEO CARRILLO related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BRIDESHEAD REVISITED", "DR. DOLITTLE 2", "LEO CARRILLO" ], "valid_edges": [ [ "25 WATTS", "has_genre", "DRAMA" ], [ "25 WATTS", "release_year", "2001" ], [ "61", "has_genre", "DRAMA" ], [ "61", "release_year", "2001" ], [ "A BEAUTIFUL MIND", "has_genre", "DRAMA" ], [ "A BEAUTIFUL MIND", "has_tags", "DRAMA" ], [ "A BEAUTIFUL MIND", "release_year", "2001" ], [ "A.I. ARTIFICIAL INTELLIGENCE", "has_genre", "DRAMA" ], [ "A.I. ARTIFICIAL INTELLIGENCE", "release_year", "2001" ], [ "ALIAS BETTY", "has_genre", "DRAMA" ], [ "ALIAS BETTY", "release_year", "2001" ], [ "AN AMERICAN RHAPSODY", "has_genre", "DRAMA" ], [ "AN AMERICAN RHAPSODY", "release_year", "2001" ], [ "ANGEL EYES", "has_genre", "DRAMA" ], [ "ANGEL EYES", "release_year", "2001" ], [ "AUTUMN SPRING", "has_genre", "DRAMA" ], [ "AUTUMN SPRING", "release_year", "2001" ], [ "AVALON", "has_genre", "DRAMA" ], [ "AVALON", "release_year", "2001" ], [ "BABY BOY", "has_genre", "DRAMA" ], [ "BABY BOY", "release_year", "2001" ], [ "BANDITS", "has_genre", "DRAMA" ], [ "BANDITS", "release_year", "2001" ], [ "BARTLEBY", "has_genre", "DRAMA" ], [ "BARTLEBY", "release_year", "2001" ], [ "BOLIVIA", "has_genre", "DRAMA" ], [ "BOLIVIA", "release_year", "2001" ], [ "BRIDE OF THE WIND", "has_genre", "DRAMA" ], [ "BRIDE OF THE WIND", "release_year", "2001" ], [ "BRIDESHEAD REVISITED", "has_genre", "DRAMA" ], [ "BROTHERHOOD OF THE WOLF", "has_genre", "DRAMA" ], [ "BROTHERHOOD OF THE WOLF", "release_year", "2001" ], [ "CAMOUFLAGE", "has_genre", "DRAMA" ], [ "CAMOUFLAGE", "release_year", "2001" ], [ "CHARLOTTE GRAY", "has_genre", "DRAMA" ], [ "CHARLOTTE GRAY", "release_year", "2001" ], [ "CONSPIRACY", "has_genre", "DRAMA" ], [ "CONSPIRACY", "release_year", "2001" ], [ "CRAZY/BEAUTIFUL", "has_genre", "DRAMA" ], [ "CRAZY/BEAUTIFUL", "release_year", "2001" ], [ "CRUSH", "has_genre", "DRAMA" ], [ "CRUSH", "release_year", "2001" ], [ "DIL CHAHTA HAI", "has_genre", "DRAMA" ], [ "DIL CHAHTA HAI", "release_year", "2001" ], [ "DON'S PLUM", "has_genre", "DRAMA" ], [ "DON'S PLUM", "release_year", "2001" ], [ "DONNIE DARKO", "has_genre", "DRAMA" ], [ "DONNIE DARKO", "release_year", "2001" ], [ "DR. DOLITTLE 2", "release_year", "2001" ], [ "DRIVEN", "has_genre", "DRAMA" ], [ "DRIVEN", "release_year", "2001" ], [ "DUST", "has_genre", "DRAMA" ], [ "DUST", "release_year", "2001" ], [ "ENIGMA", "has_genre", "DRAMA" ], [ "ENIGMA", "release_year", "2001" ], [ "FATE", "has_genre", "DRAMA" ], [ "FATE", "release_year", "2001" ], [ "FOCUS", "has_genre", "DRAMA" ], [ "FOCUS", "release_year", "2001" ], [ "GHOST WORLD", "has_genre", "DRAMA" ], [ "GHOST WORLD", "release_year", "2001" ], [ "GLITTER", "has_genre", "DRAMA" ], [ "GLITTER", "release_year", "2001" ], [ "GYPSY 83", "has_genre", "DRAMA" ], [ "GYPSY 83", "release_year", "2001" ], [ "HARVARD MAN", "has_genre", "DRAMA" ], [ "HARVARD MAN", "release_year", "2001" ], [ "HEARTS IN ATLANTIS", "has_genre", "DRAMA" ], [ "HEARTS IN ATLANTIS", "release_year", "2001" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "DRAMA" ], [ "HEDWIG AND THE ANGRY INCH", "release_year", "2001" ], [ "HIGH HEELS AND LOW LIFES", "has_genre", "DRAMA" ], [ "HIGH HEELS AND LOW LIFES", "release_year", "2001" ], [ "HISTORY IS MADE AT NIGHT", "has_genre", "DRAMA" ], [ "HISTORY IS MADE AT NIGHT", "starred_actors", "LEO CARRILLO" ], [ "HUMAN NATURE", "has_genre", "DRAMA" ], [ "HUMAN NATURE", "release_year", "2001" ], [ "I AM SAM", "has_genre", "DRAMA" ], [ "I AM SAM", "release_year", "2001" ], [ "IN THE BEDROOM", "has_genre", "DRAMA" ], [ "IN THE BEDROOM", "has_tags", "DRAMA" ], [ "IN THE BEDROOM", "release_year", "2001" ], [ "INVINCIBLE", "has_genre", "DRAMA" ], [ "INVINCIBLE", "release_year", "2001" ], [ "JACKPOT", "has_genre", "DRAMA" ], [ "JACKPOT", "release_year", "2001" ], [ "JOE SOMEBODY", "has_genre", "DRAMA" ], [ "JOE SOMEBODY", "release_year", "2001" ], [ "JULIE JOHNSON", "has_genre", "DRAMA" ], [ "JULIE JOHNSON", "release_year", "2001" ], [ "KABHI KHUSHI KABHIE GHAM...", "has_genre", "DRAMA" ], [ "KABHI KHUSHI KABHIE GHAM...", "release_year", "2001" ], [ "KINGDOM COME", "has_genre", "DRAMA" ], [ "KINGDOM COME", "release_year", "2001" ], [ "L.I.E.", "has_genre", "DRAMA" ], [ "L.I.E.", "release_year", "2001" ], [ "LAST ORDERS", "has_genre", "DRAMA" ], [ "LAST ORDERS", "release_year", "2001" ], [ "LIFE AS A HOUSE", "has_genre", "DRAMA" ], [ "LIFE AS A HOUSE", "release_year", "2001" ], [ "LITTLE SECRETS", "has_genre", "DRAMA" ], [ "LITTLE SECRETS", "release_year", "2001" ], [ "LOST AND DELIRIOUS", "has_genre", "DRAMA" ], [ "LOST AND DELIRIOUS", "release_year", "2001" ], [ "MAD LOVE", "has_genre", "DRAMA" ], [ "MAD LOVE", "release_year", "2001" ], [ "MANIC", "has_genre", "DRAMA" ], [ "MANIC", "release_year", "2001" ], [ "MEAN MACHINE", "has_genre", "DRAMA" ], [ "MEAN MACHINE", "release_year", "2001" ], [ "MONSTER'S BALL", "has_genre", "DRAMA" ], [ "MONSTER'S BALL", "release_year", "2001" ], [ "MOSTLY MARTHA", "has_genre", "DRAMA" ], [ "MOSTLY MARTHA", "release_year", "2001" ], [ "O", "has_genre", "DRAMA" ], [ "O", "release_year", "2001" ], [ "ONE 2 KA 4", "has_genre", "DRAMA" ], [ "ONE 2 KA 4", "release_year", "2001" ], [ "ONE MAN UP", "has_genre", "DRAMA" ], [ "ONE MAN UP", "release_year", "2001" ], [ "PAULINE AND PAULETTE", "has_genre", "DRAMA" ], [ "PAULINE AND PAULETTE", "release_year", "2001" ], [ "PEARL HARBOR", "has_genre", "DRAMA" ], [ "PEARL HARBOR", "has_tags", "DRAMA" ], [ "PEARL HARBOR", "release_year", "2001" ], [ "PROZAC NATION", "has_genre", "DRAMA" ], [ "PROZAC NATION", "release_year", "2001" ], [ "RAIN", "has_genre", "DRAMA" ], [ "RAIN", "release_year", "2001" ], [ "RARE BIRDS", "has_genre", "DRAMA" ], [ "RARE BIRDS", "release_year", "2001" ], [ "ROCK STAR", "has_genre", "DRAMA" ], [ "ROCK STAR", "release_year", "2001" ], [ "SEX AND LUCIA", "has_genre", "DRAMA" ], [ "SEX AND LUCIA", "release_year", "2001" ], [ "SON OF THE BRIDE", "has_genre", "DRAMA" ], [ "SON OF THE BRIDE", "release_year", "2001" ], [ "STORYTELLING", "has_genre", "DRAMA" ], [ "STORYTELLING", "release_year", "2001" ], [ "SWEET NOVEMBER", "has_genre", "DRAMA" ], [ "SWEET NOVEMBER", "release_year", "2001" ], [ "TAPE", "has_genre", "DRAMA" ], [ "TAPE", "release_year", "2001" ], [ "TEXAS RANGERS", "has_genre", "DRAMA" ], [ "TEXAS RANGERS", "release_year", "2001" ], [ "THE AFFAIR OF THE NECKLACE", "has_genre", "DRAMA" ], [ "THE AFFAIR OF THE NECKLACE", "release_year", "2001" ], [ "THE ANNIVERSARY PARTY", "has_genre", "DRAMA" ], [ "THE ANNIVERSARY PARTY", "release_year", "2001" ], [ "THE BANK", "has_genre", "DRAMA" ], [ "THE BANK", "release_year", "2001" ], [ "THE BELIEVER", "has_genre", "DRAMA" ], [ "THE BELIEVER", "release_year", "2001" ], [ "THE BROTHERS", "has_genre", "DRAMA" ], [ "THE BROTHERS", "release_year", "2001" ], [ "THE CAT'S MEOW", "has_genre", "DRAMA" ], [ "THE CAT'S MEOW", "release_year", "2001" ], [ "THE CAVEMAN'S VALENTINE", "has_genre", "DRAMA" ], [ "THE CAVEMAN'S VALENTINE", "release_year", "2001" ], [ "THE INVISIBLE CIRCUS", "has_genre", "DRAMA" ], [ "THE INVISIBLE CIRCUS", "release_year", "2001" ], [ "THE JIMMY SHOW", "has_genre", "DRAMA" ], [ "THE JIMMY SHOW", "release_year", "2001" ], [ "THE LAST CASTLE", "has_genre", "DRAMA" ], [ "THE LAST CASTLE", "release_year", "2001" ], [ "THE LAST KISS", "has_genre", "DRAMA" ], [ "THE LAST KISS", "release_year", "2001" ], [ "THE MAJESTIC", "has_genre", "DRAMA" ], [ "THE MAJESTIC", "release_year", "2001" ], [ "THE MAN FROM ELYSIAN FIELDS", "has_genre", "DRAMA" ], [ "THE MAN FROM ELYSIAN FIELDS", "release_year", "2001" ], [ "THE OTHER SIDE OF HEAVEN", "has_genre", "DRAMA" ], [ "THE OTHER SIDE OF HEAVEN", "release_year", "2001" ], [ "THE OTHERS", "has_tags", "DRAMA" ], [ "THE OTHERS", "release_year", "2001" ], [ "THE PORNOGRAPHER", "has_genre", "DRAMA" ], [ "THE PORNOGRAPHER", "release_year", "2001" ], [ "THE RIVER", "has_genre", "DRAMA" ], [ "THE RIVER", "release_year", "2001" ], [ "THE ROYAL TENENBAUMS", "has_genre", "DRAMA" ], [ "THE ROYAL TENENBAUMS", "release_year", "2001" ], [ "THE SHIPPING NEWS", "has_genre", "DRAMA" ], [ "THE SHIPPING NEWS", "release_year", "2001" ], [ "THE UNSAID", "has_genre", "DRAMA" ], [ "THE UNSAID", "release_year", "2001" ], [ "THIRTEEN CONVERSATIONS ABOUT ONE THING", "has_genre", "DRAMA" ], [ "THIRTEEN CONVERSATIONS ABOUT ONE THING", "release_year", "2001" ], [ "TIME OUT", "has_genre", "DRAMA" ], [ "TIME OUT", "release_year", "2001" ], [ "TO THE LEFT OF THE FATHER", "has_genre", "DRAMA" ], [ "TO THE LEFT OF THE FATHER", "release_year", "2001" ], [ "TORTILLA SOUP", "has_genre", "DRAMA" ], [ "TORTILLA SOUP", "release_year", "2001" ], [ "TREED MURRAY", "has_genre", "DRAMA" ], [ "TREED MURRAY", "release_year", "2001" ], [ "UNFAIR COMPETITION", "has_genre", "DRAMA" ], [ "UNFAIR COMPETITION", "release_year", "2001" ], [ "UPRISING", "has_genre", "DRAMA" ], [ "UPRISING", "release_year", "2001" ], [ "VIZONTELE", "has_genre", "DRAMA" ], [ "VIZONTELE", "release_year", "2001" ], [ "WAKING LIFE", "has_genre", "DRAMA" ], [ "WAKING LIFE", "release_year", "2001" ], [ "WORLD TRAVELER", "has_genre", "DRAMA" ], [ "WORLD TRAVELER", "release_year", "2001" ], [ "Y TU MAMÁ TAMBIÉN", "has_genre", "DRAMA" ], [ "Y TU MAMÁ TAMBIÉN", "has_tags", "DRAMA" ], [ "Y TU MAMÁ TAMBIÉN", "release_year", "2001" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37608, AUSTRALIA 7795, BEN CHAPLIN 19633, BIRTHDAY GIRL 9700, DINGO 4931, HOW DO YOU KNOW 10942, MIDNIGHT IN PARIS 9336, NICOLE KIDMAN 31494, OWEN WILSON 31134, PARIS src, edge_attr, dst 37608, has_tags, 37608 37608, has_tags, 9336 19633, has_tags, 9336 19633, starred_actors, 7795 19633, starred_actors, 9336 9700, has_tags, 37608 9700, has_tags, 31134 4931, starred_actors, 31494 10942, has_tags, 31494 10942, has_tags, 31134 10942, starred_actors, 31494 Question: In what context are BEN CHAPLIN, DINGO, and HOW DO YOU KNOW connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BEN CHAPLIN", "DINGO", "HOW DO YOU KNOW" ], "valid_edges": [ [ "AUSTRALIA", "has_tags", "AUSTRALIA" ], [ "AUSTRALIA", "has_tags", "NICOLE KIDMAN" ], [ "BIRTHDAY GIRL", "has_tags", "NICOLE KIDMAN" ], [ "BIRTHDAY GIRL", "starred_actors", "BEN CHAPLIN" ], [ "BIRTHDAY GIRL", "starred_actors", "NICOLE KIDMAN" ], [ "DINGO", "has_tags", "AUSTRALIA" ], [ "DINGO", "has_tags", "PARIS" ], [ "HOW DO YOU KNOW", "starred_actors", "OWEN WILSON" ], [ "MIDNIGHT IN PARIS", "has_tags", "OWEN WILSON" ], [ "MIDNIGHT IN PARIS", "has_tags", "PARIS" ], [ "MIDNIGHT IN PARIS", "starred_actors", "OWEN WILSON" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1892, 1932 25221, 1981 35798, 2010 9532, ARE YOU LISTENING? 14984, BLOW OUT 8065, BRIAN DE PALMA 30463, COMEDY 36212, DRAMA 31783, ENGLISH 31955, FAST LIFE 24396, GET SHORTY 9931, JANE GOLDMAN 7690, JOHN LITHGOW 27999, JOHN TRAVOLTA 16959, JUST A GIGOLO 12359, KICK-ASS 29701, MADGE EVANS 15370, MATTHEW VAUGHN 19479, SISTERS 28810, TATTOO 25509, THE DEBT 31970, THE GIRL SAID NO 3437, THE WOMAN IN BLACK 24811, THRILLER 3475, WILLIAM HAINES src, edge_attr, dst 25221, has_genre, 30463 25221, has_genre, 36212 35798, has_tags, 7690 35798, starred_actors, 7690 9532, has_genre, 36212 9532, release_year, 1892 9532, starred_actors, 29701 9532, starred_actors, 3475 14984, directed_by, 8065 14984, has_genre, 24811 14984, has_tags, 8065 14984, release_year, 25221 14984, starred_actors, 7690 14984, starred_actors, 27999 14984, written_by, 8065 31955, has_genre, 30463 31955, release_year, 1892 31955, starred_actors, 29701 31955, starred_actors, 3475 24396, has_genre, 24811 24396, has_tags, 27999 24396, starred_actors, 27999 16959, has_genre, 30463 16959, starred_actors, 3475 12359, directed_by, 15370 12359, has_genre, 30463 12359, has_tags, 15370 12359, release_year, 35798 12359, written_by, 9931 12359, written_by, 15370 19479, directed_by, 8065 19479, has_genre, 24811 19479, has_tags, 8065 19479, written_by, 8065 28810, has_genre, 24811 28810, release_year, 25221 25509, has_genre, 36212 25509, has_genre, 24811 25509, in_language, 31783 25509, release_year, 35798 25509, written_by, 9931 25509, written_by, 15370 31970, has_genre, 30463 31970, starred_actors, 3475 3437, has_genre, 36212 3437, in_language, 31783 3437, written_by, 9931 Question: In what context are BLOW OUT, JANE GOLDMAN, and WILLIAM HAINES connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BLOW OUT", "JANE GOLDMAN", "WILLIAM HAINES" ], "valid_edges": [ [ "1981", "has_genre", "COMEDY" ], [ "1981", "has_genre", "DRAMA" ], [ "2010", "has_tags", "JOHN LITHGOW" ], [ "2010", "starred_actors", "JOHN LITHGOW" ], [ "ARE YOU LISTENING?", "has_genre", "DRAMA" ], [ "ARE YOU LISTENING?", "release_year", "1932" ], [ "ARE YOU LISTENING?", "starred_actors", "MADGE EVANS" ], [ "ARE YOU LISTENING?", "starred_actors", "WILLIAM HAINES" ], [ "BLOW OUT", "directed_by", "BRIAN DE PALMA" ], [ "BLOW OUT", "has_genre", "THRILLER" ], [ "BLOW OUT", "has_tags", "BRIAN DE PALMA" ], [ "BLOW OUT", "release_year", "1981" ], [ "BLOW OUT", "starred_actors", "JOHN LITHGOW" ], [ "BLOW OUT", "starred_actors", "JOHN TRAVOLTA" ], [ "BLOW OUT", "written_by", "BRIAN DE PALMA" ], [ "FAST LIFE", "has_genre", "COMEDY" ], [ "FAST LIFE", "release_year", "1932" ], [ "FAST LIFE", "starred_actors", "MADGE EVANS" ], [ "FAST LIFE", "starred_actors", "WILLIAM HAINES" ], [ "GET SHORTY", "has_genre", "THRILLER" ], [ "GET SHORTY", "has_tags", "JOHN TRAVOLTA" ], [ "GET SHORTY", "starred_actors", "JOHN TRAVOLTA" ], [ "JUST A GIGOLO", "has_genre", "COMEDY" ], [ "JUST A GIGOLO", "starred_actors", "WILLIAM HAINES" ], [ "KICK-ASS", "directed_by", "MATTHEW VAUGHN" ], [ "KICK-ASS", "has_genre", "COMEDY" ], [ "KICK-ASS", "has_tags", "MATTHEW VAUGHN" ], [ "KICK-ASS", "release_year", "2010" ], [ "KICK-ASS", "written_by", "JANE GOLDMAN" ], [ "KICK-ASS", "written_by", "MATTHEW VAUGHN" ], [ "SISTERS", "directed_by", "BRIAN DE PALMA" ], [ "SISTERS", "has_genre", "THRILLER" ], [ "SISTERS", "has_tags", "BRIAN DE PALMA" ], [ "SISTERS", "written_by", "BRIAN DE PALMA" ], [ "TATTOO", "has_genre", "THRILLER" ], [ "TATTOO", "release_year", "1981" ], [ "THE DEBT", "has_genre", "DRAMA" ], [ "THE DEBT", "has_genre", "THRILLER" ], [ "THE DEBT", "in_language", "ENGLISH" ], [ "THE DEBT", "release_year", "2010" ], [ "THE DEBT", "written_by", "JANE GOLDMAN" ], [ "THE DEBT", "written_by", "MATTHEW VAUGHN" ], [ "THE GIRL SAID NO", "has_genre", "COMEDY" ], [ "THE GIRL SAID NO", "starred_actors", "WILLIAM HAINES" ], [ "THE WOMAN IN BLACK", "has_genre", "DRAMA" ], [ "THE WOMAN IN BLACK", "in_language", "ENGLISH" ], [ "THE WOMAN IN BLACK", "written_by", "JANE GOLDMAN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1678, 12 AND HOLDING 15374, 2005 17315, 2007 33461, 3 NEEDLES 7596, 4 28189, A LITTLE TRIP TO HEAVEN 29838, A SIMPLE TWIST OF FATE 26599, AMERICAN GUN 29881, AMERICANO 2888, AN UNFINISHED LIFE 27981, ANGEL-A 7302, AS COOL AS I AM 38707, ASYLUM 4499, AURORA BOREALIS 30335, BE WITH ME 31574, BEE SEASON 32479, BEWITCHED 37840, BLACK 29183, BREAKFAST ON PLUTO 11547, BROKEBACK MOUNTAIN 7918, BROKEDOWN PALACE 13657, BROKEN FLOWERS 19004, CAKE 29797, CINDERELLA MAN 8188, CLAIRE DANES 29211, COACH CARTER 31346, CONVERSATIONS WITH OTHER WOMEN 23452, DARK HORSE 32232, DIARY OF A MAD BLACK WOMAN 7347, DIRTY 24798, DON'T COME KNOCKING 36212, DRAMA 15272, DUMA 254, EDMOND 37496, ELIZABETHTOWN 24494, ELLIE PARKER 27441, ENTRE SES MAINS 38285, EVERYTHING IS ILLUMINATED 15891, FETCHING CODY 18446, FEVER PITCH 7391, FIERCE PEOPLE 24013, FROZEN LAND 5514, FUNNY PEOPLE 7770, GABRIELLE 16048, GET RICH OR DIE TRYIN' 6129, HAVOC 29188, HEADING SOUTH 31330, HOME 17197, IGBY GOES DOWN 12076, IN HER SHOES 1321, IRON ISLAND 6425, IT'S ALL ABOUT LOVE 15012, JARHEAD 24985, JASON SCHWARTZMAN 17160, JUNEBUG 26406, KINKY BOOTS 4794, LAST DAYS 14601, LES MISÉRABLES 29912, LIE WITH ME 17319, LONDON 3459, LONESOME JIM 35537, LORDS OF DOGTOWN 19802, LOVE 1691, LOVE'S LONG JOURNEY 21036, LOWER CITY 9938, MAN TO MAN 35670, MANDERLAY 14037, MARY 13531, MATCH POINT 570, MAUREEN MEDVED 11837, ME AND YOU AND EVERYONE WE KNOW 34359, MELISSA P. 16393, MISSING IN AMERICA 23481, MOACYR GÓES 38312, MOUTH TO MOUTH 17433, MOZART AND THE WHALE 37073, MRS. PALFREY AT THE CLAREMONT 8747, MUNICH 21030, NANA 25269, NINE LIVES 30931, NORTH COUNTRY 27113, O HOMEM QUE DESAFIOU O DIABO 14234, ODD GIRL OUT 15644, OLIVER TWIST 21568, ON A CLEAR DAY 5023, PARENTHOOD 23964, PENNIES FROM HEAVEN 20164, PRETTY PERSUASION 4584, PROOF 34066, PUZZLEHEAD 3781, QUO VADIS, BABY? 8871, RENT 17151, REVOLVER 27361, RIDING ALONE FOR THOUSANDS OF MILES 313, ROLL BOUNCE 21719, ROMANZO CRIMINALE 26229, ROMEO + JULIET 12153, RUSHMORE 35586, SAHARA 30441, SEPARATE LIES 4635, SERENITY 36273, SEXUAL LIFE 21176, SHOPGIRL 10925, SLOW BURN 15382, SOMETIMES IN APRIL 35843, SPUN 26621, STAY 24849, STEVE MARTIN 38027, SUNFLOWER 5569, SWEET LAND 11773, THANK YOU FOR SMOKING 34274, THE BALLAD OF JACK AND ROSE 17864, THE CHUMSCRUBBER 18142, THE CONSTANT GARDENER 35261, THE DARJEELING LIMITED 16597, THE DYING GAUL 7366, THE EXORCISM OF EMILY ROSE 28948, THE FAMILY STONE 10802, THE GAME OF THEIR LIVES 33315, THE GIRL IN THE CAFÉ 20237, THE ICE HARVEST 35165, THE ITALIAN 30360, THE KING 20223, THE LONGEST YARD 24108, THE MAN 8022, THE NEW WORLD 8970, THE PRINCE OF EGYPT 27029, THE PROPOSITION 19644, THE QUIET 16072, THE RAINMAKER 7237, THE SISTERHOOD OF THE TRAVELING PANTS 32210, THE SQUID AND THE WHALE 21548, THE SUN 31827, THE THING ABOUT MY FOLKS 35215, THE TRACEY FRAGMENTS 7168, THE UPSIDE OF ANGER 39409, THE VIOLIN 21433, THE WAR WITHIN 11407, THE WEATHER MAN 34902, THE WHITE COUNTESS 631, THUMBSUCKER 9970, TICKETS 38564, TO GILLIAN ON HER 37TH BIRTHDAY 20251, TO PAINT OR MAKE LOVE 22342, TRANSAMERICA 36820, TWO FOR THE MONEY 10855, WAH-WAH 7715, WALK THE LINE 39965, WHAT IS IT? src, edge_attr, dst 1678, has_genre, 36212 1678, release_year, 15374 33461, has_genre, 36212 33461, release_year, 15374 7596, has_genre, 36212 7596, release_year, 15374 28189, has_genre, 36212 28189, release_year, 15374 29838, has_genre, 36212 29838, starred_actors, 24849 29838, written_by, 24849 26599, has_genre, 36212 26599, release_year, 15374 29881, has_genre, 36212 29881, release_year, 15374 2888, has_genre, 36212 2888, release_year, 15374 27981, has_genre, 36212 27981, release_year, 15374 7302, has_genre, 36212 7302, starred_actors, 8188 38707, has_genre, 36212 38707, release_year, 15374 4499, has_genre, 36212 4499, release_year, 15374 30335, has_genre, 36212 30335, release_year, 15374 31574, has_genre, 36212 31574, release_year, 15374 32479, has_genre, 36212 32479, release_year, 15374 37840, has_genre, 36212 37840, release_year, 15374 29183, has_genre, 36212 29183, release_year, 15374 11547, has_genre, 36212 11547, release_year, 15374 7918, has_genre, 36212 7918, starred_actors, 8188 13657, has_genre, 36212 13657, has_tags, 36212 13657, release_year, 15374 19004, has_genre, 36212 19004, release_year, 15374 29797, has_genre, 36212 29797, release_year, 15374 29211, has_genre, 36212 29211, release_year, 15374 31346, has_genre, 36212 31346, release_year, 15374 23452, has_genre, 36212 23452, release_year, 15374 32232, has_genre, 36212 32232, release_year, 15374 7347, has_genre, 36212 7347, release_year, 15374 24798, has_genre, 36212 24798, release_year, 15374 15272, has_genre, 36212 15272, release_year, 15374 254, has_genre, 36212 254, release_year, 15374 37496, has_genre, 36212 37496, release_year, 15374 24494, has_genre, 36212 24494, release_year, 15374 27441, has_genre, 36212 27441, release_year, 15374 38285, has_genre, 36212 38285, has_tags, 36212 38285, release_year, 15374 15891, has_genre, 36212 15891, release_year, 15374 18446, has_genre, 36212 18446, release_year, 15374 7391, has_genre, 36212 7391, release_year, 15374 24013, has_genre, 36212 24013, release_year, 15374 5514, has_genre, 36212 5514, has_tags, 36212 5514, has_tags, 24985 7770, has_genre, 36212 7770, release_year, 15374 16048, has_genre, 36212 16048, release_year, 15374 6129, has_genre, 36212 6129, release_year, 15374 29188, has_genre, 36212 29188, release_year, 15374 31330, has_genre, 36212 31330, starred_actors, 24849 17197, has_genre, 36212 17197, has_tags, 8188 17197, starred_actors, 8188 12076, has_genre, 36212 12076, has_tags, 36212 12076, release_year, 15374 1321, has_genre, 36212 1321, release_year, 15374 6425, has_genre, 36212 6425, has_tags, 8188 6425, starred_actors, 8188 15012, has_genre, 36212 15012, release_year, 15374 17160, has_genre, 36212 17160, release_year, 15374 26406, has_genre, 36212 26406, release_year, 15374 4794, has_genre, 36212 4794, release_year, 15374 14601, has_genre, 36212 14601, has_tags, 8188 29912, has_genre, 36212 29912, release_year, 15374 17319, has_genre, 36212 17319, release_year, 15374 3459, has_genre, 36212 3459, release_year, 15374 35537, has_genre, 36212 35537, release_year, 15374 19802, has_genre, 36212 19802, release_year, 15374 1691, has_genre, 36212 1691, release_year, 15374 21036, has_genre, 36212 21036, release_year, 15374 9938, has_genre, 36212 9938, release_year, 15374 35670, has_genre, 36212 35670, release_year, 15374 14037, has_genre, 36212 14037, release_year, 15374 13531, has_genre, 36212 13531, release_year, 15374 11837, has_genre, 36212 11837, release_year, 15374 34359, has_genre, 36212 34359, release_year, 15374 16393, has_genre, 36212 16393, release_year, 15374 38312, has_genre, 36212 38312, has_tags, 36212 38312, release_year, 15374 17433, has_genre, 36212 17433, release_year, 15374 37073, has_genre, 36212 37073, release_year, 15374 8747, has_genre, 36212 8747, release_year, 15374 21030, has_genre, 36212 21030, release_year, 15374 25269, has_genre, 36212 25269, release_year, 15374 30931, has_genre, 36212 30931, release_year, 15374 27113, directed_by, 23481 27113, release_year, 17315 27113, written_by, 23481 14234, has_genre, 36212 14234, release_year, 15374 15644, has_genre, 36212 15644, release_year, 15374 21568, has_genre, 36212 21568, release_year, 15374 5023, has_genre, 36212 5023, has_tags, 24849 5023, starred_actors, 24849 23964, has_genre, 36212 23964, starred_actors, 24849 20164, has_genre, 36212 20164, release_year, 15374 4584, has_genre, 36212 4584, release_year, 15374 34066, has_genre, 36212 34066, release_year, 15374 3781, has_genre, 36212 3781, release_year, 15374 8871, has_genre, 36212 8871, release_year, 15374 17151, has_genre, 36212 17151, release_year, 15374 27361, has_genre, 36212 27361, release_year, 15374 313, has_genre, 36212 313, release_year, 15374 21719, has_genre, 36212 21719, release_year, 15374 26229, has_genre, 36212 26229, has_tags, 8188 26229, starred_actors, 8188 12153, has_genre, 36212 12153, has_tags, 24985 12153, starred_actors, 24985 35586, has_genre, 36212 35586, release_year, 15374 30441, has_genre, 36212 30441, release_year, 15374 4635, has_tags, 36212 4635, release_year, 15374 36273, has_genre, 36212 36273, release_year, 15374 21176, has_genre, 36212 21176, has_tags, 8188 21176, has_tags, 24985 21176, has_tags, 24849 21176, release_year, 15374 21176, starred_actors, 8188 21176, starred_actors, 24985 21176, starred_actors, 24849 21176, written_by, 24849 10925, has_genre, 36212 10925, release_year, 15374 15382, has_genre, 36212 15382, release_year, 15374 35843, has_genre, 36212 35843, has_tags, 24985 35843, starred_actors, 24985 26621, has_genre, 36212 26621, release_year, 15374 38027, has_genre, 36212 38027, release_year, 15374 5569, has_genre, 36212 5569, release_year, 15374 11773, has_genre, 36212 11773, release_year, 15374 34274, has_genre, 36212 34274, release_year, 15374 17864, has_genre, 36212 17864, release_year, 15374 18142, has_genre, 36212 18142, has_tags, 36212 18142, release_year, 15374 35261, has_genre, 36212 35261, has_tags, 24985 35261, starred_actors, 24985 35261, written_by, 24985 16597, has_genre, 36212 16597, release_year, 15374 7366, has_genre, 36212 7366, release_year, 15374 28948, has_genre, 36212 28948, has_tags, 8188 28948, has_tags, 36212 28948, release_year, 15374 28948, starred_actors, 8188 10802, has_genre, 36212 10802, release_year, 15374 33315, has_genre, 36212 33315, release_year, 15374 20237, has_genre, 36212 20237, release_year, 15374 35165, has_genre, 36212 35165, release_year, 15374 30360, has_genre, 36212 30360, release_year, 15374 20223, has_genre, 36212 20223, release_year, 15374 24108, has_genre, 36212 24108, release_year, 15374 8022, has_genre, 36212 8022, release_year, 15374 8970, has_genre, 36212 8970, has_tags, 24849 27029, has_genre, 36212 27029, release_year, 15374 19644, has_genre, 36212 19644, release_year, 15374 16072, has_genre, 36212 16072, has_tags, 8188 16072, starred_actors, 8188 7237, has_genre, 36212 7237, release_year, 15374 32210, has_genre, 36212 32210, has_tags, 36212 32210, release_year, 15374 21548, has_genre, 36212 21548, release_year, 15374 31827, has_genre, 36212 31827, release_year, 15374 35215, has_genre, 36212 35215, release_year, 17315 35215, written_by, 570 7168, has_genre, 36212 7168, release_year, 15374 39409, has_genre, 36212 39409, release_year, 15374 21433, has_genre, 36212 21433, release_year, 15374 11407, has_genre, 36212 11407, release_year, 15374 34902, has_genre, 36212 34902, release_year, 15374 631, has_genre, 36212 631, release_year, 15374 9970, has_genre, 36212 9970, release_year, 15374 38564, has_genre, 36212 38564, starred_actors, 8188 20251, has_genre, 36212 20251, release_year, 15374 22342, has_genre, 36212 22342, release_year, 15374 36820, has_genre, 36212 36820, release_year, 15374 10855, has_genre, 36212 10855, release_year, 15374 7715, has_genre, 36212 7715, release_year, 15374 39965, has_genre, 36212 39965, release_year, 15374 Question: For what reason are MAUREEN MEDVED, MOACYR GÓES, and SHOPGIRL associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "MAUREEN MEDVED", "MOACYR GÓES", "SHOPGIRL" ], "valid_edges": [ [ "12 AND HOLDING", "has_genre", "DRAMA" ], [ "12 AND HOLDING", "release_year", "2005" ], [ "3 NEEDLES", "has_genre", "DRAMA" ], [ "3 NEEDLES", "release_year", "2005" ], [ "4", "has_genre", "DRAMA" ], [ "4", "release_year", "2005" ], [ "A LITTLE TRIP TO HEAVEN", "has_genre", "DRAMA" ], [ "A LITTLE TRIP TO HEAVEN", "release_year", "2005" ], [ "A SIMPLE TWIST OF FATE", "has_genre", "DRAMA" ], [ "A SIMPLE TWIST OF FATE", "starred_actors", "STEVE MARTIN" ], [ "A SIMPLE TWIST OF FATE", "written_by", "STEVE MARTIN" ], [ "AMERICAN GUN", "has_genre", "DRAMA" ], [ "AMERICAN GUN", "release_year", "2005" ], [ "AMERICANO", "has_genre", "DRAMA" ], [ "AMERICANO", "release_year", "2005" ], [ "AN UNFINISHED LIFE", "has_genre", "DRAMA" ], [ "AN UNFINISHED LIFE", "release_year", "2005" ], [ "ANGEL-A", "has_genre", "DRAMA" ], [ "ANGEL-A", "release_year", "2005" ], [ "AS COOL AS I AM", "has_genre", "DRAMA" ], [ "AS COOL AS I AM", "starred_actors", "CLAIRE DANES" ], [ "ASYLUM", "has_genre", "DRAMA" ], [ "ASYLUM", "release_year", "2005" ], [ "AURORA BOREALIS", "has_genre", "DRAMA" ], [ "AURORA BOREALIS", "release_year", "2005" ], [ "BE WITH ME", "has_genre", "DRAMA" ], [ "BE WITH ME", "release_year", "2005" ], [ "BEE SEASON", "has_genre", "DRAMA" ], [ "BEE SEASON", "release_year", "2005" ], [ "BEWITCHED", "has_genre", "DRAMA" ], [ "BEWITCHED", "release_year", "2005" ], [ "BLACK", "has_genre", "DRAMA" ], [ "BLACK", "release_year", "2005" ], [ "BREAKFAST ON PLUTO", "has_genre", "DRAMA" ], [ "BREAKFAST ON PLUTO", "release_year", "2005" ], [ "BROKEBACK MOUNTAIN", "has_genre", "DRAMA" ], [ "BROKEBACK MOUNTAIN", "release_year", "2005" ], [ "BROKEDOWN PALACE", "has_genre", "DRAMA" ], [ "BROKEDOWN PALACE", "starred_actors", "CLAIRE DANES" ], [ "BROKEN FLOWERS", "has_genre", "DRAMA" ], [ "BROKEN FLOWERS", "has_tags", "DRAMA" ], [ "BROKEN FLOWERS", "release_year", "2005" ], [ "CAKE", "has_genre", "DRAMA" ], [ "CAKE", "release_year", "2005" ], [ "CINDERELLA MAN", "has_genre", "DRAMA" ], [ "CINDERELLA MAN", "release_year", "2005" ], [ "COACH CARTER", "has_genre", "DRAMA" ], [ "COACH CARTER", "release_year", "2005" ], [ "CONVERSATIONS WITH OTHER WOMEN", "has_genre", "DRAMA" ], [ "CONVERSATIONS WITH OTHER WOMEN", "release_year", "2005" ], [ "DARK HORSE", "has_genre", "DRAMA" ], [ "DARK HORSE", "release_year", "2005" ], [ "DIARY OF A MAD BLACK WOMAN", "has_genre", "DRAMA" ], [ "DIARY OF A MAD BLACK WOMAN", "release_year", "2005" ], [ "DIRTY", "has_genre", "DRAMA" ], [ "DIRTY", "release_year", "2005" ], [ "DON'T COME KNOCKING", "has_genre", "DRAMA" ], [ "DON'T COME KNOCKING", "release_year", "2005" ], [ "DUMA", "has_genre", "DRAMA" ], [ "DUMA", "release_year", "2005" ], [ "EDMOND", "has_genre", "DRAMA" ], [ "EDMOND", "release_year", "2005" ], [ "ELIZABETHTOWN", "has_genre", "DRAMA" ], [ "ELIZABETHTOWN", "release_year", "2005" ], [ "ELLIE PARKER", "has_genre", "DRAMA" ], [ "ELLIE PARKER", "release_year", "2005" ], [ "ENTRE SES MAINS", "has_genre", "DRAMA" ], [ "ENTRE SES MAINS", "release_year", "2005" ], [ "EVERYTHING IS ILLUMINATED", "has_genre", "DRAMA" ], [ "EVERYTHING IS ILLUMINATED", "has_tags", "DRAMA" ], [ "EVERYTHING IS ILLUMINATED", "release_year", "2005" ], [ "FETCHING CODY", "has_genre", "DRAMA" ], [ "FETCHING CODY", "release_year", "2005" ], [ "FEVER PITCH", "has_genre", "DRAMA" ], [ "FEVER PITCH", "release_year", "2005" ], [ "FIERCE PEOPLE", "has_genre", "DRAMA" ], [ "FIERCE PEOPLE", "release_year", "2005" ], [ "FROZEN LAND", "has_genre", "DRAMA" ], [ "FROZEN LAND", "release_year", "2005" ], [ "FUNNY PEOPLE", "has_genre", "DRAMA" ], [ "FUNNY PEOPLE", "has_tags", "DRAMA" ], [ "FUNNY PEOPLE", "has_tags", "JASON SCHWARTZMAN" ], [ "GABRIELLE", "has_genre", "DRAMA" ], [ "GABRIELLE", "release_year", "2005" ], [ "GET RICH OR DIE TRYIN'", "has_genre", "DRAMA" ], [ "GET RICH OR DIE TRYIN'", "release_year", "2005" ], [ "HAVOC", "has_genre", "DRAMA" ], [ "HAVOC", "release_year", "2005" ], [ "HEADING SOUTH", "has_genre", "DRAMA" ], [ "HEADING SOUTH", "release_year", "2005" ], [ "HOME", "has_genre", "DRAMA" ], [ "HOME", "starred_actors", "STEVE MARTIN" ], [ "IGBY GOES DOWN", "has_genre", "DRAMA" ], [ "IGBY GOES DOWN", "has_tags", "CLAIRE DANES" ], [ "IGBY GOES DOWN", "starred_actors", "CLAIRE DANES" ], [ "IN HER SHOES", "has_genre", "DRAMA" ], [ "IN HER SHOES", "has_tags", "DRAMA" ], [ "IN HER SHOES", "release_year", "2005" ], [ "IRON ISLAND", "has_genre", "DRAMA" ], [ "IRON ISLAND", "release_year", "2005" ], [ "IT'S ALL ABOUT LOVE", "has_genre", "DRAMA" ], [ "IT'S ALL ABOUT LOVE", "has_tags", "CLAIRE DANES" ], [ "IT'S ALL ABOUT LOVE", "starred_actors", "CLAIRE DANES" ], [ "JARHEAD", "has_genre", "DRAMA" ], [ "JARHEAD", "release_year", "2005" ], [ "JUNEBUG", "has_genre", "DRAMA" ], [ "JUNEBUG", "release_year", "2005" ], [ "KINKY BOOTS", "has_genre", "DRAMA" ], [ "KINKY BOOTS", "release_year", "2005" ], [ "LAST DAYS", "has_genre", "DRAMA" ], [ "LAST DAYS", "release_year", "2005" ], [ "LES MISÉRABLES", "has_genre", "DRAMA" ], [ "LES MISÉRABLES", "has_tags", "CLAIRE DANES" ], [ "LIE WITH ME", "has_genre", "DRAMA" ], [ "LIE WITH ME", "release_year", "2005" ], [ "LONDON", "has_genre", "DRAMA" ], [ "LONDON", "release_year", "2005" ], [ "LONESOME JIM", "has_genre", "DRAMA" ], [ "LONESOME JIM", "release_year", "2005" ], [ "LORDS OF DOGTOWN", "has_genre", "DRAMA" ], [ "LORDS OF DOGTOWN", "release_year", "2005" ], [ "LOVE", "has_genre", "DRAMA" ], [ "LOVE", "release_year", "2005" ], [ "LOVE'S LONG JOURNEY", "has_genre", "DRAMA" ], [ "LOVE'S LONG JOURNEY", "release_year", "2005" ], [ "LOWER CITY", "has_genre", "DRAMA" ], [ "LOWER CITY", "release_year", "2005" ], [ "MAN TO MAN", "has_genre", "DRAMA" ], [ "MAN TO MAN", "release_year", "2005" ], [ "MANDERLAY", "has_genre", "DRAMA" ], [ "MANDERLAY", "release_year", "2005" ], [ "MARY", "has_genre", "DRAMA" ], [ "MARY", "release_year", "2005" ], [ "MATCH POINT", "has_genre", "DRAMA" ], [ "MATCH POINT", "release_year", "2005" ], [ "ME AND YOU AND EVERYONE WE KNOW", "has_genre", "DRAMA" ], [ "ME AND YOU AND EVERYONE WE KNOW", "release_year", "2005" ], [ "MELISSA P.", "has_genre", "DRAMA" ], [ "MELISSA P.", "release_year", "2005" ], [ "MISSING IN AMERICA", "has_genre", "DRAMA" ], [ "MISSING IN AMERICA", "release_year", "2005" ], [ "MOUTH TO MOUTH", "has_genre", "DRAMA" ], [ "MOUTH TO MOUTH", "has_tags", "DRAMA" ], [ "MOUTH TO MOUTH", "release_year", "2005" ], [ "MOZART AND THE WHALE", "has_genre", "DRAMA" ], [ "MOZART AND THE WHALE", "release_year", "2005" ], [ "MRS. PALFREY AT THE CLAREMONT", "has_genre", "DRAMA" ], [ "MRS. PALFREY AT THE CLAREMONT", "release_year", "2005" ], [ "MUNICH", "has_genre", "DRAMA" ], [ "MUNICH", "release_year", "2005" ], [ "NANA", "has_genre", "DRAMA" ], [ "NANA", "release_year", "2005" ], [ "NINE LIVES", "has_genre", "DRAMA" ], [ "NINE LIVES", "release_year", "2005" ], [ "NORTH COUNTRY", "has_genre", "DRAMA" ], [ "NORTH COUNTRY", "release_year", "2005" ], [ "O HOMEM QUE DESAFIOU O DIABO", "directed_by", "MOACYR GÓES" ], [ "O HOMEM QUE DESAFIOU O DIABO", "release_year", "2007" ], [ "O HOMEM QUE DESAFIOU O DIABO", "written_by", "MOACYR GÓES" ], [ "ODD GIRL OUT", "has_genre", "DRAMA" ], [ "ODD GIRL OUT", "release_year", "2005" ], [ "OLIVER TWIST", "has_genre", "DRAMA" ], [ "OLIVER TWIST", "release_year", "2005" ], [ "ON A CLEAR DAY", "has_genre", "DRAMA" ], [ "ON A CLEAR DAY", "release_year", "2005" ], [ "PARENTHOOD", "has_genre", "DRAMA" ], [ "PARENTHOOD", "has_tags", "STEVE MARTIN" ], [ "PARENTHOOD", "starred_actors", "STEVE MARTIN" ], [ "PENNIES FROM HEAVEN", "has_genre", "DRAMA" ], [ "PENNIES FROM HEAVEN", "starred_actors", "STEVE MARTIN" ], [ "PRETTY PERSUASION", "has_genre", "DRAMA" ], [ "PRETTY PERSUASION", "release_year", "2005" ], [ "PROOF", "has_genre", "DRAMA" ], [ "PROOF", "release_year", "2005" ], [ "PUZZLEHEAD", "has_genre", "DRAMA" ], [ "PUZZLEHEAD", "release_year", "2005" ], [ "QUO VADIS, BABY?", "has_genre", "DRAMA" ], [ "QUO VADIS, BABY?", "release_year", "2005" ], [ "RENT", "has_genre", "DRAMA" ], [ "RENT", "release_year", "2005" ], [ "REVOLVER", "has_genre", "DRAMA" ], [ "REVOLVER", "release_year", "2005" ], [ "RIDING ALONE FOR THOUSANDS OF MILES", "has_genre", "DRAMA" ], [ "RIDING ALONE FOR THOUSANDS OF MILES", "release_year", "2005" ], [ "ROLL BOUNCE", "has_genre", "DRAMA" ], [ "ROLL BOUNCE", "release_year", "2005" ], [ "ROMANZO CRIMINALE", "has_genre", "DRAMA" ], [ "ROMANZO CRIMINALE", "release_year", "2005" ], [ "ROMEO + JULIET", "has_genre", "DRAMA" ], [ "ROMEO + JULIET", "has_tags", "CLAIRE DANES" ], [ "ROMEO + JULIET", "starred_actors", "CLAIRE DANES" ], [ "RUSHMORE", "has_genre", "DRAMA" ], [ "RUSHMORE", "has_tags", "JASON SCHWARTZMAN" ], [ "RUSHMORE", "starred_actors", "JASON SCHWARTZMAN" ], [ "SAHARA", "has_genre", "DRAMA" ], [ "SAHARA", "release_year", "2005" ], [ "SEPARATE LIES", "has_genre", "DRAMA" ], [ "SEPARATE LIES", "release_year", "2005" ], [ "SERENITY", "has_tags", "DRAMA" ], [ "SERENITY", "release_year", "2005" ], [ "SEXUAL LIFE", "has_genre", "DRAMA" ], [ "SEXUAL LIFE", "release_year", "2005" ], [ "SHOPGIRL", "has_genre", "DRAMA" ], [ "SHOPGIRL", "has_tags", "CLAIRE DANES" ], [ "SHOPGIRL", "has_tags", "JASON SCHWARTZMAN" ], [ "SHOPGIRL", "has_tags", "STEVE MARTIN" ], [ "SHOPGIRL", "release_year", "2005" ], [ "SHOPGIRL", "starred_actors", "CLAIRE DANES" ], [ "SHOPGIRL", "starred_actors", "JASON SCHWARTZMAN" ], [ "SHOPGIRL", "starred_actors", "STEVE MARTIN" ], [ "SHOPGIRL", "written_by", "STEVE MARTIN" ], [ "SLOW BURN", "has_genre", "DRAMA" ], [ "SLOW BURN", "release_year", "2005" ], [ "SOMETIMES IN APRIL", "has_genre", "DRAMA" ], [ "SOMETIMES IN APRIL", "release_year", "2005" ], [ "SPUN", "has_genre", "DRAMA" ], [ "SPUN", "has_tags", "JASON SCHWARTZMAN" ], [ "SPUN", "starred_actors", "JASON SCHWARTZMAN" ], [ "STAY", "has_genre", "DRAMA" ], [ "STAY", "release_year", "2005" ], [ "SUNFLOWER", "has_genre", "DRAMA" ], [ "SUNFLOWER", "release_year", "2005" ], [ "SWEET LAND", "has_genre", "DRAMA" ], [ "SWEET LAND", "release_year", "2005" ], [ "THANK YOU FOR SMOKING", "has_genre", "DRAMA" ], [ "THANK YOU FOR SMOKING", "release_year", "2005" ], [ "THE BALLAD OF JACK AND ROSE", "has_genre", "DRAMA" ], [ "THE BALLAD OF JACK AND ROSE", "release_year", "2005" ], [ "THE CHUMSCRUBBER", "has_genre", "DRAMA" ], [ "THE CHUMSCRUBBER", "release_year", "2005" ], [ "THE CONSTANT GARDENER", "has_genre", "DRAMA" ], [ "THE CONSTANT GARDENER", "has_tags", "DRAMA" ], [ "THE CONSTANT GARDENER", "release_year", "2005" ], [ "THE DARJEELING LIMITED", "has_genre", "DRAMA" ], [ "THE DARJEELING LIMITED", "has_tags", "JASON SCHWARTZMAN" ], [ "THE DARJEELING LIMITED", "starred_actors", "JASON SCHWARTZMAN" ], [ "THE DARJEELING LIMITED", "written_by", "JASON SCHWARTZMAN" ], [ "THE DYING GAUL", "has_genre", "DRAMA" ], [ "THE DYING GAUL", "release_year", "2005" ], [ "THE EXORCISM OF EMILY ROSE", "has_genre", "DRAMA" ], [ "THE EXORCISM OF EMILY ROSE", "release_year", "2005" ], [ "THE FAMILY STONE", "has_genre", "DRAMA" ], [ "THE FAMILY STONE", "has_tags", "CLAIRE DANES" ], [ "THE FAMILY STONE", "has_tags", "DRAMA" ], [ "THE FAMILY STONE", "release_year", "2005" ], [ "THE FAMILY STONE", "starred_actors", "CLAIRE DANES" ], [ "THE GAME OF THEIR LIVES", "has_genre", "DRAMA" ], [ "THE GAME OF THEIR LIVES", "release_year", "2005" ], [ "THE GIRL IN THE CAFÉ", "has_genre", "DRAMA" ], [ "THE GIRL IN THE CAFÉ", "release_year", "2005" ], [ "THE ICE HARVEST", "has_genre", "DRAMA" ], [ "THE ICE HARVEST", "release_year", "2005" ], [ "THE ITALIAN", "has_genre", "DRAMA" ], [ "THE ITALIAN", "release_year", "2005" ], [ "THE KING", "has_genre", "DRAMA" ], [ "THE KING", "release_year", "2005" ], [ "THE LONGEST YARD", "has_genre", "DRAMA" ], [ "THE LONGEST YARD", "release_year", "2005" ], [ "THE MAN", "has_genre", "DRAMA" ], [ "THE MAN", "release_year", "2005" ], [ "THE NEW WORLD", "has_genre", "DRAMA" ], [ "THE NEW WORLD", "release_year", "2005" ], [ "THE PRINCE OF EGYPT", "has_genre", "DRAMA" ], [ "THE PRINCE OF EGYPT", "has_tags", "STEVE MARTIN" ], [ "THE PROPOSITION", "has_genre", "DRAMA" ], [ "THE PROPOSITION", "release_year", "2005" ], [ "THE QUIET", "has_genre", "DRAMA" ], [ "THE QUIET", "release_year", "2005" ], [ "THE RAINMAKER", "has_genre", "DRAMA" ], [ "THE RAINMAKER", "has_tags", "CLAIRE DANES" ], [ "THE RAINMAKER", "starred_actors", "CLAIRE DANES" ], [ "THE SISTERHOOD OF THE TRAVELING PANTS", "has_genre", "DRAMA" ], [ "THE SISTERHOOD OF THE TRAVELING PANTS", "release_year", "2005" ], [ "THE SQUID AND THE WHALE", "has_genre", "DRAMA" ], [ "THE SQUID AND THE WHALE", "has_tags", "DRAMA" ], [ "THE SQUID AND THE WHALE", "release_year", "2005" ], [ "THE SUN", "has_genre", "DRAMA" ], [ "THE SUN", "release_year", "2005" ], [ "THE THING ABOUT MY FOLKS", "has_genre", "DRAMA" ], [ "THE THING ABOUT MY FOLKS", "release_year", "2005" ], [ "THE TRACEY FRAGMENTS", "has_genre", "DRAMA" ], [ "THE TRACEY FRAGMENTS", "release_year", "2007" ], [ "THE TRACEY FRAGMENTS", "written_by", "MAUREEN MEDVED" ], [ "THE UPSIDE OF ANGER", "has_genre", "DRAMA" ], [ "THE UPSIDE OF ANGER", "release_year", "2005" ], [ "THE VIOLIN", "has_genre", "DRAMA" ], [ "THE VIOLIN", "release_year", "2005" ], [ "THE WAR WITHIN", "has_genre", "DRAMA" ], [ "THE WAR WITHIN", "release_year", "2005" ], [ "THE WEATHER MAN", "has_genre", "DRAMA" ], [ "THE WEATHER MAN", "release_year", "2005" ], [ "THE WHITE COUNTESS", "has_genre", "DRAMA" ], [ "THE WHITE COUNTESS", "release_year", "2005" ], [ "THUMBSUCKER", "has_genre", "DRAMA" ], [ "THUMBSUCKER", "release_year", "2005" ], [ "TICKETS", "has_genre", "DRAMA" ], [ "TICKETS", "release_year", "2005" ], [ "TO GILLIAN ON HER 37TH BIRTHDAY", "has_genre", "DRAMA" ], [ "TO GILLIAN ON HER 37TH BIRTHDAY", "starred_actors", "CLAIRE DANES" ], [ "TO PAINT OR MAKE LOVE", "has_genre", "DRAMA" ], [ "TO PAINT OR MAKE LOVE", "release_year", "2005" ], [ "TRANSAMERICA", "has_genre", "DRAMA" ], [ "TRANSAMERICA", "release_year", "2005" ], [ "TWO FOR THE MONEY", "has_genre", "DRAMA" ], [ "TWO FOR THE MONEY", "release_year", "2005" ], [ "WAH-WAH", "has_genre", "DRAMA" ], [ "WAH-WAH", "release_year", "2005" ], [ "WALK THE LINE", "has_genre", "DRAMA" ], [ "WALK THE LINE", "release_year", "2005" ], [ "WHAT IS IT?", "has_genre", "DRAMA" ], [ "WHAT IS IT?", "release_year", "2005" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 31486, 1970 38751, CHRISTOPHER LEE 20884, COUNT DRACULA 15064, EQUINOX 12336, MATTHEW MODINE 33746, SCARS OF DRACULA 26987, TASTE THE BLOOD OF DRACULA 5903, THE BLOOD OF FU MANCHU 22053, THE REAL BLONDE 21526, TRIBES src, edge_attr, dst 20884, has_tags, 38751 20884, release_year, 31486 20884, starred_actors, 38751 15064, release_year, 31486 15064, starred_actors, 12336 33746, release_year, 31486 33746, starred_actors, 38751 26987, has_tags, 38751 26987, release_year, 31486 26987, starred_actors, 38751 5903, starred_actors, 38751 22053, starred_actors, 12336 21526, release_year, 31486 Question: For what reason are THE BLOOD OF FU MANCHU, THE REAL BLONDE, and TRIBES associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "THE BLOOD OF FU MANCHU", "THE REAL BLONDE", "TRIBES" ], "valid_edges": [ [ "COUNT DRACULA", "has_tags", "CHRISTOPHER LEE" ], [ "COUNT DRACULA", "release_year", "1970" ], [ "COUNT DRACULA", "starred_actors", "CHRISTOPHER LEE" ], [ "EQUINOX", "release_year", "1970" ], [ "EQUINOX", "starred_actors", "MATTHEW MODINE" ], [ "SCARS OF DRACULA", "release_year", "1970" ], [ "SCARS OF DRACULA", "starred_actors", "CHRISTOPHER LEE" ], [ "TASTE THE BLOOD OF DRACULA", "has_tags", "CHRISTOPHER LEE" ], [ "TASTE THE BLOOD OF DRACULA", "release_year", "1970" ], [ "TASTE THE BLOOD OF DRACULA", "starred_actors", "CHRISTOPHER LEE" ], [ "THE BLOOD OF FU MANCHU", "starred_actors", "CHRISTOPHER LEE" ], [ "THE REAL BLONDE", "starred_actors", "MATTHEW MODINE" ], [ "TRIBES", "release_year", "1970" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 21775, 06/05 37484, 2004 30265, BRAZIL 6852, CHEECH MARIN 40091, CONTROL ROOM 31783, ENGLISH 19728, EVILENKO 24815, GOING THE DISTANCE 3285, IN MY COUNTRY 15150, KAMIKAZE GIRLS 30600, LADIES IN LAVENDER 2410, MACHETE 10198, MACHUCA 39135, REACHING FOR THE MOON 38241, RING OF DARKNESS 17979, ROBERT DE NIRO 32465, THE FOOTBALL FACTORY 4420, THE HUNTING OF THE PRESIDENT 32925, THE LIFE AND DEATH OF PETER SELLERS 22880, THE MACHINIST 38433, THE MERCHANT OF VENICE 22654, THREE WAY 23737, WALK ON WATER src, edge_attr, dst 21775, in_language, 31783 21775, release_year, 37484 30265, has_tags, 17979 30265, starred_actors, 17979 40091, in_language, 31783 40091, release_year, 37484 19728, in_language, 31783 19728, release_year, 37484 24815, in_language, 31783 24815, release_year, 37484 3285, in_language, 31783 3285, release_year, 37484 15150, in_language, 31783 15150, release_year, 37484 30600, in_language, 31783 30600, release_year, 37484 2410, has_tags, 6852 2410, has_tags, 17979 2410, starred_actors, 17979 10198, in_language, 31783 10198, release_year, 37484 39135, has_tags, 30265 39135, in_language, 31783 38241, in_language, 31783 38241, release_year, 37484 32465, in_language, 31783 32465, release_year, 37484 4420, in_language, 31783 4420, release_year, 37484 32925, in_language, 31783 32925, release_year, 37484 22880, in_language, 31783 22880, release_year, 37484 38433, in_language, 31783 38433, release_year, 37484 22654, release_year, 37484 23737, in_language, 31783 23737, release_year, 37484 Question: In what context are CHEECH MARIN, REACHING FOR THE MOON, and THREE WAY connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CHEECH MARIN", "REACHING FOR THE MOON", "THREE WAY" ], "valid_edges": [ [ "06/05", "in_language", "ENGLISH" ], [ "06/05", "release_year", "2004" ], [ "BRAZIL", "has_tags", "ROBERT DE NIRO" ], [ "BRAZIL", "starred_actors", "ROBERT DE NIRO" ], [ "CONTROL ROOM", "in_language", "ENGLISH" ], [ "CONTROL ROOM", "release_year", "2004" ], [ "EVILENKO", "in_language", "ENGLISH" ], [ "EVILENKO", "release_year", "2004" ], [ "GOING THE DISTANCE", "in_language", "ENGLISH" ], [ "GOING THE DISTANCE", "release_year", "2004" ], [ "IN MY COUNTRY", "in_language", "ENGLISH" ], [ "IN MY COUNTRY", "release_year", "2004" ], [ "KAMIKAZE GIRLS", "in_language", "ENGLISH" ], [ "KAMIKAZE GIRLS", "release_year", "2004" ], [ "LADIES IN LAVENDER", "in_language", "ENGLISH" ], [ "LADIES IN LAVENDER", "release_year", "2004" ], [ "MACHETE", "has_tags", "CHEECH MARIN" ], [ "MACHETE", "has_tags", "ROBERT DE NIRO" ], [ "MACHETE", "starred_actors", "ROBERT DE NIRO" ], [ "MACHUCA", "in_language", "ENGLISH" ], [ "MACHUCA", "release_year", "2004" ], [ "REACHING FOR THE MOON", "has_tags", "BRAZIL" ], [ "REACHING FOR THE MOON", "in_language", "ENGLISH" ], [ "RING OF DARKNESS", "in_language", "ENGLISH" ], [ "RING OF DARKNESS", "release_year", "2004" ], [ "THE FOOTBALL FACTORY", "in_language", "ENGLISH" ], [ "THE FOOTBALL FACTORY", "release_year", "2004" ], [ "THE HUNTING OF THE PRESIDENT", "in_language", "ENGLISH" ], [ "THE HUNTING OF THE PRESIDENT", "release_year", "2004" ], [ "THE LIFE AND DEATH OF PETER SELLERS", "in_language", "ENGLISH" ], [ "THE LIFE AND DEATH OF PETER SELLERS", "release_year", "2004" ], [ "THE MACHINIST", "in_language", "ENGLISH" ], [ "THE MACHINIST", "release_year", "2004" ], [ "THE MERCHANT OF VENICE", "in_language", "ENGLISH" ], [ "THE MERCHANT OF VENICE", "release_year", "2004" ], [ "THREE WAY", "release_year", "2004" ], [ "WALK ON WATER", "in_language", "ENGLISH" ], [ "WALK ON WATER", "release_year", "2004" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26762, 2008 30247, AN EMPRESS AND THE WARRIORS 26260, BLUE SKY 17256, DONNIE YEN 36212, DRAMA 1498, ERMANNO OLMI 10121, IP MAN 38168, IP MAN 2 26301, MARTIAL ARTS 4738, RAMA LAURIE STAGNER 9970, TICKETS 27749, WALKING, WALKING 5052, WING CHUN src, edge_attr, dst 30247, has_genre, 36212 30247, release_year, 26762 30247, starred_actors, 17256 26260, has_genre, 36212 26260, written_by, 4738 10121, has_tags, 17256 10121, has_tags, 10121 10121, has_tags, 26301 10121, has_tags, 5052 10121, release_year, 26762 10121, starred_actors, 17256 38168, has_genre, 36212 38168, has_tags, 17256 38168, has_tags, 10121 38168, has_tags, 26301 38168, has_tags, 5052 38168, starred_actors, 17256 9970, directed_by, 1498 9970, has_genre, 36212 9970, has_tags, 1498 9970, written_by, 1498 27749, directed_by, 1498 27749, has_genre, 36212 27749, written_by, 1498 Question: How are DONNIE YEN, ERMANNO OLMI, and RAMA LAURIE STAGNER related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DONNIE YEN", "ERMANNO OLMI", "RAMA LAURIE STAGNER" ], "valid_edges": [ [ "AN EMPRESS AND THE WARRIORS", "has_genre", "DRAMA" ], [ "AN EMPRESS AND THE WARRIORS", "release_year", "2008" ], [ "AN EMPRESS AND THE WARRIORS", "starred_actors", "DONNIE YEN" ], [ "BLUE SKY", "has_genre", "DRAMA" ], [ "BLUE SKY", "written_by", "RAMA LAURIE STAGNER" ], [ "IP MAN", "has_tags", "DONNIE YEN" ], [ "IP MAN", "has_tags", "IP MAN" ], [ "IP MAN", "has_tags", "MARTIAL ARTS" ], [ "IP MAN", "has_tags", "WING CHUN" ], [ "IP MAN", "release_year", "2008" ], [ "IP MAN", "starred_actors", "DONNIE YEN" ], [ "IP MAN 2", "has_genre", "DRAMA" ], [ "IP MAN 2", "has_tags", "DONNIE YEN" ], [ "IP MAN 2", "has_tags", "IP MAN" ], [ "IP MAN 2", "has_tags", "MARTIAL ARTS" ], [ "IP MAN 2", "has_tags", "WING CHUN" ], [ "IP MAN 2", "starred_actors", "DONNIE YEN" ], [ "TICKETS", "directed_by", "ERMANNO OLMI" ], [ "TICKETS", "has_genre", "DRAMA" ], [ "TICKETS", "has_tags", "ERMANNO OLMI" ], [ "TICKETS", "written_by", "ERMANNO OLMI" ], [ "WALKING, WALKING", "directed_by", "ERMANNO OLMI" ], [ "WALKING, WALKING", "has_genre", "DRAMA" ], [ "WALKING, WALKING", "written_by", "ERMANNO OLMI" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26633, 1989 24438, 1993 1274, ADDAMS FAMILY VALUES 26799, BACK TO THE FUTURE PART II 28679, CANNIBAL WOMEN IN THE AVOCADO JUNGLE OF DEATH 23496, CHRISTOPHER LLOYD 23875, PIANO 3434, SHANNON TWEED 38878, THE DREAM TEAM 19496, THE PIANO 29852, THIRTY TWO SHORT FILMS ABOUT GLENN GOULD src, edge_attr, dst 1274, has_tags, 23496 1274, release_year, 24438 1274, starred_actors, 23496 26799, has_tags, 23496 26799, release_year, 26633 26799, starred_actors, 23496 28679, release_year, 26633 28679, starred_actors, 3434 38878, has_tags, 23496 38878, release_year, 26633 38878, starred_actors, 23496 19496, has_tags, 23875 19496, release_year, 24438 29852, has_tags, 23875 29852, release_year, 24438 Question: For what reason are CHRISTOPHER LLOYD, SHANNON TWEED, and THIRTY TWO SHORT FILMS ABOUT GLENN GOULD associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CHRISTOPHER LLOYD", "SHANNON TWEED", "THIRTY TWO SHORT FILMS ABOUT GLENN GOULD" ], "valid_edges": [ [ "ADDAMS FAMILY VALUES", "has_tags", "CHRISTOPHER LLOYD" ], [ "ADDAMS FAMILY VALUES", "release_year", "1993" ], [ "ADDAMS FAMILY VALUES", "starred_actors", "CHRISTOPHER LLOYD" ], [ "BACK TO THE FUTURE PART II", "has_tags", "CHRISTOPHER LLOYD" ], [ "BACK TO THE FUTURE PART II", "release_year", "1989" ], [ "BACK TO THE FUTURE PART II", "starred_actors", "CHRISTOPHER LLOYD" ], [ "CANNIBAL WOMEN IN THE AVOCADO JUNGLE OF DEATH", "release_year", "1989" ], [ "CANNIBAL WOMEN IN THE AVOCADO JUNGLE OF DEATH", "starred_actors", "SHANNON TWEED" ], [ "THE DREAM TEAM", "has_tags", "CHRISTOPHER LLOYD" ], [ "THE DREAM TEAM", "release_year", "1989" ], [ "THE DREAM TEAM", "starred_actors", "CHRISTOPHER LLOYD" ], [ "THE PIANO", "has_tags", "PIANO" ], [ "THE PIANO", "release_year", "1993" ], [ "THIRTY TWO SHORT FILMS ABOUT GLENN GOULD", "has_tags", "PIANO" ], [ "THIRTY TWO SHORT FILMS ABOUT GLENN GOULD", "release_year", "1993" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24438, 1993 28293, AMMA ASANTE 23223, BELLE 4847, BOXING HELENA 8003, CALAMARI UNION 30463, COMEDY 36212, DRAMA 11065, FATAL INSTINCT 109, JUST WRITE 33442, KARI HEISKANEN 19787, SHERILYN FENN 20345, THE SCENESTERS 24929, THREE OF HEARTS src, edge_attr, dst 23223, directed_by, 28293 23223, has_genre, 36212 4847, has_genre, 36212 4847, release_year, 24438 4847, starred_actors, 19787 8003, has_genre, 30463 8003, has_tags, 30463 8003, starred_actors, 33442 11065, has_genre, 30463 11065, release_year, 24438 11065, starred_actors, 19787 109, has_genre, 30463 109, starred_actors, 19787 20345, has_genre, 30463 20345, starred_actors, 19787 24929, has_genre, 30463 24929, release_year, 24438 24929, starred_actors, 19787 Question: For what reason are AMMA ASANTE, KARI HEISKANEN, and SHERILYN FENN associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "AMMA ASANTE", "KARI HEISKANEN", "SHERILYN FENN" ], "valid_edges": [ [ "BELLE", "directed_by", "AMMA ASANTE" ], [ "BELLE", "has_genre", "DRAMA" ], [ "BOXING HELENA", "has_genre", "DRAMA" ], [ "BOXING HELENA", "release_year", "1993" ], [ "BOXING HELENA", "starred_actors", "SHERILYN FENN" ], [ "CALAMARI UNION", "has_genre", "COMEDY" ], [ "CALAMARI UNION", "has_tags", "COMEDY" ], [ "CALAMARI UNION", "starred_actors", "KARI HEISKANEN" ], [ "FATAL INSTINCT", "has_genre", "COMEDY" ], [ "FATAL INSTINCT", "release_year", "1993" ], [ "FATAL INSTINCT", "starred_actors", "SHERILYN FENN" ], [ "JUST WRITE", "has_genre", "COMEDY" ], [ "JUST WRITE", "starred_actors", "SHERILYN FENN" ], [ "THE SCENESTERS", "has_genre", "COMEDY" ], [ "THE SCENESTERS", "starred_actors", "SHERILYN FENN" ], [ "THREE OF HEARTS", "has_genre", "COMEDY" ], [ "THREE OF HEARTS", "release_year", "1993" ], [ "THREE OF HEARTS", "starred_actors", "SHERILYN FENN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6776, 2000 30463, COMEDY 6012, FRENCH 15972, JIRA MALIGOOL 39509, MARCEL PAGNOL 8234, THE BAKER'S WIFE 15575, THE IRON LADIES 13003, THE WELL-DIGGER'S DAUGHTER 23886, THE WOG BOY 10434, VINCE COLOSIMO src, edge_attr, dst 8234, directed_by, 39509 8234, has_genre, 30463 8234, has_tags, 39509 8234, in_language, 6012 15575, has_genre, 30463 15575, release_year, 6776 15575, written_by, 15972 13003, directed_by, 39509 13003, has_genre, 30463 13003, has_tags, 39509 13003, in_language, 6012 13003, written_by, 39509 23886, has_genre, 30463 23886, release_year, 6776 23886, starred_actors, 10434 Question: How are JIRA MALIGOOL, MARCEL PAGNOL, and VINCE COLOSIMO related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JIRA MALIGOOL", "MARCEL PAGNOL", "VINCE COLOSIMO" ], "valid_edges": [ [ "THE BAKER'S WIFE", "directed_by", "MARCEL PAGNOL" ], [ "THE BAKER'S WIFE", "has_genre", "COMEDY" ], [ "THE BAKER'S WIFE", "has_tags", "MARCEL PAGNOL" ], [ "THE BAKER'S WIFE", "in_language", "FRENCH" ], [ "THE IRON LADIES", "has_genre", "COMEDY" ], [ "THE IRON LADIES", "release_year", "2000" ], [ "THE IRON LADIES", "written_by", "JIRA MALIGOOL" ], [ "THE WELL-DIGGER'S DAUGHTER", "directed_by", "MARCEL PAGNOL" ], [ "THE WELL-DIGGER'S DAUGHTER", "has_genre", "COMEDY" ], [ "THE WELL-DIGGER'S DAUGHTER", "has_tags", "MARCEL PAGNOL" ], [ "THE WELL-DIGGER'S DAUGHTER", "in_language", "FRENCH" ], [ "THE WELL-DIGGER'S DAUGHTER", "written_by", "MARCEL PAGNOL" ], [ "THE WOG BOY", "has_genre", "COMEDY" ], [ "THE WOG BOY", "release_year", "2000" ], [ "THE WOG BOY", "starred_actors", "VINCE COLOSIMO" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26423, 1950 6216, 1952 39624, 1957 27810, 1968 1006, 1996 13999, ANDREW V. MCLAGLEN 5661, ANTHONY MANN 35990, ARTHUR KENNEDY 4816, BANDOLERO! 3204, BEND OF THE RIVER 16749, BROKEN ARROW 29246, CARBINE WILLIAMS 14087, COMES A HORSEMAN 7159, DESTRY RIDES AGAIN 8406, FIRECREEK 36979, GINA BELLMAN 34477, HARVEY 34149, HENRY FONDA 7736, JAMES STEWART 13255, JOHN FORD 36999, MAUREEN O'HARA 20920, MR. HOBBS TAKES A VACATION 37497, NATIONAL FILM REGISTRY 35223, NIGHT PASSAGE 9638, ON OUR MERRY WAY 7098, SHENANDOAH 38066, SHIRLEY JONES 24498, SILENT TRIGGER 26381, STRATEGIC AIR COMMAND 7763, THE CHEYENNE SOCIAL CLUB 27995, THE FAR COUNTRY 26752, THE GLENN MILLER STORY 17394, THE MAN FROM LARAMIE 36235, THE MAN WHO SHOT LIBERTY VALANCE 39232, THE NAKED SPUR 2555, THE RARE BREED 31357, THE SHOOTIST 935, THE SPIRIT OF ST. LOUIS 32490, THUNDER BAY 37207, TWO RODE TOGETHER 36026, WESTERN 26441, WINCHESTER '73 src, edge_attr, dst 4816, directed_by, 13999 4816, release_year, 27810 4816, starred_actors, 7736 3204, directed_by, 5661 3204, has_genre, 36026 3204, has_tags, 5661 3204, has_tags, 7736 3204, release_year, 6216 3204, starred_actors, 35990 3204, starred_actors, 7736 16749, has_genre, 36026 16749, release_year, 26423 16749, release_year, 1006 16749, starred_actors, 7736 29246, release_year, 6216 29246, starred_actors, 7736 14087, has_genre, 36026 7159, has_genre, 36026 7159, has_tags, 7736 7159, has_tags, 37497 7159, starred_actors, 7736 8406, has_genre, 36026 8406, release_year, 27810 8406, starred_actors, 34149 8406, starred_actors, 7736 34477, has_tags, 7736 34477, release_year, 26423 34477, release_year, 1006 34477, starred_actors, 7736 20920, starred_actors, 7736 20920, starred_actors, 36999 35223, has_genre, 36026 35223, release_year, 39624 35223, starred_actors, 7736 9638, starred_actors, 34149 9638, starred_actors, 7736 7098, directed_by, 13999 7098, has_tags, 13999 7098, has_tags, 7736 7098, starred_actors, 7736 24498, release_year, 1006 24498, starred_actors, 36979 26381, directed_by, 5661 26381, starred_actors, 7736 7763, has_genre, 36026 7763, starred_actors, 34149 7763, starred_actors, 7736 7763, starred_actors, 38066 27995, directed_by, 5661 27995, has_tags, 5661 27995, starred_actors, 7736 26752, directed_by, 5661 26752, has_tags, 5661 26752, has_tags, 7736 26752, starred_actors, 7736 17394, directed_by, 5661 17394, has_genre, 36026 17394, has_tags, 5661 17394, starred_actors, 35990 17394, starred_actors, 7736 36235, directed_by, 13255 36235, has_genre, 36026 36235, has_tags, 7736 36235, has_tags, 13255 36235, has_tags, 37497 36235, has_tags, 36026 36235, starred_actors, 7736 39232, directed_by, 5661 39232, has_genre, 36026 39232, has_tags, 5661 39232, has_tags, 7736 39232, starred_actors, 7736 2555, directed_by, 13999 2555, has_genre, 36026 2555, starred_actors, 7736 2555, starred_actors, 36999 31357, has_genre, 36026 31357, starred_actors, 7736 935, release_year, 39624 935, starred_actors, 7736 32490, directed_by, 5661 32490, starred_actors, 7736 37207, directed_by, 13255 37207, has_genre, 36026 37207, starred_actors, 7736 37207, starred_actors, 38066 26441, directed_by, 5661 26441, has_genre, 36026 26441, has_tags, 5661 26441, release_year, 26423 26441, starred_actors, 7736 Question: For what reason are COMES A HORSEMAN, GINA BELLMAN, and JAMES STEWART associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "COMES A HORSEMAN", "GINA BELLMAN", "JAMES STEWART" ], "valid_edges": [ [ "BANDOLERO!", "directed_by", "ANDREW V. MCLAGLEN" ], [ "BANDOLERO!", "release_year", "1968" ], [ "BANDOLERO!", "starred_actors", "JAMES STEWART" ], [ "BEND OF THE RIVER", "directed_by", "ANTHONY MANN" ], [ "BEND OF THE RIVER", "has_genre", "WESTERN" ], [ "BEND OF THE RIVER", "has_tags", "ANTHONY MANN" ], [ "BEND OF THE RIVER", "has_tags", "JAMES STEWART" ], [ "BEND OF THE RIVER", "release_year", "1952" ], [ "BEND OF THE RIVER", "starred_actors", "ARTHUR KENNEDY" ], [ "BEND OF THE RIVER", "starred_actors", "JAMES STEWART" ], [ "BROKEN ARROW", "has_genre", "WESTERN" ], [ "BROKEN ARROW", "release_year", "1950" ], [ "BROKEN ARROW", "release_year", "1996" ], [ "BROKEN ARROW", "starred_actors", "JAMES STEWART" ], [ "CARBINE WILLIAMS", "release_year", "1952" ], [ "CARBINE WILLIAMS", "starred_actors", "JAMES STEWART" ], [ "COMES A HORSEMAN", "has_genre", "WESTERN" ], [ "DESTRY RIDES AGAIN", "has_genre", "WESTERN" ], [ "DESTRY RIDES AGAIN", "has_tags", "JAMES STEWART" ], [ "DESTRY RIDES AGAIN", "has_tags", "NATIONAL FILM REGISTRY" ], [ "DESTRY RIDES AGAIN", "starred_actors", "JAMES STEWART" ], [ "FIRECREEK", "has_genre", "WESTERN" ], [ "FIRECREEK", "release_year", "1968" ], [ "FIRECREEK", "starred_actors", "HENRY FONDA" ], [ "FIRECREEK", "starred_actors", "JAMES STEWART" ], [ "HARVEY", "has_tags", "JAMES STEWART" ], [ "HARVEY", "release_year", "1950" ], [ "HARVEY", "release_year", "1996" ], [ "HARVEY", "starred_actors", "JAMES STEWART" ], [ "MR. HOBBS TAKES A VACATION", "starred_actors", "JAMES STEWART" ], [ "MR. HOBBS TAKES A VACATION", "starred_actors", "MAUREEN O'HARA" ], [ "NIGHT PASSAGE", "has_genre", "WESTERN" ], [ "NIGHT PASSAGE", "release_year", "1957" ], [ "NIGHT PASSAGE", "starred_actors", "JAMES STEWART" ], [ "ON OUR MERRY WAY", "starred_actors", "HENRY FONDA" ], [ "ON OUR MERRY WAY", "starred_actors", "JAMES STEWART" ], [ "SHENANDOAH", "directed_by", "ANDREW V. MCLAGLEN" ], [ "SHENANDOAH", "has_tags", "ANDREW V. MCLAGLEN" ], [ "SHENANDOAH", "has_tags", "JAMES STEWART" ], [ "SHENANDOAH", "starred_actors", "JAMES STEWART" ], [ "SILENT TRIGGER", "release_year", "1996" ], [ "SILENT TRIGGER", "starred_actors", "GINA BELLMAN" ], [ "STRATEGIC AIR COMMAND", "directed_by", "ANTHONY MANN" ], [ "STRATEGIC AIR COMMAND", "starred_actors", "JAMES STEWART" ], [ "THE CHEYENNE SOCIAL CLUB", "has_genre", "WESTERN" ], [ "THE CHEYENNE SOCIAL CLUB", "starred_actors", "HENRY FONDA" ], [ "THE CHEYENNE SOCIAL CLUB", "starred_actors", "JAMES STEWART" ], [ "THE CHEYENNE SOCIAL CLUB", "starred_actors", "SHIRLEY JONES" ], [ "THE FAR COUNTRY", "directed_by", "ANTHONY MANN" ], [ "THE FAR COUNTRY", "has_tags", "ANTHONY MANN" ], [ "THE FAR COUNTRY", "starred_actors", "JAMES STEWART" ], [ "THE GLENN MILLER STORY", "directed_by", "ANTHONY MANN" ], [ "THE GLENN MILLER STORY", "has_tags", "ANTHONY MANN" ], [ "THE GLENN MILLER STORY", "has_tags", "JAMES STEWART" ], [ "THE GLENN MILLER STORY", "starred_actors", "JAMES STEWART" ], [ "THE MAN FROM LARAMIE", "directed_by", "ANTHONY MANN" ], [ "THE MAN FROM LARAMIE", "has_genre", "WESTERN" ], [ "THE MAN FROM LARAMIE", "has_tags", "ANTHONY MANN" ], [ "THE MAN FROM LARAMIE", "starred_actors", "ARTHUR KENNEDY" ], [ "THE MAN FROM LARAMIE", "starred_actors", "JAMES STEWART" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "directed_by", "JOHN FORD" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_genre", "WESTERN" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "JAMES STEWART" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "JOHN FORD" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "WESTERN" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "starred_actors", "JAMES STEWART" ], [ "THE NAKED SPUR", "directed_by", "ANTHONY MANN" ], [ "THE NAKED SPUR", "has_genre", "WESTERN" ], [ "THE NAKED SPUR", "has_tags", "ANTHONY MANN" ], [ "THE NAKED SPUR", "has_tags", "JAMES STEWART" ], [ "THE NAKED SPUR", "starred_actors", "JAMES STEWART" ], [ "THE RARE BREED", "directed_by", "ANDREW V. MCLAGLEN" ], [ "THE RARE BREED", "has_genre", "WESTERN" ], [ "THE RARE BREED", "starred_actors", "JAMES STEWART" ], [ "THE RARE BREED", "starred_actors", "MAUREEN O'HARA" ], [ "THE SHOOTIST", "has_genre", "WESTERN" ], [ "THE SHOOTIST", "starred_actors", "JAMES STEWART" ], [ "THE SPIRIT OF ST. LOUIS", "release_year", "1957" ], [ "THE SPIRIT OF ST. LOUIS", "starred_actors", "JAMES STEWART" ], [ "THUNDER BAY", "directed_by", "ANTHONY MANN" ], [ "THUNDER BAY", "starred_actors", "JAMES STEWART" ], [ "TWO RODE TOGETHER", "directed_by", "JOHN FORD" ], [ "TWO RODE TOGETHER", "has_genre", "WESTERN" ], [ "TWO RODE TOGETHER", "starred_actors", "JAMES STEWART" ], [ "TWO RODE TOGETHER", "starred_actors", "SHIRLEY JONES" ], [ "WINCHESTER '73", "directed_by", "ANTHONY MANN" ], [ "WINCHESTER '73", "has_genre", "WESTERN" ], [ "WINCHESTER '73", "has_tags", "ANTHONY MANN" ], [ "WINCHESTER '73", "release_year", "1950" ], [ "WINCHESTER '73", "starred_actors", "JAMES STEWART" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 38097, 1985 13408, 2001 31672, A.K. 17638, BRIEF CROSSING 38311, CHAOS 36073, FAT GIRL 6012, FRENCH 35881, GIRLS JUST WANT TO HAVE FUN 2004, JOSEF VON STERNBERG 25785, KISS OF THE DRAGON 26375, MARLENE DIETRICH 1422, MOROCCO 29620, POLICE 27191, RENDEZ-VOUS 8379, ROMANCE 11723, SHOAH 39270, SUBWAY 28368, THE DEVIL IS A WOMAN 35826, THE PEANUT BUTTER SOLUTION 39469, THE PORNOGRAPHER 12294, VAGABOND 29077, WASABI 19257, WINGED MIGRATION src, edge_attr, dst 31672, in_language, 6012 31672, release_year, 38097 17638, in_language, 6012 17638, release_year, 13408 38311, in_language, 6012 38311, release_year, 13408 36073, in_language, 6012 36073, release_year, 13408 35881, release_year, 38097 25785, in_language, 6012 25785, release_year, 13408 1422, directed_by, 2004 1422, has_genre, 8379 1422, has_tags, 2004 1422, has_tags, 26375 1422, starred_actors, 26375 29620, in_language, 6012 29620, release_year, 38097 27191, in_language, 6012 27191, release_year, 38097 8379, in_language, 6012 11723, in_language, 6012 11723, release_year, 38097 39270, in_language, 6012 39270, release_year, 38097 28368, directed_by, 2004 28368, has_genre, 8379 28368, has_tags, 2004 28368, starred_actors, 26375 35826, in_language, 6012 35826, release_year, 38097 39469, in_language, 6012 39469, release_year, 13408 12294, in_language, 6012 12294, release_year, 38097 29077, in_language, 6012 29077, release_year, 13408 19257, in_language, 6012 19257, release_year, 13408 Question: For what reason are GIRLS JUST WANT TO HAVE FUN, JOSEF VON STERNBERG, and THE PORNOGRAPHER associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "GIRLS JUST WANT TO HAVE FUN", "JOSEF VON STERNBERG", "THE PORNOGRAPHER" ], "valid_edges": [ [ "A.K.", "in_language", "FRENCH" ], [ "A.K.", "release_year", "1985" ], [ "BRIEF CROSSING", "in_language", "FRENCH" ], [ "BRIEF CROSSING", "release_year", "2001" ], [ "CHAOS", "in_language", "FRENCH" ], [ "CHAOS", "release_year", "2001" ], [ "FAT GIRL", "in_language", "FRENCH" ], [ "FAT GIRL", "release_year", "2001" ], [ "GIRLS JUST WANT TO HAVE FUN", "release_year", "1985" ], [ "KISS OF THE DRAGON", "in_language", "FRENCH" ], [ "KISS OF THE DRAGON", "release_year", "2001" ], [ "MOROCCO", "directed_by", "JOSEF VON STERNBERG" ], [ "MOROCCO", "has_genre", "ROMANCE" ], [ "MOROCCO", "has_tags", "JOSEF VON STERNBERG" ], [ "MOROCCO", "has_tags", "MARLENE DIETRICH" ], [ "MOROCCO", "starred_actors", "MARLENE DIETRICH" ], [ "POLICE", "in_language", "FRENCH" ], [ "POLICE", "release_year", "1985" ], [ "RENDEZ-VOUS", "in_language", "FRENCH" ], [ "RENDEZ-VOUS", "release_year", "1985" ], [ "ROMANCE", "in_language", "FRENCH" ], [ "SHOAH", "in_language", "FRENCH" ], [ "SHOAH", "release_year", "1985" ], [ "SUBWAY", "in_language", "FRENCH" ], [ "SUBWAY", "release_year", "1985" ], [ "THE DEVIL IS A WOMAN", "directed_by", "JOSEF VON STERNBERG" ], [ "THE DEVIL IS A WOMAN", "has_genre", "ROMANCE" ], [ "THE DEVIL IS A WOMAN", "has_tags", "JOSEF VON STERNBERG" ], [ "THE DEVIL IS A WOMAN", "starred_actors", "MARLENE DIETRICH" ], [ "THE PEANUT BUTTER SOLUTION", "in_language", "FRENCH" ], [ "THE PEANUT BUTTER SOLUTION", "release_year", "1985" ], [ "THE PORNOGRAPHER", "in_language", "FRENCH" ], [ "THE PORNOGRAPHER", "release_year", "2001" ], [ "VAGABOND", "in_language", "FRENCH" ], [ "VAGABOND", "release_year", "1985" ], [ "WASABI", "in_language", "FRENCH" ], [ "WASABI", "release_year", "2001" ], [ "WINGED MIGRATION", "in_language", "FRENCH" ], [ "WINGED MIGRATION", "release_year", "2001" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26277, A FEW GOOD MEN 15184, AARON SORKIN 3522, ANTI-SEMITISM 32020, DANIELA SILVERIO 36212, DRAMA 31621, GENTLEMAN'S AGREEMENT 37734, IDENTIFICATION OF A WOMAN 30221, LAW 5106, THE SOCIAL NETWORK src, edge_attr, dst 26277, has_genre, 36212 26277, has_tags, 15184 26277, has_tags, 36212 26277, has_tags, 30221 26277, written_by, 15184 31621, has_genre, 36212 31621, has_tags, 3522 37734, has_genre, 36212 37734, starred_actors, 32020 5106, has_genre, 36212 5106, has_tags, 15184 5106, has_tags, 30221 5106, written_by, 15184 Question: For what reason are ANTI-SEMITISM, DANIELA SILVERIO, and LAW associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ANTI-SEMITISM", "DANIELA SILVERIO", "LAW" ], "valid_edges": [ [ "A FEW GOOD MEN", "has_genre", "DRAMA" ], [ "A FEW GOOD MEN", "has_tags", "AARON SORKIN" ], [ "A FEW GOOD MEN", "has_tags", "DRAMA" ], [ "A FEW GOOD MEN", "has_tags", "LAW" ], [ "A FEW GOOD MEN", "written_by", "AARON SORKIN" ], [ "GENTLEMAN'S AGREEMENT", "has_genre", "DRAMA" ], [ "GENTLEMAN'S AGREEMENT", "has_tags", "ANTI-SEMITISM" ], [ "IDENTIFICATION OF A WOMAN", "has_genre", "DRAMA" ], [ "IDENTIFICATION OF A WOMAN", "starred_actors", "DANIELA SILVERIO" ], [ "THE SOCIAL NETWORK", "has_genre", "DRAMA" ], [ "THE SOCIAL NETWORK", "has_tags", "AARON SORKIN" ], [ "THE SOCIAL NETWORK", "has_tags", "LAW" ], [ "THE SOCIAL NETWORK", "written_by", "AARON SORKIN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 32857, ALLISON ANDERS 10045, BD-R 6399, BORDER RADIO 16659, CASINO ROYALE 3138, CHRISTOPHER MELONI 30463, COMEDY 15796, DANIEL CRAIG 36212, DRAMA 18387, FLASHBACKS OF A FOOL 20761, FOUR ROOMS 13081, R 16954, SYLVIA 38039, THE DIARY OF A TEENAGE GIRL 7240, THE GIRL WITH THE DRAGON TATTOO src, edge_attr, dst 6399, directed_by, 32857 6399, has_tags, 32857 6399, has_tags, 10045 6399, written_by, 32857 16659, has_genre, 30463 16659, has_tags, 10045 16659, has_tags, 15796 16659, starred_actors, 15796 18387, has_genre, 36212 18387, has_tags, 13081 18387, starred_actors, 15796 20761, directed_by, 32857 20761, has_genre, 30463 20761, has_tags, 32857 20761, has_tags, 30463 20761, written_by, 32857 16954, has_genre, 36212 16954, has_tags, 15796 16954, starred_actors, 15796 38039, has_genre, 36212 38039, starred_actors, 3138 7240, has_genre, 36212 7240, has_tags, 15796 7240, has_tags, 13081 7240, starred_actors, 15796 Question: For what reason are ALLISON ANDERS, CHRISTOPHER MELONI, and DANIEL CRAIG associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ALLISON ANDERS", "CHRISTOPHER MELONI", "DANIEL CRAIG" ], "valid_edges": [ [ "BORDER RADIO", "directed_by", "ALLISON ANDERS" ], [ "BORDER RADIO", "has_tags", "ALLISON ANDERS" ], [ "BORDER RADIO", "has_tags", "BD-R" ], [ "BORDER RADIO", "written_by", "ALLISON ANDERS" ], [ "CASINO ROYALE", "has_genre", "COMEDY" ], [ "CASINO ROYALE", "has_tags", "BD-R" ], [ "CASINO ROYALE", "has_tags", "DANIEL CRAIG" ], [ "CASINO ROYALE", "starred_actors", "DANIEL CRAIG" ], [ "FLASHBACKS OF A FOOL", "has_genre", "DRAMA" ], [ "FLASHBACKS OF A FOOL", "has_tags", "R" ], [ "FLASHBACKS OF A FOOL", "starred_actors", "DANIEL CRAIG" ], [ "FOUR ROOMS", "directed_by", "ALLISON ANDERS" ], [ "FOUR ROOMS", "has_genre", "COMEDY" ], [ "FOUR ROOMS", "has_tags", "ALLISON ANDERS" ], [ "FOUR ROOMS", "has_tags", "COMEDY" ], [ "FOUR ROOMS", "written_by", "ALLISON ANDERS" ], [ "SYLVIA", "has_genre", "DRAMA" ], [ "SYLVIA", "has_tags", "DANIEL CRAIG" ], [ "SYLVIA", "starred_actors", "DANIEL CRAIG" ], [ "THE DIARY OF A TEENAGE GIRL", "has_genre", "DRAMA" ], [ "THE DIARY OF A TEENAGE GIRL", "starred_actors", "CHRISTOPHER MELONI" ], [ "THE GIRL WITH THE DRAGON TATTOO", "has_genre", "DRAMA" ], [ "THE GIRL WITH THE DRAGON TATTOO", "has_tags", "DANIEL CRAIG" ], [ "THE GIRL WITH THE DRAGON TATTOO", "has_tags", "R" ], [ "THE GIRL WITH THE DRAGON TATTOO", "starred_actors", "DANIEL CRAIG" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 25221, 1981 22892, GORY 29418, JEREMY IRONS 27927, LOU BRESLOW 22845, MUSIC 9638, ON OUR MERRY WAY 22714, OWN 6630, THE EVIL DEAD 25206, THE FRENCH LIEUTENANT'S WOMAN 14478, THE LION KING 38433, THE MERCHANT OF VENICE src, edge_attr, dst 9638, has_genre, 22845 9638, written_by, 27927 6630, has_tags, 22892 6630, has_tags, 22714 6630, release_year, 25221 25206, has_tags, 29418 25206, release_year, 25221 25206, starred_actors, 29418 14478, has_tags, 29418 14478, has_tags, 22845 14478, has_tags, 22714 14478, starred_actors, 29418 38433, has_tags, 22714 38433, starred_actors, 29418 Question: In what context are GORY, JEREMY IRONS, and LOU BRESLOW connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "GORY", "JEREMY IRONS", "LOU BRESLOW" ], "valid_edges": [ [ "ON OUR MERRY WAY", "has_genre", "MUSIC" ], [ "ON OUR MERRY WAY", "written_by", "LOU BRESLOW" ], [ "THE EVIL DEAD", "has_tags", "GORY" ], [ "THE EVIL DEAD", "has_tags", "OWN" ], [ "THE EVIL DEAD", "release_year", "1981" ], [ "THE FRENCH LIEUTENANT'S WOMAN", "has_tags", "JEREMY IRONS" ], [ "THE FRENCH LIEUTENANT'S WOMAN", "release_year", "1981" ], [ "THE FRENCH LIEUTENANT'S WOMAN", "starred_actors", "JEREMY IRONS" ], [ "THE LION KING", "has_tags", "JEREMY IRONS" ], [ "THE LION KING", "has_tags", "MUSIC" ], [ "THE LION KING", "has_tags", "OWN" ], [ "THE LION KING", "starred_actors", "JEREMY IRONS" ], [ "THE MERCHANT OF VENICE", "has_tags", "OWN" ], [ "THE MERCHANT OF VENICE", "starred_actors", "JEREMY IRONS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26423, 1950 37224, 1990 859, ACTORS 37068, ALFRED E. GREEN 23277, DAYS OF THUNDER 35304, NASCAR 3317, THE JACKIE ROBINSON STORY 1341, TREASURE ISLAND src, edge_attr, dst 23277, has_tags, 35304 23277, release_year, 37224 3317, directed_by, 37068 3317, release_year, 26423 1341, has_tags, 859 1341, release_year, 26423 1341, release_year, 37224 Question: How are ACTORS, ALFRED E. GREEN, and NASCAR related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ACTORS", "ALFRED E. GREEN", "NASCAR" ], "valid_edges": [ [ "DAYS OF THUNDER", "has_tags", "NASCAR" ], [ "DAYS OF THUNDER", "release_year", "1990" ], [ "THE JACKIE ROBINSON STORY", "directed_by", "ALFRED E. GREEN" ], [ "THE JACKIE ROBINSON STORY", "release_year", "1950" ], [ "TREASURE ISLAND", "has_tags", "ACTORS" ], [ "TREASURE ISLAND", "release_year", "1950" ], [ "TREASURE ISLAND", "release_year", "1990" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39435, 1975 3807, FASCISM 16200, ITALIAN 15549, JEFFREY KRAMER 19396, ROMANO MIGLIORINI 39117, SALÒ, OR THE 120 DAYS OF SODOM 1045, SMILE 18637, THE INGLORIOUS BASTARDS src, edge_attr, dst 39117, has_tags, 3807 39117, in_language, 16200 39117, release_year, 39435 1045, directed_by, 15549 1045, release_year, 39435 1045, written_by, 15549 18637, in_language, 16200 18637, written_by, 19396 Question: For what reason are FASCISM, JEFFREY KRAMER, and ROMANO MIGLIORINI associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "FASCISM", "JEFFREY KRAMER", "ROMANO MIGLIORINI" ], "valid_edges": [ [ "SALÒ, OR THE 120 DAYS OF SODOM", "has_tags", "FASCISM" ], [ "SALÒ, OR THE 120 DAYS OF SODOM", "in_language", "ITALIAN" ], [ "SALÒ, OR THE 120 DAYS OF SODOM", "release_year", "1975" ], [ "SMILE", "directed_by", "JEFFREY KRAMER" ], [ "SMILE", "release_year", "1975" ], [ "SMILE", "written_by", "JEFFREY KRAMER" ], [ "THE INGLORIOUS BASTARDS", "in_language", "ITALIAN" ], [ "THE INGLORIOUS BASTARDS", "written_by", "ROMANO MIGLIORINI" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35845, 2006 27261, 2009 1912, BEYOND ALL BOUNDARIES 4197, BLUEBEARD 6283, CARGO 37236, EDWARD DMYTRYK 14735, FINAL DESTINATION 3 24481, FRANCHISE 22215, FRIDAY THE 13TH 15753, HALLOWEEN II 28852, HANNAH FREE 6780, INTO THE STORM 3942, SALVAGE 5812, SAW III 180, SAW VI 9228, SCARY MOVIE 4 34989, STAR TREK 23472, TERMINATOR SALVATION 36692, THE CAINE MUTINY 31206, THE FINAL DESTINATION 24155, WORLD WAR II src, edge_attr, dst 1912, has_tags, 24155 1912, release_year, 27261 4197, directed_by, 37236 4197, release_year, 27261 4197, written_by, 37236 6283, release_year, 35845 6283, release_year, 27261 14735, has_tags, 24481 14735, release_year, 35845 22215, has_tags, 24481 22215, release_year, 27261 15753, has_tags, 24481 15753, release_year, 27261 28852, release_year, 27261 6780, has_tags, 24155 6780, release_year, 27261 3942, release_year, 35845 3942, release_year, 27261 5812, has_tags, 24481 5812, release_year, 35845 180, has_tags, 24481 180, release_year, 27261 9228, has_tags, 24481 9228, release_year, 35845 34989, has_tags, 24481 34989, release_year, 27261 23472, has_tags, 24481 23472, release_year, 27261 36692, directed_by, 37236 36692, has_tags, 37236 36692, has_tags, 24155 31206, has_tags, 24481 31206, release_year, 27261 Question: In what context are FINAL DESTINATION 3, HANNAH FREE, and THE CAINE MUTINY connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "FINAL DESTINATION 3", "HANNAH FREE", "THE CAINE MUTINY" ], "valid_edges": [ [ "BEYOND ALL BOUNDARIES", "has_tags", "WORLD WAR II" ], [ "BEYOND ALL BOUNDARIES", "release_year", "2009" ], [ "BLUEBEARD", "directed_by", "EDWARD DMYTRYK" ], [ "BLUEBEARD", "release_year", "2009" ], [ "BLUEBEARD", "written_by", "EDWARD DMYTRYK" ], [ "CARGO", "release_year", "2006" ], [ "CARGO", "release_year", "2009" ], [ "FINAL DESTINATION 3", "has_tags", "FRANCHISE" ], [ "FINAL DESTINATION 3", "release_year", "2006" ], [ "FRIDAY THE 13TH", "has_tags", "FRANCHISE" ], [ "FRIDAY THE 13TH", "release_year", "2009" ], [ "HALLOWEEN II", "has_tags", "FRANCHISE" ], [ "HALLOWEEN II", "release_year", "2009" ], [ "HANNAH FREE", "release_year", "2009" ], [ "INTO THE STORM", "has_tags", "WORLD WAR II" ], [ "INTO THE STORM", "release_year", "2009" ], [ "SALVAGE", "release_year", "2006" ], [ "SALVAGE", "release_year", "2009" ], [ "SAW III", "has_tags", "FRANCHISE" ], [ "SAW III", "release_year", "2006" ], [ "SAW VI", "has_tags", "FRANCHISE" ], [ "SAW VI", "release_year", "2009" ], [ "SCARY MOVIE 4", "has_tags", "FRANCHISE" ], [ "SCARY MOVIE 4", "release_year", "2006" ], [ "STAR TREK", "has_tags", "FRANCHISE" ], [ "STAR TREK", "release_year", "2009" ], [ "TERMINATOR SALVATION", "has_tags", "FRANCHISE" ], [ "TERMINATOR SALVATION", "release_year", "2009" ], [ "THE CAINE MUTINY", "directed_by", "EDWARD DMYTRYK" ], [ "THE CAINE MUTINY", "has_tags", "EDWARD DMYTRYK" ], [ "THE CAINE MUTINY", "has_tags", "WORLD WAR II" ], [ "THE FINAL DESTINATION", "has_tags", "FRANCHISE" ], [ "THE FINAL DESTINATION", "release_year", "2009" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1892, 1932 33637, 1959 25221, 1981 37172, BELA LUGOSI 34733, CHANDU THE MAGICIAN 33269, ISLAND OF LOST SOULS 12435, JOHN WAYNE 18744, MURDERS IN THE RUE MORGUE 5794, ONLY WHEN I LAUGH 28388, PLAN 9 FROM OUTER SPACE 36102, RIO BRAVO 13251, THE BIG STAMPEDE 35827, THE DEATH KISS 5663, THE HORSE SOLDIERS 7028, THE HURRICANE EXPRESS 26820, THE MUMMY 35444, THE SHADOW OF THE EAGLE 14902, ZOMBIE 33616, ZOMBIE LAKE src, edge_attr, dst 34733, release_year, 1892 34733, starred_actors, 37172 33269, has_tags, 37172 33269, release_year, 1892 33269, starred_actors, 37172 18744, release_year, 1892 18744, starred_actors, 37172 5794, release_year, 25221 28388, has_tags, 37172 28388, has_tags, 14902 28388, release_year, 33637 36102, has_tags, 12435 36102, release_year, 33637 36102, starred_actors, 12435 13251, release_year, 1892 13251, starred_actors, 12435 35827, release_year, 1892 35827, starred_actors, 37172 5663, has_tags, 12435 5663, release_year, 33637 5663, starred_actors, 12435 7028, release_year, 1892 7028, starred_actors, 12435 26820, release_year, 1892 26820, release_year, 33637 35444, has_tags, 12435 35444, release_year, 1892 35444, starred_actors, 12435 33616, has_tags, 14902 33616, release_year, 25221 Question: For what reason are ONLY WHEN I LAUGH, PLAN 9 FROM OUTER SPACE, and THE BIG STAMPEDE associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ONLY WHEN I LAUGH", "PLAN 9 FROM OUTER SPACE", "THE BIG STAMPEDE" ], "valid_edges": [ [ "CHANDU THE MAGICIAN", "release_year", "1932" ], [ "CHANDU THE MAGICIAN", "starred_actors", "BELA LUGOSI" ], [ "ISLAND OF LOST SOULS", "has_tags", "BELA LUGOSI" ], [ "ISLAND OF LOST SOULS", "release_year", "1932" ], [ "ISLAND OF LOST SOULS", "starred_actors", "BELA LUGOSI" ], [ "MURDERS IN THE RUE MORGUE", "release_year", "1932" ], [ "MURDERS IN THE RUE MORGUE", "starred_actors", "BELA LUGOSI" ], [ "ONLY WHEN I LAUGH", "release_year", "1981" ], [ "PLAN 9 FROM OUTER SPACE", "has_tags", "BELA LUGOSI" ], [ "PLAN 9 FROM OUTER SPACE", "has_tags", "ZOMBIE" ], [ "PLAN 9 FROM OUTER SPACE", "release_year", "1959" ], [ "RIO BRAVO", "has_tags", "JOHN WAYNE" ], [ "RIO BRAVO", "release_year", "1959" ], [ "RIO BRAVO", "starred_actors", "JOHN WAYNE" ], [ "THE BIG STAMPEDE", "release_year", "1932" ], [ "THE BIG STAMPEDE", "starred_actors", "JOHN WAYNE" ], [ "THE DEATH KISS", "release_year", "1932" ], [ "THE DEATH KISS", "starred_actors", "BELA LUGOSI" ], [ "THE HORSE SOLDIERS", "has_tags", "JOHN WAYNE" ], [ "THE HORSE SOLDIERS", "release_year", "1959" ], [ "THE HORSE SOLDIERS", "starred_actors", "JOHN WAYNE" ], [ "THE HURRICANE EXPRESS", "release_year", "1932" ], [ "THE HURRICANE EXPRESS", "starred_actors", "JOHN WAYNE" ], [ "THE MUMMY", "release_year", "1932" ], [ "THE MUMMY", "release_year", "1959" ], [ "THE SHADOW OF THE EAGLE", "has_tags", "JOHN WAYNE" ], [ "THE SHADOW OF THE EAGLE", "release_year", "1932" ], [ "THE SHADOW OF THE EAGLE", "starred_actors", "JOHN WAYNE" ], [ "ZOMBIE LAKE", "has_tags", "ZOMBIE" ], [ "ZOMBIE LAKE", "release_year", "1981" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26762, 2008 17521, ACES 'N' EIGHTS 39289, ACTION 39750, ALIENS 10293, CONSPIRACY 33868, DEAN DEVLIN 5148, DEATH RACE 3553, GODZILLA 5870, HORROR 23780, HURT 8842, INDEPENDENCE DAY 27533, IRON MAN 27764, PAINTED SKIN 681, PISTOL WHIPPED 9720, QUANTUM OF SOLACE 12811, RAMBO 31404, ROLAND EMMERICH 6507, SOFIA VASSILIEVA 8325, STARGATE 2820, THE FORBIDDEN KINGDOM 1081, TRANSPORTER 3 8868, VANTAGE POINT 25527, VICE 22588, WANTED 22214, WAR src, edge_attr, dst 17521, has_genre, 39289 17521, release_year, 26762 39750, has_genre, 39289 39750, has_tags, 39289 10293, has_genre, 39289 10293, release_year, 26762 5148, has_genre, 39289 5148, release_year, 26762 3553, directed_by, 31404 3553, has_genre, 5870 3553, has_tags, 3553 3553, has_tags, 31404 3553, written_by, 33868 3553, written_by, 31404 23780, has_genre, 5870 23780, starred_actors, 6507 8842, directed_by, 31404 8842, has_tags, 39750 8842, has_tags, 31404 8842, has_tags, 22214 8842, written_by, 33868 8842, written_by, 31404 27533, has_genre, 39289 27533, has_tags, 39289 27533, release_year, 26762 27764, has_genre, 39289 27764, release_year, 26762 681, has_genre, 39289 681, release_year, 26762 9720, has_genre, 39289 9720, has_tags, 39289 9720, release_year, 26762 12811, has_genre, 39289 12811, has_tags, 39289 12811, release_year, 26762 8325, directed_by, 31404 8325, has_tags, 8325 8325, written_by, 33868 8325, written_by, 31404 2820, has_genre, 39289 2820, release_year, 26762 1081, has_genre, 39289 1081, has_tags, 39289 1081, release_year, 26762 8868, has_genre, 39289 8868, release_year, 26762 25527, has_genre, 39289 25527, release_year, 26762 22588, has_genre, 39289 22588, has_tags, 39289 22588, release_year, 26762 22214, has_genre, 39289 Question: How are DEAN DEVLIN, PAINTED SKIN, and SOFIA VASSILIEVA related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DEAN DEVLIN", "PAINTED SKIN", "SOFIA VASSILIEVA" ], "valid_edges": [ [ "ACES 'N' EIGHTS", "has_genre", "ACTION" ], [ "ACES 'N' EIGHTS", "release_year", "2008" ], [ "ALIENS", "has_genre", "ACTION" ], [ "ALIENS", "has_tags", "ACTION" ], [ "CONSPIRACY", "has_genre", "ACTION" ], [ "CONSPIRACY", "release_year", "2008" ], [ "DEATH RACE", "has_genre", "ACTION" ], [ "DEATH RACE", "release_year", "2008" ], [ "GODZILLA", "directed_by", "ROLAND EMMERICH" ], [ "GODZILLA", "has_genre", "HORROR" ], [ "GODZILLA", "has_tags", "GODZILLA" ], [ "GODZILLA", "has_tags", "ROLAND EMMERICH" ], [ "GODZILLA", "written_by", "DEAN DEVLIN" ], [ "GODZILLA", "written_by", "ROLAND EMMERICH" ], [ "HURT", "has_genre", "HORROR" ], [ "HURT", "starred_actors", "SOFIA VASSILIEVA" ], [ "INDEPENDENCE DAY", "directed_by", "ROLAND EMMERICH" ], [ "INDEPENDENCE DAY", "has_tags", "ALIENS" ], [ "INDEPENDENCE DAY", "has_tags", "ROLAND EMMERICH" ], [ "INDEPENDENCE DAY", "has_tags", "WAR" ], [ "INDEPENDENCE DAY", "written_by", "DEAN DEVLIN" ], [ "INDEPENDENCE DAY", "written_by", "ROLAND EMMERICH" ], [ "IRON MAN", "has_genre", "ACTION" ], [ "IRON MAN", "has_tags", "ACTION" ], [ "IRON MAN", "release_year", "2008" ], [ "PAINTED SKIN", "has_genre", "ACTION" ], [ "PAINTED SKIN", "release_year", "2008" ], [ "PISTOL WHIPPED", "has_genre", "ACTION" ], [ "PISTOL WHIPPED", "release_year", "2008" ], [ "QUANTUM OF SOLACE", "has_genre", "ACTION" ], [ "QUANTUM OF SOLACE", "has_tags", "ACTION" ], [ "QUANTUM OF SOLACE", "release_year", "2008" ], [ "RAMBO", "has_genre", "ACTION" ], [ "RAMBO", "has_tags", "ACTION" ], [ "RAMBO", "release_year", "2008" ], [ "STARGATE", "directed_by", "ROLAND EMMERICH" ], [ "STARGATE", "has_tags", "STARGATE" ], [ "STARGATE", "written_by", "DEAN DEVLIN" ], [ "STARGATE", "written_by", "ROLAND EMMERICH" ], [ "THE FORBIDDEN KINGDOM", "has_genre", "ACTION" ], [ "THE FORBIDDEN KINGDOM", "release_year", "2008" ], [ "TRANSPORTER 3", "has_genre", "ACTION" ], [ "TRANSPORTER 3", "has_tags", "ACTION" ], [ "TRANSPORTER 3", "release_year", "2008" ], [ "VANTAGE POINT", "has_genre", "ACTION" ], [ "VANTAGE POINT", "release_year", "2008" ], [ "VICE", "has_genre", "ACTION" ], [ "VICE", "release_year", "2008" ], [ "WANTED", "has_genre", "ACTION" ], [ "WANTED", "has_tags", "ACTION" ], [ "WANTED", "release_year", "2008" ], [ "WAR", "has_genre", "ACTION" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 8539, 1982 6776, 2000 34054, ADRIENNE BARBEAU 37912, CAT PEOPLE 30260, CREEPSHOW 25730, KENT SMITH 32591, SCREAM 3 31618, SWAMP THING 13494, TROIS 11529, WES CRAVEN src, edge_attr, dst 37912, release_year, 8539 37912, starred_actors, 25730 30260, release_year, 8539 30260, starred_actors, 34054 32591, directed_by, 11529 32591, has_tags, 11529 32591, release_year, 6776 31618, directed_by, 11529 31618, has_tags, 11529 31618, release_year, 8539 31618, starred_actors, 34054 31618, written_by, 11529 13494, release_year, 6776 Question: In what context are KENT SMITH, SWAMP THING, and TROIS connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "KENT SMITH", "SWAMP THING", "TROIS" ], "valid_edges": [ [ "CAT PEOPLE", "release_year", "1982" ], [ "CAT PEOPLE", "starred_actors", "KENT SMITH" ], [ "CREEPSHOW", "release_year", "1982" ], [ "CREEPSHOW", "starred_actors", "ADRIENNE BARBEAU" ], [ "SCREAM 3", "directed_by", "WES CRAVEN" ], [ "SCREAM 3", "has_tags", "WES CRAVEN" ], [ "SCREAM 3", "release_year", "2000" ], [ "SWAMP THING", "directed_by", "WES CRAVEN" ], [ "SWAMP THING", "has_tags", "WES CRAVEN" ], [ "SWAMP THING", "release_year", "1982" ], [ "SWAMP THING", "starred_actors", "ADRIENNE BARBEAU" ], [ "SWAMP THING", "written_by", "WES CRAVEN" ], [ "TROIS", "release_year", "2000" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17480, 1988 35845, 2006 29424, 2011 23250, 50/50 14062, ALL THE BOYS LOVE MANDY LANE 1805, AMBER HEARD 33796, DEMOTED 39870, DRIVE ANGRY 10658, HEARTBREAK HOTEL 25761, JONATHAN LEVINE 13237, PULSE 10133, UNKNOWN src, edge_attr, dst 23250, directed_by, 25761 23250, has_tags, 25761 23250, release_year, 29424 14062, directed_by, 25761 14062, release_year, 35845 14062, starred_actors, 1805 33796, release_year, 29424 39870, has_tags, 1805 39870, release_year, 29424 39870, starred_actors, 1805 10658, release_year, 17480 13237, release_year, 17480 13237, release_year, 35845 10133, release_year, 35845 10133, release_year, 29424 Question: In what context are ALL THE BOYS LOVE MANDY LANE, DEMOTED, and HEARTBREAK HOTEL connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ALL THE BOYS LOVE MANDY LANE", "DEMOTED", "HEARTBREAK HOTEL" ], "valid_edges": [ [ "50/50", "directed_by", "JONATHAN LEVINE" ], [ "50/50", "has_tags", "JONATHAN LEVINE" ], [ "50/50", "release_year", "2011" ], [ "ALL THE BOYS LOVE MANDY LANE", "directed_by", "JONATHAN LEVINE" ], [ "ALL THE BOYS LOVE MANDY LANE", "release_year", "2006" ], [ "ALL THE BOYS LOVE MANDY LANE", "starred_actors", "AMBER HEARD" ], [ "DEMOTED", "release_year", "2011" ], [ "DRIVE ANGRY", "has_tags", "AMBER HEARD" ], [ "DRIVE ANGRY", "release_year", "2011" ], [ "DRIVE ANGRY", "starred_actors", "AMBER HEARD" ], [ "HEARTBREAK HOTEL", "release_year", "1988" ], [ "PULSE", "release_year", "1988" ], [ "PULSE", "release_year", "2006" ], [ "UNKNOWN", "release_year", "2006" ], [ "UNKNOWN", "release_year", "2011" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9177, 1956 20257, ADOLPHE MENJOU 21856, ANASTASIA 35067, BOXING 12366, BUNDLE OF JOY 35437, DAVID BUTLER 38130, ELENA AND HER MEN 1475, HARRY CLORK 15210, INGRID BERGMAN 34119, MAURICE VALENCY 28026, SOMEBODY UP THERE LIKES ME 22837, TEA FOR TWO 13314, THE GIRL HE LEFT BEHIND 1368, THE MILKY WAY 21662, THE VISIT src, edge_attr, dst 21856, has_tags, 15210 21856, release_year, 9177 21856, starred_actors, 15210 12366, release_year, 9177 12366, starred_actors, 20257 38130, release_year, 9177 38130, starred_actors, 15210 28026, has_tags, 35067 28026, release_year, 9177 22837, directed_by, 35437 22837, written_by, 1475 13314, directed_by, 35437 13314, release_year, 9177 1368, has_tags, 35067 1368, starred_actors, 20257 1368, written_by, 1475 21662, starred_actors, 15210 21662, written_by, 34119 Question: For what reason are 1956, HARRY CLORK, and MAURICE VALENCY associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "1956", "HARRY CLORK", "MAURICE VALENCY" ], "valid_edges": [ [ "ANASTASIA", "has_tags", "INGRID BERGMAN" ], [ "ANASTASIA", "release_year", "1956" ], [ "ANASTASIA", "starred_actors", "INGRID BERGMAN" ], [ "BUNDLE OF JOY", "release_year", "1956" ], [ "BUNDLE OF JOY", "starred_actors", "ADOLPHE MENJOU" ], [ "ELENA AND HER MEN", "release_year", "1956" ], [ "ELENA AND HER MEN", "starred_actors", "INGRID BERGMAN" ], [ "SOMEBODY UP THERE LIKES ME", "has_tags", "BOXING" ], [ "SOMEBODY UP THERE LIKES ME", "release_year", "1956" ], [ "TEA FOR TWO", "directed_by", "DAVID BUTLER" ], [ "TEA FOR TWO", "written_by", "HARRY CLORK" ], [ "THE GIRL HE LEFT BEHIND", "directed_by", "DAVID BUTLER" ], [ "THE GIRL HE LEFT BEHIND", "release_year", "1956" ], [ "THE MILKY WAY", "has_tags", "BOXING" ], [ "THE MILKY WAY", "starred_actors", "ADOLPHE MENJOU" ], [ "THE MILKY WAY", "written_by", "HARRY CLORK" ], [ "THE VISIT", "starred_actors", "INGRID BERGMAN" ], [ "THE VISIT", "written_by", "MAURICE VALENCY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 15506, 1933 36163, 1967 1407, 42ND STREET 15460, CLAMBAKE 28538, DANCING LADY 27897, DOCTOR DOLITTLE 28372, FLIRTATION WALK 20824, FLYING DOWN TO RIO 4057, FOOTLIGHT PARADE 12817, FRANK BORZAGE 9762, GOING HOLLYWOOD 28905, GOLD DIGGERS OF 1933 12843, HOW TO SUCCEED IN BUSINESS WITHOUT REALLY TRYING 26727, I EVEN MET HAPPY GYPSIES 24411, LADY BE GOOD 22149, LIONEL BARRYMORE 31195, LOOKING FORWARD 8151, MAN'S CASTLE 24593, MUSICAL 20443, NIGHT FLIGHT 23990, SECRETS 5384, STAGE DOOR CANTEEN 23817, STATE FAIR 32813, THE HAPPIEST MILLIONAIRE 29621, THE STRANGER'S RETURN 34585, THE YOUNG GIRLS OF ROCHEFORT 25218, THOROUGHLY MODERN MILLIE src, edge_attr, dst 1407, has_genre, 24593 1407, release_year, 15506 15460, has_genre, 24593 15460, release_year, 36163 28538, has_genre, 24593 28538, release_year, 15506 27897, has_tags, 24593 27897, release_year, 36163 28372, directed_by, 12817 28372, has_genre, 24593 20824, has_genre, 24593 20824, release_year, 15506 4057, has_genre, 24593 4057, has_tags, 24593 4057, release_year, 15506 9762, has_genre, 24593 9762, release_year, 15506 28905, has_genre, 24593 28905, release_year, 15506 12843, has_genre, 24593 12843, has_tags, 24593 12843, release_year, 36163 26727, release_year, 36163 24411, has_genre, 24593 24411, starred_actors, 22149 31195, release_year, 15506 31195, starred_actors, 22149 8151, directed_by, 12817 8151, has_tags, 12817 8151, release_year, 15506 20443, release_year, 15506 20443, starred_actors, 22149 23990, directed_by, 12817 23990, has_tags, 12817 23990, release_year, 15506 5384, directed_by, 12817 5384, has_genre, 24593 23817, has_genre, 24593 23817, release_year, 15506 32813, has_genre, 24593 32813, release_year, 36163 29621, release_year, 15506 29621, starred_actors, 22149 34585, has_genre, 24593 34585, has_tags, 24593 34585, release_year, 36163 25218, has_genre, 24593 25218, release_year, 36163 Question: In what context are FLIRTATION WALK, I EVEN MET HAPPY GYPSIES, and LOOKING FORWARD connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "FLIRTATION WALK", "I EVEN MET HAPPY GYPSIES", "LOOKING FORWARD" ], "valid_edges": [ [ "42ND STREET", "has_genre", "MUSICAL" ], [ "42ND STREET", "release_year", "1933" ], [ "CLAMBAKE", "has_genre", "MUSICAL" ], [ "CLAMBAKE", "release_year", "1967" ], [ "DANCING LADY", "has_genre", "MUSICAL" ], [ "DANCING LADY", "release_year", "1933" ], [ "DOCTOR DOLITTLE", "has_tags", "MUSICAL" ], [ "DOCTOR DOLITTLE", "release_year", "1967" ], [ "FLIRTATION WALK", "directed_by", "FRANK BORZAGE" ], [ "FLIRTATION WALK", "has_genre", "MUSICAL" ], [ "FLYING DOWN TO RIO", "has_genre", "MUSICAL" ], [ "FLYING DOWN TO RIO", "release_year", "1933" ], [ "FOOTLIGHT PARADE", "has_genre", "MUSICAL" ], [ "FOOTLIGHT PARADE", "has_tags", "MUSICAL" ], [ "FOOTLIGHT PARADE", "release_year", "1933" ], [ "GOING HOLLYWOOD", "has_genre", "MUSICAL" ], [ "GOING HOLLYWOOD", "release_year", "1933" ], [ "GOLD DIGGERS OF 1933", "has_genre", "MUSICAL" ], [ "GOLD DIGGERS OF 1933", "release_year", "1933" ], [ "HOW TO SUCCEED IN BUSINESS WITHOUT REALLY TRYING", "has_genre", "MUSICAL" ], [ "HOW TO SUCCEED IN BUSINESS WITHOUT REALLY TRYING", "has_tags", "MUSICAL" ], [ "HOW TO SUCCEED IN BUSINESS WITHOUT REALLY TRYING", "release_year", "1967" ], [ "I EVEN MET HAPPY GYPSIES", "release_year", "1967" ], [ "LADY BE GOOD", "has_genre", "MUSICAL" ], [ "LADY BE GOOD", "starred_actors", "LIONEL BARRYMORE" ], [ "LOOKING FORWARD", "release_year", "1933" ], [ "LOOKING FORWARD", "starred_actors", "LIONEL BARRYMORE" ], [ "MAN'S CASTLE", "directed_by", "FRANK BORZAGE" ], [ "MAN'S CASTLE", "has_tags", "FRANK BORZAGE" ], [ "MAN'S CASTLE", "release_year", "1933" ], [ "NIGHT FLIGHT", "release_year", "1933" ], [ "NIGHT FLIGHT", "starred_actors", "LIONEL BARRYMORE" ], [ "SECRETS", "directed_by", "FRANK BORZAGE" ], [ "SECRETS", "has_tags", "FRANK BORZAGE" ], [ "SECRETS", "release_year", "1933" ], [ "STAGE DOOR CANTEEN", "directed_by", "FRANK BORZAGE" ], [ "STAGE DOOR CANTEEN", "has_genre", "MUSICAL" ], [ "STATE FAIR", "has_genre", "MUSICAL" ], [ "STATE FAIR", "release_year", "1933" ], [ "THE HAPPIEST MILLIONAIRE", "has_genre", "MUSICAL" ], [ "THE HAPPIEST MILLIONAIRE", "release_year", "1967" ], [ "THE STRANGER'S RETURN", "release_year", "1933" ], [ "THE STRANGER'S RETURN", "starred_actors", "LIONEL BARRYMORE" ], [ "THE YOUNG GIRLS OF ROCHEFORT", "has_genre", "MUSICAL" ], [ "THE YOUNG GIRLS OF ROCHEFORT", "has_tags", "MUSICAL" ], [ "THE YOUNG GIRLS OF ROCHEFORT", "release_year", "1967" ], [ "THOROUGHLY MODERN MILLIE", "has_genre", "MUSICAL" ], [ "THOROUGHLY MODERN MILLIE", "release_year", "1967" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39624, 1957 25423, APRIL LOVE 15729, BLACK RIVER 1578, FUNNY FACE 7972, HEAVEN KNOWS, MR. ALLISON 14375, HIGH SCHOOL MUSICAL 23829, HIGH SCHOOL MUSICAL 2 11051, I AM WAITING 16243, JAILHOUSE ROCK 36874, JAPANESE 20863, LES GIRLS 3960, LOVING YOU 21686, MOONLIGHT SERENADE 24593, MUSICAL 8682, PAL JOEY 6035, PRINCESS RACCOON 16848, SILK STOCKINGS 39568, THE BROADWAY MELODY 27792, THE JOKER IS WILD 34429, THE LORAX 30738, THE PAJAMA GAME 13374, THRONE OF BLOOD 10062, ZAC EFRON src, edge_attr, dst 25423, has_genre, 24593 25423, release_year, 39624 15729, in_language, 36874 15729, release_year, 39624 1578, has_genre, 24593 1578, has_tags, 24593 1578, release_year, 39624 7972, has_tags, 36874 7972, in_language, 36874 7972, release_year, 39624 14375, has_tags, 24593 14375, has_tags, 10062 14375, starred_actors, 10062 23829, has_tags, 24593 23829, starred_actors, 10062 11051, in_language, 36874 11051, release_year, 39624 16243, has_genre, 24593 16243, release_year, 39624 20863, has_genre, 24593 20863, has_tags, 24593 20863, release_year, 39624 3960, has_genre, 24593 3960, release_year, 39624 21686, has_genre, 24593 21686, in_language, 36874 8682, has_genre, 24593 8682, release_year, 39624 6035, has_genre, 24593 6035, in_language, 36874 16848, has_genre, 24593 16848, release_year, 39624 39568, has_genre, 24593 27792, has_genre, 24593 27792, release_year, 39624 34429, starred_actors, 10062 30738, has_genre, 24593 30738, release_year, 39624 13374, has_tags, 36874 13374, in_language, 36874 13374, release_year, 39624 Question: How are HEAVEN KNOWS, MR. ALLISON, THE BROADWAY MELODY, and THE LORAX related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "HEAVEN KNOWS, MR. ALLISON", "THE BROADWAY MELODY", "THE LORAX" ], "valid_edges": [ [ "APRIL LOVE", "has_genre", "MUSICAL" ], [ "APRIL LOVE", "release_year", "1957" ], [ "BLACK RIVER", "in_language", "JAPANESE" ], [ "BLACK RIVER", "release_year", "1957" ], [ "FUNNY FACE", "has_genre", "MUSICAL" ], [ "FUNNY FACE", "has_tags", "MUSICAL" ], [ "FUNNY FACE", "release_year", "1957" ], [ "HEAVEN KNOWS, MR. ALLISON", "has_tags", "JAPANESE" ], [ "HEAVEN KNOWS, MR. ALLISON", "in_language", "JAPANESE" ], [ "HEAVEN KNOWS, MR. ALLISON", "release_year", "1957" ], [ "HIGH SCHOOL MUSICAL", "has_tags", "MUSICAL" ], [ "HIGH SCHOOL MUSICAL", "has_tags", "ZAC EFRON" ], [ "HIGH SCHOOL MUSICAL", "starred_actors", "ZAC EFRON" ], [ "HIGH SCHOOL MUSICAL 2", "has_tags", "MUSICAL" ], [ "HIGH SCHOOL MUSICAL 2", "starred_actors", "ZAC EFRON" ], [ "I AM WAITING", "in_language", "JAPANESE" ], [ "I AM WAITING", "release_year", "1957" ], [ "JAILHOUSE ROCK", "has_genre", "MUSICAL" ], [ "JAILHOUSE ROCK", "release_year", "1957" ], [ "LES GIRLS", "has_genre", "MUSICAL" ], [ "LES GIRLS", "has_tags", "MUSICAL" ], [ "LES GIRLS", "release_year", "1957" ], [ "LOVING YOU", "has_genre", "MUSICAL" ], [ "LOVING YOU", "release_year", "1957" ], [ "MOONLIGHT SERENADE", "has_genre", "MUSICAL" ], [ "MOONLIGHT SERENADE", "in_language", "JAPANESE" ], [ "PAL JOEY", "has_genre", "MUSICAL" ], [ "PAL JOEY", "release_year", "1957" ], [ "PRINCESS RACCOON", "has_genre", "MUSICAL" ], [ "PRINCESS RACCOON", "in_language", "JAPANESE" ], [ "SILK STOCKINGS", "has_genre", "MUSICAL" ], [ "SILK STOCKINGS", "release_year", "1957" ], [ "THE BROADWAY MELODY", "has_genre", "MUSICAL" ], [ "THE JOKER IS WILD", "has_genre", "MUSICAL" ], [ "THE JOKER IS WILD", "release_year", "1957" ], [ "THE LORAX", "starred_actors", "ZAC EFRON" ], [ "THE PAJAMA GAME", "has_genre", "MUSICAL" ], [ "THE PAJAMA GAME", "release_year", "1957" ], [ "THRONE OF BLOOD", "has_tags", "JAPANESE" ], [ "THRONE OF BLOOD", "in_language", "JAPANESE" ], [ "THRONE OF BLOOD", "release_year", "1957" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 31604, 1978 19493, ANDY SAMBERG 8339, BLOODBROTHERS 5571, CLOUDY WITH A CHANCE OF MEATBALLS 14087, COMES A HORSEMAN 22796, HOOPER 34869, HOTEL TRANSYLVANIA 1038, JAMES CAAN 18164, JEFF BRIDGES 17397, KISS ME GOODBYE 26953, ROBERT MULLIGAN 4261, SALLY FIELD 25567, SAME TIME, NEXT YEAR 10896, SONY PICTURES ANIMATION 37759, STAY HUNGRY 23237, SURF'S UP 16732, THE END 5511, WITCH'S NIGHT OUT src, edge_attr, dst 8339, directed_by, 26953 8339, release_year, 31604 5571, has_tags, 19493 5571, has_tags, 10896 5571, starred_actors, 19493 5571, starred_actors, 1038 14087, release_year, 31604 14087, starred_actors, 1038 22796, release_year, 31604 22796, starred_actors, 4261 34869, has_tags, 19493 34869, has_tags, 10896 34869, starred_actors, 19493 17397, directed_by, 26953 17397, has_tags, 1038 17397, has_tags, 18164 17397, has_tags, 4261 17397, starred_actors, 1038 17397, starred_actors, 18164 17397, starred_actors, 4261 25567, directed_by, 26953 25567, has_tags, 26953 25567, release_year, 31604 37759, starred_actors, 18164 37759, starred_actors, 4261 23237, has_tags, 18164 23237, has_tags, 10896 23237, starred_actors, 18164 16732, release_year, 31604 16732, starred_actors, 4261 5511, release_year, 31604 Question: How are KISS ME GOODBYE, SONY PICTURES ANIMATION, and WITCH'S NIGHT OUT related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "KISS ME GOODBYE", "SONY PICTURES ANIMATION", "WITCH'S NIGHT OUT" ], "valid_edges": [ [ "BLOODBROTHERS", "directed_by", "ROBERT MULLIGAN" ], [ "BLOODBROTHERS", "release_year", "1978" ], [ "CLOUDY WITH A CHANCE OF MEATBALLS", "has_tags", "ANDY SAMBERG" ], [ "CLOUDY WITH A CHANCE OF MEATBALLS", "has_tags", "SONY PICTURES ANIMATION" ], [ "CLOUDY WITH A CHANCE OF MEATBALLS", "starred_actors", "ANDY SAMBERG" ], [ "CLOUDY WITH A CHANCE OF MEATBALLS", "starred_actors", "JAMES CAAN" ], [ "COMES A HORSEMAN", "release_year", "1978" ], [ "COMES A HORSEMAN", "starred_actors", "JAMES CAAN" ], [ "HOOPER", "release_year", "1978" ], [ "HOOPER", "starred_actors", "SALLY FIELD" ], [ "HOTEL TRANSYLVANIA", "has_tags", "ANDY SAMBERG" ], [ "HOTEL TRANSYLVANIA", "has_tags", "SONY PICTURES ANIMATION" ], [ "HOTEL TRANSYLVANIA", "starred_actors", "ANDY SAMBERG" ], [ "KISS ME GOODBYE", "directed_by", "ROBERT MULLIGAN" ], [ "KISS ME GOODBYE", "has_tags", "JAMES CAAN" ], [ "KISS ME GOODBYE", "has_tags", "JEFF BRIDGES" ], [ "KISS ME GOODBYE", "has_tags", "SALLY FIELD" ], [ "KISS ME GOODBYE", "starred_actors", "JAMES CAAN" ], [ "KISS ME GOODBYE", "starred_actors", "JEFF BRIDGES" ], [ "KISS ME GOODBYE", "starred_actors", "SALLY FIELD" ], [ "SAME TIME, NEXT YEAR", "directed_by", "ROBERT MULLIGAN" ], [ "SAME TIME, NEXT YEAR", "has_tags", "ROBERT MULLIGAN" ], [ "SAME TIME, NEXT YEAR", "release_year", "1978" ], [ "STAY HUNGRY", "starred_actors", "JEFF BRIDGES" ], [ "STAY HUNGRY", "starred_actors", "SALLY FIELD" ], [ "SURF'S UP", "has_tags", "JEFF BRIDGES" ], [ "SURF'S UP", "has_tags", "SONY PICTURES ANIMATION" ], [ "SURF'S UP", "starred_actors", "JEFF BRIDGES" ], [ "THE END", "release_year", "1978" ], [ "THE END", "starred_actors", "SALLY FIELD" ], [ "WITCH'S NIGHT OUT", "release_year", "1978" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36268, 1980 37484, 2004 15374, 2005 35845, 2006 29424, 2011 39289, ACTION 36853, ALTERED STATES 33134, ANY WHICH WAY YOU CAN 32931, ASSASSINATION GAMES 1743, BAD TIMING 29513, CANNIBAL HOLOCAUST 25738, CHRISTMAS EVIL 13888, CITY OF THE LIVING DEAD 16813, CONTAMINATION 14724, CRIME 32554, CUBE ZERO 9248, DEATH SHIP 1028, DEEPSTAR SIX 9986, DELITTO A PORTA ROMANA 771, DRESSED TO KILL 31653, EATEN ALIVE! 31783, ENGLISH 12394, ERNIE BARBARASH 14623, FADE TO BLACK 22215, FRIDAY THE 13TH 24174, FUN IS BEAUTIFUL 19224, GHOSTS 35657, GLORIA 13041, HAL HOLBROOK 31948, HARVEY KEITEL 1408, HE KNOWS YOU'RE ALONE 2600, HELL OF THE LIVING DEAD 5870, HORROR 24167, INFERNO 16200, ITALIAN 4472, JAMIE LEE CURTIS 24437, MANIAC 1153, MICHAEL CAINE 30047, MOTEL HELL 19825, MOTHER'S DAY 25714, NIGHTMARE CITY 24736, PROM NIGHT 23458, PSYCHOLOGICAL 33108, RUNNING SCARED 6292, SATURN 3 32387, SIMON 5409, SLASHER 7556, SPANISH 5864, THE AWAKENING 34039, THE CHANGELING 27423, THE FOG 5592, THE HEARSE 23688, THE HUNTER 2393, THE ISLAND 24875, THE KIDNAPPING OF THE PRESIDENT 38433, THE MERCHANT OF VENICE 21636, THE OCTAGON 19018, THE SHINING 14962, THE WATCHER IN THE WOODS 24811, THRILLER 34977, TICKING CLOCK 6768, TRISH VAN DEVERE 25262, WINDOWS 21887, WITHOUT WARNING 14902, ZOMBIE 39354, ZOMBIES src, edge_attr, dst 36853, has_genre, 5870 36853, release_year, 36268 33134, has_genre, 39289 33134, release_year, 36268 32931, directed_by, 12394 32931, has_genre, 39289 32931, release_year, 29424 1743, has_genre, 24811 1743, release_year, 36268 1743, starred_actors, 31948 29513, has_tags, 16200 29513, release_year, 36268 25738, has_genre, 5870 25738, release_year, 36268 13888, has_genre, 5870 13888, has_tags, 5870 13888, has_tags, 16200 13888, in_language, 31783 13888, in_language, 16200 13888, release_year, 36268 16813, has_genre, 5870 16813, release_year, 36268 32554, directed_by, 12394 32554, has_genre, 24811 32554, has_tags, 23458 32554, release_year, 37484 32554, written_by, 12394 9248, has_genre, 5870 9248, release_year, 36268 1028, has_genre, 5870 9986, has_genre, 14724 9986, in_language, 16200 9986, release_year, 36268 771, has_genre, 24811 771, has_tags, 1153 771, release_year, 36268 771, starred_actors, 1153 31653, in_language, 16200 31653, release_year, 36268 14623, has_genre, 24811 14623, release_year, 36268 14623, release_year, 35845 22215, has_genre, 5870 22215, has_tags, 5409 22215, release_year, 36268 24174, in_language, 16200 24174, release_year, 36268 35657, has_genre, 14724 35657, has_genre, 24811 35657, in_language, 7556 35657, release_year, 36268 1408, has_genre, 5870 1408, release_year, 36268 2600, has_genre, 5870 2600, has_tags, 14902 2600, has_tags, 39354 2600, in_language, 16200 2600, release_year, 36268 24167, has_genre, 5870 24167, has_genre, 24811 24167, in_language, 16200 24167, release_year, 36268 24437, has_genre, 5870 24437, has_tags, 5409 24437, release_year, 36268 30047, has_genre, 5870 30047, release_year, 36268 19825, has_genre, 5870 19825, has_genre, 24811 19825, release_year, 36268 25714, has_tags, 14902 25714, has_tags, 39354 25714, in_language, 16200 25714, in_language, 7556 25714, release_year, 36268 24736, has_genre, 5870 24736, has_tags, 5409 24736, release_year, 36268 24736, starred_actors, 4472 33108, has_genre, 39289 33108, has_genre, 14724 33108, release_year, 36268 33108, release_year, 35845 6292, has_genre, 24811 6292, release_year, 36268 6292, starred_actors, 31948 32387, release_year, 36268 32387, release_year, 37484 5864, has_genre, 5870 5864, has_tags, 5870 5864, release_year, 36268 5864, release_year, 29424 34039, has_genre, 5870 34039, release_year, 36268 34039, starred_actors, 6768 27423, has_genre, 5870 27423, has_tags, 19224 27423, has_tags, 13041 27423, has_tags, 5870 27423, has_tags, 4472 27423, release_year, 36268 27423, release_year, 15374 27423, starred_actors, 4472 5592, has_genre, 5870 5592, release_year, 36268 5592, starred_actors, 6768 23688, has_genre, 24811 23688, release_year, 36268 23688, release_year, 29424 2393, has_tags, 24811 2393, release_year, 36268 2393, release_year, 15374 2393, starred_actors, 1153 24875, has_genre, 24811 24875, release_year, 36268 24875, starred_actors, 13041 38433, in_language, 31783 38433, release_year, 36268 38433, release_year, 37484 21636, has_genre, 39289 21636, release_year, 36268 19018, has_genre, 5870 19018, has_tags, 19224 19018, has_tags, 5870 19018, has_tags, 23458 19018, release_year, 36268 14962, has_genre, 5870 14962, in_language, 31783 14962, release_year, 36268 34977, directed_by, 12394 34977, has_genre, 39289 34977, release_year, 29424 25262, has_genre, 24811 25262, release_year, 36268 21887, has_genre, 5870 21887, release_year, 36268 Question: In what context are 1980, DEEPSTAR SIX, and ERNIE BARBARASH connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "1980", "DEEPSTAR SIX", "ERNIE BARBARASH" ], "valid_edges": [ [ "ALTERED STATES", "has_genre", "HORROR" ], [ "ALTERED STATES", "release_year", "1980" ], [ "ANY WHICH WAY YOU CAN", "has_genre", "ACTION" ], [ "ANY WHICH WAY YOU CAN", "release_year", "1980" ], [ "ASSASSINATION GAMES", "directed_by", "ERNIE BARBARASH" ], [ "ASSASSINATION GAMES", "has_genre", "ACTION" ], [ "ASSASSINATION GAMES", "release_year", "2011" ], [ "BAD TIMING", "has_genre", "THRILLER" ], [ "BAD TIMING", "release_year", "1980" ], [ "BAD TIMING", "starred_actors", "HARVEY KEITEL" ], [ "CANNIBAL HOLOCAUST", "has_tags", "ITALIAN" ], [ "CANNIBAL HOLOCAUST", "release_year", "1980" ], [ "CHRISTMAS EVIL", "has_genre", "HORROR" ], [ "CHRISTMAS EVIL", "release_year", "1980" ], [ "CITY OF THE LIVING DEAD", "has_genre", "HORROR" ], [ "CITY OF THE LIVING DEAD", "has_tags", "HORROR" ], [ "CITY OF THE LIVING DEAD", "has_tags", "ITALIAN" ], [ "CITY OF THE LIVING DEAD", "in_language", "ENGLISH" ], [ "CITY OF THE LIVING DEAD", "in_language", "ITALIAN" ], [ "CITY OF THE LIVING DEAD", "release_year", "1980" ], [ "CONTAMINATION", "has_genre", "HORROR" ], [ "CONTAMINATION", "release_year", "1980" ], [ "CUBE ZERO", "directed_by", "ERNIE BARBARASH" ], [ "CUBE ZERO", "has_genre", "THRILLER" ], [ "CUBE ZERO", "has_tags", "PSYCHOLOGICAL" ], [ "CUBE ZERO", "release_year", "2004" ], [ "CUBE ZERO", "written_by", "ERNIE BARBARASH" ], [ "DEATH SHIP", "has_genre", "HORROR" ], [ "DEATH SHIP", "release_year", "1980" ], [ "DEEPSTAR SIX", "has_genre", "HORROR" ], [ "DELITTO A PORTA ROMANA", "has_genre", "CRIME" ], [ "DELITTO A PORTA ROMANA", "in_language", "ITALIAN" ], [ "DELITTO A PORTA ROMANA", "release_year", "1980" ], [ "DRESSED TO KILL", "has_genre", "THRILLER" ], [ "DRESSED TO KILL", "has_tags", "MICHAEL CAINE" ], [ "DRESSED TO KILL", "release_year", "1980" ], [ "DRESSED TO KILL", "starred_actors", "MICHAEL CAINE" ], [ "EATEN ALIVE!", "in_language", "ITALIAN" ], [ "EATEN ALIVE!", "release_year", "1980" ], [ "FADE TO BLACK", "has_genre", "THRILLER" ], [ "FADE TO BLACK", "release_year", "1980" ], [ "FADE TO BLACK", "release_year", "2006" ], [ "FRIDAY THE 13TH", "has_genre", "HORROR" ], [ "FRIDAY THE 13TH", "has_tags", "SLASHER" ], [ "FRIDAY THE 13TH", "release_year", "1980" ], [ "FUN IS BEAUTIFUL", "in_language", "ITALIAN" ], [ "FUN IS BEAUTIFUL", "release_year", "1980" ], [ "GLORIA", "has_genre", "CRIME" ], [ "GLORIA", "has_genre", "THRILLER" ], [ "GLORIA", "in_language", "SPANISH" ], [ "GLORIA", "release_year", "1980" ], [ "HE KNOWS YOU'RE ALONE", "has_genre", "HORROR" ], [ "HE KNOWS YOU'RE ALONE", "release_year", "1980" ], [ "HELL OF THE LIVING DEAD", "has_genre", "HORROR" ], [ "HELL OF THE LIVING DEAD", "has_tags", "ZOMBIE" ], [ "HELL OF THE LIVING DEAD", "has_tags", "ZOMBIES" ], [ "HELL OF THE LIVING DEAD", "in_language", "ITALIAN" ], [ "HELL OF THE LIVING DEAD", "release_year", "1980" ], [ "INFERNO", "has_genre", "HORROR" ], [ "INFERNO", "has_genre", "THRILLER" ], [ "INFERNO", "in_language", "ITALIAN" ], [ "INFERNO", "release_year", "1980" ], [ "MANIAC", "has_genre", "HORROR" ], [ "MANIAC", "has_tags", "SLASHER" ], [ "MANIAC", "release_year", "1980" ], [ "MOTEL HELL", "has_genre", "HORROR" ], [ "MOTEL HELL", "release_year", "1980" ], [ "MOTHER'S DAY", "has_genre", "HORROR" ], [ "MOTHER'S DAY", "has_genre", "THRILLER" ], [ "MOTHER'S DAY", "release_year", "1980" ], [ "NIGHTMARE CITY", "has_tags", "ZOMBIE" ], [ "NIGHTMARE CITY", "has_tags", "ZOMBIES" ], [ "NIGHTMARE CITY", "in_language", "ITALIAN" ], [ "NIGHTMARE CITY", "in_language", "SPANISH" ], [ "NIGHTMARE CITY", "release_year", "1980" ], [ "PROM NIGHT", "has_genre", "HORROR" ], [ "PROM NIGHT", "has_tags", "SLASHER" ], [ "PROM NIGHT", "release_year", "1980" ], [ "PROM NIGHT", "starred_actors", "JAMIE LEE CURTIS" ], [ "RUNNING SCARED", "has_genre", "ACTION" ], [ "RUNNING SCARED", "has_genre", "CRIME" ], [ "RUNNING SCARED", "release_year", "1980" ], [ "RUNNING SCARED", "release_year", "2006" ], [ "SATURN 3", "has_genre", "THRILLER" ], [ "SATURN 3", "release_year", "1980" ], [ "SATURN 3", "starred_actors", "HARVEY KEITEL" ], [ "SIMON", "release_year", "1980" ], [ "SIMON", "release_year", "2004" ], [ "THE AWAKENING", "has_genre", "HORROR" ], [ "THE AWAKENING", "has_tags", "HORROR" ], [ "THE AWAKENING", "release_year", "1980" ], [ "THE AWAKENING", "release_year", "2011" ], [ "THE CHANGELING", "has_genre", "HORROR" ], [ "THE CHANGELING", "release_year", "1980" ], [ "THE CHANGELING", "starred_actors", "TRISH VAN DEVERE" ], [ "THE FOG", "has_genre", "HORROR" ], [ "THE FOG", "has_tags", "GHOSTS" ], [ "THE FOG", "has_tags", "HAL HOLBROOK" ], [ "THE FOG", "has_tags", "HORROR" ], [ "THE FOG", "has_tags", "JAMIE LEE CURTIS" ], [ "THE FOG", "release_year", "1980" ], [ "THE FOG", "release_year", "2005" ], [ "THE FOG", "starred_actors", "JAMIE LEE CURTIS" ], [ "THE HEARSE", "has_genre", "HORROR" ], [ "THE HEARSE", "release_year", "1980" ], [ "THE HEARSE", "starred_actors", "TRISH VAN DEVERE" ], [ "THE HUNTER", "has_genre", "THRILLER" ], [ "THE HUNTER", "release_year", "1980" ], [ "THE HUNTER", "release_year", "2011" ], [ "THE ISLAND", "has_tags", "THRILLER" ], [ "THE ISLAND", "release_year", "1980" ], [ "THE ISLAND", "release_year", "2005" ], [ "THE ISLAND", "starred_actors", "MICHAEL CAINE" ], [ "THE KIDNAPPING OF THE PRESIDENT", "has_genre", "THRILLER" ], [ "THE KIDNAPPING OF THE PRESIDENT", "release_year", "1980" ], [ "THE KIDNAPPING OF THE PRESIDENT", "starred_actors", "HAL HOLBROOK" ], [ "THE MERCHANT OF VENICE", "in_language", "ENGLISH" ], [ "THE MERCHANT OF VENICE", "release_year", "1980" ], [ "THE MERCHANT OF VENICE", "release_year", "2004" ], [ "THE OCTAGON", "has_genre", "ACTION" ], [ "THE OCTAGON", "release_year", "1980" ], [ "THE SHINING", "has_genre", "HORROR" ], [ "THE SHINING", "has_tags", "GHOSTS" ], [ "THE SHINING", "has_tags", "HORROR" ], [ "THE SHINING", "has_tags", "PSYCHOLOGICAL" ], [ "THE SHINING", "release_year", "1980" ], [ "THE WATCHER IN THE WOODS", "has_genre", "HORROR" ], [ "THE WATCHER IN THE WOODS", "in_language", "ENGLISH" ], [ "THE WATCHER IN THE WOODS", "release_year", "1980" ], [ "TICKING CLOCK", "directed_by", "ERNIE BARBARASH" ], [ "TICKING CLOCK", "has_genre", "ACTION" ], [ "TICKING CLOCK", "release_year", "2011" ], [ "WINDOWS", "has_genre", "THRILLER" ], [ "WINDOWS", "release_year", "1980" ], [ "WITHOUT WARNING", "has_genre", "HORROR" ], [ "WITHOUT WARNING", "release_year", "1980" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 31196, 1974 9538, DON SIEGEL 31376, HARRY AND TONTO 23458, PSYCHOLOGICAL 16380, THE BLACK WINDMILL 28677, THE CONVERSATION 6513, THE VILLAGE 37550, TWO MULES FOR SISTER SARA src, edge_attr, dst 31376, release_year, 31196 16380, directed_by, 9538 16380, release_year, 31196 28677, has_tags, 23458 28677, release_year, 31196 6513, has_tags, 23458 37550, directed_by, 9538 37550, has_tags, 9538 Question: How are HARRY AND TONTO, THE VILLAGE, and TWO MULES FOR SISTER SARA related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "HARRY AND TONTO", "THE VILLAGE", "TWO MULES FOR SISTER SARA" ], "valid_edges": [ [ "HARRY AND TONTO", "release_year", "1974" ], [ "THE BLACK WINDMILL", "directed_by", "DON SIEGEL" ], [ "THE BLACK WINDMILL", "release_year", "1974" ], [ "THE CONVERSATION", "has_tags", "PSYCHOLOGICAL" ], [ "THE CONVERSATION", "release_year", "1974" ], [ "THE VILLAGE", "has_tags", "PSYCHOLOGICAL" ], [ "TWO MULES FOR SISTER SARA", "directed_by", "DON SIEGEL" ], [ "TWO MULES FOR SISTER SARA", "has_tags", "DON SIEGEL" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 8486, 1999 30284, ALL ABOUT MY MOTHER 13445, BAHAMAS 10045, BD-R 4592, BEAU TRAVAIL 2067, BETWEEN YOUR LEGS 16659, CASINO ROYALE 19200, CRIMINAL LOVERS 17072, FAREWELL, HOME SWEET HOME 6012, FRENCH 23299, GET CARTER 35657, GLORIA 10457, GOYA IN BORDEAUX 5722, HUMAN RESOURCES 35335, IT ALL STARTS TODAY 9866, MY LITTLE BUSINESS 37006, NO ONE WRITES TO THE COLONEL 23816, NOBODY KNOWS ANYBODY 21386, POLA X 33958, RACHAEL LEIGH COOK 8379, ROMANCE 4126, ROSETTA 11432, SECOND SKIN 3631, SET ME FREE 38502, SHE'S ALL THAT 21147, SOLAS 7556, SPANISH 6150, THE CONFESSION 16209, THE HI-LINE 9799, THE LOST SON 29990, THE NAMELESS 37903, THE NINTH GATE 3569, WHY NOT ME? src, edge_attr, dst 30284, has_tags, 7556 30284, in_language, 7556 30284, release_year, 8486 4592, in_language, 6012 4592, release_year, 8486 2067, in_language, 7556 2067, release_year, 8486 16659, has_tags, 13445 16659, has_tags, 10045 19200, has_tags, 6012 19200, in_language, 6012 19200, release_year, 8486 17072, in_language, 6012 17072, release_year, 8486 23299, has_tags, 10045 23299, starred_actors, 33958 35657, in_language, 7556 35657, release_year, 8486 10457, in_language, 7556 10457, release_year, 8486 5722, in_language, 6012 5722, release_year, 8486 35335, in_language, 6012 35335, release_year, 8486 9866, in_language, 6012 9866, release_year, 8486 37006, in_language, 7556 37006, release_year, 8486 23816, in_language, 7556 23816, release_year, 8486 21386, in_language, 6012 21386, release_year, 8486 8379, in_language, 6012 8379, release_year, 8486 4126, in_language, 6012 4126, release_year, 8486 11432, in_language, 7556 11432, release_year, 8486 3631, in_language, 6012 3631, release_year, 8486 38502, has_tags, 33958 38502, release_year, 8486 38502, starred_actors, 33958 21147, in_language, 7556 21147, release_year, 8486 6150, in_language, 6012 6150, release_year, 8486 16209, release_year, 8486 16209, starred_actors, 33958 9799, in_language, 6012 9799, release_year, 8486 29990, in_language, 7556 29990, release_year, 8486 37903, in_language, 6012 37903, in_language, 7556 37903, release_year, 8486 3569, has_tags, 6012 3569, in_language, 6012 3569, release_year, 8486 Question: In what context are BAHAMAS, RACHAEL LEIGH COOK, and THE NINTH GATE connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BAHAMAS", "RACHAEL LEIGH COOK", "THE NINTH GATE" ], "valid_edges": [ [ "ALL ABOUT MY MOTHER", "has_tags", "SPANISH" ], [ "ALL ABOUT MY MOTHER", "in_language", "SPANISH" ], [ "ALL ABOUT MY MOTHER", "release_year", "1999" ], [ "BEAU TRAVAIL", "in_language", "FRENCH" ], [ "BEAU TRAVAIL", "release_year", "1999" ], [ "BETWEEN YOUR LEGS", "in_language", "SPANISH" ], [ "BETWEEN YOUR LEGS", "release_year", "1999" ], [ "CASINO ROYALE", "has_tags", "BAHAMAS" ], [ "CASINO ROYALE", "has_tags", "BD-R" ], [ "CRIMINAL LOVERS", "has_tags", "FRENCH" ], [ "CRIMINAL LOVERS", "in_language", "FRENCH" ], [ "CRIMINAL LOVERS", "release_year", "1999" ], [ "FAREWELL, HOME SWEET HOME", "in_language", "FRENCH" ], [ "FAREWELL, HOME SWEET HOME", "release_year", "1999" ], [ "GET CARTER", "has_tags", "BD-R" ], [ "GET CARTER", "starred_actors", "RACHAEL LEIGH COOK" ], [ "GLORIA", "in_language", "SPANISH" ], [ "GLORIA", "release_year", "1999" ], [ "GOYA IN BORDEAUX", "in_language", "SPANISH" ], [ "GOYA IN BORDEAUX", "release_year", "1999" ], [ "HUMAN RESOURCES", "in_language", "FRENCH" ], [ "HUMAN RESOURCES", "release_year", "1999" ], [ "IT ALL STARTS TODAY", "in_language", "FRENCH" ], [ "IT ALL STARTS TODAY", "release_year", "1999" ], [ "MY LITTLE BUSINESS", "in_language", "FRENCH" ], [ "MY LITTLE BUSINESS", "release_year", "1999" ], [ "NO ONE WRITES TO THE COLONEL", "in_language", "SPANISH" ], [ "NO ONE WRITES TO THE COLONEL", "release_year", "1999" ], [ "NOBODY KNOWS ANYBODY", "in_language", "SPANISH" ], [ "NOBODY KNOWS ANYBODY", "release_year", "1999" ], [ "POLA X", "in_language", "FRENCH" ], [ "POLA X", "release_year", "1999" ], [ "ROMANCE", "in_language", "FRENCH" ], [ "ROMANCE", "release_year", "1999" ], [ "ROSETTA", "in_language", "FRENCH" ], [ "ROSETTA", "release_year", "1999" ], [ "SECOND SKIN", "in_language", "SPANISH" ], [ "SECOND SKIN", "release_year", "1999" ], [ "SET ME FREE", "in_language", "FRENCH" ], [ "SET ME FREE", "release_year", "1999" ], [ "SHE'S ALL THAT", "has_tags", "RACHAEL LEIGH COOK" ], [ "SHE'S ALL THAT", "release_year", "1999" ], [ "SHE'S ALL THAT", "starred_actors", "RACHAEL LEIGH COOK" ], [ "SOLAS", "in_language", "SPANISH" ], [ "SOLAS", "release_year", "1999" ], [ "THE CONFESSION", "in_language", "FRENCH" ], [ "THE CONFESSION", "release_year", "1999" ], [ "THE HI-LINE", "release_year", "1999" ], [ "THE HI-LINE", "starred_actors", "RACHAEL LEIGH COOK" ], [ "THE LOST SON", "in_language", "FRENCH" ], [ "THE LOST SON", "release_year", "1999" ], [ "THE NAMELESS", "in_language", "SPANISH" ], [ "THE NAMELESS", "release_year", "1999" ], [ "THE NINTH GATE", "in_language", "FRENCH" ], [ "THE NINTH GATE", "in_language", "SPANISH" ], [ "THE NINTH GATE", "release_year", "1999" ], [ "WHY NOT ME?", "has_tags", "FRENCH" ], [ "WHY NOT ME?", "in_language", "FRENCH" ], [ "WHY NOT ME?", "release_year", "1999" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 7977, 1969 39435, 1975 13211, CALIBER 9 906, FERNANDO DI LEO 10387, FRITZ LANG 39145, FURY 16200, ITALIAN 16430, KIDNAP SYNDICATE 20195, NAKED VIOLENCE 13806, NORMAN KRASNA 19487, OVERLORD 1985, SEVEN BEAUTIES 28423, SHOOT FIRST, DIE LATER 35043, SYLVIA SIDNEY 405, THE HIDING PLACE 22214, WAR 39783, YOU AND ME 1088, YOU ONLY LIVE ONCE src, edge_attr, dst 7977, has_genre, 22214 13211, directed_by, 906 13211, in_language, 16200 13211, written_by, 906 39145, directed_by, 10387 39145, has_genre, 22214 39145, has_tags, 10387 39145, has_tags, 22214 39145, starred_actors, 35043 39145, written_by, 10387 39145, written_by, 13806 16430, directed_by, 906 16430, in_language, 16200 16430, release_year, 39435 16430, written_by, 906 20195, directed_by, 906 20195, in_language, 16200 20195, release_year, 7977 20195, written_by, 906 19487, has_genre, 22214 19487, release_year, 39435 1985, has_genre, 22214 1985, release_year, 39435 28423, directed_by, 906 28423, in_language, 16200 28423, written_by, 906 405, has_genre, 22214 405, release_year, 39435 39783, directed_by, 10387 39783, has_tags, 10387 39783, starred_actors, 35043 39783, written_by, 13806 1088, directed_by, 10387 1088, has_tags, 10387 1088, starred_actors, 35043 Question: For what reason are FERNANDO DI LEO, OVERLORD, and SYLVIA SIDNEY associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "FERNANDO DI LEO", "OVERLORD", "SYLVIA SIDNEY" ], "valid_edges": [ [ "1969", "has_genre", "WAR" ], [ "CALIBER 9", "directed_by", "FERNANDO DI LEO" ], [ "CALIBER 9", "in_language", "ITALIAN" ], [ "CALIBER 9", "written_by", "FERNANDO DI LEO" ], [ "FURY", "directed_by", "FRITZ LANG" ], [ "FURY", "has_genre", "WAR" ], [ "FURY", "has_tags", "FRITZ LANG" ], [ "FURY", "has_tags", "WAR" ], [ "FURY", "starred_actors", "SYLVIA SIDNEY" ], [ "FURY", "written_by", "FRITZ LANG" ], [ "FURY", "written_by", "NORMAN KRASNA" ], [ "KIDNAP SYNDICATE", "directed_by", "FERNANDO DI LEO" ], [ "KIDNAP SYNDICATE", "in_language", "ITALIAN" ], [ "KIDNAP SYNDICATE", "release_year", "1975" ], [ "KIDNAP SYNDICATE", "written_by", "FERNANDO DI LEO" ], [ "NAKED VIOLENCE", "directed_by", "FERNANDO DI LEO" ], [ "NAKED VIOLENCE", "in_language", "ITALIAN" ], [ "NAKED VIOLENCE", "release_year", "1969" ], [ "NAKED VIOLENCE", "written_by", "FERNANDO DI LEO" ], [ "OVERLORD", "has_genre", "WAR" ], [ "OVERLORD", "release_year", "1975" ], [ "SEVEN BEAUTIES", "has_genre", "WAR" ], [ "SEVEN BEAUTIES", "release_year", "1975" ], [ "SHOOT FIRST, DIE LATER", "directed_by", "FERNANDO DI LEO" ], [ "SHOOT FIRST, DIE LATER", "in_language", "ITALIAN" ], [ "SHOOT FIRST, DIE LATER", "written_by", "FERNANDO DI LEO" ], [ "THE HIDING PLACE", "has_genre", "WAR" ], [ "THE HIDING PLACE", "release_year", "1975" ], [ "YOU AND ME", "directed_by", "FRITZ LANG" ], [ "YOU AND ME", "has_tags", "FRITZ LANG" ], [ "YOU AND ME", "starred_actors", "SYLVIA SIDNEY" ], [ "YOU AND ME", "written_by", "NORMAN KRASNA" ], [ "YOU ONLY LIVE ONCE", "directed_by", "FRITZ LANG" ], [ "YOU ONLY LIVE ONCE", "has_tags", "FRITZ LANG" ], [ "YOU ONLY LIVE ONCE", "starred_actors", "SYLVIA SIDNEY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35747, 1408 15374, 2005 17315, 2007 38712, 30 DAYS OF NIGHT 2960, ARENA 31464, BALLS OF FURY 7664, CLEANER 29211, COACH CARTER 4928, GRACIE 184, GUY X 17696, JOSH HARTNETT 34241, MAGICIANS 17433, MOZART AND THE WHALE 8324, RESURRECTING THE CHAMP 4695, ROBERT WEBB 13814, SAMUEL L. JACKSON 32404, SPORT 25192, STEEP 18707, THE COMEBACKS 27636, THE FINAL SEASON 334, THE GAME PLAN 36410, THE GREATEST GAME EVER PLAYED 20223, THE LONGEST YARD 24108, THE MAN 36820, TWO FOR THE MONEY src, edge_attr, dst 35747, has_tags, 13814 35747, release_year, 17315 38712, has_tags, 17696 38712, release_year, 17315 38712, starred_actors, 17696 2960, has_genre, 32404 2960, starred_actors, 13814 31464, has_genre, 32404 31464, release_year, 17315 7664, release_year, 17315 7664, starred_actors, 13814 29211, has_genre, 32404 29211, has_tags, 13814 29211, release_year, 15374 29211, starred_actors, 13814 4928, has_genre, 32404 4928, release_year, 17315 184, release_year, 15374 34241, has_tags, 34241 34241, release_year, 17315 34241, starred_actors, 4695 17433, release_year, 15374 17433, starred_actors, 17696 8324, has_genre, 32404 8324, has_tags, 17696 8324, has_tags, 13814 8324, release_year, 17315 8324, starred_actors, 17696 8324, starred_actors, 13814 25192, has_genre, 32404 25192, release_year, 17315 18707, has_genre, 32404 18707, release_year, 17315 27636, has_genre, 32404 27636, release_year, 17315 334, has_genre, 32404 334, release_year, 17315 36410, has_genre, 32404 36410, release_year, 15374 20223, has_genre, 32404 20223, release_year, 15374 24108, has_tags, 13814 24108, release_year, 15374 24108, starred_actors, 13814 36820, has_genre, 32404 36820, release_year, 15374 Question: For what reason are GUY X, RESURRECTING THE CHAMP, and ROBERT WEBB associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "GUY X", "RESURRECTING THE CHAMP", "ROBERT WEBB" ], "valid_edges": [ [ "1408", "has_tags", "SAMUEL L. JACKSON" ], [ "1408", "release_year", "2007" ], [ "30 DAYS OF NIGHT", "has_tags", "JOSH HARTNETT" ], [ "30 DAYS OF NIGHT", "release_year", "2007" ], [ "30 DAYS OF NIGHT", "starred_actors", "JOSH HARTNETT" ], [ "ARENA", "has_genre", "SPORT" ], [ "ARENA", "starred_actors", "SAMUEL L. JACKSON" ], [ "BALLS OF FURY", "has_genre", "SPORT" ], [ "BALLS OF FURY", "release_year", "2007" ], [ "CLEANER", "release_year", "2007" ], [ "CLEANER", "starred_actors", "SAMUEL L. JACKSON" ], [ "COACH CARTER", "has_genre", "SPORT" ], [ "COACH CARTER", "has_tags", "SAMUEL L. JACKSON" ], [ "COACH CARTER", "release_year", "2005" ], [ "COACH CARTER", "starred_actors", "SAMUEL L. JACKSON" ], [ "GRACIE", "has_genre", "SPORT" ], [ "GRACIE", "release_year", "2007" ], [ "GUY X", "release_year", "2005" ], [ "MAGICIANS", "has_tags", "MAGICIANS" ], [ "MAGICIANS", "release_year", "2007" ], [ "MAGICIANS", "starred_actors", "ROBERT WEBB" ], [ "MOZART AND THE WHALE", "release_year", "2005" ], [ "MOZART AND THE WHALE", "starred_actors", "JOSH HARTNETT" ], [ "RESURRECTING THE CHAMP", "has_genre", "SPORT" ], [ "RESURRECTING THE CHAMP", "has_tags", "JOSH HARTNETT" ], [ "RESURRECTING THE CHAMP", "has_tags", "SAMUEL L. JACKSON" ], [ "RESURRECTING THE CHAMP", "release_year", "2007" ], [ "RESURRECTING THE CHAMP", "starred_actors", "JOSH HARTNETT" ], [ "RESURRECTING THE CHAMP", "starred_actors", "SAMUEL L. JACKSON" ], [ "STEEP", "has_genre", "SPORT" ], [ "STEEP", "release_year", "2007" ], [ "THE COMEBACKS", "has_genre", "SPORT" ], [ "THE COMEBACKS", "release_year", "2007" ], [ "THE FINAL SEASON", "has_genre", "SPORT" ], [ "THE FINAL SEASON", "release_year", "2007" ], [ "THE GAME PLAN", "has_genre", "SPORT" ], [ "THE GAME PLAN", "release_year", "2007" ], [ "THE GREATEST GAME EVER PLAYED", "has_genre", "SPORT" ], [ "THE GREATEST GAME EVER PLAYED", "release_year", "2005" ], [ "THE LONGEST YARD", "has_genre", "SPORT" ], [ "THE LONGEST YARD", "release_year", "2005" ], [ "THE MAN", "has_tags", "SAMUEL L. JACKSON" ], [ "THE MAN", "release_year", "2005" ], [ "THE MAN", "starred_actors", "SAMUEL L. JACKSON" ], [ "TWO FOR THE MONEY", "has_genre", "SPORT" ], [ "TWO FOR THE MONEY", "release_year", "2005" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10997, A HIGH WIND IN JAMAICA 1148, CONFESSIONS 36212, DRAMA 17080, FIVE MINUTES OF HEAVEN 3369, GUY HIBBERT src, edge_attr, dst 10997, has_genre, 36212 1148, has_genre, 36212 17080, has_genre, 36212 17080, written_by, 3369 Question: How are A HIGH WIND IN JAMAICA, CONFESSIONS, and GUY HIBBERT related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "A HIGH WIND IN JAMAICA", "CONFESSIONS", "GUY HIBBERT" ], "valid_edges": [ [ "A HIGH WIND IN JAMAICA", "has_genre", "DRAMA" ], [ "CONFESSIONS", "has_genre", "DRAMA" ], [ "FIVE MINUTES OF HEAVEN", "has_genre", "DRAMA" ], [ "FIVE MINUTES OF HEAVEN", "written_by", "GUY HIBBERT" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26633, 1989 37224, 1990 10702, 1991 24438, 1993 3702, 1995 1006, 1996 4763, ADVENTURE 24177, ANIMATION 4329, ANNETTE BENING 26799, BACK TO THE FUTURE PART II 19219, BACK TO THE FUTURE PART III 34596, BLUE IN THE FACE 13903, BRIGHT LIGHTS, BIG CITY 9980, CASUALTIES OF WAR 23496, CHRISTOPHER LLOYD 30463, COMEDY 3160, DOC HOLLYWOOD 36212, DRAMA 26053, FOR LOVE OR MONEY 5585, GREEDY 17539, LEA THOMPSON 12766, LIFE WITH MIKEY 14951, LIGHT OF DAY 14985, MARS ATTACKS! 5678, MICHAEL J. FOX 27601, MICHAEL OLIVER 22398, MIDNIGHT MADNESS 22714, OWN 25436, PROBLEM CHILD 32090, ROBERT ZEMECKIS 32533, SCIENCE FICTION 22847, STUART LITTLE 20756, TEEN WOLF 2633, THE AMERICAN PRESIDENT 21684, THE FRIGHTENERS 39873, THE GOLDEN BOWL 32102, THE HARD WAY 38127, THOMAS F. WILSON 28129, TIME 6351, TIME TRAVEL src, edge_attr, dst 26799, directed_by, 32090 26799, has_genre, 4763 26799, has_tags, 4763 26799, has_tags, 23496 26799, has_tags, 17539 26799, has_tags, 5678 26799, has_tags, 22714 26799, has_tags, 32090 26799, has_tags, 32533 26799, has_tags, 28129 26799, has_tags, 6351 26799, release_year, 26633 26799, starred_actors, 23496 26799, starred_actors, 17539 26799, starred_actors, 5678 26799, starred_actors, 38127 26799, written_by, 32090 19219, directed_by, 32090 19219, has_genre, 4763 19219, has_tags, 4763 19219, has_tags, 23496 19219, has_tags, 17539 19219, has_tags, 5678 19219, has_tags, 22714 19219, has_tags, 32090 19219, has_tags, 32533 19219, has_tags, 28129 19219, has_tags, 6351 19219, release_year, 37224 19219, starred_actors, 23496 19219, starred_actors, 5678 19219, starred_actors, 38127 19219, written_by, 32090 34596, has_genre, 30463 34596, release_year, 3702 34596, starred_actors, 5678 13903, has_genre, 36212 13903, starred_actors, 5678 9980, has_genre, 36212 9980, release_year, 26633 9980, starred_actors, 5678 3160, has_genre, 30463 3160, has_tags, 30463 3160, has_tags, 5678 3160, release_year, 10702 3160, starred_actors, 5678 26053, has_genre, 30463 26053, has_tags, 5678 26053, release_year, 24438 26053, starred_actors, 5678 5585, has_genre, 30463 5585, has_tags, 5678 5585, starred_actors, 5678 12766, has_genre, 30463 12766, has_tags, 5678 12766, release_year, 24438 12766, starred_actors, 5678 14951, has_genre, 36212 14951, starred_actors, 5678 14985, has_genre, 30463 14985, has_tags, 24177 14985, has_tags, 4329 14985, has_tags, 30463 14985, has_tags, 5678 14985, release_year, 1006 14985, starred_actors, 4329 22398, has_genre, 30463 22398, has_tags, 5678 22398, starred_actors, 5678 25436, has_genre, 30463 25436, release_year, 37224 25436, starred_actors, 27601 22847, has_genre, 24177 22847, has_genre, 30463 22847, has_tags, 24177 22847, has_tags, 30463 22847, has_tags, 5678 22847, starred_actors, 5678 20756, has_genre, 30463 20756, has_tags, 30463 20756, has_tags, 5678 20756, starred_actors, 5678 2633, has_genre, 30463 2633, has_genre, 36212 2633, has_tags, 4329 2633, has_tags, 36212 2633, release_year, 3702 2633, starred_actors, 4329 2633, starred_actors, 5678 21684, has_genre, 30463 21684, has_tags, 5678 21684, release_year, 1006 21684, starred_actors, 5678 39873, has_genre, 36212 32102, has_genre, 30463 32102, has_genre, 36212 32102, has_tags, 5678 32102, release_year, 10702 32102, starred_actors, 5678 Question: How are MICHAEL J. FOX, MICHAEL OLIVER, and THE GOLDEN BOWL related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "MICHAEL J. FOX", "MICHAEL OLIVER", "THE GOLDEN BOWL" ], "valid_edges": [ [ "BACK TO THE FUTURE PART II", "directed_by", "ROBERT ZEMECKIS" ], [ "BACK TO THE FUTURE PART II", "has_genre", "ADVENTURE" ], [ "BACK TO THE FUTURE PART II", "has_tags", "ADVENTURE" ], [ "BACK TO THE FUTURE PART II", "has_tags", "CHRISTOPHER LLOYD" ], [ "BACK TO THE FUTURE PART II", "has_tags", "LEA THOMPSON" ], [ "BACK TO THE FUTURE PART II", "has_tags", "MICHAEL J. FOX" ], [ "BACK TO THE FUTURE PART II", "has_tags", "OWN" ], [ "BACK TO THE FUTURE PART II", "has_tags", "ROBERT ZEMECKIS" ], [ "BACK TO THE FUTURE PART II", "has_tags", "SCIENCE FICTION" ], [ "BACK TO THE FUTURE PART II", "has_tags", "TIME" ], [ "BACK TO THE FUTURE PART II", "has_tags", "TIME TRAVEL" ], [ "BACK TO THE FUTURE PART II", "release_year", "1989" ], [ "BACK TO THE FUTURE PART II", "starred_actors", "CHRISTOPHER LLOYD" ], [ "BACK TO THE FUTURE PART II", "starred_actors", "LEA THOMPSON" ], [ "BACK TO THE FUTURE PART II", "starred_actors", "MICHAEL J. FOX" ], [ "BACK TO THE FUTURE PART II", "starred_actors", "THOMAS F. WILSON" ], [ "BACK TO THE FUTURE PART II", "written_by", "ROBERT ZEMECKIS" ], [ "BACK TO THE FUTURE PART III", "directed_by", "ROBERT ZEMECKIS" ], [ "BACK TO THE FUTURE PART III", "has_genre", "ADVENTURE" ], [ "BACK TO THE FUTURE PART III", "has_tags", "ADVENTURE" ], [ "BACK TO THE FUTURE PART III", "has_tags", "CHRISTOPHER LLOYD" ], [ "BACK TO THE FUTURE PART III", "has_tags", "LEA THOMPSON" ], [ "BACK TO THE FUTURE PART III", "has_tags", "MICHAEL J. FOX" ], [ "BACK TO THE FUTURE PART III", "has_tags", "OWN" ], [ "BACK TO THE FUTURE PART III", "has_tags", "ROBERT ZEMECKIS" ], [ "BACK TO THE FUTURE PART III", "has_tags", "SCIENCE FICTION" ], [ "BACK TO THE FUTURE PART III", "has_tags", "TIME" ], [ "BACK TO THE FUTURE PART III", "has_tags", "TIME TRAVEL" ], [ "BACK TO THE FUTURE PART III", "release_year", "1990" ], [ "BACK TO THE FUTURE PART III", "starred_actors", "CHRISTOPHER LLOYD" ], [ "BACK TO THE FUTURE PART III", "starred_actors", "MICHAEL J. FOX" ], [ "BACK TO THE FUTURE PART III", "starred_actors", "THOMAS F. WILSON" ], [ "BACK TO THE FUTURE PART III", "written_by", "ROBERT ZEMECKIS" ], [ "BLUE IN THE FACE", "has_genre", "COMEDY" ], [ "BLUE IN THE FACE", "release_year", "1995" ], [ "BLUE IN THE FACE", "starred_actors", "MICHAEL J. FOX" ], [ "BRIGHT LIGHTS, BIG CITY", "has_genre", "DRAMA" ], [ "BRIGHT LIGHTS, BIG CITY", "starred_actors", "MICHAEL J. FOX" ], [ "CASUALTIES OF WAR", "has_genre", "DRAMA" ], [ "CASUALTIES OF WAR", "release_year", "1989" ], [ "CASUALTIES OF WAR", "starred_actors", "MICHAEL J. FOX" ], [ "DOC HOLLYWOOD", "has_genre", "COMEDY" ], [ "DOC HOLLYWOOD", "has_tags", "COMEDY" ], [ "DOC HOLLYWOOD", "has_tags", "MICHAEL J. FOX" ], [ "DOC HOLLYWOOD", "release_year", "1991" ], [ "DOC HOLLYWOOD", "starred_actors", "MICHAEL J. FOX" ], [ "FOR LOVE OR MONEY", "has_genre", "COMEDY" ], [ "FOR LOVE OR MONEY", "has_tags", "MICHAEL J. FOX" ], [ "FOR LOVE OR MONEY", "release_year", "1993" ], [ "FOR LOVE OR MONEY", "starred_actors", "MICHAEL J. FOX" ], [ "GREEDY", "has_genre", "COMEDY" ], [ "GREEDY", "has_tags", "MICHAEL J. FOX" ], [ "GREEDY", "starred_actors", "MICHAEL J. FOX" ], [ "LIFE WITH MIKEY", "has_genre", "COMEDY" ], [ "LIFE WITH MIKEY", "has_tags", "MICHAEL J. FOX" ], [ "LIFE WITH MIKEY", "release_year", "1993" ], [ "LIFE WITH MIKEY", "starred_actors", "MICHAEL J. FOX" ], [ "LIGHT OF DAY", "has_genre", "DRAMA" ], [ "LIGHT OF DAY", "starred_actors", "MICHAEL J. FOX" ], [ "MARS ATTACKS!", "has_genre", "COMEDY" ], [ "MARS ATTACKS!", "has_tags", "ANIMATION" ], [ "MARS ATTACKS!", "has_tags", "ANNETTE BENING" ], [ "MARS ATTACKS!", "has_tags", "COMEDY" ], [ "MARS ATTACKS!", "has_tags", "MICHAEL J. FOX" ], [ "MARS ATTACKS!", "release_year", "1996" ], [ "MARS ATTACKS!", "starred_actors", "ANNETTE BENING" ], [ "MIDNIGHT MADNESS", "has_genre", "COMEDY" ], [ "MIDNIGHT MADNESS", "has_tags", "MICHAEL J. FOX" ], [ "MIDNIGHT MADNESS", "starred_actors", "MICHAEL J. FOX" ], [ "PROBLEM CHILD", "has_genre", "COMEDY" ], [ "PROBLEM CHILD", "release_year", "1990" ], [ "PROBLEM CHILD", "starred_actors", "MICHAEL OLIVER" ], [ "STUART LITTLE", "has_genre", "ANIMATION" ], [ "STUART LITTLE", "has_genre", "COMEDY" ], [ "STUART LITTLE", "has_tags", "ANIMATION" ], [ "STUART LITTLE", "has_tags", "COMEDY" ], [ "STUART LITTLE", "has_tags", "MICHAEL J. FOX" ], [ "STUART LITTLE", "starred_actors", "MICHAEL J. FOX" ], [ "TEEN WOLF", "has_genre", "COMEDY" ], [ "TEEN WOLF", "has_tags", "COMEDY" ], [ "TEEN WOLF", "has_tags", "MICHAEL J. FOX" ], [ "TEEN WOLF", "starred_actors", "MICHAEL J. FOX" ], [ "THE AMERICAN PRESIDENT", "has_genre", "COMEDY" ], [ "THE AMERICAN PRESIDENT", "has_genre", "DRAMA" ], [ "THE AMERICAN PRESIDENT", "has_tags", "ANNETTE BENING" ], [ "THE AMERICAN PRESIDENT", "has_tags", "DRAMA" ], [ "THE AMERICAN PRESIDENT", "release_year", "1995" ], [ "THE AMERICAN PRESIDENT", "starred_actors", "ANNETTE BENING" ], [ "THE AMERICAN PRESIDENT", "starred_actors", "MICHAEL J. FOX" ], [ "THE FRIGHTENERS", "has_genre", "COMEDY" ], [ "THE FRIGHTENERS", "has_tags", "MICHAEL J. FOX" ], [ "THE FRIGHTENERS", "release_year", "1996" ], [ "THE FRIGHTENERS", "starred_actors", "MICHAEL J. FOX" ], [ "THE GOLDEN BOWL", "has_genre", "DRAMA" ], [ "THE HARD WAY", "has_genre", "COMEDY" ], [ "THE HARD WAY", "has_genre", "DRAMA" ], [ "THE HARD WAY", "has_tags", "MICHAEL J. FOX" ], [ "THE HARD WAY", "release_year", "1991" ], [ "THE HARD WAY", "starred_actors", "MICHAEL J. FOX" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10825, 1973 9377, 2014 9989, ALICE AND MARTIN 2975, BIRD PEOPLE 20757, CLOUDS OF SILS MARIA 39775, IN YOUR EYES 8248, JAPAN 36621, JEREMY 11017, JULIETTE BINOCHE 824, LATITUDES 37024, OUTRAGE 234, PEARL HARBOR 8379, ROMANCE 36977, THE GIRL WHO LEAPT THROUGH TIME 315, THE REWRITE src, edge_attr, dst 9989, has_genre, 8379 9989, starred_actors, 11017 2975, release_year, 9377 20757, release_year, 9377 20757, starred_actors, 11017 39775, has_genre, 8379 39775, release_year, 9377 36621, has_genre, 8379 36621, release_year, 10825 824, has_genre, 8379 824, release_year, 9377 37024, has_tags, 8248 37024, release_year, 10825 234, has_genre, 8379 234, has_tags, 8248 234, has_tags, 8379 36977, has_tags, 8248 36977, has_tags, 8379 315, has_genre, 8379 315, has_tags, 8379 315, release_year, 9377 Question: How are ALICE AND MARTIN, BIRD PEOPLE, and OUTRAGE related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ALICE AND MARTIN", "BIRD PEOPLE", "OUTRAGE" ], "valid_edges": [ [ "ALICE AND MARTIN", "has_genre", "ROMANCE" ], [ "ALICE AND MARTIN", "starred_actors", "JULIETTE BINOCHE" ], [ "BIRD PEOPLE", "release_year", "2014" ], [ "CLOUDS OF SILS MARIA", "release_year", "2014" ], [ "CLOUDS OF SILS MARIA", "starred_actors", "JULIETTE BINOCHE" ], [ "IN YOUR EYES", "has_genre", "ROMANCE" ], [ "IN YOUR EYES", "release_year", "2014" ], [ "JEREMY", "has_genre", "ROMANCE" ], [ "JEREMY", "release_year", "1973" ], [ "LATITUDES", "has_genre", "ROMANCE" ], [ "LATITUDES", "release_year", "2014" ], [ "OUTRAGE", "has_tags", "JAPAN" ], [ "OUTRAGE", "release_year", "1973" ], [ "PEARL HARBOR", "has_genre", "ROMANCE" ], [ "PEARL HARBOR", "has_tags", "JAPAN" ], [ "PEARL HARBOR", "has_tags", "ROMANCE" ], [ "THE GIRL WHO LEAPT THROUGH TIME", "has_tags", "JAPAN" ], [ "THE GIRL WHO LEAPT THROUGH TIME", "has_tags", "ROMANCE" ], [ "THE REWRITE", "has_genre", "ROMANCE" ], [ "THE REWRITE", "has_tags", "ROMANCE" ], [ "THE REWRITE", "release_year", "2014" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37967, 13 SINS 9377, 2014 37304, 21 JUMP STREET 26212, 3 DAYS TO KILL 6070, A BETTER WAY TO DIE 11686, A DARK TRUTH 29141, A MOST WANTED MAN 14987, A SECOND CHANCE 35101, ABDUCTION 39289, ACTION 35731, ACTION JACKSON 23806, ADDICTED 17258, AMERICAN HEIST 30709, AMERICAN SNIPER 20033, ANGEL 10248, ASSASSINATION 327, ASSASSINS 694, ASSAULT ON PRECINCT 13 23899, BAD COMPANY 36514, BRICK MANSIONS 6261, CELLULAR 20734, COBRA 28056, CONSPIRACY THEORY 9647, D-DAY 8961, DEATH PROOF 5148, DEATH RACE 23647, DERAILED 18348, DHOOM 6692, DISTRICT 9 38660, DIVERGENT 15961, DON 33511, DRACULA UNTOLD 32221, END OF DAYS 16653, ENEMIES CLOSER 8491, ESCAPE PLAN 28859, EXTREME OPS 25626, F/X 28271, F/X2 35493, FIRESTORM 21299, FIRST BLOOD 278, FORTRESS 26691, FREEZER 12703, GABRIEL 3724, GAMER 23299, GET CARTER 22832, GETAWAY 9642, GONE GIRL 13851, GOOD PEOPLE 37384, GUNDAY 22447, GUY BOLTON 9479, HANNA 12085, HAPPY NEW YEAR 19720, HAYWIRE 2752, HIDDEN AGENDA 25951, HIGHWAYMEN 29663, HOW TO TRAIN YOUR DRAGON 2 34230, I, FRANKENSTEIN 37328, ICEMAN 34211, IN ORDER OF DISAPPEARANCE 34430, IN THE BLOOD 23544, INCEPTION 33200, JESSABELLE 3365, JOHN WICK 32132, KILLER ELITE 26839, KILLERS 19523, LEFT BEHIND 35217, LOOPER 13743, LUCY 8068, MALEFICENT 18434, MAN ON A LEDGE 22373, MAN ON FIRE 36936, MAXIMUM CONVICTION 7626, NEED FOR SPEED 30350, NEXT 22868, NIGHTCRAWLER 29893, NO GOOD DEED 32201, NON-STOP 31027, NOT SAFE FOR WORK 17600, OFF LIMITS 4756, ONCE UPON A TIME IN SHANGHAI 12482, OPEN WINDOWS 32279, PARKER 21835, POINT BLANK 38688, POINT BREAK 10480, PREMIUM RUSH 16828, RACE WITH THE DEVIL 12428, RAGE 29252, REASONABLE DOUBT 18215, REDIRECTED 5554, RIDE ALONG 8516, ROBOCOP 29808, RONIN 2771, RUNNING ON KARMA 4804, S.W.A.T. 37097, SABOTAGE 30173, SALT 33939, SALTING THE BATTLEFIELD 10303, SEEKING JUSTICE 29005, SIN CITY 30321, SINNERS AND SAINTS 13, SNAKES ON A PLANE 31629, SO UNDERCOVER 27160, SOLO 2485, SPARKS 26269, STEREO 14619, STONEHEARST ASYLUM 30932, SWORDFISH 30003, TAKEN 22826, TAKEN 2 23782, TAKEN 3 27494, TAKERS 39976, TEENAGE MUTANT NINJA TURTLES 23821, THE BAG MAN 12208, THE BOURNE ULTIMATUM 30049, THE CAPTIVE 10912, THE EQUALIZER 2878, THE EVIL THAT MEN DO 24251, THE EXPENDABLES 3 19685, THE FINAL CUT 6524, THE GETAWAY 34975, THE GUEST 25954, THE HUNT FOR RED OCTOBER 4223, THE INTERVIEW 11904, THE KILLER ELITE 29213, THE LEGEND OF HERCULES 30751, THE LOFT 3760, THE MATRIX 11359, THE MAZE RUNNER 8839, THE MECHANIC 5250, THE MONKEY KING 15422, THE NEGOTIATOR 33328, THE NET 14632, THE NEXT MAN 31276, THE NUMBERS STATION 14064, THE OUTSIDER 22522, THE PEACEMAKER 30014, THE RAID 2 8660, THE RECKONING 20527, THE SCRIBBLER 28095, THE SIGNAL 22385, THE SUM OF ALL FEARS 25974, THE TRANSPORTER 23525, THE TWO FACES OF JANUARY 21593, THE VOICES 12441, THE WARRIORS 24811, THRILLER 14992, TRANSIT 22110, TRESPASS 37099, TRIANGLE 7138, TURBULENCE 10238, UNDERWORLD 5560, UNSTOPPABLE 12376, V FOR VENDETTA 5603, VEHICLE 19 26489, WELCOME TO THE PUNCH 6262, WHITE BIRD IN A BLIZZARD 32403, WHITE HOUSE DOWN 28356, WICKED BLOOD 36150, WILD GEESE II 31782, YOUNG ONES src, edge_attr, dst 37967, has_genre, 24811 37967, release_year, 9377 37304, has_genre, 39289 37304, has_tags, 9377 26212, has_genre, 39289 26212, has_genre, 24811 26212, release_year, 9377 6070, has_genre, 39289 6070, has_genre, 24811 11686, has_genre, 39289 11686, has_genre, 24811 29141, has_genre, 24811 29141, has_tags, 24811 29141, release_year, 9377 14987, has_genre, 24811 14987, release_year, 9377 35101, has_genre, 39289 35101, has_genre, 24811 35101, has_tags, 39289 35731, has_genre, 39289 35731, has_tags, 39289 35731, release_year, 9377 23806, has_genre, 24811 23806, release_year, 9377 17258, has_genre, 39289 17258, release_year, 9377 30709, has_genre, 39289 30709, release_year, 9377 20033, written_by, 22447 10248, has_genre, 39289 10248, has_genre, 24811 327, has_genre, 39289 327, has_genre, 24811 694, has_genre, 39289 694, has_genre, 24811 694, has_tags, 39289 23899, has_genre, 39289 23899, has_genre, 24811 23899, has_tags, 24811 36514, has_genre, 39289 36514, release_year, 9377 6261, has_genre, 24811 6261, has_tags, 39289 6261, has_tags, 24811 20734, has_genre, 39289 20734, has_tags, 39289 20734, has_tags, 24811 28056, has_genre, 39289 28056, has_tags, 24811 9647, has_genre, 39289 9647, has_genre, 24811 8961, has_genre, 39289 8961, has_genre, 24811 5148, has_genre, 39289 5148, has_genre, 24811 23647, has_genre, 39289 23647, has_genre, 24811 18348, has_genre, 39289 18348, has_genre, 24811 6692, has_genre, 39289 6692, has_genre, 24811 6692, has_tags, 39289 6692, has_tags, 24811 38660, has_tags, 39289 38660, release_year, 9377 15961, has_genre, 39289 15961, has_genre, 24811 33511, has_genre, 39289 33511, release_year, 9377 32221, has_genre, 39289 32221, has_tags, 24811 16653, has_genre, 39289 16653, has_genre, 24811 8491, has_genre, 39289 8491, has_genre, 24811 28859, has_genre, 39289 28859, has_genre, 24811 25626, has_genre, 39289 25626, has_genre, 24811 28271, has_genre, 39289 28271, has_genre, 24811 35493, has_genre, 39289 35493, has_genre, 24811 21299, has_genre, 39289 21299, has_genre, 24811 21299, has_tags, 39289 278, has_genre, 39289 278, has_genre, 24811 26691, has_genre, 39289 26691, has_genre, 24811 26691, release_year, 9377 12703, has_genre, 39289 12703, has_tags, 20033 3724, has_genre, 39289 3724, has_genre, 24811 3724, has_tags, 39289 23299, has_genre, 39289 23299, has_genre, 24811 22832, has_genre, 39289 22832, has_genre, 24811 9642, has_genre, 24811 9642, has_tags, 9377 9642, has_tags, 24811 9642, release_year, 9377 13851, has_genre, 24811 13851, release_year, 9377 37384, has_genre, 39289 37384, release_year, 9377 9479, has_genre, 39289 9479, has_genre, 24811 9479, has_tags, 39289 9479, has_tags, 24811 12085, has_genre, 39289 12085, release_year, 9377 19720, has_genre, 39289 19720, has_genre, 24811 19720, has_tags, 39289 2752, has_genre, 39289 2752, has_genre, 24811 25951, has_genre, 39289 25951, has_genre, 24811 29663, has_genre, 39289 29663, release_year, 9377 34230, has_genre, 39289 34230, release_year, 9377 37328, has_genre, 39289 37328, release_year, 9377 34211, has_genre, 39289 34211, release_year, 9377 34430, has_genre, 39289 34430, release_year, 9377 23544, has_genre, 39289 23544, has_tags, 39289 23544, has_tags, 24811 33200, has_genre, 24811 33200, release_year, 9377 3365, has_genre, 39289 3365, has_genre, 24811 3365, has_tags, 39289 32132, has_genre, 39289 32132, has_genre, 24811 32132, has_tags, 39289 26839, has_genre, 39289 26839, release_year, 9377 19523, has_genre, 39289 19523, has_genre, 24811 19523, release_year, 9377 35217, has_genre, 39289 35217, has_tags, 24811 13743, has_genre, 39289 13743, release_year, 9377 8068, has_genre, 39289 8068, release_year, 9377 18434, has_genre, 39289 18434, has_genre, 24811 22373, has_genre, 39289 22373, has_genre, 24811 22373, has_tags, 39289 36936, has_genre, 39289 36936, has_genre, 24811 7626, has_genre, 39289 7626, has_tags, 39289 7626, release_year, 9377 30350, has_genre, 39289 30350, has_genre, 24811 30350, has_tags, 39289 22868, has_genre, 24811 22868, has_tags, 24811 22868, release_year, 9377 29893, has_genre, 24811 29893, release_year, 9377 32201, has_genre, 39289 32201, release_year, 9377 31027, has_genre, 24811 31027, release_year, 9377 17600, has_genre, 39289 17600, has_genre, 24811 4756, has_genre, 39289 4756, release_year, 9377 12482, has_genre, 24811 12482, release_year, 9377 32279, has_genre, 39289 32279, has_genre, 24811 21835, has_genre, 39289 21835, has_genre, 24811 21835, has_tags, 39289 21835, has_tags, 24811 38688, has_genre, 39289 38688, has_genre, 24811 10480, has_genre, 39289 10480, has_genre, 24811 10480, has_tags, 39289 10480, has_tags, 24811 16828, has_genre, 39289 16828, has_genre, 24811 12428, has_genre, 39289 12428, has_genre, 24811 12428, release_year, 9377 29252, has_genre, 24811 29252, release_year, 9377 18215, has_genre, 39289 18215, release_year, 9377 5554, has_genre, 39289 5554, release_year, 9377 8516, has_genre, 39289 8516, has_tags, 39289 8516, release_year, 9377 29808, has_genre, 39289 29808, has_tags, 39289 29808, has_tags, 24811 2771, has_genre, 39289 2771, has_genre, 24811 4804, has_genre, 39289 4804, has_genre, 24811 4804, has_tags, 39289 37097, has_genre, 24811 37097, release_year, 9377 30173, has_genre, 39289 30173, has_tags, 39289 30173, has_tags, 24811 33939, has_genre, 39289 33939, release_year, 9377 10303, has_genre, 39289 10303, has_genre, 24811 10303, has_tags, 39289 29005, has_genre, 24811 29005, has_tags, 39289 30321, has_genre, 39289 30321, has_genre, 24811 13, has_genre, 39289 13, has_genre, 24811 31629, has_genre, 39289 27160, has_genre, 39289 27160, has_genre, 24811 2485, has_genre, 39289 2485, has_genre, 24811 26269, has_genre, 24811 26269, release_year, 9377 14619, has_genre, 24811 14619, release_year, 9377 30932, has_genre, 39289 30932, has_genre, 24811 30932, has_tags, 39289 30003, has_genre, 39289 30003, has_genre, 24811 30003, has_tags, 39289 30003, has_tags, 24811 22826, has_genre, 39289 22826, has_genre, 24811 23782, has_genre, 39289 23782, has_genre, 24811 23782, has_tags, 39289 23782, release_year, 9377 27494, has_genre, 39289 27494, has_genre, 24811 39976, has_genre, 39289 39976, has_tags, 39289 39976, release_year, 9377 23821, has_genre, 24811 23821, release_year, 9377 12208, has_genre, 39289 12208, has_genre, 24811 12208, has_tags, 39289 12208, has_tags, 24811 30049, has_genre, 24811 30049, release_year, 9377 10912, has_genre, 39289 10912, has_genre, 24811 10912, has_tags, 39289 10912, release_year, 9377 2878, has_genre, 39289 2878, has_genre, 24811 24251, has_genre, 39289 24251, release_year, 9377 19685, has_genre, 39289 19685, has_genre, 24811 6524, has_genre, 39289 6524, has_genre, 24811 34975, has_genre, 24811 34975, release_year, 9377 25954, has_genre, 39289 25954, has_genre, 24811 25954, has_tags, 39289 25954, has_tags, 24811 4223, has_genre, 39289 4223, has_genre, 24811 4223, release_year, 9377 11904, has_genre, 39289 11904, has_genre, 24811 29213, has_genre, 39289 29213, release_year, 9377 30751, has_genre, 24811 30751, release_year, 9377 3760, has_genre, 39289 3760, has_tags, 39289 3760, has_tags, 24811 11359, has_genre, 39289 11359, has_tags, 39289 11359, release_year, 9377 8839, has_genre, 39289 8839, has_genre, 24811 8839, has_tags, 39289 5250, has_genre, 39289 5250, release_year, 9377 15422, has_genre, 39289 15422, has_tags, 24811 33328, has_genre, 39289 33328, has_tags, 39289 33328, has_tags, 24811 14632, has_genre, 39289 14632, has_genre, 24811 31276, has_genre, 39289 31276, has_genre, 24811 14064, has_genre, 39289 14064, release_year, 9377 22522, has_genre, 39289 22522, has_genre, 24811 30014, has_genre, 39289 30014, has_tags, 39289 30014, release_year, 9377 8660, has_genre, 24811 8660, release_year, 9377 20527, has_genre, 24811 20527, release_year, 9377 28095, has_genre, 24811 28095, release_year, 9377 22385, has_genre, 39289 22385, has_genre, 24811 25974, has_genre, 39289 25974, has_genre, 24811 25974, has_tags, 39289 23525, has_genre, 24811 23525, release_year, 9377 21593, has_genre, 24811 21593, release_year, 9377 12441, has_genre, 39289 12441, has_genre, 24811 14992, has_genre, 39289 14992, has_genre, 24811 22110, has_genre, 39289 22110, has_genre, 24811 37099, has_genre, 39289 37099, has_genre, 24811 7138, has_genre, 39289 7138, has_genre, 24811 10238, has_genre, 39289 10238, has_genre, 24811 10238, has_tags, 39289 5560, has_genre, 39289 5560, has_genre, 24811 12376, has_genre, 39289 12376, has_genre, 24811 12376, has_tags, 39289 12376, has_tags, 24811 5603, has_genre, 39289 5603, has_genre, 24811 26489, has_genre, 39289 26489, has_genre, 24811 6262, has_genre, 24811 6262, release_year, 9377 32403, has_genre, 39289 32403, has_genre, 24811 32403, has_tags, 39289 32403, has_tags, 24811 28356, has_genre, 39289 28356, has_genre, 24811 28356, release_year, 9377 36150, has_genre, 39289 36150, has_genre, 24811 31782, has_genre, 39289 31782, release_year, 9377 Question: For what reason are A MOST WANTED MAN, GUY BOLTON, and SO UNDERCOVER associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "A MOST WANTED MAN", "GUY BOLTON", "SO UNDERCOVER" ], "valid_edges": [ [ "13 SINS", "has_genre", "THRILLER" ], [ "13 SINS", "release_year", "2014" ], [ "21 JUMP STREET", "has_genre", "ACTION" ], [ "21 JUMP STREET", "has_tags", "2014" ], [ "3 DAYS TO KILL", "has_genre", "ACTION" ], [ "3 DAYS TO KILL", "has_genre", "THRILLER" ], [ "3 DAYS TO KILL", "release_year", "2014" ], [ "A BETTER WAY TO DIE", "has_genre", "ACTION" ], [ "A BETTER WAY TO DIE", "has_genre", "THRILLER" ], [ "A DARK TRUTH", "has_genre", "ACTION" ], [ "A DARK TRUTH", "has_genre", "THRILLER" ], [ "A MOST WANTED MAN", "has_genre", "THRILLER" ], [ "A MOST WANTED MAN", "has_tags", "THRILLER" ], [ "A MOST WANTED MAN", "release_year", "2014" ], [ "A SECOND CHANCE", "has_genre", "THRILLER" ], [ "A SECOND CHANCE", "release_year", "2014" ], [ "ABDUCTION", "has_genre", "ACTION" ], [ "ABDUCTION", "has_genre", "THRILLER" ], [ "ABDUCTION", "has_tags", "ACTION" ], [ "ACTION JACKSON", "has_genre", "ACTION" ], [ "ACTION JACKSON", "has_tags", "ACTION" ], [ "ACTION JACKSON", "release_year", "2014" ], [ "ADDICTED", "has_genre", "THRILLER" ], [ "ADDICTED", "release_year", "2014" ], [ "AMERICAN HEIST", "has_genre", "ACTION" ], [ "AMERICAN HEIST", "release_year", "2014" ], [ "AMERICAN SNIPER", "has_genre", "ACTION" ], [ "AMERICAN SNIPER", "release_year", "2014" ], [ "ANGEL", "written_by", "GUY BOLTON" ], [ "ASSASSINATION", "has_genre", "ACTION" ], [ "ASSASSINATION", "has_genre", "THRILLER" ], [ "ASSASSINS", "has_genre", "ACTION" ], [ "ASSASSINS", "has_genre", "THRILLER" ], [ "ASSAULT ON PRECINCT 13", "has_genre", "ACTION" ], [ "ASSAULT ON PRECINCT 13", "has_genre", "THRILLER" ], [ "ASSAULT ON PRECINCT 13", "has_tags", "ACTION" ], [ "BAD COMPANY", "has_genre", "ACTION" ], [ "BAD COMPANY", "has_genre", "THRILLER" ], [ "BAD COMPANY", "has_tags", "THRILLER" ], [ "BRICK MANSIONS", "has_genre", "ACTION" ], [ "BRICK MANSIONS", "release_year", "2014" ], [ "CELLULAR", "has_genre", "THRILLER" ], [ "CELLULAR", "has_tags", "ACTION" ], [ "CELLULAR", "has_tags", "THRILLER" ], [ "COBRA", "has_genre", "ACTION" ], [ "COBRA", "has_tags", "ACTION" ], [ "COBRA", "has_tags", "THRILLER" ], [ "CONSPIRACY THEORY", "has_genre", "ACTION" ], [ "CONSPIRACY THEORY", "has_tags", "THRILLER" ], [ "D-DAY", "has_genre", "ACTION" ], [ "D-DAY", "has_genre", "THRILLER" ], [ "DEATH PROOF", "has_genre", "ACTION" ], [ "DEATH PROOF", "has_genre", "THRILLER" ], [ "DEATH RACE", "has_genre", "ACTION" ], [ "DEATH RACE", "has_genre", "THRILLER" ], [ "DERAILED", "has_genre", "ACTION" ], [ "DERAILED", "has_genre", "THRILLER" ], [ "DHOOM", "has_genre", "ACTION" ], [ "DHOOM", "has_genre", "THRILLER" ], [ "DISTRICT 9", "has_genre", "ACTION" ], [ "DISTRICT 9", "has_genre", "THRILLER" ], [ "DISTRICT 9", "has_tags", "ACTION" ], [ "DISTRICT 9", "has_tags", "THRILLER" ], [ "DIVERGENT", "has_tags", "ACTION" ], [ "DIVERGENT", "release_year", "2014" ], [ "DON", "has_genre", "ACTION" ], [ "DON", "has_genre", "THRILLER" ], [ "DRACULA UNTOLD", "has_genre", "ACTION" ], [ "DRACULA UNTOLD", "release_year", "2014" ], [ "END OF DAYS", "has_genre", "ACTION" ], [ "END OF DAYS", "has_tags", "THRILLER" ], [ "ENEMIES CLOSER", "has_genre", "ACTION" ], [ "ENEMIES CLOSER", "has_genre", "THRILLER" ], [ "ESCAPE PLAN", "has_genre", "ACTION" ], [ "ESCAPE PLAN", "has_genre", "THRILLER" ], [ "EXTREME OPS", "has_genre", "ACTION" ], [ "EXTREME OPS", "has_genre", "THRILLER" ], [ "F/X", "has_genre", "ACTION" ], [ "F/X", "has_genre", "THRILLER" ], [ "F/X2", "has_genre", "ACTION" ], [ "F/X2", "has_genre", "THRILLER" ], [ "FIRESTORM", "has_genre", "ACTION" ], [ "FIRESTORM", "has_genre", "THRILLER" ], [ "FIRST BLOOD", "has_genre", "ACTION" ], [ "FIRST BLOOD", "has_genre", "THRILLER" ], [ "FIRST BLOOD", "has_tags", "ACTION" ], [ "FORTRESS", "has_genre", "ACTION" ], [ "FORTRESS", "has_genre", "THRILLER" ], [ "FREEZER", "has_genre", "ACTION" ], [ "FREEZER", "has_genre", "THRILLER" ], [ "FREEZER", "release_year", "2014" ], [ "GABRIEL", "has_genre", "ACTION" ], [ "GABRIEL", "has_tags", "ANGEL" ], [ "GAMER", "has_genre", "ACTION" ], [ "GAMER", "has_genre", "THRILLER" ], [ "GAMER", "has_tags", "ACTION" ], [ "GET CARTER", "has_genre", "ACTION" ], [ "GET CARTER", "has_genre", "THRILLER" ], [ "GETAWAY", "has_genre", "ACTION" ], [ "GETAWAY", "has_genre", "THRILLER" ], [ "GONE GIRL", "has_genre", "THRILLER" ], [ "GONE GIRL", "has_tags", "2014" ], [ "GONE GIRL", "has_tags", "THRILLER" ], [ "GONE GIRL", "release_year", "2014" ], [ "GOOD PEOPLE", "has_genre", "THRILLER" ], [ "GOOD PEOPLE", "release_year", "2014" ], [ "GUNDAY", "has_genre", "ACTION" ], [ "GUNDAY", "release_year", "2014" ], [ "HANNA", "has_genre", "ACTION" ], [ "HANNA", "has_genre", "THRILLER" ], [ "HANNA", "has_tags", "ACTION" ], [ "HANNA", "has_tags", "THRILLER" ], [ "HAPPY NEW YEAR", "has_genre", "ACTION" ], [ "HAPPY NEW YEAR", "release_year", "2014" ], [ "HAYWIRE", "has_genre", "ACTION" ], [ "HAYWIRE", "has_genre", "THRILLER" ], [ "HAYWIRE", "has_tags", "ACTION" ], [ "HIDDEN AGENDA", "has_genre", "ACTION" ], [ "HIDDEN AGENDA", "has_genre", "THRILLER" ], [ "HIGHWAYMEN", "has_genre", "ACTION" ], [ "HIGHWAYMEN", "has_genre", "THRILLER" ], [ "HOW TO TRAIN YOUR DRAGON 2", "has_genre", "ACTION" ], [ "HOW TO TRAIN YOUR DRAGON 2", "release_year", "2014" ], [ "I, FRANKENSTEIN", "has_genre", "ACTION" ], [ "I, FRANKENSTEIN", "release_year", "2014" ], [ "ICEMAN", "has_genre", "ACTION" ], [ "ICEMAN", "release_year", "2014" ], [ "IN ORDER OF DISAPPEARANCE", "has_genre", "ACTION" ], [ "IN ORDER OF DISAPPEARANCE", "release_year", "2014" ], [ "IN THE BLOOD", "has_genre", "ACTION" ], [ "IN THE BLOOD", "release_year", "2014" ], [ "INCEPTION", "has_genre", "ACTION" ], [ "INCEPTION", "has_tags", "ACTION" ], [ "INCEPTION", "has_tags", "THRILLER" ], [ "JESSABELLE", "has_genre", "THRILLER" ], [ "JESSABELLE", "release_year", "2014" ], [ "JOHN WICK", "has_genre", "ACTION" ], [ "JOHN WICK", "has_genre", "THRILLER" ], [ "JOHN WICK", "has_tags", "ACTION" ], [ "KILLER ELITE", "has_genre", "ACTION" ], [ "KILLER ELITE", "has_genre", "THRILLER" ], [ "KILLER ELITE", "has_tags", "ACTION" ], [ "KILLERS", "has_genre", "ACTION" ], [ "KILLERS", "release_year", "2014" ], [ "LEFT BEHIND", "has_genre", "ACTION" ], [ "LEFT BEHIND", "has_genre", "THRILLER" ], [ "LEFT BEHIND", "release_year", "2014" ], [ "LOOPER", "has_genre", "ACTION" ], [ "LOOPER", "has_tags", "THRILLER" ], [ "LUCY", "has_genre", "ACTION" ], [ "LUCY", "release_year", "2014" ], [ "MALEFICENT", "has_genre", "ACTION" ], [ "MALEFICENT", "release_year", "2014" ], [ "MAN ON A LEDGE", "has_genre", "ACTION" ], [ "MAN ON A LEDGE", "has_genre", "THRILLER" ], [ "MAN ON FIRE", "has_genre", "ACTION" ], [ "MAN ON FIRE", "has_genre", "THRILLER" ], [ "MAN ON FIRE", "has_tags", "ACTION" ], [ "MAXIMUM CONVICTION", "has_genre", "ACTION" ], [ "MAXIMUM CONVICTION", "has_genre", "THRILLER" ], [ "NEED FOR SPEED", "has_genre", "ACTION" ], [ "NEED FOR SPEED", "has_tags", "ACTION" ], [ "NEED FOR SPEED", "release_year", "2014" ], [ "NEXT", "has_genre", "ACTION" ], [ "NEXT", "has_genre", "THRILLER" ], [ "NEXT", "has_tags", "ACTION" ], [ "NIGHTCRAWLER", "has_genre", "THRILLER" ], [ "NIGHTCRAWLER", "has_tags", "THRILLER" ], [ "NIGHTCRAWLER", "release_year", "2014" ], [ "NO GOOD DEED", "has_genre", "THRILLER" ], [ "NO GOOD DEED", "release_year", "2014" ], [ "NON-STOP", "has_genre", "ACTION" ], [ "NON-STOP", "release_year", "2014" ], [ "NOT SAFE FOR WORK", "has_genre", "THRILLER" ], [ "NOT SAFE FOR WORK", "release_year", "2014" ], [ "OFF LIMITS", "has_genre", "ACTION" ], [ "OFF LIMITS", "has_genre", "THRILLER" ], [ "ONCE UPON A TIME IN SHANGHAI", "has_genre", "ACTION" ], [ "ONCE UPON A TIME IN SHANGHAI", "release_year", "2014" ], [ "OPEN WINDOWS", "has_genre", "THRILLER" ], [ "OPEN WINDOWS", "release_year", "2014" ], [ "PARKER", "has_genre", "ACTION" ], [ "PARKER", "has_genre", "THRILLER" ], [ "POINT BLANK", "has_genre", "ACTION" ], [ "POINT BLANK", "has_genre", "THRILLER" ], [ "POINT BLANK", "has_tags", "ACTION" ], [ "POINT BLANK", "has_tags", "THRILLER" ], [ "POINT BREAK", "has_genre", "ACTION" ], [ "POINT BREAK", "has_genre", "THRILLER" ], [ "PREMIUM RUSH", "has_genre", "ACTION" ], [ "PREMIUM RUSH", "has_genre", "THRILLER" ], [ "PREMIUM RUSH", "has_tags", "ACTION" ], [ "PREMIUM RUSH", "has_tags", "THRILLER" ], [ "RACE WITH THE DEVIL", "has_genre", "ACTION" ], [ "RACE WITH THE DEVIL", "has_genre", "THRILLER" ], [ "RAGE", "has_genre", "ACTION" ], [ "RAGE", "has_genre", "THRILLER" ], [ "RAGE", "release_year", "2014" ], [ "REASONABLE DOUBT", "has_genre", "THRILLER" ], [ "REASONABLE DOUBT", "release_year", "2014" ], [ "REDIRECTED", "has_genre", "ACTION" ], [ "REDIRECTED", "release_year", "2014" ], [ "RIDE ALONG", "has_genre", "ACTION" ], [ "RIDE ALONG", "release_year", "2014" ], [ "ROBOCOP", "has_genre", "ACTION" ], [ "ROBOCOP", "has_tags", "ACTION" ], [ "ROBOCOP", "release_year", "2014" ], [ "RONIN", "has_genre", "ACTION" ], [ "RONIN", "has_tags", "ACTION" ], [ "RONIN", "has_tags", "THRILLER" ], [ "RUNNING ON KARMA", "has_genre", "ACTION" ], [ "RUNNING ON KARMA", "has_genre", "THRILLER" ], [ "S.W.A.T.", "has_genre", "ACTION" ], [ "S.W.A.T.", "has_genre", "THRILLER" ], [ "S.W.A.T.", "has_tags", "ACTION" ], [ "SABOTAGE", "has_genre", "THRILLER" ], [ "SABOTAGE", "release_year", "2014" ], [ "SALT", "has_genre", "ACTION" ], [ "SALT", "has_tags", "ACTION" ], [ "SALT", "has_tags", "THRILLER" ], [ "SALTING THE BATTLEFIELD", "has_genre", "ACTION" ], [ "SALTING THE BATTLEFIELD", "release_year", "2014" ], [ "SEEKING JUSTICE", "has_genre", "ACTION" ], [ "SEEKING JUSTICE", "has_genre", "THRILLER" ], [ "SEEKING JUSTICE", "has_tags", "ACTION" ], [ "SIN CITY", "has_genre", "THRILLER" ], [ "SIN CITY", "has_tags", "ACTION" ], [ "SINNERS AND SAINTS", "has_genre", "ACTION" ], [ "SINNERS AND SAINTS", "has_genre", "THRILLER" ], [ "SNAKES ON A PLANE", "has_genre", "ACTION" ], [ "SNAKES ON A PLANE", "has_genre", "THRILLER" ], [ "SO UNDERCOVER", "has_genre", "ACTION" ], [ "SOLO", "has_genre", "ACTION" ], [ "SOLO", "has_genre", "THRILLER" ], [ "SPARKS", "has_genre", "ACTION" ], [ "SPARKS", "has_genre", "THRILLER" ], [ "STEREO", "has_genre", "THRILLER" ], [ "STEREO", "release_year", "2014" ], [ "STONEHEARST ASYLUM", "has_genre", "THRILLER" ], [ "STONEHEARST ASYLUM", "release_year", "2014" ], [ "SWORDFISH", "has_genre", "ACTION" ], [ "SWORDFISH", "has_genre", "THRILLER" ], [ "SWORDFISH", "has_tags", "ACTION" ], [ "TAKEN", "has_genre", "ACTION" ], [ "TAKEN", "has_genre", "THRILLER" ], [ "TAKEN", "has_tags", "ACTION" ], [ "TAKEN", "has_tags", "THRILLER" ], [ "TAKEN 2", "has_genre", "ACTION" ], [ "TAKEN 2", "has_genre", "THRILLER" ], [ "TAKEN 3", "has_genre", "ACTION" ], [ "TAKEN 3", "has_genre", "THRILLER" ], [ "TAKEN 3", "has_tags", "ACTION" ], [ "TAKEN 3", "release_year", "2014" ], [ "TAKERS", "has_genre", "ACTION" ], [ "TAKERS", "has_genre", "THRILLER" ], [ "TEENAGE MUTANT NINJA TURTLES", "has_genre", "ACTION" ], [ "TEENAGE MUTANT NINJA TURTLES", "has_tags", "ACTION" ], [ "TEENAGE MUTANT NINJA TURTLES", "release_year", "2014" ], [ "THE BAG MAN", "has_genre", "THRILLER" ], [ "THE BAG MAN", "release_year", "2014" ], [ "THE BOURNE ULTIMATUM", "has_genre", "ACTION" ], [ "THE BOURNE ULTIMATUM", "has_genre", "THRILLER" ], [ "THE BOURNE ULTIMATUM", "has_tags", "ACTION" ], [ "THE BOURNE ULTIMATUM", "has_tags", "THRILLER" ], [ "THE CAPTIVE", "has_genre", "THRILLER" ], [ "THE CAPTIVE", "release_year", "2014" ], [ "THE EQUALIZER", "has_genre", "ACTION" ], [ "THE EQUALIZER", "has_genre", "THRILLER" ], [ "THE EQUALIZER", "has_tags", "ACTION" ], [ "THE EQUALIZER", "release_year", "2014" ], [ "THE EVIL THAT MEN DO", "has_genre", "ACTION" ], [ "THE EVIL THAT MEN DO", "has_genre", "THRILLER" ], [ "THE EXPENDABLES 3", "has_genre", "ACTION" ], [ "THE EXPENDABLES 3", "release_year", "2014" ], [ "THE FINAL CUT", "has_genre", "ACTION" ], [ "THE FINAL CUT", "has_genre", "THRILLER" ], [ "THE GETAWAY", "has_genre", "ACTION" ], [ "THE GETAWAY", "has_genre", "THRILLER" ], [ "THE GUEST", "has_genre", "THRILLER" ], [ "THE GUEST", "release_year", "2014" ], [ "THE HUNT FOR RED OCTOBER", "has_genre", "ACTION" ], [ "THE HUNT FOR RED OCTOBER", "has_genre", "THRILLER" ], [ "THE HUNT FOR RED OCTOBER", "has_tags", "ACTION" ], [ "THE HUNT FOR RED OCTOBER", "has_tags", "THRILLER" ], [ "THE INTERVIEW", "has_genre", "ACTION" ], [ "THE INTERVIEW", "has_genre", "THRILLER" ], [ "THE INTERVIEW", "release_year", "2014" ], [ "THE KILLER ELITE", "has_genre", "ACTION" ], [ "THE KILLER ELITE", "has_genre", "THRILLER" ], [ "THE LEGEND OF HERCULES", "has_genre", "ACTION" ], [ "THE LEGEND OF HERCULES", "release_year", "2014" ], [ "THE LOFT", "has_genre", "THRILLER" ], [ "THE LOFT", "release_year", "2014" ], [ "THE MATRIX", "has_genre", "ACTION" ], [ "THE MATRIX", "has_tags", "ACTION" ], [ "THE MATRIX", "has_tags", "THRILLER" ], [ "THE MAZE RUNNER", "has_genre", "ACTION" ], [ "THE MAZE RUNNER", "has_tags", "ACTION" ], [ "THE MAZE RUNNER", "release_year", "2014" ], [ "THE MECHANIC", "has_genre", "ACTION" ], [ "THE MECHANIC", "has_genre", "THRILLER" ], [ "THE MECHANIC", "has_tags", "ACTION" ], [ "THE MONKEY KING", "has_genre", "ACTION" ], [ "THE MONKEY KING", "release_year", "2014" ], [ "THE NEGOTIATOR", "has_genre", "ACTION" ], [ "THE NEGOTIATOR", "has_tags", "THRILLER" ], [ "THE NET", "has_genre", "ACTION" ], [ "THE NET", "has_tags", "ACTION" ], [ "THE NET", "has_tags", "THRILLER" ], [ "THE NEXT MAN", "has_genre", "ACTION" ], [ "THE NEXT MAN", "has_genre", "THRILLER" ], [ "THE NUMBERS STATION", "has_genre", "ACTION" ], [ "THE NUMBERS STATION", "has_genre", "THRILLER" ], [ "THE OUTSIDER", "has_genre", "ACTION" ], [ "THE OUTSIDER", "release_year", "2014" ], [ "THE PEACEMAKER", "has_genre", "ACTION" ], [ "THE PEACEMAKER", "has_genre", "THRILLER" ], [ "THE RAID 2", "has_genre", "ACTION" ], [ "THE RAID 2", "has_tags", "ACTION" ], [ "THE RAID 2", "release_year", "2014" ], [ "THE RECKONING", "has_genre", "THRILLER" ], [ "THE RECKONING", "release_year", "2014" ], [ "THE SCRIBBLER", "has_genre", "THRILLER" ], [ "THE SCRIBBLER", "release_year", "2014" ], [ "THE SIGNAL", "has_genre", "THRILLER" ], [ "THE SIGNAL", "release_year", "2014" ], [ "THE SUM OF ALL FEARS", "has_genre", "ACTION" ], [ "THE SUM OF ALL FEARS", "has_genre", "THRILLER" ], [ "THE TRANSPORTER", "has_genre", "ACTION" ], [ "THE TRANSPORTER", "has_genre", "THRILLER" ], [ "THE TRANSPORTER", "has_tags", "ACTION" ], [ "THE TWO FACES OF JANUARY", "has_genre", "THRILLER" ], [ "THE TWO FACES OF JANUARY", "release_year", "2014" ], [ "THE VOICES", "has_genre", "THRILLER" ], [ "THE VOICES", "release_year", "2014" ], [ "THE WARRIORS", "has_genre", "ACTION" ], [ "THE WARRIORS", "has_genre", "THRILLER" ], [ "TRANSIT", "has_genre", "ACTION" ], [ "TRANSIT", "has_genre", "THRILLER" ], [ "TRESPASS", "has_genre", "ACTION" ], [ "TRESPASS", "has_genre", "THRILLER" ], [ "TRIANGLE", "has_genre", "ACTION" ], [ "TRIANGLE", "has_genre", "THRILLER" ], [ "TURBULENCE", "has_genre", "ACTION" ], [ "TURBULENCE", "has_genre", "THRILLER" ], [ "UNDERWORLD", "has_genre", "ACTION" ], [ "UNDERWORLD", "has_genre", "THRILLER" ], [ "UNDERWORLD", "has_tags", "ACTION" ], [ "UNSTOPPABLE", "has_genre", "ACTION" ], [ "UNSTOPPABLE", "has_genre", "THRILLER" ], [ "V FOR VENDETTA", "has_genre", "ACTION" ], [ "V FOR VENDETTA", "has_genre", "THRILLER" ], [ "V FOR VENDETTA", "has_tags", "ACTION" ], [ "V FOR VENDETTA", "has_tags", "THRILLER" ], [ "VEHICLE 19", "has_genre", "ACTION" ], [ "VEHICLE 19", "has_genre", "THRILLER" ], [ "WELCOME TO THE PUNCH", "has_genre", "ACTION" ], [ "WELCOME TO THE PUNCH", "has_genre", "THRILLER" ], [ "WHITE BIRD IN A BLIZZARD", "has_genre", "THRILLER" ], [ "WHITE BIRD IN A BLIZZARD", "release_year", "2014" ], [ "WHITE HOUSE DOWN", "has_genre", "ACTION" ], [ "WHITE HOUSE DOWN", "has_genre", "THRILLER" ], [ "WHITE HOUSE DOWN", "has_tags", "ACTION" ], [ "WHITE HOUSE DOWN", "has_tags", "THRILLER" ], [ "WICKED BLOOD", "has_genre", "ACTION" ], [ "WICKED BLOOD", "has_genre", "THRILLER" ], [ "WICKED BLOOD", "release_year", "2014" ], [ "WILD GEESE II", "has_genre", "ACTION" ], [ "WILD GEESE II", "has_genre", "THRILLER" ], [ "YOUNG ONES", "has_genre", "ACTION" ], [ "YOUNG ONES", "release_year", "2014" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 135, 1926 8486, 1999 29818, 3 BAD MEN 22900, DUEL IN THE SUN 22149, LIONEL BARRYMORE 36671, MAIA CAMPBELL 8379, ROMANCE 35403, TEARS OF THE BLACK TIGER 26527, THE BELLS 28418, THE TEMPTRESS 28632, THE VIRGINIAN 10866, THE WINNING OF BARBARA WORTH 23874, TRIPPIN' 36026, WESTERN src, edge_attr, dst 29818, has_genre, 36026 29818, release_year, 135 22900, has_genre, 36026 22900, starred_actors, 22149 8379, release_year, 8486 35403, has_genre, 8379 35403, has_tags, 36026 26527, release_year, 135 26527, starred_actors, 22149 28418, release_year, 135 28418, starred_actors, 22149 28632, has_genre, 8379 28632, has_genre, 36026 10866, has_genre, 36026 10866, release_year, 135 23874, release_year, 8486 23874, starred_actors, 36671 Question: In what context are MAIA CAMPBELL, TEARS OF THE BLACK TIGER, and THE BELLS connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "MAIA CAMPBELL", "TEARS OF THE BLACK TIGER", "THE BELLS" ], "valid_edges": [ [ "3 BAD MEN", "has_genre", "WESTERN" ], [ "3 BAD MEN", "release_year", "1926" ], [ "DUEL IN THE SUN", "has_genre", "WESTERN" ], [ "DUEL IN THE SUN", "starred_actors", "LIONEL BARRYMORE" ], [ "ROMANCE", "release_year", "1999" ], [ "TEARS OF THE BLACK TIGER", "has_genre", "ROMANCE" ], [ "TEARS OF THE BLACK TIGER", "has_tags", "WESTERN" ], [ "THE BELLS", "release_year", "1926" ], [ "THE BELLS", "starred_actors", "LIONEL BARRYMORE" ], [ "THE TEMPTRESS", "release_year", "1926" ], [ "THE TEMPTRESS", "starred_actors", "LIONEL BARRYMORE" ], [ "THE VIRGINIAN", "has_genre", "ROMANCE" ], [ "THE VIRGINIAN", "has_genre", "WESTERN" ], [ "THE WINNING OF BARBARA WORTH", "has_genre", "WESTERN" ], [ "THE WINNING OF BARBARA WORTH", "release_year", "1926" ], [ "TRIPPIN'", "release_year", "1999" ], [ "TRIPPIN'", "starred_actors", "MAIA CAMPBELL" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 4608, CLASS 19379, CRUEL INTENTIONS 2 36212, DRAMA 33112, ROGER KUMBLE 8673, THE TURIN HORSE src, edge_attr, dst 4608, has_genre, 36212 19379, directed_by, 33112 19379, has_genre, 36212 19379, written_by, 33112 8673, has_genre, 36212 Question: For what reason are CLASS, ROGER KUMBLE, and THE TURIN HORSE associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CLASS", "ROGER KUMBLE", "THE TURIN HORSE" ], "valid_edges": [ [ "CLASS", "has_genre", "DRAMA" ], [ "CRUEL INTENTIONS 2", "directed_by", "ROGER KUMBLE" ], [ "CRUEL INTENTIONS 2", "has_genre", "DRAMA" ], [ "CRUEL INTENTIONS 2", "written_by", "ROGER KUMBLE" ], [ "THE TURIN HORSE", "has_genre", "DRAMA" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 22772, 1961 17315, 2007 8265, ALDO GIUFFRÈ 944, BRIDGE TO THE SUN 22600, JUDGMENT AT NUREMBERG 20807, NICHOLAS BRENDON 17275, THE FOUR DAYS OF NAPLES 39789, THE LAST TIME I SAW ARCHIE 27987, UNHOLY 22214, WAR src, edge_attr, dst 944, has_genre, 22214 944, release_year, 22772 22600, has_genre, 22214 22600, has_tags, 22214 22600, release_year, 22772 17275, has_genre, 22214 17275, starred_actors, 8265 39789, has_genre, 22214 39789, release_year, 22772 27987, release_year, 17315 27987, starred_actors, 20807 22214, release_year, 17315 Question: In what context are ALDO GIUFFRÈ, BRIDGE TO THE SUN, and NICHOLAS BRENDON connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ALDO GIUFFRÈ", "BRIDGE TO THE SUN", "NICHOLAS BRENDON" ], "valid_edges": [ [ "BRIDGE TO THE SUN", "has_genre", "WAR" ], [ "BRIDGE TO THE SUN", "release_year", "1961" ], [ "JUDGMENT AT NUREMBERG", "has_genre", "WAR" ], [ "JUDGMENT AT NUREMBERG", "has_tags", "WAR" ], [ "JUDGMENT AT NUREMBERG", "release_year", "1961" ], [ "THE FOUR DAYS OF NAPLES", "has_genre", "WAR" ], [ "THE FOUR DAYS OF NAPLES", "starred_actors", "ALDO GIUFFRÈ" ], [ "THE LAST TIME I SAW ARCHIE", "has_genre", "WAR" ], [ "THE LAST TIME I SAW ARCHIE", "release_year", "1961" ], [ "UNHOLY", "release_year", "2007" ], [ "UNHOLY", "starred_actors", "NICHOLAS BRENDON" ], [ "WAR", "release_year", "2007" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27810, 1968 7841, 1987 9589, BLUE 9585, CORRUPTION 36953, DORIS DAY 31444, KARL MALDEN 24089, NUTS 35865, ON THE WATERFRONT 10317, RON LINK 35453, WHERE WERE YOU WHEN THE LIGHTS WENT OUT? 3600, WITH SIX YOU GET EGGROLL 16941, ZOMBIE HIGH src, edge_attr, dst 9589, release_year, 27810 9589, starred_actors, 31444 9585, release_year, 27810 24089, release_year, 7841 24089, starred_actors, 31444 35865, has_tags, 9585 35865, has_tags, 31444 35865, starred_actors, 31444 35453, release_year, 27810 35453, starred_actors, 36953 3600, release_year, 27810 3600, starred_actors, 36953 16941, directed_by, 10317 16941, release_year, 7841 Question: For what reason are KARL MALDEN, RON LINK, and WHERE WERE YOU WHEN THE LIGHTS WENT OUT? associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "KARL MALDEN", "RON LINK", "WHERE WERE YOU WHEN THE LIGHTS WENT OUT?" ], "valid_edges": [ [ "BLUE", "release_year", "1968" ], [ "BLUE", "starred_actors", "KARL MALDEN" ], [ "CORRUPTION", "release_year", "1968" ], [ "NUTS", "release_year", "1987" ], [ "NUTS", "starred_actors", "KARL MALDEN" ], [ "ON THE WATERFRONT", "has_tags", "CORRUPTION" ], [ "ON THE WATERFRONT", "has_tags", "KARL MALDEN" ], [ "ON THE WATERFRONT", "starred_actors", "KARL MALDEN" ], [ "WHERE WERE YOU WHEN THE LIGHTS WENT OUT?", "release_year", "1968" ], [ "WHERE WERE YOU WHEN THE LIGHTS WENT OUT?", "starred_actors", "DORIS DAY" ], [ "WITH SIX YOU GET EGGROLL", "release_year", "1968" ], [ "WITH SIX YOU GET EGGROLL", "starred_actors", "DORIS DAY" ], [ "ZOMBIE HIGH", "directed_by", "RON LINK" ], [ "ZOMBIE HIGH", "release_year", "1987" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6238, A BRIEF HISTORY OF TIME 12841, DOCUMENTARY 13596, ERROL MORRIS 21005, FOR THE BIBLE TELLS ME SO 24544, GENE ROBINSON 9975, JEFFREY FRIEDMAN 37499, PARAGRAPH 175 21801, ROB EPSTEIN 24948, THE CELLULOID CLOSET 11160, THE THIN BLUE LINE 38742, THE UNKNOWN KNOWN src, edge_attr, dst 6238, directed_by, 13596 6238, has_genre, 12841 6238, has_tags, 13596 21005, has_genre, 12841 21005, has_tags, 12841 21005, starred_actors, 24544 37499, directed_by, 9975 37499, directed_by, 21801 37499, has_genre, 12841 24948, directed_by, 9975 24948, directed_by, 21801 24948, has_genre, 12841 24948, has_tags, 12841 24948, has_tags, 21801 24948, written_by, 9975 24948, written_by, 21801 11160, directed_by, 13596 11160, has_genre, 12841 11160, has_tags, 13596 11160, written_by, 13596 38742, directed_by, 13596 38742, has_genre, 12841 38742, starred_actors, 13596 38742, written_by, 13596 Question: For what reason are ERROL MORRIS, GENE ROBINSON, and JEFFREY FRIEDMAN associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ERROL MORRIS", "GENE ROBINSON", "JEFFREY FRIEDMAN" ], "valid_edges": [ [ "A BRIEF HISTORY OF TIME", "directed_by", "ERROL MORRIS" ], [ "A BRIEF HISTORY OF TIME", "has_genre", "DOCUMENTARY" ], [ "A BRIEF HISTORY OF TIME", "has_tags", "ERROL MORRIS" ], [ "FOR THE BIBLE TELLS ME SO", "has_genre", "DOCUMENTARY" ], [ "FOR THE BIBLE TELLS ME SO", "has_tags", "DOCUMENTARY" ], [ "FOR THE BIBLE TELLS ME SO", "starred_actors", "GENE ROBINSON" ], [ "PARAGRAPH 175", "directed_by", "JEFFREY FRIEDMAN" ], [ "PARAGRAPH 175", "directed_by", "ROB EPSTEIN" ], [ "PARAGRAPH 175", "has_genre", "DOCUMENTARY" ], [ "THE CELLULOID CLOSET", "directed_by", "JEFFREY FRIEDMAN" ], [ "THE CELLULOID CLOSET", "directed_by", "ROB EPSTEIN" ], [ "THE CELLULOID CLOSET", "has_genre", "DOCUMENTARY" ], [ "THE CELLULOID CLOSET", "has_tags", "DOCUMENTARY" ], [ "THE CELLULOID CLOSET", "has_tags", "ROB EPSTEIN" ], [ "THE CELLULOID CLOSET", "written_by", "JEFFREY FRIEDMAN" ], [ "THE CELLULOID CLOSET", "written_by", "ROB EPSTEIN" ], [ "THE THIN BLUE LINE", "directed_by", "ERROL MORRIS" ], [ "THE THIN BLUE LINE", "has_genre", "DOCUMENTARY" ], [ "THE THIN BLUE LINE", "has_tags", "ERROL MORRIS" ], [ "THE THIN BLUE LINE", "written_by", "ERROL MORRIS" ], [ "THE UNKNOWN KNOWN", "directed_by", "ERROL MORRIS" ], [ "THE UNKNOWN KNOWN", "has_genre", "DOCUMENTARY" ], [ "THE UNKNOWN KNOWN", "starred_actors", "ERROL MORRIS" ], [ "THE UNKNOWN KNOWN", "written_by", "ERROL MORRIS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 14259, 1997 36580, BARRY GIFFORD 15936, DAVID LYNCH 28252, DISTANT DRUMS 278, FORTRESS 37809, LORYN LOCKLIN 398, LOST HIGHWAY 24811, THRILLER 36026, WESTERN 18038, WILD AT HEART src, edge_attr, dst 28252, has_genre, 36026 278, has_genre, 24811 278, starred_actors, 37809 398, directed_by, 15936 398, has_genre, 24811 398, has_tags, 15936 398, release_year, 14259 398, written_by, 36580 398, written_by, 15936 36026, release_year, 14259 18038, directed_by, 15936 18038, has_genre, 24811 18038, has_tags, 15936 18038, written_by, 36580 18038, written_by, 15936 Question: How are BARRY GIFFORD, DISTANT DRUMS, and LORYN LOCKLIN related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BARRY GIFFORD", "DISTANT DRUMS", "LORYN LOCKLIN" ], "valid_edges": [ [ "DISTANT DRUMS", "has_genre", "WESTERN" ], [ "FORTRESS", "has_genre", "THRILLER" ], [ "FORTRESS", "starred_actors", "LORYN LOCKLIN" ], [ "LOST HIGHWAY", "directed_by", "DAVID LYNCH" ], [ "LOST HIGHWAY", "has_genre", "THRILLER" ], [ "LOST HIGHWAY", "has_tags", "DAVID LYNCH" ], [ "LOST HIGHWAY", "release_year", "1997" ], [ "LOST HIGHWAY", "written_by", "BARRY GIFFORD" ], [ "LOST HIGHWAY", "written_by", "DAVID LYNCH" ], [ "WESTERN", "release_year", "1997" ], [ "WILD AT HEART", "directed_by", "DAVID LYNCH" ], [ "WILD AT HEART", "has_genre", "THRILLER" ], [ "WILD AT HEART", "has_tags", "DAVID LYNCH" ], [ "WILD AT HEART", "written_by", "BARRY GIFFORD" ], [ "WILD AT HEART", "written_by", "DAVID LYNCH" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 724, 1979 6405, APOCALYPSE NOW 32828, BADLANDS 11298, BOLIVIA 35953, BUTCH CASSIDY AND THE SUNDANCE KID 6267, MARTIN SHEEN 37497, NATIONAL FILM REGISTRY 17018, WILLIAM RICHERT 1934, WINTER KILLS src, edge_attr, dst 6405, has_tags, 6267 6405, has_tags, 37497 6405, release_year, 724 6405, starred_actors, 6267 32828, has_tags, 6267 32828, has_tags, 37497 32828, starred_actors, 6267 35953, has_tags, 11298 35953, has_tags, 37497 1934, directed_by, 17018 1934, release_year, 724 1934, written_by, 17018 Question: In what context are BOLIVIA, MARTIN SHEEN, and WILLIAM RICHERT connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BOLIVIA", "MARTIN SHEEN", "WILLIAM RICHERT" ], "valid_edges": [ [ "APOCALYPSE NOW", "has_tags", "MARTIN SHEEN" ], [ "APOCALYPSE NOW", "has_tags", "NATIONAL FILM REGISTRY" ], [ "APOCALYPSE NOW", "release_year", "1979" ], [ "APOCALYPSE NOW", "starred_actors", "MARTIN SHEEN" ], [ "BADLANDS", "has_tags", "MARTIN SHEEN" ], [ "BADLANDS", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BADLANDS", "starred_actors", "MARTIN SHEEN" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "BOLIVIA" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "NATIONAL FILM REGISTRY" ], [ "WINTER KILLS", "directed_by", "WILLIAM RICHERT" ], [ "WINTER KILLS", "release_year", "1979" ], [ "WINTER KILLS", "written_by", "WILLIAM RICHERT" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27810, 1968 17315, 2007 14403, BATTLE FOR TERRA 9790, BLAKE EDWARDS 5241, DARLING LILI 5038, FINIAN'S RAINBOW 29924, FRED ASTAIRE 16002, FRED SAIDY 18638, INSPECTOR CLOUSEAU 30818, JACK LEMMON 16406, JULIE ANDREWS 24593, MUSICAL 8397, MY SISTER EILEEN 35298, OPERATION MAD BALL 33297, OPERATION PETTICOAT 36805, RICHARD QUINE 18254, THE NOTORIOUS LANDLADY 929, THE PARTY 32562, VICTOR VICTORIA 22214, WAR src, edge_attr, dst 14403, release_year, 17315 5241, directed_by, 9790 5241, has_genre, 24593 5241, starred_actors, 16406 5241, written_by, 9790 5038, has_genre, 24593 5038, has_tags, 29924 5038, has_tags, 24593 5038, release_year, 27810 5038, starred_actors, 29924 5038, written_by, 16002 18638, release_year, 27810 18638, written_by, 9790 8397, directed_by, 36805 8397, has_genre, 24593 8397, starred_actors, 30818 8397, written_by, 9790 8397, written_by, 36805 35298, directed_by, 36805 35298, has_genre, 22214 35298, starred_actors, 30818 35298, written_by, 9790 33297, directed_by, 9790 33297, has_genre, 22214 33297, has_tags, 9790 18254, directed_by, 36805 18254, has_tags, 30818 18254, starred_actors, 29924 18254, starred_actors, 30818 18254, written_by, 9790 929, directed_by, 9790 929, has_tags, 9790 929, release_year, 27810 929, written_by, 9790 32562, directed_by, 9790 32562, has_genre, 24593 32562, has_tags, 9790 32562, has_tags, 16406 32562, starred_actors, 16406 32562, written_by, 9790 22214, release_year, 17315 Question: For what reason are BATTLE FOR TERRA, BLAKE EDWARDS, and FRED SAIDY associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BATTLE FOR TERRA", "BLAKE EDWARDS", "FRED SAIDY" ], "valid_edges": [ [ "BATTLE FOR TERRA", "release_year", "2007" ], [ "DARLING LILI", "directed_by", "BLAKE EDWARDS" ], [ "DARLING LILI", "has_genre", "MUSICAL" ], [ "DARLING LILI", "starred_actors", "JULIE ANDREWS" ], [ "DARLING LILI", "written_by", "BLAKE EDWARDS" ], [ "FINIAN'S RAINBOW", "has_genre", "MUSICAL" ], [ "FINIAN'S RAINBOW", "has_tags", "FRED ASTAIRE" ], [ "FINIAN'S RAINBOW", "has_tags", "MUSICAL" ], [ "FINIAN'S RAINBOW", "release_year", "1968" ], [ "FINIAN'S RAINBOW", "starred_actors", "FRED ASTAIRE" ], [ "FINIAN'S RAINBOW", "written_by", "FRED SAIDY" ], [ "INSPECTOR CLOUSEAU", "release_year", "1968" ], [ "INSPECTOR CLOUSEAU", "written_by", "BLAKE EDWARDS" ], [ "MY SISTER EILEEN", "directed_by", "RICHARD QUINE" ], [ "MY SISTER EILEEN", "has_genre", "MUSICAL" ], [ "MY SISTER EILEEN", "starred_actors", "JACK LEMMON" ], [ "MY SISTER EILEEN", "written_by", "BLAKE EDWARDS" ], [ "MY SISTER EILEEN", "written_by", "RICHARD QUINE" ], [ "OPERATION MAD BALL", "directed_by", "RICHARD QUINE" ], [ "OPERATION MAD BALL", "has_genre", "WAR" ], [ "OPERATION MAD BALL", "starred_actors", "JACK LEMMON" ], [ "OPERATION MAD BALL", "written_by", "BLAKE EDWARDS" ], [ "OPERATION PETTICOAT", "directed_by", "BLAKE EDWARDS" ], [ "OPERATION PETTICOAT", "has_genre", "WAR" ], [ "OPERATION PETTICOAT", "has_tags", "BLAKE EDWARDS" ], [ "THE NOTORIOUS LANDLADY", "directed_by", "RICHARD QUINE" ], [ "THE NOTORIOUS LANDLADY", "has_tags", "JACK LEMMON" ], [ "THE NOTORIOUS LANDLADY", "starred_actors", "FRED ASTAIRE" ], [ "THE NOTORIOUS LANDLADY", "starred_actors", "JACK LEMMON" ], [ "THE NOTORIOUS LANDLADY", "written_by", "BLAKE EDWARDS" ], [ "THE PARTY", "directed_by", "BLAKE EDWARDS" ], [ "THE PARTY", "has_tags", "BLAKE EDWARDS" ], [ "THE PARTY", "release_year", "1968" ], [ "THE PARTY", "written_by", "BLAKE EDWARDS" ], [ "VICTOR VICTORIA", "directed_by", "BLAKE EDWARDS" ], [ "VICTOR VICTORIA", "has_genre", "MUSICAL" ], [ "VICTOR VICTORIA", "has_tags", "BLAKE EDWARDS" ], [ "VICTOR VICTORIA", "has_tags", "JULIE ANDREWS" ], [ "VICTOR VICTORIA", "starred_actors", "JULIE ANDREWS" ], [ "VICTOR VICTORIA", "written_by", "BLAKE EDWARDS" ], [ "WAR", "release_year", "2007" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 25717, 1953 16580, BRINGING DOWN THE HOUSE 28076, DIANE KEATON 32694, DON TAYLOR 38250, FATHER OF THE BRIDE 29397, LÁSZLÓ KARDOS 16378, MAD MONEY 13199, QUEEN LATIFAH 7122, SMALL TOWN GIRL 21196, STALAG 17 24849, STEVE MARTIN src, edge_attr, dst 16580, starred_actors, 13199 16580, starred_actors, 24849 38250, has_tags, 24849 38250, starred_actors, 28076 38250, starred_actors, 32694 38250, starred_actors, 24849 16378, has_tags, 28076 16378, has_tags, 13199 16378, starred_actors, 28076 7122, directed_by, 29397 7122, release_year, 25717 21196, release_year, 25717 21196, starred_actors, 32694 Question: In what context are DON TAYLOR, LÁSZLÓ KARDOS, and QUEEN LATIFAH connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DON TAYLOR", "LÁSZLÓ KARDOS", "QUEEN LATIFAH" ], "valid_edges": [ [ "BRINGING DOWN THE HOUSE", "starred_actors", "QUEEN LATIFAH" ], [ "BRINGING DOWN THE HOUSE", "starred_actors", "STEVE MARTIN" ], [ "FATHER OF THE BRIDE", "has_tags", "STEVE MARTIN" ], [ "FATHER OF THE BRIDE", "starred_actors", "DIANE KEATON" ], [ "FATHER OF THE BRIDE", "starred_actors", "DON TAYLOR" ], [ "FATHER OF THE BRIDE", "starred_actors", "STEVE MARTIN" ], [ "MAD MONEY", "has_tags", "DIANE KEATON" ], [ "MAD MONEY", "has_tags", "QUEEN LATIFAH" ], [ "MAD MONEY", "starred_actors", "DIANE KEATON" ], [ "SMALL TOWN GIRL", "directed_by", "LÁSZLÓ KARDOS" ], [ "SMALL TOWN GIRL", "release_year", "1953" ], [ "STALAG 17", "release_year", "1953" ], [ "STALAG 17", "starred_actors", "DON TAYLOR" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 14259, 1997 24331, DAVID CHUNG 1580, JOHN WESLEY HARDIN 18456, THE BALLAD OF LITTLE JO 15059, THE LAWLESS BREED 4814, WARRIORS OF VIRTUE 36026, WESTERN src, edge_attr, dst 18456, has_genre, 36026 18456, starred_actors, 24331 15059, has_genre, 36026 15059, written_by, 1580 4814, release_year, 14259 36026, release_year, 14259 Question: How are DAVID CHUNG, JOHN WESLEY HARDIN, and WARRIORS OF VIRTUE related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DAVID CHUNG", "JOHN WESLEY HARDIN", "WARRIORS OF VIRTUE" ], "valid_edges": [ [ "THE BALLAD OF LITTLE JO", "has_genre", "WESTERN" ], [ "THE BALLAD OF LITTLE JO", "starred_actors", "DAVID CHUNG" ], [ "THE LAWLESS BREED", "has_genre", "WESTERN" ], [ "THE LAWLESS BREED", "written_by", "JOHN WESLEY HARDIN" ], [ "WARRIORS OF VIRTUE", "release_year", "1997" ], [ "WESTERN", "release_year", "1997" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17480, 1988 3471, A HANDFUL OF DUST 26728, ALIEN NATION 20999, ALONG CAME A SPIDER 25660, BULLETPROOF 31878, CLEAN AND SOBER 5743, DAMON WAYANS 18349, EARTH GIRLS ARE EASY 1038, JAMES CAAN 26861, MORGAN FREEMAN src, edge_attr, dst 3471, release_year, 17480 26728, release_year, 17480 26728, starred_actors, 1038 20999, has_tags, 26861 20999, starred_actors, 26861 25660, starred_actors, 5743 25660, starred_actors, 1038 31878, has_tags, 26861 31878, release_year, 17480 31878, starred_actors, 26861 18349, release_year, 17480 18349, starred_actors, 5743 Question: In what context are A HANDFUL OF DUST, ALONG CAME A SPIDER, and BULLETPROOF connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "A HANDFUL OF DUST", "ALONG CAME A SPIDER", "BULLETPROOF" ], "valid_edges": [ [ "A HANDFUL OF DUST", "release_year", "1988" ], [ "ALIEN NATION", "release_year", "1988" ], [ "ALIEN NATION", "starred_actors", "JAMES CAAN" ], [ "ALONG CAME A SPIDER", "has_tags", "MORGAN FREEMAN" ], [ "ALONG CAME A SPIDER", "starred_actors", "MORGAN FREEMAN" ], [ "BULLETPROOF", "starred_actors", "DAMON WAYANS" ], [ "BULLETPROOF", "starred_actors", "JAMES CAAN" ], [ "CLEAN AND SOBER", "has_tags", "MORGAN FREEMAN" ], [ "CLEAN AND SOBER", "release_year", "1988" ], [ "CLEAN AND SOBER", "starred_actors", "MORGAN FREEMAN" ], [ "EARTH GIRLS ARE EASY", "release_year", "1988" ], [ "EARTH GIRLS ARE EASY", "starred_actors", "DAMON WAYANS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3863, 1962 9367, BETTE DAVIS 5189, CAPE FEAR 6158, EDGAR ALLAN POE 26688, ERNESTO GASTALDI 3400, GAMBLING CITY 29624, MADAME SIN 29026, PSYCHOLOGICAL THRILLER 16724, ROBERT ALDRICH 1890, SERGIO MARTINO 11790, SODOM AND GOMORRAH 26202, TALES OF TERROR 17058, THE HORRIBLE DR. HICHCOCK 28071, WHAT EVER HAPPENED TO BABY JANE? 3151, YOUR VICE IS A LOCKED ROOM AND ONLY I HAVE THE KEY src, edge_attr, dst 5189, has_tags, 29026 5189, release_year, 3863 3400, directed_by, 1890 3400, written_by, 26688 3400, written_by, 1890 29624, starred_actors, 9367 11790, directed_by, 16724 11790, release_year, 3863 26202, has_tags, 6158 26202, release_year, 3863 26202, written_by, 6158 17058, release_year, 3863 17058, written_by, 26688 28071, directed_by, 16724 28071, has_tags, 9367 28071, has_tags, 29026 28071, has_tags, 16724 28071, release_year, 3863 28071, starred_actors, 9367 3151, directed_by, 1890 3151, written_by, 6158 Question: In what context are 1962, MADAME SIN, and SERGIO MARTINO connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "1962", "MADAME SIN", "SERGIO MARTINO" ], "valid_edges": [ [ "CAPE FEAR", "has_tags", "PSYCHOLOGICAL THRILLER" ], [ "CAPE FEAR", "release_year", "1962" ], [ "GAMBLING CITY", "directed_by", "SERGIO MARTINO" ], [ "GAMBLING CITY", "written_by", "ERNESTO GASTALDI" ], [ "GAMBLING CITY", "written_by", "SERGIO MARTINO" ], [ "MADAME SIN", "starred_actors", "BETTE DAVIS" ], [ "SODOM AND GOMORRAH", "directed_by", "ROBERT ALDRICH" ], [ "SODOM AND GOMORRAH", "release_year", "1962" ], [ "TALES OF TERROR", "has_tags", "EDGAR ALLAN POE" ], [ "TALES OF TERROR", "release_year", "1962" ], [ "TALES OF TERROR", "written_by", "EDGAR ALLAN POE" ], [ "THE HORRIBLE DR. HICHCOCK", "release_year", "1962" ], [ "THE HORRIBLE DR. HICHCOCK", "written_by", "ERNESTO GASTALDI" ], [ "WHAT EVER HAPPENED TO BABY JANE?", "directed_by", "ROBERT ALDRICH" ], [ "WHAT EVER HAPPENED TO BABY JANE?", "has_tags", "BETTE DAVIS" ], [ "WHAT EVER HAPPENED TO BABY JANE?", "has_tags", "PSYCHOLOGICAL THRILLER" ], [ "WHAT EVER HAPPENED TO BABY JANE?", "has_tags", "ROBERT ALDRICH" ], [ "WHAT EVER HAPPENED TO BABY JANE?", "release_year", "1962" ], [ "WHAT EVER HAPPENED TO BABY JANE?", "starred_actors", "BETTE DAVIS" ], [ "YOUR VICE IS A LOCKED ROOM AND ONLY I HAVE THE KEY", "directed_by", "SERGIO MARTINO" ], [ "YOUR VICE IS A LOCKED ROOM AND ONLY I HAVE THE KEY", "written_by", "EDGAR ALLAN POE" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1430, 1949 39045, ALFRED HITCHCOCK 36458, ALLAN DWAN 6610, DESTINATION TOKYO 19427, JAMES BRIDIE 28476, MURDER 23006, SANDS OF IWO JIMA 5482, THE PARADINE CASE 164, UNDER CAPRICORN 22214, WAR src, edge_attr, dst 6610, has_genre, 22214 23006, directed_by, 36458 23006, has_genre, 22214 23006, has_tags, 36458 23006, release_year, 1430 5482, directed_by, 39045 5482, has_tags, 28476 5482, written_by, 19427 164, directed_by, 39045 164, release_year, 1430 164, written_by, 19427 22214, has_tags, 28476 Question: In what context are ALLAN DWAN, DESTINATION TOKYO, and JAMES BRIDIE connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ALLAN DWAN", "DESTINATION TOKYO", "JAMES BRIDIE" ], "valid_edges": [ [ "DESTINATION TOKYO", "has_genre", "WAR" ], [ "SANDS OF IWO JIMA", "directed_by", "ALLAN DWAN" ], [ "SANDS OF IWO JIMA", "has_genre", "WAR" ], [ "SANDS OF IWO JIMA", "has_tags", "ALLAN DWAN" ], [ "SANDS OF IWO JIMA", "release_year", "1949" ], [ "THE PARADINE CASE", "directed_by", "ALFRED HITCHCOCK" ], [ "THE PARADINE CASE", "has_tags", "MURDER" ], [ "THE PARADINE CASE", "written_by", "JAMES BRIDIE" ], [ "UNDER CAPRICORN", "directed_by", "ALFRED HITCHCOCK" ], [ "UNDER CAPRICORN", "release_year", "1949" ], [ "UNDER CAPRICORN", "written_by", "JAMES BRIDIE" ], [ "WAR", "has_tags", "MURDER" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 21278, A SUMMER'S TALE 16826, DANIÈLE GÉGAUFF 16016, DIAMOND GIRL 6012, FRENCH 16465, JONATHAN CAKE 3489, MELVIL POUPAUD 1103, PLEASURE PARTY 8379, ROMANCE src, edge_attr, dst 21278, has_genre, 8379 21278, in_language, 6012 21278, starred_actors, 3489 16016, has_genre, 8379 16016, starred_actors, 16465 1103, in_language, 6012 1103, starred_actors, 16826 Question: In what context are DANIÈLE GÉGAUFF, JONATHAN CAKE, and MELVIL POUPAUD connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DANIÈLE GÉGAUFF", "JONATHAN CAKE", "MELVIL POUPAUD" ], "valid_edges": [ [ "A SUMMER'S TALE", "has_genre", "ROMANCE" ], [ "A SUMMER'S TALE", "in_language", "FRENCH" ], [ "A SUMMER'S TALE", "starred_actors", "MELVIL POUPAUD" ], [ "DIAMOND GIRL", "has_genre", "ROMANCE" ], [ "DIAMOND GIRL", "starred_actors", "JONATHAN CAKE" ], [ "PLEASURE PARTY", "in_language", "FRENCH" ], [ "PLEASURE PARTY", "starred_actors", "DANIÈLE GÉGAUFF" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 8486, 1999 22694, ALAN PARKER 17481, ANGELA'S ASHES 32409, JOE BREEN 35341, ORFEU 35792, ROBERT CARLYLE 4345, THE COMMITMENTS 13675, THE FULL MONTY 32164, VINICIUS DE MORAES 13642, WORKING CLASS src, edge_attr, dst 17481, directed_by, 22694 17481, has_tags, 22694 17481, release_year, 8486 17481, starred_actors, 32409 17481, starred_actors, 35792 17481, written_by, 22694 35341, release_year, 8486 35341, written_by, 32164 4345, directed_by, 22694 4345, has_tags, 22694 4345, has_tags, 13642 13675, has_tags, 35792 13675, has_tags, 13642 13675, starred_actors, 35792 Question: How are JOE BREEN, VINICIUS DE MORAES, and WORKING CLASS related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JOE BREEN", "VINICIUS DE MORAES", "WORKING CLASS" ], "valid_edges": [ [ "ANGELA'S ASHES", "directed_by", "ALAN PARKER" ], [ "ANGELA'S ASHES", "has_tags", "ALAN PARKER" ], [ "ANGELA'S ASHES", "release_year", "1999" ], [ "ANGELA'S ASHES", "starred_actors", "JOE BREEN" ], [ "ANGELA'S ASHES", "starred_actors", "ROBERT CARLYLE" ], [ "ANGELA'S ASHES", "written_by", "ALAN PARKER" ], [ "ORFEU", "release_year", "1999" ], [ "ORFEU", "written_by", "VINICIUS DE MORAES" ], [ "THE COMMITMENTS", "directed_by", "ALAN PARKER" ], [ "THE COMMITMENTS", "has_tags", "ALAN PARKER" ], [ "THE COMMITMENTS", "has_tags", "WORKING CLASS" ], [ "THE FULL MONTY", "has_tags", "ROBERT CARLYLE" ], [ "THE FULL MONTY", "has_tags", "WORKING CLASS" ], [ "THE FULL MONTY", "starred_actors", "ROBERT CARLYLE" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10349, CHICAGO 36212, DRAMA 34569, FRANK URSON 35421, GO FISH 22945, HIGH FIDELITY 3972, IN OLD CHICAGO 20283, MEAN CREEK 8552, MEDIUM COOL 1409, MOE HOWARD 22845, MUSIC 1372, RETURN TO ME 15995, ROCKIN' IN THE ROCKIES 39016, STOLEN SUMMER 32295, THE DILEMMA src, edge_attr, dst 10349, directed_by, 34569 10349, has_genre, 36212 10349, has_tags, 10349 10349, has_tags, 22845 35421, has_genre, 36212 35421, has_tags, 10349 22945, has_genre, 36212 22945, has_tags, 10349 22945, has_tags, 36212 3972, has_genre, 36212 3972, has_tags, 10349 20283, has_genre, 36212 20283, has_tags, 36212 8552, has_genre, 36212 8552, has_tags, 10349 1372, has_genre, 36212 1372, has_tags, 10349 15995, has_genre, 22845 15995, starred_actors, 1409 39016, has_genre, 36212 39016, has_tags, 10349 32295, has_genre, 36212 32295, has_tags, 10349 Question: For what reason are FRANK URSON, MEAN CREEK, and MOE HOWARD associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "FRANK URSON", "MEAN CREEK", "MOE HOWARD" ], "valid_edges": [ [ "CHICAGO", "directed_by", "FRANK URSON" ], [ "CHICAGO", "has_genre", "DRAMA" ], [ "CHICAGO", "has_tags", "CHICAGO" ], [ "CHICAGO", "has_tags", "MUSIC" ], [ "GO FISH", "has_genre", "DRAMA" ], [ "GO FISH", "has_tags", "CHICAGO" ], [ "HIGH FIDELITY", "has_genre", "DRAMA" ], [ "HIGH FIDELITY", "has_tags", "CHICAGO" ], [ "HIGH FIDELITY", "has_tags", "DRAMA" ], [ "IN OLD CHICAGO", "has_genre", "DRAMA" ], [ "IN OLD CHICAGO", "has_tags", "CHICAGO" ], [ "MEAN CREEK", "has_genre", "DRAMA" ], [ "MEAN CREEK", "has_tags", "DRAMA" ], [ "MEDIUM COOL", "has_genre", "DRAMA" ], [ "MEDIUM COOL", "has_tags", "CHICAGO" ], [ "RETURN TO ME", "has_genre", "DRAMA" ], [ "RETURN TO ME", "has_tags", "CHICAGO" ], [ "ROCKIN' IN THE ROCKIES", "has_genre", "MUSIC" ], [ "ROCKIN' IN THE ROCKIES", "starred_actors", "MOE HOWARD" ], [ "STOLEN SUMMER", "has_genre", "DRAMA" ], [ "STOLEN SUMMER", "has_tags", "CHICAGO" ], [ "THE DILEMMA", "has_genre", "DRAMA" ], [ "THE DILEMMA", "has_tags", "CHICAGO" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27816, BANANAS 32479, BEWITCHED 30330, CLEAVANT DERRICKS 30463, COMEDY 38118, MOSCOW ON THE HUDSON 9271, OFF BEAT src, edge_attr, dst 27816, has_genre, 30463 27816, has_tags, 30463 32479, has_genre, 30463 32479, has_tags, 30463 38118, has_genre, 30463 38118, starred_actors, 30330 9271, has_genre, 30463 9271, starred_actors, 30330 Question: How are BANANAS, BEWITCHED, and CLEAVANT DERRICKS related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BANANAS", "BEWITCHED", "CLEAVANT DERRICKS" ], "valid_edges": [ [ "BANANAS", "has_genre", "COMEDY" ], [ "BANANAS", "has_tags", "COMEDY" ], [ "BEWITCHED", "has_genre", "COMEDY" ], [ "BEWITCHED", "has_tags", "COMEDY" ], [ "MOSCOW ON THE HUDSON", "has_genre", "COMEDY" ], [ "MOSCOW ON THE HUDSON", "starred_actors", "CLEAVANT DERRICKS" ], [ "OFF BEAT", "has_genre", "COMEDY" ], [ "OFF BEAT", "starred_actors", "CLEAVANT DERRICKS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 2779, A PROPHET 4763, ADVENTURE 7373, DALE VAN EVERY 36212, DRAMA 6012, FRENCH 23711, JACQUES AUDIARD 39185, NORTH WEST FRONTIER 6593, ROBIN ESTRIDGE 30316, RUST AND BONE 3627, THE TALK OF THE TOWN 33295, TRADER HORN src, edge_attr, dst 2779, directed_by, 23711 2779, has_genre, 36212 2779, has_tags, 6012 2779, has_tags, 23711 2779, in_language, 6012 2779, written_by, 23711 39185, has_genre, 4763 39185, written_by, 6593 30316, directed_by, 23711 30316, has_genre, 36212 30316, has_tags, 23711 30316, in_language, 6012 30316, written_by, 23711 3627, has_genre, 36212 3627, written_by, 7373 33295, has_genre, 4763 33295, written_by, 7373 Question: How are DALE VAN EVERY, JACQUES AUDIARD, and ROBIN ESTRIDGE related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DALE VAN EVERY", "JACQUES AUDIARD", "ROBIN ESTRIDGE" ], "valid_edges": [ [ "A PROPHET", "directed_by", "JACQUES AUDIARD" ], [ "A PROPHET", "has_genre", "DRAMA" ], [ "A PROPHET", "has_tags", "FRENCH" ], [ "A PROPHET", "has_tags", "JACQUES AUDIARD" ], [ "A PROPHET", "in_language", "FRENCH" ], [ "A PROPHET", "written_by", "JACQUES AUDIARD" ], [ "NORTH WEST FRONTIER", "has_genre", "ADVENTURE" ], [ "NORTH WEST FRONTIER", "written_by", "ROBIN ESTRIDGE" ], [ "RUST AND BONE", "directed_by", "JACQUES AUDIARD" ], [ "RUST AND BONE", "has_genre", "DRAMA" ], [ "RUST AND BONE", "has_tags", "JACQUES AUDIARD" ], [ "RUST AND BONE", "in_language", "FRENCH" ], [ "RUST AND BONE", "written_by", "JACQUES AUDIARD" ], [ "THE TALK OF THE TOWN", "has_genre", "DRAMA" ], [ "THE TALK OF THE TOWN", "written_by", "DALE VAN EVERY" ], [ "TRADER HORN", "has_genre", "ADVENTURE" ], [ "TRADER HORN", "written_by", "DALE VAN EVERY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24818, 1992 4310, 24 HOUR PARTY PEOPLE 9005, 3 NINJAS 30146, A CHRISTMAS CAROL 4269, A HARD DAY'S NIGHT 31344, A LEAGUE OF THEIR OWN 29389, A MIGHTY WIND 8198, A PRAIRIE HOME COMPANION 8049, A PRIVATE FUNCTION 8837, AIRHEADS 26858, ARMY OF DARKNESS 14271, BEETHOVEN 9127, BIG GIRLS DON'T CRY... THEY GET EVEN 32193, BLAME IT ON THE BELLBOY 16023, BLUES BROTHERS 2000 19829, BOOMERANG 350, BOYS ON THE SIDE 8606, BRAIN DONORS 23319, BUFFY THE VAMPIRE SLAYER 30182, BURGLAR 33773, BÉBÉ'S KIDS 2450, CALIFORNIA SUITE 10877, CAPTAIN RON 29831, CB4 9284, CHANCES ARE 10349, CHICAGO 15721, CIAO, PROFESSORE! 12356, CLASS ACT 30463, COMEDY 10272, CONFESSIONS OF A TEENAGE DRAMA QUEEN 33111, COPPER MOUNTAIN 30836, COSI 11807, CRITTERS 4 30019, CROSSROADS 27380, DEATH BECOMES HER 18420, DOUBLE DYNAMITE 27674, EASY COME, EASY GO 10757, EDDIE 2380, EMILE ARDOLINO 9457, ENCINO MAN 31630, EVIL TOONS 3955, FINDING NORTH 5636, FOLKS! 5287, FROZEN 32553, FROZEN ASSETS 8788, FUN IN ACAPULCO 21640, GARDEN STATE 29593, GET CRAZY 19795, GET YOURSELF A COLLEGE GIRL 25033, GOING MY WAY 19871, GYPSY 20263, HAIR 9798, HAIRSPRAY 1292, HEDWIG AND THE ANGRY INCH 3829, HERO 14375, HIGH SCHOOL MUSICAL 17578, HOCUS POCUS 18546, HONEYMOON IN VEGAS 17037, HOUSE PARTY 25277, HUSBANDS AND WIVES 33279, IN BRUGES 4419, IN THE SOUP 36998, JAMES CRAIG 10109, JOSIE AND THE PUSSYCATS 16510, JOYFUL NOISE 2938, JUMPIN' JACK FLASH 5692, KATHY NAJIMY 1477, KEEPING MUM 6013, KILLING BONO 25510, KING OF BEGGARS 13704, KUFFS 18950, LADYBUGS 191, LEAVING NORMAL 8851, LITTLE SHOP OF HORRORS 24500, LITTLE SISTER 17663, MADE IN AMERICA 28518, MAGGIE SMITH 8268, MALEDETTO IL GIORNO CHE T'HO INCONTRATO 10560, MAN BITES DOG 24068, MAN TROUBLE 4561, MEMOIRS OF AN INVISIBLE MAN 34536, MISTRESS 39399, MO' MONEY 17135, MOM AND DAD SAVE THE WORLD 20003, MONSTERS, INC. 815, MR. BASEBALL 22845, MUSIC 2483, MUSIC AND LYRICS 21919, MY COUSIN VINNY 2581, MY NEW GUN 40064, MY OLD LADY 14797, O BROTHER, WHERE ART THOU? 5775, OCCULT 9638, ON OUR MERRY WAY 35308, ONE HUNDRED MEN AND A GIRL 14917, OUT ON A LIMB 16910, PARENTI SERPENTI 25678, PETER'S FRIENDS 6864, PITCH PERFECT 34602, PUNCH-DRUNK LOVE 25023, QUARTET 15214, RADIO DAYS 32180, RAT RACE 36575, RHINESTONE 30475, RIO 22107, ROCK 'N' ROLL HIGH SCHOOL 38381, ROCK STAR 901, SCHOOL OF ROCK 30519, SCOTT PILGRIM VS. THE WORLD 21512, SHERLOCK HOLMES 3358, SINGLES 8652, SISTER ACT 22068, SOUL MEN 13437, SOUND OF NOISE 4459, SPICE WORLD 17370, STAY TUNED 2033, STOP! OR MY MOM WILL SHOOT 22993, STRAIGHT TALK 1432, STRICTLY BALLROOM 37498, TENACIOUS D IN THE PICK OF DESTINY 39535, THAT THING YOU DO! 25270, THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT 23599, THE BEST EXOTIC MARIGOLD HOTEL 36928, THE BIKINI CARWASH COMPANY 26008, THE BLUES BROTHERS 13869, THE DISTINGUISHED GENTLEMAN 20929, THE FIGHTING TEMPTATIONS 27031, THE FIRST WIVES CLUB 13675, THE FULL MONTY 2656, THE GIRL CAN'T HELP IT 21831, THE GUN IN BETTY LOU'S HANDBAG 31283, THE HOUND OF THE BASKERVILLES 39978, THE HUMAN COMEDY 19226, THE MARC PEASE EXPERIENCE 24724, THE MIGHTY DUCKS 26128, THE MUPPET CHRISTMAS CAROL 11189, THE MUPPETS 24035, THE NORTHERNERS 10721, THE ROCKY HORROR PICTURE SHOW 8791, THE SECOND BEST EXOTIC MARIGOLD HOTEL 37600, THE SECRET POLICEMAN'S OTHER BALL 29027, THE TELEPHONE 31313, THE WEST POINT STORY 2281, TOYS 7279, TWIN DRAGONS 36262, UNFAITHFULLY YOURS 10376, USED PEOPLE 38839, WAYNE'S WORLD 12506, WENDY MAKKENA 20751, WHITE MEN CAN'T JUMP 37332, WHOOPI GOLDBERG src, edge_attr, dst 4310, has_genre, 30463 4310, has_tags, 22845 9005, has_genre, 30463 9005, release_year, 24818 30146, has_genre, 30463 30146, starred_actors, 37332 4269, has_genre, 30463 4269, has_genre, 22845 4269, has_tags, 30463 4269, has_tags, 22845 31344, has_genre, 30463 31344, release_year, 24818 29389, has_genre, 30463 29389, has_genre, 22845 8198, has_genre, 30463 8198, has_genre, 22845 8049, has_genre, 30463 8049, starred_actors, 28518 8837, has_genre, 30463 8837, has_genre, 22845 8837, has_tags, 30463 26858, has_genre, 30463 26858, has_tags, 30463 26858, release_year, 24818 14271, has_genre, 30463 14271, has_tags, 30463 14271, release_year, 24818 9127, has_genre, 30463 9127, release_year, 24818 32193, has_genre, 30463 32193, release_year, 24818 16023, has_genre, 30463 16023, has_tags, 22845 19829, has_genre, 30463 19829, release_year, 24818 350, has_genre, 30463 350, has_tags, 37332 350, starred_actors, 37332 8606, has_genre, 30463 8606, release_year, 24818 23319, has_genre, 30463 23319, has_tags, 30463 23319, release_year, 24818 30182, has_genre, 30463 30182, starred_actors, 37332 33773, has_genre, 30463 33773, release_year, 24818 2450, has_genre, 30463 2450, starred_actors, 28518 10877, has_genre, 30463 10877, has_tags, 30463 10877, release_year, 24818 29831, has_genre, 30463 29831, has_genre, 22845 9284, directed_by, 2380 9284, has_genre, 30463 10349, has_genre, 30463 10349, has_tags, 22845 15721, has_genre, 30463 15721, release_year, 24818 12356, has_genre, 30463 12356, release_year, 24818 10272, has_genre, 30463 10272, has_genre, 22845 10272, has_tags, 30463 33111, has_genre, 30463 33111, has_genre, 22845 30836, has_genre, 30463 30836, has_genre, 22845 11807, has_genre, 30463 11807, release_year, 24818 30019, has_genre, 30463 30019, has_genre, 22845 27380, has_genre, 30463 27380, release_year, 24818 18420, has_genre, 30463 18420, has_genre, 22845 27674, has_genre, 30463 27674, has_genre, 22845 10757, has_genre, 30463 10757, starred_actors, 37332 9457, has_genre, 30463 9457, release_year, 24818 31630, has_genre, 30463 31630, release_year, 24818 3955, has_genre, 30463 3955, starred_actors, 12506 5636, has_genre, 30463 5636, release_year, 24818 5287, has_genre, 30463 5287, has_tags, 22845 32553, has_genre, 30463 32553, release_year, 24818 8788, has_genre, 30463 8788, has_genre, 22845 21640, has_genre, 30463 21640, has_tags, 22845 29593, has_genre, 30463 29593, has_genre, 22845 19795, has_genre, 30463 19795, has_genre, 22845 25033, has_genre, 30463 25033, has_genre, 22845 19871, directed_by, 2380 19871, has_genre, 30463 20263, has_genre, 30463 20263, has_tags, 22845 9798, has_genre, 30463 9798, has_genre, 22845 9798, has_tags, 30463 1292, has_genre, 30463 1292, has_genre, 22845 1292, has_tags, 22845 3829, has_genre, 30463 3829, release_year, 24818 14375, has_genre, 30463 14375, has_tags, 22845 17578, has_genre, 30463 17578, starred_actors, 5692 18546, has_genre, 30463 18546, release_year, 24818 17037, has_genre, 30463 17037, has_genre, 22845 25277, has_genre, 30463 25277, release_year, 24818 33279, has_genre, 30463 33279, has_tags, 30463 33279, has_tags, 22845 4419, has_genre, 30463 4419, release_year, 24818 10109, has_genre, 30463 10109, has_genre, 22845 16510, has_genre, 30463 16510, has_genre, 22845 2938, has_genre, 30463 2938, has_tags, 37332 2938, starred_actors, 37332 1477, has_genre, 30463 1477, has_tags, 28518 1477, starred_actors, 28518 6013, has_genre, 30463 6013, has_genre, 22845 6013, has_tags, 22845 25510, has_genre, 30463 25510, release_year, 24818 13704, has_genre, 30463 13704, release_year, 24818 18950, has_genre, 30463 18950, release_year, 24818 191, has_genre, 30463 191, release_year, 24818 8851, has_genre, 30463 8851, has_tags, 22845 24500, has_genre, 30463 24500, release_year, 24818 17663, has_genre, 30463 17663, has_tags, 37332 17663, starred_actors, 37332 8268, has_genre, 30463 8268, release_year, 24818 10560, has_genre, 30463 10560, release_year, 24818 24068, has_genre, 30463 24068, release_year, 24818 4561, has_genre, 30463 4561, release_year, 24818 34536, has_genre, 30463 34536, release_year, 24818 39399, has_genre, 30463 39399, release_year, 24818 17135, has_genre, 30463 17135, release_year, 24818 20003, has_genre, 30463 20003, has_tags, 30463 20003, has_tags, 22845 815, has_genre, 30463 815, release_year, 24818 2483, has_genre, 30463 2483, has_genre, 22845 2483, has_tags, 30463 21919, has_genre, 30463 21919, has_tags, 30463 21919, release_year, 24818 2581, has_genre, 30463 2581, release_year, 24818 40064, has_genre, 30463 40064, starred_actors, 28518 14797, has_genre, 30463 14797, has_tags, 30463 14797, has_tags, 22845 9638, has_genre, 30463 9638, has_genre, 22845 35308, has_genre, 30463 35308, has_genre, 22845 14917, has_genre, 30463 14917, release_year, 24818 16910, has_genre, 30463 16910, release_year, 24818 25678, has_genre, 30463 25678, release_year, 24818 6864, has_genre, 30463 6864, has_genre, 22845 6864, has_tags, 22845 34602, has_genre, 30463 34602, has_tags, 30463 34602, has_tags, 22845 25023, has_genre, 30463 25023, has_tags, 30463 25023, starred_actors, 28518 15214, has_genre, 30463 15214, has_tags, 22845 32180, has_genre, 30463 32180, has_tags, 30463 32180, has_tags, 37332 36575, has_genre, 30463 36575, has_genre, 22845 30475, has_genre, 30463 30475, has_tags, 30463 30475, has_tags, 22845 22107, has_genre, 30463 22107, has_genre, 22845 38381, has_genre, 30463 38381, has_genre, 22845 901, has_genre, 30463 901, has_genre, 22845 901, has_tags, 22845 30519, has_genre, 30463 30519, has_tags, 30463 30519, has_tags, 22845 21512, has_tags, 30463 21512, has_tags, 5775 21512, has_tags, 21512 3358, has_genre, 30463 3358, release_year, 24818 8652, directed_by, 2380 8652, has_genre, 30463 8652, has_genre, 22845 8652, has_tags, 28518 8652, has_tags, 37332 8652, release_year, 24818 8652, starred_actors, 5692 8652, starred_actors, 28518 8652, starred_actors, 12506 8652, starred_actors, 37332 22068, has_genre, 30463 22068, has_genre, 22845 13437, has_genre, 30463 13437, has_genre, 22845 13437, has_tags, 22845 4459, has_genre, 30463 4459, has_genre, 22845 4459, has_tags, 22845 17370, has_genre, 30463 17370, release_year, 24818 2033, has_genre, 30463 2033, has_tags, 30463 2033, release_year, 24818 22993, has_genre, 30463 22993, release_year, 24818 1432, has_genre, 30463 1432, release_year, 24818 37498, has_genre, 30463 37498, has_genre, 22845 37498, has_tags, 30463 37498, has_tags, 22845 39535, has_genre, 30463 39535, has_genre, 22845 39535, has_tags, 22845 25270, has_genre, 30463 25270, has_genre, 22845 23599, has_genre, 30463 23599, has_tags, 28518 36928, has_genre, 30463 36928, release_year, 24818 26008, has_genre, 30463 26008, has_tags, 30463 26008, has_tags, 22845 13869, has_genre, 30463 13869, release_year, 24818 20929, has_genre, 30463 20929, has_genre, 22845 27031, has_genre, 30463 27031, starred_actors, 28518 13675, has_genre, 30463 13675, has_genre, 22845 2656, has_genre, 30463 2656, has_genre, 22845 21831, has_genre, 30463 21831, release_year, 24818 31283, has_genre, 30463 31283, has_tags, 21512 39978, has_genre, 30463 39978, starred_actors, 36998 19226, has_genre, 30463 19226, has_genre, 22845 24724, has_genre, 30463 24724, release_year, 24818 26128, has_genre, 30463 26128, release_year, 24818 11189, has_genre, 30463 11189, has_tags, 30463 11189, has_tags, 22845 24035, has_genre, 30463 24035, release_year, 24818 10721, has_genre, 30463 10721, has_tags, 22845 8791, has_genre, 30463 8791, starred_actors, 28518 37600, has_genre, 30463 37600, has_genre, 22845 29027, has_genre, 30463 29027, starred_actors, 37332 31313, has_genre, 30463 31313, has_genre, 22845 2281, has_genre, 30463 2281, has_tags, 22845 2281, release_year, 24818 7279, has_genre, 30463 7279, release_year, 24818 36262, has_genre, 30463 36262, has_genre, 22845 10376, has_genre, 30463 10376, release_year, 24818 38839, has_genre, 30463 38839, has_tags, 30463 38839, release_year, 24818 20751, has_genre, 30463 20751, has_tags, 30463 20751, release_year, 24818 Question: How are JAMES CRAIG, OCCULT, and SISTER ACT related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JAMES CRAIG", "OCCULT", "SISTER ACT" ], "valid_edges": [ [ "24 HOUR PARTY PEOPLE", "has_genre", "COMEDY" ], [ "24 HOUR PARTY PEOPLE", "has_tags", "MUSIC" ], [ "3 NINJAS", "has_genre", "COMEDY" ], [ "3 NINJAS", "release_year", "1992" ], [ "A CHRISTMAS CAROL", "has_genre", "COMEDY" ], [ "A CHRISTMAS CAROL", "starred_actors", "WHOOPI GOLDBERG" ], [ "A HARD DAY'S NIGHT", "has_genre", "COMEDY" ], [ "A HARD DAY'S NIGHT", "has_genre", "MUSIC" ], [ "A HARD DAY'S NIGHT", "has_tags", "COMEDY" ], [ "A HARD DAY'S NIGHT", "has_tags", "MUSIC" ], [ "A LEAGUE OF THEIR OWN", "has_genre", "COMEDY" ], [ "A LEAGUE OF THEIR OWN", "release_year", "1992" ], [ "A MIGHTY WIND", "has_genre", "COMEDY" ], [ "A MIGHTY WIND", "has_genre", "MUSIC" ], [ "A PRAIRIE HOME COMPANION", "has_genre", "COMEDY" ], [ "A PRAIRIE HOME COMPANION", "has_genre", "MUSIC" ], [ "A PRIVATE FUNCTION", "has_genre", "COMEDY" ], [ "A PRIVATE FUNCTION", "starred_actors", "MAGGIE SMITH" ], [ "AIRHEADS", "has_genre", "COMEDY" ], [ "AIRHEADS", "has_genre", "MUSIC" ], [ "AIRHEADS", "has_tags", "COMEDY" ], [ "ARMY OF DARKNESS", "has_genre", "COMEDY" ], [ "ARMY OF DARKNESS", "has_tags", "COMEDY" ], [ "ARMY OF DARKNESS", "release_year", "1992" ], [ "BEETHOVEN", "has_genre", "COMEDY" ], [ "BEETHOVEN", "has_tags", "COMEDY" ], [ "BEETHOVEN", "release_year", "1992" ], [ "BIG GIRLS DON'T CRY... THEY GET EVEN", "has_genre", "COMEDY" ], [ "BIG GIRLS DON'T CRY... THEY GET EVEN", "release_year", "1992" ], [ "BLAME IT ON THE BELLBOY", "has_genre", "COMEDY" ], [ "BLAME IT ON THE BELLBOY", "release_year", "1992" ], [ "BLUES BROTHERS 2000", "has_genre", "COMEDY" ], [ "BLUES BROTHERS 2000", "has_tags", "MUSIC" ], [ "BOOMERANG", "has_genre", "COMEDY" ], [ "BOOMERANG", "release_year", "1992" ], [ "BOYS ON THE SIDE", "has_genre", "COMEDY" ], [ "BOYS ON THE SIDE", "has_tags", "WHOOPI GOLDBERG" ], [ "BOYS ON THE SIDE", "starred_actors", "WHOOPI GOLDBERG" ], [ "BRAIN DONORS", "has_genre", "COMEDY" ], [ "BRAIN DONORS", "release_year", "1992" ], [ "BUFFY THE VAMPIRE SLAYER", "has_genre", "COMEDY" ], [ "BUFFY THE VAMPIRE SLAYER", "has_tags", "COMEDY" ], [ "BUFFY THE VAMPIRE SLAYER", "release_year", "1992" ], [ "BURGLAR", "has_genre", "COMEDY" ], [ "BURGLAR", "starred_actors", "WHOOPI GOLDBERG" ], [ "BÉBÉ'S KIDS", "has_genre", "COMEDY" ], [ "BÉBÉ'S KIDS", "release_year", "1992" ], [ "CALIFORNIA SUITE", "has_genre", "COMEDY" ], [ "CALIFORNIA SUITE", "starred_actors", "MAGGIE SMITH" ], [ "CAPTAIN RON", "has_genre", "COMEDY" ], [ "CAPTAIN RON", "has_tags", "COMEDY" ], [ "CAPTAIN RON", "release_year", "1992" ], [ "CB4", "has_genre", "COMEDY" ], [ "CB4", "has_genre", "MUSIC" ], [ "CHANCES ARE", "directed_by", "EMILE ARDOLINO" ], [ "CHANCES ARE", "has_genre", "COMEDY" ], [ "CHICAGO", "has_genre", "COMEDY" ], [ "CHICAGO", "has_tags", "MUSIC" ], [ "CIAO, PROFESSORE!", "has_genre", "COMEDY" ], [ "CIAO, PROFESSORE!", "release_year", "1992" ], [ "CLASS ACT", "has_genre", "COMEDY" ], [ "CLASS ACT", "release_year", "1992" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_genre", "COMEDY" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_genre", "MUSIC" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_tags", "COMEDY" ], [ "COPPER MOUNTAIN", "has_genre", "COMEDY" ], [ "COPPER MOUNTAIN", "has_genre", "MUSIC" ], [ "COSI", "has_genre", "COMEDY" ], [ "COSI", "has_genre", "MUSIC" ], [ "CRITTERS 4", "has_genre", "COMEDY" ], [ "CRITTERS 4", "release_year", "1992" ], [ "CROSSROADS", "has_genre", "COMEDY" ], [ "CROSSROADS", "has_genre", "MUSIC" ], [ "DEATH BECOMES HER", "has_genre", "COMEDY" ], [ "DEATH BECOMES HER", "release_year", "1992" ], [ "DOUBLE DYNAMITE", "has_genre", "COMEDY" ], [ "DOUBLE DYNAMITE", "has_genre", "MUSIC" ], [ "EASY COME, EASY GO", "has_genre", "COMEDY" ], [ "EASY COME, EASY GO", "has_genre", "MUSIC" ], [ "EDDIE", "has_genre", "COMEDY" ], [ "EDDIE", "starred_actors", "WHOOPI GOLDBERG" ], [ "ENCINO MAN", "has_genre", "COMEDY" ], [ "ENCINO MAN", "release_year", "1992" ], [ "EVIL TOONS", "has_genre", "COMEDY" ], [ "EVIL TOONS", "release_year", "1992" ], [ "FINDING NORTH", "has_genre", "COMEDY" ], [ "FINDING NORTH", "starred_actors", "WENDY MAKKENA" ], [ "FOLKS!", "has_genre", "COMEDY" ], [ "FOLKS!", "release_year", "1992" ], [ "FROZEN", "has_genre", "COMEDY" ], [ "FROZEN", "has_tags", "MUSIC" ], [ "FROZEN ASSETS", "has_genre", "COMEDY" ], [ "FROZEN ASSETS", "release_year", "1992" ], [ "FUN IN ACAPULCO", "has_genre", "COMEDY" ], [ "FUN IN ACAPULCO", "has_genre", "MUSIC" ], [ "GARDEN STATE", "has_genre", "COMEDY" ], [ "GARDEN STATE", "has_tags", "MUSIC" ], [ "GET CRAZY", "has_genre", "COMEDY" ], [ "GET CRAZY", "has_genre", "MUSIC" ], [ "GET YOURSELF A COLLEGE GIRL", "has_genre", "COMEDY" ], [ "GET YOURSELF A COLLEGE GIRL", "has_genre", "MUSIC" ], [ "GOING MY WAY", "has_genre", "COMEDY" ], [ "GOING MY WAY", "has_genre", "MUSIC" ], [ "GYPSY", "directed_by", "EMILE ARDOLINO" ], [ "GYPSY", "has_genre", "COMEDY" ], [ "HAIR", "has_genre", "COMEDY" ], [ "HAIR", "has_tags", "MUSIC" ], [ "HAIRSPRAY", "has_genre", "COMEDY" ], [ "HAIRSPRAY", "has_genre", "MUSIC" ], [ "HAIRSPRAY", "has_tags", "COMEDY" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "COMEDY" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "MUSIC" ], [ "HEDWIG AND THE ANGRY INCH", "has_tags", "MUSIC" ], [ "HERO", "has_genre", "COMEDY" ], [ "HERO", "release_year", "1992" ], [ "HIGH SCHOOL MUSICAL", "has_genre", "COMEDY" ], [ "HIGH SCHOOL MUSICAL", "has_tags", "MUSIC" ], [ "HOCUS POCUS", "has_genre", "COMEDY" ], [ "HOCUS POCUS", "starred_actors", "KATHY NAJIMY" ], [ "HONEYMOON IN VEGAS", "has_genre", "COMEDY" ], [ "HONEYMOON IN VEGAS", "release_year", "1992" ], [ "HOUSE PARTY", "has_genre", "COMEDY" ], [ "HOUSE PARTY", "has_genre", "MUSIC" ], [ "HUSBANDS AND WIVES", "has_genre", "COMEDY" ], [ "HUSBANDS AND WIVES", "release_year", "1992" ], [ "IN BRUGES", "has_genre", "COMEDY" ], [ "IN BRUGES", "has_tags", "COMEDY" ], [ "IN BRUGES", "has_tags", "MUSIC" ], [ "IN THE SOUP", "has_genre", "COMEDY" ], [ "IN THE SOUP", "release_year", "1992" ], [ "JOSIE AND THE PUSSYCATS", "has_genre", "COMEDY" ], [ "JOSIE AND THE PUSSYCATS", "has_genre", "MUSIC" ], [ "JOYFUL NOISE", "has_genre", "COMEDY" ], [ "JOYFUL NOISE", "has_genre", "MUSIC" ], [ "JUMPIN' JACK FLASH", "has_genre", "COMEDY" ], [ "JUMPIN' JACK FLASH", "has_tags", "WHOOPI GOLDBERG" ], [ "JUMPIN' JACK FLASH", "starred_actors", "WHOOPI GOLDBERG" ], [ "KEEPING MUM", "has_genre", "COMEDY" ], [ "KEEPING MUM", "has_tags", "MAGGIE SMITH" ], [ "KEEPING MUM", "starred_actors", "MAGGIE SMITH" ], [ "KILLING BONO", "has_genre", "COMEDY" ], [ "KILLING BONO", "has_genre", "MUSIC" ], [ "KILLING BONO", "has_tags", "MUSIC" ], [ "KING OF BEGGARS", "has_genre", "COMEDY" ], [ "KING OF BEGGARS", "release_year", "1992" ], [ "KUFFS", "has_genre", "COMEDY" ], [ "KUFFS", "release_year", "1992" ], [ "LADYBUGS", "has_genre", "COMEDY" ], [ "LADYBUGS", "release_year", "1992" ], [ "LEAVING NORMAL", "has_genre", "COMEDY" ], [ "LEAVING NORMAL", "release_year", "1992" ], [ "LITTLE SHOP OF HORRORS", "has_genre", "COMEDY" ], [ "LITTLE SHOP OF HORRORS", "has_tags", "MUSIC" ], [ "LITTLE SISTER", "has_genre", "COMEDY" ], [ "LITTLE SISTER", "release_year", "1992" ], [ "MADE IN AMERICA", "has_genre", "COMEDY" ], [ "MADE IN AMERICA", "has_tags", "WHOOPI GOLDBERG" ], [ "MADE IN AMERICA", "starred_actors", "WHOOPI GOLDBERG" ], [ "MALEDETTO IL GIORNO CHE T'HO INCONTRATO", "has_genre", "COMEDY" ], [ "MALEDETTO IL GIORNO CHE T'HO INCONTRATO", "release_year", "1992" ], [ "MAN BITES DOG", "has_genre", "COMEDY" ], [ "MAN BITES DOG", "release_year", "1992" ], [ "MAN TROUBLE", "has_genre", "COMEDY" ], [ "MAN TROUBLE", "release_year", "1992" ], [ "MEMOIRS OF AN INVISIBLE MAN", "has_genre", "COMEDY" ], [ "MEMOIRS OF AN INVISIBLE MAN", "release_year", "1992" ], [ "MISTRESS", "has_genre", "COMEDY" ], [ "MISTRESS", "release_year", "1992" ], [ "MO' MONEY", "has_genre", "COMEDY" ], [ "MO' MONEY", "release_year", "1992" ], [ "MOM AND DAD SAVE THE WORLD", "has_genre", "COMEDY" ], [ "MOM AND DAD SAVE THE WORLD", "release_year", "1992" ], [ "MONSTERS, INC.", "has_genre", "COMEDY" ], [ "MONSTERS, INC.", "has_tags", "COMEDY" ], [ "MONSTERS, INC.", "has_tags", "MUSIC" ], [ "MR. BASEBALL", "has_genre", "COMEDY" ], [ "MR. BASEBALL", "release_year", "1992" ], [ "MUSIC AND LYRICS", "has_genre", "COMEDY" ], [ "MUSIC AND LYRICS", "has_genre", "MUSIC" ], [ "MUSIC AND LYRICS", "has_tags", "COMEDY" ], [ "MY COUSIN VINNY", "has_genre", "COMEDY" ], [ "MY COUSIN VINNY", "has_tags", "COMEDY" ], [ "MY COUSIN VINNY", "release_year", "1992" ], [ "MY NEW GUN", "has_genre", "COMEDY" ], [ "MY NEW GUN", "release_year", "1992" ], [ "MY OLD LADY", "has_genre", "COMEDY" ], [ "MY OLD LADY", "starred_actors", "MAGGIE SMITH" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "COMEDY" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "COMEDY" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "MUSIC" ], [ "ON OUR MERRY WAY", "has_genre", "COMEDY" ], [ "ON OUR MERRY WAY", "has_genre", "MUSIC" ], [ "ONE HUNDRED MEN AND A GIRL", "has_genre", "COMEDY" ], [ "ONE HUNDRED MEN AND A GIRL", "has_genre", "MUSIC" ], [ "OUT ON A LIMB", "has_genre", "COMEDY" ], [ "OUT ON A LIMB", "release_year", "1992" ], [ "PARENTI SERPENTI", "has_genre", "COMEDY" ], [ "PARENTI SERPENTI", "release_year", "1992" ], [ "PETER'S FRIENDS", "has_genre", "COMEDY" ], [ "PETER'S FRIENDS", "release_year", "1992" ], [ "PITCH PERFECT", "has_genre", "COMEDY" ], [ "PITCH PERFECT", "has_genre", "MUSIC" ], [ "PITCH PERFECT", "has_tags", "MUSIC" ], [ "PUNCH-DRUNK LOVE", "has_genre", "COMEDY" ], [ "PUNCH-DRUNK LOVE", "has_tags", "COMEDY" ], [ "PUNCH-DRUNK LOVE", "has_tags", "MUSIC" ], [ "QUARTET", "has_genre", "COMEDY" ], [ "QUARTET", "has_tags", "COMEDY" ], [ "QUARTET", "starred_actors", "MAGGIE SMITH" ], [ "RADIO DAYS", "has_genre", "COMEDY" ], [ "RADIO DAYS", "has_tags", "MUSIC" ], [ "RAT RACE", "has_genre", "COMEDY" ], [ "RAT RACE", "has_tags", "COMEDY" ], [ "RAT RACE", "has_tags", "WHOOPI GOLDBERG" ], [ "RHINESTONE", "has_genre", "COMEDY" ], [ "RHINESTONE", "has_genre", "MUSIC" ], [ "RIO", "has_genre", "COMEDY" ], [ "RIO", "has_tags", "COMEDY" ], [ "RIO", "has_tags", "MUSIC" ], [ "ROCK 'N' ROLL HIGH SCHOOL", "has_genre", "COMEDY" ], [ "ROCK 'N' ROLL HIGH SCHOOL", "has_genre", "MUSIC" ], [ "ROCK STAR", "has_genre", "COMEDY" ], [ "ROCK STAR", "has_genre", "MUSIC" ], [ "SCHOOL OF ROCK", "has_genre", "COMEDY" ], [ "SCHOOL OF ROCK", "has_genre", "MUSIC" ], [ "SCHOOL OF ROCK", "has_tags", "MUSIC" ], [ "SCOTT PILGRIM VS. THE WORLD", "has_genre", "COMEDY" ], [ "SCOTT PILGRIM VS. THE WORLD", "has_tags", "COMEDY" ], [ "SCOTT PILGRIM VS. THE WORLD", "has_tags", "MUSIC" ], [ "SHERLOCK HOLMES", "has_tags", "COMEDY" ], [ "SHERLOCK HOLMES", "has_tags", "OCCULT" ], [ "SHERLOCK HOLMES", "has_tags", "SHERLOCK HOLMES" ], [ "SINGLES", "has_genre", "COMEDY" ], [ "SINGLES", "release_year", "1992" ], [ "SISTER ACT", "directed_by", "EMILE ARDOLINO" ], [ "SISTER ACT", "has_genre", "COMEDY" ], [ "SISTER ACT", "has_genre", "MUSIC" ], [ "SISTER ACT", "has_tags", "MAGGIE SMITH" ], [ "SISTER ACT", "has_tags", "WHOOPI GOLDBERG" ], [ "SISTER ACT", "release_year", "1992" ], [ "SISTER ACT", "starred_actors", "KATHY NAJIMY" ], [ "SISTER ACT", "starred_actors", "MAGGIE SMITH" ], [ "SISTER ACT", "starred_actors", "WENDY MAKKENA" ], [ "SISTER ACT", "starred_actors", "WHOOPI GOLDBERG" ], [ "SOUL MEN", "has_genre", "COMEDY" ], [ "SOUL MEN", "has_genre", "MUSIC" ], [ "SOUND OF NOISE", "has_genre", "COMEDY" ], [ "SOUND OF NOISE", "has_genre", "MUSIC" ], [ "SOUND OF NOISE", "has_tags", "MUSIC" ], [ "SPICE WORLD", "has_genre", "COMEDY" ], [ "SPICE WORLD", "has_genre", "MUSIC" ], [ "SPICE WORLD", "has_tags", "MUSIC" ], [ "STAY TUNED", "has_genre", "COMEDY" ], [ "STAY TUNED", "release_year", "1992" ], [ "STOP! OR MY MOM WILL SHOOT", "has_genre", "COMEDY" ], [ "STOP! OR MY MOM WILL SHOOT", "has_tags", "COMEDY" ], [ "STOP! OR MY MOM WILL SHOOT", "release_year", "1992" ], [ "STRAIGHT TALK", "has_genre", "COMEDY" ], [ "STRAIGHT TALK", "release_year", "1992" ], [ "STRICTLY BALLROOM", "has_genre", "COMEDY" ], [ "STRICTLY BALLROOM", "release_year", "1992" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "has_genre", "COMEDY" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "has_genre", "MUSIC" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "has_tags", "COMEDY" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "has_tags", "MUSIC" ], [ "THAT THING YOU DO!", "has_genre", "COMEDY" ], [ "THAT THING YOU DO!", "has_genre", "MUSIC" ], [ "THAT THING YOU DO!", "has_tags", "MUSIC" ], [ "THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT", "has_genre", "MUSIC" ], [ "THE BEST EXOTIC MARIGOLD HOTEL", "has_genre", "COMEDY" ], [ "THE BEST EXOTIC MARIGOLD HOTEL", "has_tags", "MAGGIE SMITH" ], [ "THE BIKINI CARWASH COMPANY", "has_genre", "COMEDY" ], [ "THE BIKINI CARWASH COMPANY", "release_year", "1992" ], [ "THE BLUES BROTHERS", "has_genre", "COMEDY" ], [ "THE BLUES BROTHERS", "has_tags", "COMEDY" ], [ "THE BLUES BROTHERS", "has_tags", "MUSIC" ], [ "THE DISTINGUISHED GENTLEMAN", "has_genre", "COMEDY" ], [ "THE DISTINGUISHED GENTLEMAN", "release_year", "1992" ], [ "THE FIGHTING TEMPTATIONS", "has_genre", "COMEDY" ], [ "THE FIGHTING TEMPTATIONS", "has_genre", "MUSIC" ], [ "THE FIRST WIVES CLUB", "has_genre", "COMEDY" ], [ "THE FIRST WIVES CLUB", "starred_actors", "MAGGIE SMITH" ], [ "THE FULL MONTY", "has_genre", "COMEDY" ], [ "THE FULL MONTY", "has_genre", "MUSIC" ], [ "THE GIRL CAN'T HELP IT", "has_genre", "COMEDY" ], [ "THE GIRL CAN'T HELP IT", "has_genre", "MUSIC" ], [ "THE GUN IN BETTY LOU'S HANDBAG", "has_genre", "COMEDY" ], [ "THE GUN IN BETTY LOU'S HANDBAG", "release_year", "1992" ], [ "THE HOUND OF THE BASKERVILLES", "has_genre", "COMEDY" ], [ "THE HOUND OF THE BASKERVILLES", "has_tags", "SHERLOCK HOLMES" ], [ "THE HUMAN COMEDY", "has_genre", "COMEDY" ], [ "THE HUMAN COMEDY", "starred_actors", "JAMES CRAIG" ], [ "THE MARC PEASE EXPERIENCE", "has_genre", "COMEDY" ], [ "THE MARC PEASE EXPERIENCE", "has_genre", "MUSIC" ], [ "THE MIGHTY DUCKS", "has_genre", "COMEDY" ], [ "THE MIGHTY DUCKS", "release_year", "1992" ], [ "THE MUPPET CHRISTMAS CAROL", "has_genre", "COMEDY" ], [ "THE MUPPET CHRISTMAS CAROL", "release_year", "1992" ], [ "THE MUPPETS", "has_genre", "COMEDY" ], [ "THE MUPPETS", "has_tags", "COMEDY" ], [ "THE MUPPETS", "has_tags", "MUSIC" ], [ "THE NORTHERNERS", "has_genre", "COMEDY" ], [ "THE NORTHERNERS", "release_year", "1992" ], [ "THE ROCKY HORROR PICTURE SHOW", "has_genre", "COMEDY" ], [ "THE ROCKY HORROR PICTURE SHOW", "has_tags", "MUSIC" ], [ "THE SECOND BEST EXOTIC MARIGOLD HOTEL", "has_genre", "COMEDY" ], [ "THE SECOND BEST EXOTIC MARIGOLD HOTEL", "starred_actors", "MAGGIE SMITH" ], [ "THE SECRET POLICEMAN'S OTHER BALL", "has_genre", "COMEDY" ], [ "THE SECRET POLICEMAN'S OTHER BALL", "has_genre", "MUSIC" ], [ "THE TELEPHONE", "has_genre", "COMEDY" ], [ "THE TELEPHONE", "starred_actors", "WHOOPI GOLDBERG" ], [ "THE WEST POINT STORY", "has_genre", "COMEDY" ], [ "THE WEST POINT STORY", "has_genre", "MUSIC" ], [ "TOYS", "has_genre", "COMEDY" ], [ "TOYS", "has_tags", "MUSIC" ], [ "TOYS", "release_year", "1992" ], [ "TWIN DRAGONS", "has_genre", "COMEDY" ], [ "TWIN DRAGONS", "release_year", "1992" ], [ "UNFAITHFULLY YOURS", "has_genre", "COMEDY" ], [ "UNFAITHFULLY YOURS", "has_genre", "MUSIC" ], [ "USED PEOPLE", "has_genre", "COMEDY" ], [ "USED PEOPLE", "release_year", "1992" ], [ "WAYNE'S WORLD", "has_genre", "COMEDY" ], [ "WAYNE'S WORLD", "has_tags", "COMEDY" ], [ "WAYNE'S WORLD", "release_year", "1992" ], [ "WHITE MEN CAN'T JUMP", "has_genre", "COMEDY" ], [ "WHITE MEN CAN'T JUMP", "has_tags", "COMEDY" ], [ "WHITE MEN CAN'T JUMP", "release_year", "1992" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 658, 2012 30665, 7 DAYS IN HAVANA 40144, CARANCHO 14724, CRIME 28900, JEREMY RENNER 8993, PABLO TRAPERO 16103, THE AVENGERS 7809, THE BIG HEAT 35366, THE BOURNE LEGACY 21183, WHITE ELEPHANT 32616, WILLIAM P. MCGIVERN src, edge_attr, dst 30665, directed_by, 8993 30665, release_year, 658 30665, written_by, 8993 40144, directed_by, 8993 40144, has_genre, 14724 40144, written_by, 8993 16103, has_tags, 28900 16103, release_year, 658 7809, has_genre, 14724 7809, written_by, 32616 35366, has_tags, 28900 35366, release_year, 658 35366, starred_actors, 28900 21183, directed_by, 8993 21183, release_year, 658 21183, written_by, 8993 Question: In what context are PABLO TRAPERO, THE BOURNE LEGACY, and WILLIAM P. MCGIVERN connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "PABLO TRAPERO", "THE BOURNE LEGACY", "WILLIAM P. MCGIVERN" ], "valid_edges": [ [ "7 DAYS IN HAVANA", "directed_by", "PABLO TRAPERO" ], [ "7 DAYS IN HAVANA", "release_year", "2012" ], [ "7 DAYS IN HAVANA", "written_by", "PABLO TRAPERO" ], [ "CARANCHO", "directed_by", "PABLO TRAPERO" ], [ "CARANCHO", "has_genre", "CRIME" ], [ "CARANCHO", "written_by", "PABLO TRAPERO" ], [ "THE AVENGERS", "has_tags", "JEREMY RENNER" ], [ "THE AVENGERS", "release_year", "2012" ], [ "THE BIG HEAT", "has_genre", "CRIME" ], [ "THE BIG HEAT", "written_by", "WILLIAM P. MCGIVERN" ], [ "THE BOURNE LEGACY", "has_tags", "JEREMY RENNER" ], [ "THE BOURNE LEGACY", "release_year", "2012" ], [ "THE BOURNE LEGACY", "starred_actors", "JEREMY RENNER" ], [ "WHITE ELEPHANT", "directed_by", "PABLO TRAPERO" ], [ "WHITE ELEPHANT", "release_year", "2012" ], [ "WHITE ELEPHANT", "written_by", "PABLO TRAPERO" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13408, 2001 17315, 2007 24524, AKS 20999, ALONG CAME A SPIDER 16071, ANAMORPH 12750, ANTITRUST 19554, AWAKE 26119, BLACK WATER 10473, BLACKWOODS 33881, BOARDING GATE 23863, CAPTIVITY 38311, CHAOS 30917, CHERRY CRUSH 7664, CLEANER 39282, DEAD SILENCE 8961, DEATH PROOF 11558, DESCENT 6015, DISTURBIA 13064, DOMESTIC DISTURBANCE 15291, DON'T SAY A WORD 27306, EARTH VS. THE SPIDER 12628, EASTERN PROMISES 30496, EMMETT'S MARK 3242, FERMAT'S ROOM 37985, FRAILTY 5287, FROZEN 9003, FUNNY GAMES 17938, HANNIBAL 2752, HIDDEN AGENDA 26493, I KNOW WHO KILLED ME 27489, INTACTO 27830, JOSHUA 378, JOY RIDE 22804, LUST, CAUTION 26860, MAD DETECTIVE 39315, MICHAEL CLAYTON 24632, MIMIC 2 5053, MULHOLLAND DRIVE 29903, NAKED FEAR 30350, NEXT 7805, NO COUNTRY FOR OLD MEN 30966, P2 32178, PERFECT STRANGER 38005, RENDITION 24844, SCOTT WOLF 6119, SLEUTH 24221, SPEAKING OF SEX 25120, SPIRAL 40061, STUCK 26125, SUNSHINE 30932, SWORDFISH 33436, THE BANK 5365, THE BODY 12208, THE BOURNE ULTIMATUM 10389, THE BRAVE ONE 25509, THE DEBT 4175, THE DETECTIVE 2599, THE EXPERIMENT 6242, THE FOURTH ANGEL 35772, THE GIRL BY THE LAKE 3847, THE GLASS HOUSE 22621, THE HITCHER 23333, THE HOLE 7134, THE INVASION 39043, THE LEARNING CURVE 36991, THE LIFE BEFORE HER EYES 5166, THE NUMBER 23 28095, THE SIGNAL 33478, THE TAILOR OF PANAMA 24811, THRILLER 22446, TIMBER FALLS 17169, TRAINING DAY 8974, TREED MURRAY 37099, TRIANGLE 23568, VANILLA SKY 25736, ZEBRA LOUNGE src, edge_attr, dst 24524, has_genre, 24811 24524, release_year, 13408 20999, has_tags, 24811 20999, release_year, 13408 16071, has_genre, 24811 16071, release_year, 17315 12750, has_genre, 24811 12750, release_year, 13408 19554, has_genre, 24811 19554, release_year, 17315 26119, has_tags, 24811 26119, release_year, 17315 10473, has_genre, 24811 10473, release_year, 13408 33881, has_genre, 24811 33881, release_year, 17315 23863, has_genre, 24811 23863, release_year, 17315 38311, has_genre, 24811 38311, release_year, 13408 30917, has_genre, 24811 30917, release_year, 17315 7664, has_genre, 24811 7664, release_year, 17315 39282, has_genre, 24811 39282, release_year, 17315 8961, has_genre, 24811 8961, release_year, 17315 11558, has_genre, 24811 11558, release_year, 17315 6015, has_genre, 24811 6015, has_tags, 24811 6015, release_year, 17315 13064, has_genre, 24811 13064, release_year, 13408 15291, has_genre, 24811 15291, has_tags, 24811 15291, release_year, 13408 27306, has_genre, 24811 27306, release_year, 13408 12628, has_genre, 24811 12628, release_year, 17315 30496, has_genre, 24811 30496, starred_actors, 24844 3242, has_genre, 24811 3242, release_year, 17315 37985, has_genre, 24811 37985, release_year, 13408 5287, has_genre, 24811 5287, release_year, 17315 9003, has_genre, 24811 9003, has_tags, 24811 9003, release_year, 17315 17938, has_genre, 24811 17938, release_year, 13408 2752, has_genre, 24811 2752, release_year, 13408 26493, has_genre, 24811 26493, release_year, 17315 27489, has_genre, 24811 27489, release_year, 13408 27830, has_genre, 24811 27830, has_tags, 24811 27830, release_year, 17315 378, has_genre, 24811 378, release_year, 13408 22804, has_genre, 24811 22804, release_year, 17315 26860, has_genre, 24811 26860, release_year, 17315 39315, has_tags, 24811 39315, release_year, 17315 24632, has_genre, 24811 24632, release_year, 13408 5053, has_genre, 24811 5053, has_tags, 24811 5053, release_year, 13408 29903, has_genre, 24811 29903, release_year, 17315 30350, has_genre, 24811 30350, release_year, 17315 7805, has_genre, 24811 7805, has_tags, 24811 7805, release_year, 17315 30966, has_genre, 24811 30966, release_year, 17315 32178, has_genre, 24811 32178, has_tags, 24811 32178, release_year, 17315 38005, has_genre, 24811 38005, release_year, 17315 6119, has_genre, 24811 6119, release_year, 17315 24221, release_year, 13408 25120, has_genre, 24811 25120, release_year, 17315 40061, has_genre, 24811 40061, release_year, 17315 26125, has_genre, 24811 26125, release_year, 17315 30932, has_genre, 24811 30932, release_year, 13408 33436, has_genre, 24811 33436, release_year, 13408 5365, has_genre, 24811 5365, release_year, 13408 12208, has_genre, 24811 12208, has_tags, 24811 12208, release_year, 17315 10389, has_genre, 24811 10389, release_year, 17315 25509, has_genre, 24811 25509, release_year, 17315 4175, has_genre, 24811 4175, release_year, 17315 2599, has_genre, 24811 2599, release_year, 13408 6242, has_genre, 24811 6242, release_year, 13408 35772, has_genre, 24811 35772, release_year, 17315 3847, has_genre, 24811 3847, release_year, 13408 22621, has_genre, 24811 22621, release_year, 17315 23333, has_genre, 24811 23333, release_year, 13408 7134, has_genre, 24811 7134, release_year, 17315 39043, has_genre, 24811 39043, release_year, 13408 36991, has_genre, 24811 36991, release_year, 17315 5166, has_genre, 24811 5166, release_year, 17315 28095, has_genre, 24811 28095, release_year, 17315 33478, has_genre, 24811 33478, release_year, 13408 22446, has_genre, 24811 22446, release_year, 17315 17169, has_genre, 24811 17169, release_year, 13408 8974, has_genre, 24811 8974, release_year, 13408 37099, has_genre, 24811 37099, release_year, 17315 23568, has_tags, 24811 23568, release_year, 13408 25736, has_genre, 24811 25736, release_year, 13408 Question: For what reason are BLACK WATER, SCOTT WOLF, and SPEAKING OF SEX associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BLACK WATER", "SCOTT WOLF", "SPEAKING OF SEX" ], "valid_edges": [ [ "AKS", "has_genre", "THRILLER" ], [ "AKS", "release_year", "2001" ], [ "ALONG CAME A SPIDER", "has_tags", "THRILLER" ], [ "ALONG CAME A SPIDER", "release_year", "2001" ], [ "ANAMORPH", "has_genre", "THRILLER" ], [ "ANAMORPH", "release_year", "2007" ], [ "ANTITRUST", "has_genre", "THRILLER" ], [ "ANTITRUST", "release_year", "2001" ], [ "AWAKE", "has_genre", "THRILLER" ], [ "AWAKE", "release_year", "2007" ], [ "BLACK WATER", "has_tags", "THRILLER" ], [ "BLACK WATER", "release_year", "2007" ], [ "BLACKWOODS", "has_genre", "THRILLER" ], [ "BLACKWOODS", "release_year", "2001" ], [ "BOARDING GATE", "has_genre", "THRILLER" ], [ "BOARDING GATE", "release_year", "2007" ], [ "CAPTIVITY", "has_genre", "THRILLER" ], [ "CAPTIVITY", "release_year", "2007" ], [ "CHAOS", "has_genre", "THRILLER" ], [ "CHAOS", "release_year", "2001" ], [ "CHERRY CRUSH", "has_genre", "THRILLER" ], [ "CHERRY CRUSH", "release_year", "2007" ], [ "CLEANER", "has_genre", "THRILLER" ], [ "CLEANER", "release_year", "2007" ], [ "DEAD SILENCE", "has_genre", "THRILLER" ], [ "DEAD SILENCE", "release_year", "2007" ], [ "DEATH PROOF", "has_genre", "THRILLER" ], [ "DEATH PROOF", "release_year", "2007" ], [ "DESCENT", "has_genre", "THRILLER" ], [ "DESCENT", "release_year", "2007" ], [ "DISTURBIA", "has_genre", "THRILLER" ], [ "DISTURBIA", "has_tags", "THRILLER" ], [ "DISTURBIA", "release_year", "2007" ], [ "DOMESTIC DISTURBANCE", "has_genre", "THRILLER" ], [ "DOMESTIC DISTURBANCE", "release_year", "2001" ], [ "DON'T SAY A WORD", "has_genre", "THRILLER" ], [ "DON'T SAY A WORD", "has_tags", "THRILLER" ], [ "DON'T SAY A WORD", "release_year", "2001" ], [ "EARTH VS. THE SPIDER", "has_genre", "THRILLER" ], [ "EARTH VS. THE SPIDER", "release_year", "2001" ], [ "EASTERN PROMISES", "has_genre", "THRILLER" ], [ "EASTERN PROMISES", "release_year", "2007" ], [ "EMMETT'S MARK", "has_genre", "THRILLER" ], [ "EMMETT'S MARK", "starred_actors", "SCOTT WOLF" ], [ "FERMAT'S ROOM", "has_genre", "THRILLER" ], [ "FERMAT'S ROOM", "release_year", "2007" ], [ "FRAILTY", "has_genre", "THRILLER" ], [ "FRAILTY", "release_year", "2001" ], [ "FROZEN", "has_genre", "THRILLER" ], [ "FROZEN", "release_year", "2007" ], [ "FUNNY GAMES", "has_genre", "THRILLER" ], [ "FUNNY GAMES", "has_tags", "THRILLER" ], [ "FUNNY GAMES", "release_year", "2007" ], [ "HANNIBAL", "has_genre", "THRILLER" ], [ "HANNIBAL", "release_year", "2001" ], [ "HIDDEN AGENDA", "has_genre", "THRILLER" ], [ "HIDDEN AGENDA", "release_year", "2001" ], [ "I KNOW WHO KILLED ME", "has_genre", "THRILLER" ], [ "I KNOW WHO KILLED ME", "release_year", "2007" ], [ "INTACTO", "has_genre", "THRILLER" ], [ "INTACTO", "release_year", "2001" ], [ "JOSHUA", "has_genre", "THRILLER" ], [ "JOSHUA", "has_tags", "THRILLER" ], [ "JOSHUA", "release_year", "2007" ], [ "JOY RIDE", "has_genre", "THRILLER" ], [ "JOY RIDE", "release_year", "2001" ], [ "LUST, CAUTION", "has_genre", "THRILLER" ], [ "LUST, CAUTION", "release_year", "2007" ], [ "MAD DETECTIVE", "has_genre", "THRILLER" ], [ "MAD DETECTIVE", "release_year", "2007" ], [ "MICHAEL CLAYTON", "has_tags", "THRILLER" ], [ "MICHAEL CLAYTON", "release_year", "2007" ], [ "MIMIC 2", "has_genre", "THRILLER" ], [ "MIMIC 2", "release_year", "2001" ], [ "MULHOLLAND DRIVE", "has_genre", "THRILLER" ], [ "MULHOLLAND DRIVE", "has_tags", "THRILLER" ], [ "MULHOLLAND DRIVE", "release_year", "2001" ], [ "NAKED FEAR", "has_genre", "THRILLER" ], [ "NAKED FEAR", "release_year", "2007" ], [ "NEXT", "has_genre", "THRILLER" ], [ "NEXT", "release_year", "2007" ], [ "NO COUNTRY FOR OLD MEN", "has_genre", "THRILLER" ], [ "NO COUNTRY FOR OLD MEN", "has_tags", "THRILLER" ], [ "NO COUNTRY FOR OLD MEN", "release_year", "2007" ], [ "P2", "has_genre", "THRILLER" ], [ "P2", "release_year", "2007" ], [ "PERFECT STRANGER", "has_genre", "THRILLER" ], [ "PERFECT STRANGER", "has_tags", "THRILLER" ], [ "PERFECT STRANGER", "release_year", "2007" ], [ "RENDITION", "has_genre", "THRILLER" ], [ "RENDITION", "release_year", "2007" ], [ "SLEUTH", "has_genre", "THRILLER" ], [ "SLEUTH", "release_year", "2007" ], [ "SPEAKING OF SEX", "release_year", "2001" ], [ "SPIRAL", "has_genre", "THRILLER" ], [ "SPIRAL", "release_year", "2007" ], [ "STUCK", "has_genre", "THRILLER" ], [ "STUCK", "release_year", "2007" ], [ "SUNSHINE", "has_genre", "THRILLER" ], [ "SUNSHINE", "release_year", "2007" ], [ "SWORDFISH", "has_genre", "THRILLER" ], [ "SWORDFISH", "release_year", "2001" ], [ "THE BANK", "has_genre", "THRILLER" ], [ "THE BANK", "release_year", "2001" ], [ "THE BODY", "has_genre", "THRILLER" ], [ "THE BODY", "release_year", "2001" ], [ "THE BOURNE ULTIMATUM", "has_genre", "THRILLER" ], [ "THE BOURNE ULTIMATUM", "has_tags", "THRILLER" ], [ "THE BOURNE ULTIMATUM", "release_year", "2007" ], [ "THE BRAVE ONE", "has_genre", "THRILLER" ], [ "THE BRAVE ONE", "release_year", "2007" ], [ "THE DEBT", "has_genre", "THRILLER" ], [ "THE DEBT", "release_year", "2007" ], [ "THE DETECTIVE", "has_genre", "THRILLER" ], [ "THE DETECTIVE", "release_year", "2007" ], [ "THE EXPERIMENT", "has_genre", "THRILLER" ], [ "THE EXPERIMENT", "release_year", "2001" ], [ "THE FOURTH ANGEL", "has_genre", "THRILLER" ], [ "THE FOURTH ANGEL", "release_year", "2001" ], [ "THE GIRL BY THE LAKE", "has_genre", "THRILLER" ], [ "THE GIRL BY THE LAKE", "release_year", "2007" ], [ "THE GLASS HOUSE", "has_genre", "THRILLER" ], [ "THE GLASS HOUSE", "release_year", "2001" ], [ "THE HITCHER", "has_genre", "THRILLER" ], [ "THE HITCHER", "release_year", "2007" ], [ "THE HOLE", "has_genre", "THRILLER" ], [ "THE HOLE", "release_year", "2001" ], [ "THE INVASION", "has_genre", "THRILLER" ], [ "THE INVASION", "release_year", "2007" ], [ "THE LEARNING CURVE", "has_genre", "THRILLER" ], [ "THE LEARNING CURVE", "release_year", "2001" ], [ "THE LIFE BEFORE HER EYES", "has_genre", "THRILLER" ], [ "THE LIFE BEFORE HER EYES", "release_year", "2007" ], [ "THE NUMBER 23", "has_genre", "THRILLER" ], [ "THE NUMBER 23", "release_year", "2007" ], [ "THE SIGNAL", "has_genre", "THRILLER" ], [ "THE SIGNAL", "release_year", "2007" ], [ "THE TAILOR OF PANAMA", "has_genre", "THRILLER" ], [ "THE TAILOR OF PANAMA", "release_year", "2001" ], [ "TIMBER FALLS", "has_genre", "THRILLER" ], [ "TIMBER FALLS", "release_year", "2007" ], [ "TRAINING DAY", "has_genre", "THRILLER" ], [ "TRAINING DAY", "release_year", "2001" ], [ "TREED MURRAY", "has_genre", "THRILLER" ], [ "TREED MURRAY", "release_year", "2001" ], [ "TRIANGLE", "has_genre", "THRILLER" ], [ "TRIANGLE", "release_year", "2007" ], [ "VANILLA SKY", "has_tags", "THRILLER" ], [ "VANILLA SKY", "release_year", "2001" ], [ "ZEBRA LOUNGE", "has_genre", "THRILLER" ], [ "ZEBRA LOUNGE", "release_year", "2001" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 8539, 1982 18504, 300 MILES TO HEAVEN 3849, A QUESTION OF SILENCE 3466, A SHORT FILM ABOUT LOVE 10184, ALL THAT I LOVE 8047, AN OFFICER AND A GENTLEMAN 20033, ANGEL 39876, ANNIE 16584, ARLENE SARNER 1156, AVALON 29743, BEST FRIENDS 26260, BLUE SKY 27, CAMERA BUFF 17892, CAMOUFLAGE 21730, DAY OF THE WACKO 2115, DEAD RINGERS 8663, DEEP END 35313, DESPERATE SEARCH 39164, DINER 36212, DRAMA 9693, FANNY AND ALEXANDER 5599, FIVE DAYS ONE SUMMER 15398, FLOATING SKYSCRAPERS 34973, FOUR NIGHTS WITH ANNA 9999, GANDHI 5359, HONKYTONK MAN 37734, IDENTIFICATION OF A WOMAN 25995, IF YOU COULD SEE WHAT I HEAR 15343, IN DARKNESS 29418, JEREMY IRONS 23999, JERRY LEICHTLING 2723, JERZY SKOLIMOWSKI 15322, LOLITA 36539, M. BUTTERFLY 35181, MARGIN CALL 23574, MISSING 12803, MONSIGNOR 19819, MOONLIGHTING 15644, OLIVER TWIST 25824, PARADISE 11477, PATRICIA MEDINA 20473, PEGGY SUE GOT MARRIED 38321, PENITENTIARY II 20075, POLISH 1280, QUERELLE 30622, SALTO 34329, SCHINDLER'S LIST 20221, SHOOT THE MOON 9274, SIX PACK 2950, SIX WEEKS 1857, SOME KIND OF HERO 35597, SOPHIE'S CHOICE 20689, STARSTRUCK 29038, STEALING BEAUTY 23708, SUICIDE ROOM 7985, SYMMETRY 12282, TATARAK 2819, TEMPEST 4666, TEX 14122, THAT CHAMPIONSHIP SEASON 36088, THAT NIGHT IN VARENNES 9426, THE ASHES 7224, THE BORDER 8920, THE DARK HOUSE 25509, THE DEBT 22234, THE ELEPHANT MAN 25206, THE FRENCH LIEUTENANT'S WOMAN 35661, THE MAN FROM SNOWY RIVER 38433, THE MERCHANT OF VENICE 27045, THE MISSION 15155, THE NIGHT OF THE SHOOTING STARS 29172, THE PLAGUE DOGS 20953, THE PREFAB PEOPLE 21368, THE PROMISED LAND 8251, THE SECRET OF NIMH 14833, THE SIMPLE-MINDED MURDERER 279, THE VERDICT 14988, THE WAY BACK 6079, THE WEDDING NIGHT 8555, THE WOMAN IN THE FIFTH 15504, THE WORDS 38787, THE WORLD ACCORDING TO GARP 11863, THE YEAR OF LIVING DANGEROUSLY 27750, VICE SQUAD 32286, WHITE DOG 28023, WHITE NIGHTS 6567, WITH FIRE AND SWORD src, edge_attr, dst 18504, has_genre, 36212 18504, in_language, 20075 3849, has_genre, 36212 3849, release_year, 8539 3466, has_genre, 36212 3466, in_language, 20075 10184, has_genre, 36212 10184, in_language, 20075 8047, has_genre, 36212 8047, release_year, 8539 20033, has_genre, 36212 20033, release_year, 8539 39876, has_genre, 36212 39876, release_year, 8539 1156, has_genre, 36212 1156, in_language, 20075 29743, has_genre, 36212 29743, release_year, 8539 26260, has_genre, 36212 26260, written_by, 16584 26260, written_by, 23999 27, has_genre, 36212 27, in_language, 20075 17892, has_genre, 36212 17892, in_language, 20075 21730, has_genre, 36212 21730, in_language, 20075 2115, has_genre, 36212 2115, starred_actors, 29418 8663, directed_by, 2723 8663, has_genre, 36212 8663, has_tags, 2723 8663, written_by, 2723 35313, has_genre, 36212 35313, starred_actors, 11477 39164, has_genre, 36212 39164, release_year, 8539 9693, has_genre, 36212 9693, release_year, 8539 5599, has_genre, 36212 5599, release_year, 8539 15398, has_genre, 36212 15398, in_language, 20075 34973, directed_by, 2723 34973, has_genre, 36212 34973, in_language, 20075 34973, written_by, 2723 9999, has_genre, 36212 9999, release_year, 8539 5359, has_genre, 36212 5359, release_year, 8539 37734, has_genre, 36212 37734, release_year, 8539 25995, has_genre, 36212 25995, release_year, 8539 15343, has_genre, 36212 15343, in_language, 20075 15322, has_genre, 36212 15322, has_tags, 36212 15322, starred_actors, 29418 36539, has_genre, 36212 36539, starred_actors, 29418 35181, has_genre, 36212 35181, has_tags, 29418 35181, starred_actors, 29418 23574, has_genre, 36212 23574, release_year, 8539 12803, has_genre, 36212 12803, release_year, 8539 19819, directed_by, 2723 19819, has_genre, 36212 19819, has_tags, 2723 19819, in_language, 20075 19819, release_year, 8539 19819, starred_actors, 29418 19819, written_by, 2723 15644, has_genre, 36212 15644, release_year, 8539 25824, has_genre, 36212 25824, release_year, 8539 20473, has_genre, 36212 20473, has_tags, 36212 20473, written_by, 16584 20473, written_by, 23999 38321, has_genre, 36212 38321, release_year, 8539 1280, has_genre, 36212 1280, release_year, 8539 30622, has_genre, 36212 30622, has_tags, 20075 30622, in_language, 20075 34329, has_genre, 36212 34329, has_tags, 36212 34329, in_language, 20075 20221, has_genre, 36212 20221, release_year, 8539 9274, has_genre, 36212 9274, release_year, 8539 2950, has_genre, 36212 2950, release_year, 8539 1857, has_genre, 36212 1857, release_year, 8539 35597, has_genre, 36212 35597, in_language, 20075 35597, release_year, 8539 20689, has_genre, 36212 20689, release_year, 8539 29038, has_genre, 36212 29038, has_tags, 29418 23708, has_genre, 36212 23708, in_language, 20075 7985, has_genre, 36212 7985, in_language, 20075 12282, has_genre, 36212 12282, in_language, 20075 2819, has_genre, 36212 2819, release_year, 8539 4666, has_genre, 36212 4666, release_year, 8539 14122, has_genre, 36212 14122, release_year, 8539 36088, has_genre, 36212 36088, release_year, 8539 9426, has_genre, 36212 9426, in_language, 20075 7224, has_genre, 36212 7224, release_year, 8539 8920, has_genre, 36212 8920, in_language, 20075 25509, has_genre, 36212 25509, in_language, 20075 22234, has_genre, 36212 22234, release_year, 8539 25206, has_genre, 36212 25206, has_tags, 29418 25206, starred_actors, 29418 35661, has_genre, 36212 35661, release_year, 8539 38433, has_genre, 36212 38433, starred_actors, 29418 27045, has_genre, 36212 27045, has_tags, 29418 27045, starred_actors, 29418 15155, has_genre, 36212 15155, release_year, 8539 29172, has_genre, 36212 29172, release_year, 8539 20953, has_genre, 36212 20953, release_year, 8539 21368, has_genre, 36212 21368, in_language, 20075 8251, has_genre, 36212 8251, release_year, 8539 14833, has_genre, 36212 14833, release_year, 8539 279, has_genre, 36212 279, release_year, 8539 14988, has_genre, 36212 14988, in_language, 20075 6079, has_genre, 36212 6079, in_language, 20075 8555, has_genre, 36212 8555, in_language, 20075 15504, has_genre, 36212 15504, has_tags, 29418 15504, starred_actors, 29418 38787, has_genre, 36212 38787, release_year, 8539 11863, has_genre, 36212 11863, release_year, 8539 27750, has_genre, 36212 27750, release_year, 8539 32286, has_genre, 36212 32286, release_year, 8539 28023, has_genre, 36212 28023, starred_actors, 2723 6567, has_genre, 36212 6567, in_language, 20075 Question: In what context are ARLENE SARNER, MOONLIGHTING, and PATRICIA MEDINA connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ARLENE SARNER", "MOONLIGHTING", "PATRICIA MEDINA" ], "valid_edges": [ [ "300 MILES TO HEAVEN", "has_genre", "DRAMA" ], [ "300 MILES TO HEAVEN", "in_language", "POLISH" ], [ "A QUESTION OF SILENCE", "has_genre", "DRAMA" ], [ "A QUESTION OF SILENCE", "release_year", "1982" ], [ "A SHORT FILM ABOUT LOVE", "has_genre", "DRAMA" ], [ "A SHORT FILM ABOUT LOVE", "in_language", "POLISH" ], [ "ALL THAT I LOVE", "has_genre", "DRAMA" ], [ "ALL THAT I LOVE", "in_language", "POLISH" ], [ "AN OFFICER AND A GENTLEMAN", "has_genre", "DRAMA" ], [ "AN OFFICER AND A GENTLEMAN", "release_year", "1982" ], [ "ANGEL", "has_genre", "DRAMA" ], [ "ANGEL", "release_year", "1982" ], [ "ANNIE", "has_genre", "DRAMA" ], [ "ANNIE", "release_year", "1982" ], [ "AVALON", "has_genre", "DRAMA" ], [ "AVALON", "in_language", "POLISH" ], [ "BEST FRIENDS", "has_genre", "DRAMA" ], [ "BEST FRIENDS", "release_year", "1982" ], [ "BLUE SKY", "has_genre", "DRAMA" ], [ "BLUE SKY", "written_by", "ARLENE SARNER" ], [ "BLUE SKY", "written_by", "JERRY LEICHTLING" ], [ "CAMERA BUFF", "has_genre", "DRAMA" ], [ "CAMERA BUFF", "in_language", "POLISH" ], [ "CAMOUFLAGE", "has_genre", "DRAMA" ], [ "CAMOUFLAGE", "in_language", "POLISH" ], [ "DAY OF THE WACKO", "has_genre", "DRAMA" ], [ "DAY OF THE WACKO", "in_language", "POLISH" ], [ "DEAD RINGERS", "has_genre", "DRAMA" ], [ "DEAD RINGERS", "starred_actors", "JEREMY IRONS" ], [ "DEEP END", "directed_by", "JERZY SKOLIMOWSKI" ], [ "DEEP END", "has_genre", "DRAMA" ], [ "DEEP END", "has_tags", "JERZY SKOLIMOWSKI" ], [ "DEEP END", "written_by", "JERZY SKOLIMOWSKI" ], [ "DESPERATE SEARCH", "has_genre", "DRAMA" ], [ "DESPERATE SEARCH", "starred_actors", "PATRICIA MEDINA" ], [ "DINER", "has_genre", "DRAMA" ], [ "DINER", "release_year", "1982" ], [ "FANNY AND ALEXANDER", "has_genre", "DRAMA" ], [ "FANNY AND ALEXANDER", "release_year", "1982" ], [ "FIVE DAYS ONE SUMMER", "has_genre", "DRAMA" ], [ "FIVE DAYS ONE SUMMER", "release_year", "1982" ], [ "FLOATING SKYSCRAPERS", "has_genre", "DRAMA" ], [ "FLOATING SKYSCRAPERS", "in_language", "POLISH" ], [ "FOUR NIGHTS WITH ANNA", "directed_by", "JERZY SKOLIMOWSKI" ], [ "FOUR NIGHTS WITH ANNA", "has_genre", "DRAMA" ], [ "FOUR NIGHTS WITH ANNA", "in_language", "POLISH" ], [ "FOUR NIGHTS WITH ANNA", "written_by", "JERZY SKOLIMOWSKI" ], [ "GANDHI", "has_genre", "DRAMA" ], [ "GANDHI", "release_year", "1982" ], [ "HONKYTONK MAN", "has_genre", "DRAMA" ], [ "HONKYTONK MAN", "release_year", "1982" ], [ "IDENTIFICATION OF A WOMAN", "has_genre", "DRAMA" ], [ "IDENTIFICATION OF A WOMAN", "release_year", "1982" ], [ "IF YOU COULD SEE WHAT I HEAR", "has_genre", "DRAMA" ], [ "IF YOU COULD SEE WHAT I HEAR", "release_year", "1982" ], [ "IN DARKNESS", "has_genre", "DRAMA" ], [ "IN DARKNESS", "in_language", "POLISH" ], [ "LOLITA", "has_genre", "DRAMA" ], [ "LOLITA", "has_tags", "DRAMA" ], [ "LOLITA", "starred_actors", "JEREMY IRONS" ], [ "M. BUTTERFLY", "has_genre", "DRAMA" ], [ "M. BUTTERFLY", "starred_actors", "JEREMY IRONS" ], [ "MARGIN CALL", "has_genre", "DRAMA" ], [ "MARGIN CALL", "has_tags", "JEREMY IRONS" ], [ "MARGIN CALL", "starred_actors", "JEREMY IRONS" ], [ "MISSING", "has_genre", "DRAMA" ], [ "MISSING", "release_year", "1982" ], [ "MONSIGNOR", "has_genre", "DRAMA" ], [ "MONSIGNOR", "release_year", "1982" ], [ "MOONLIGHTING", "directed_by", "JERZY SKOLIMOWSKI" ], [ "MOONLIGHTING", "has_genre", "DRAMA" ], [ "MOONLIGHTING", "has_tags", "JERZY SKOLIMOWSKI" ], [ "MOONLIGHTING", "in_language", "POLISH" ], [ "MOONLIGHTING", "release_year", "1982" ], [ "MOONLIGHTING", "starred_actors", "JEREMY IRONS" ], [ "MOONLIGHTING", "written_by", "JERZY SKOLIMOWSKI" ], [ "OLIVER TWIST", "has_genre", "DRAMA" ], [ "OLIVER TWIST", "release_year", "1982" ], [ "PARADISE", "has_genre", "DRAMA" ], [ "PARADISE", "release_year", "1982" ], [ "PEGGY SUE GOT MARRIED", "has_genre", "DRAMA" ], [ "PEGGY SUE GOT MARRIED", "has_tags", "DRAMA" ], [ "PEGGY SUE GOT MARRIED", "written_by", "ARLENE SARNER" ], [ "PEGGY SUE GOT MARRIED", "written_by", "JERRY LEICHTLING" ], [ "PENITENTIARY II", "has_genre", "DRAMA" ], [ "PENITENTIARY II", "release_year", "1982" ], [ "QUERELLE", "has_genre", "DRAMA" ], [ "QUERELLE", "release_year", "1982" ], [ "SALTO", "has_genre", "DRAMA" ], [ "SALTO", "has_tags", "POLISH" ], [ "SALTO", "in_language", "POLISH" ], [ "SCHINDLER'S LIST", "has_genre", "DRAMA" ], [ "SCHINDLER'S LIST", "has_tags", "DRAMA" ], [ "SCHINDLER'S LIST", "in_language", "POLISH" ], [ "SHOOT THE MOON", "has_genre", "DRAMA" ], [ "SHOOT THE MOON", "release_year", "1982" ], [ "SIX PACK", "has_genre", "DRAMA" ], [ "SIX PACK", "release_year", "1982" ], [ "SIX WEEKS", "has_genre", "DRAMA" ], [ "SIX WEEKS", "release_year", "1982" ], [ "SOME KIND OF HERO", "has_genre", "DRAMA" ], [ "SOME KIND OF HERO", "release_year", "1982" ], [ "SOPHIE'S CHOICE", "has_genre", "DRAMA" ], [ "SOPHIE'S CHOICE", "in_language", "POLISH" ], [ "SOPHIE'S CHOICE", "release_year", "1982" ], [ "STARSTRUCK", "has_genre", "DRAMA" ], [ "STARSTRUCK", "release_year", "1982" ], [ "STEALING BEAUTY", "has_genre", "DRAMA" ], [ "STEALING BEAUTY", "has_tags", "JEREMY IRONS" ], [ "SUICIDE ROOM", "has_genre", "DRAMA" ], [ "SUICIDE ROOM", "in_language", "POLISH" ], [ "SYMMETRY", "has_genre", "DRAMA" ], [ "SYMMETRY", "in_language", "POLISH" ], [ "TATARAK", "has_genre", "DRAMA" ], [ "TATARAK", "in_language", "POLISH" ], [ "TEMPEST", "has_genre", "DRAMA" ], [ "TEMPEST", "release_year", "1982" ], [ "TEX", "has_genre", "DRAMA" ], [ "TEX", "release_year", "1982" ], [ "THAT CHAMPIONSHIP SEASON", "has_genre", "DRAMA" ], [ "THAT CHAMPIONSHIP SEASON", "release_year", "1982" ], [ "THAT NIGHT IN VARENNES", "has_genre", "DRAMA" ], [ "THAT NIGHT IN VARENNES", "release_year", "1982" ], [ "THE ASHES", "has_genre", "DRAMA" ], [ "THE ASHES", "in_language", "POLISH" ], [ "THE BORDER", "has_genre", "DRAMA" ], [ "THE BORDER", "release_year", "1982" ], [ "THE DARK HOUSE", "has_genre", "DRAMA" ], [ "THE DARK HOUSE", "in_language", "POLISH" ], [ "THE DEBT", "has_genre", "DRAMA" ], [ "THE DEBT", "in_language", "POLISH" ], [ "THE ELEPHANT MAN", "has_genre", "DRAMA" ], [ "THE ELEPHANT MAN", "release_year", "1982" ], [ "THE FRENCH LIEUTENANT'S WOMAN", "has_genre", "DRAMA" ], [ "THE FRENCH LIEUTENANT'S WOMAN", "has_tags", "JEREMY IRONS" ], [ "THE FRENCH LIEUTENANT'S WOMAN", "starred_actors", "JEREMY IRONS" ], [ "THE MAN FROM SNOWY RIVER", "has_genre", "DRAMA" ], [ "THE MAN FROM SNOWY RIVER", "release_year", "1982" ], [ "THE MERCHANT OF VENICE", "has_genre", "DRAMA" ], [ "THE MERCHANT OF VENICE", "starred_actors", "JEREMY IRONS" ], [ "THE MISSION", "has_genre", "DRAMA" ], [ "THE MISSION", "has_tags", "JEREMY IRONS" ], [ "THE MISSION", "starred_actors", "JEREMY IRONS" ], [ "THE NIGHT OF THE SHOOTING STARS", "has_genre", "DRAMA" ], [ "THE NIGHT OF THE SHOOTING STARS", "release_year", "1982" ], [ "THE PLAGUE DOGS", "has_genre", "DRAMA" ], [ "THE PLAGUE DOGS", "release_year", "1982" ], [ "THE PREFAB PEOPLE", "has_genre", "DRAMA" ], [ "THE PREFAB PEOPLE", "release_year", "1982" ], [ "THE PROMISED LAND", "has_genre", "DRAMA" ], [ "THE PROMISED LAND", "in_language", "POLISH" ], [ "THE SECRET OF NIMH", "has_genre", "DRAMA" ], [ "THE SECRET OF NIMH", "release_year", "1982" ], [ "THE SIMPLE-MINDED MURDERER", "has_genre", "DRAMA" ], [ "THE SIMPLE-MINDED MURDERER", "release_year", "1982" ], [ "THE VERDICT", "has_genre", "DRAMA" ], [ "THE VERDICT", "release_year", "1982" ], [ "THE WAY BACK", "has_genre", "DRAMA" ], [ "THE WAY BACK", "in_language", "POLISH" ], [ "THE WEDDING NIGHT", "has_genre", "DRAMA" ], [ "THE WEDDING NIGHT", "in_language", "POLISH" ], [ "THE WOMAN IN THE FIFTH", "has_genre", "DRAMA" ], [ "THE WOMAN IN THE FIFTH", "in_language", "POLISH" ], [ "THE WORDS", "has_genre", "DRAMA" ], [ "THE WORDS", "has_tags", "JEREMY IRONS" ], [ "THE WORDS", "starred_actors", "JEREMY IRONS" ], [ "THE WORLD ACCORDING TO GARP", "has_genre", "DRAMA" ], [ "THE WORLD ACCORDING TO GARP", "release_year", "1982" ], [ "THE YEAR OF LIVING DANGEROUSLY", "has_genre", "DRAMA" ], [ "THE YEAR OF LIVING DANGEROUSLY", "release_year", "1982" ], [ "VICE SQUAD", "has_genre", "DRAMA" ], [ "VICE SQUAD", "release_year", "1982" ], [ "WHITE DOG", "has_genre", "DRAMA" ], [ "WHITE DOG", "release_year", "1982" ], [ "WHITE NIGHTS", "has_genre", "DRAMA" ], [ "WHITE NIGHTS", "starred_actors", "JERZY SKOLIMOWSKI" ], [ "WITH FIRE AND SWORD", "has_genre", "DRAMA" ], [ "WITH FIRE AND SWORD", "in_language", "POLISH" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26257, 1994 658, 2012 33217, 35 SHOTS OF RUM 30332, AMOUR 23257, AN UNFORGETTABLE SUMMER 25053, BASTARDS 4592, BEAU TRAVAIL 8230, BREAKING WIND 24707, CAMILLE REWINDS 21065, CHARLIE CHAN AT MONTE CARLO 31594, CHARLIE CHAN IN LONDON 4476, CHOCOLAT 22712, CLAIRE DENIS 7480, EDEN 32892, ENGLISH VINGLISH 28849, EUGENE FORDE 19570, FAREWELL, MY QUEEN 409, FARINELLI 6012, FRENCH 5647, HANNAH ARENDT 34345, HAPPINESS NEVER COMES ALONE 4762, I CAN'T SLEEP 38589, I DO 32290, IN THE HOUSE 18091, L'ENFER 14601, LES MISÉRABLES 39727, LIFE OF PI 17372, LOL 29549, MINA TANNENBAUM 7974, MY FATHER THE HERO 24915, MY WAY 21677, ON THE ROAD 38602, OUR CHILDREN 11056, PAULETTE 10493, POPULAIRE 25851, RED LIGHTS 33501, RENOIR 30316, RUST AND BONE 31774, SEE HOW THEY FALL 25060, SEXUAL CHRONICLES OF A FRENCH FAMILY 37345, SIMON KILLER 33759, SOMETHING IN THE AIR 3885, THE ARTIST AND THE MODEL 16929, THE GIRL 24652, THE MAN WHO LAUGHS 28735, THE OTHER SON 17457, THE SUICIDE SHOP 266, THREE WORLDS 27598, TROUBLE EVERY DAY 12860, TRUE LIES 20399, WARNER OLAND 38905, WHAT'S IN A NAME? 23392, WHITE MATERIAL 23141, WILD REEDS 33318, YOU AIN'T SEEN NOTHIN' YET 40040, ZARAFA src, edge_attr, dst 33217, directed_by, 22712 33217, has_tags, 22712 33217, in_language, 6012 33217, written_by, 22712 30332, has_tags, 6012 30332, in_language, 6012 30332, release_year, 658 23257, in_language, 6012 23257, release_year, 26257 25053, directed_by, 22712 25053, in_language, 6012 25053, written_by, 22712 4592, directed_by, 22712 4592, in_language, 6012 4592, written_by, 22712 8230, release_year, 658 24707, in_language, 6012 24707, release_year, 658 21065, directed_by, 28849 21065, has_tags, 28849 21065, in_language, 6012 21065, starred_actors, 20399 31594, directed_by, 28849 31594, has_tags, 28849 31594, starred_actors, 20399 4476, directed_by, 22712 4476, has_tags, 22712 4476, has_tags, 6012 4476, in_language, 6012 4476, written_by, 22712 7480, in_language, 6012 7480, release_year, 658 32892, in_language, 6012 32892, release_year, 658 19570, in_language, 6012 19570, release_year, 658 409, in_language, 6012 409, release_year, 26257 5647, in_language, 6012 5647, release_year, 658 34345, in_language, 6012 34345, release_year, 658 4762, directed_by, 22712 4762, in_language, 6012 4762, release_year, 26257 4762, written_by, 22712 38589, has_tags, 6012 38589, in_language, 6012 38589, release_year, 658 32290, in_language, 6012 32290, release_year, 658 18091, in_language, 6012 18091, release_year, 26257 14601, in_language, 6012 14601, release_year, 658 39727, in_language, 6012 39727, release_year, 658 17372, in_language, 6012 17372, release_year, 658 29549, in_language, 6012 29549, release_year, 26257 7974, in_language, 6012 7974, release_year, 26257 24915, in_language, 6012 24915, release_year, 658 21677, in_language, 6012 21677, release_year, 658 38602, in_language, 6012 38602, release_year, 658 11056, in_language, 6012 11056, release_year, 658 10493, in_language, 6012 10493, release_year, 658 25851, has_tags, 6012 25851, in_language, 6012 25851, release_year, 658 33501, in_language, 6012 33501, release_year, 658 30316, in_language, 6012 30316, release_year, 658 31774, in_language, 6012 31774, release_year, 26257 25060, in_language, 6012 25060, release_year, 658 37345, in_language, 6012 37345, release_year, 658 33759, in_language, 6012 33759, release_year, 658 3885, in_language, 6012 3885, release_year, 658 16929, in_language, 6012 16929, release_year, 658 24652, in_language, 6012 24652, release_year, 658 28735, in_language, 6012 28735, release_year, 658 17457, in_language, 6012 17457, release_year, 658 266, in_language, 6012 266, release_year, 658 27598, directed_by, 22712 27598, in_language, 6012 27598, written_by, 22712 12860, in_language, 6012 12860, release_year, 26257 38905, has_tags, 6012 38905, in_language, 6012 38905, release_year, 658 23392, directed_by, 22712 23392, has_tags, 22712 23392, in_language, 6012 23392, written_by, 22712 23141, in_language, 6012 23141, release_year, 26257 33318, in_language, 6012 33318, release_year, 658 40040, in_language, 6012 40040, release_year, 658 Question: For what reason are BREAKING WIND, EUGENE FORDE, and I CAN'T SLEEP associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BREAKING WIND", "EUGENE FORDE", "I CAN'T SLEEP" ], "valid_edges": [ [ "35 SHOTS OF RUM", "directed_by", "CLAIRE DENIS" ], [ "35 SHOTS OF RUM", "has_tags", "CLAIRE DENIS" ], [ "35 SHOTS OF RUM", "in_language", "FRENCH" ], [ "35 SHOTS OF RUM", "written_by", "CLAIRE DENIS" ], [ "AMOUR", "has_tags", "FRENCH" ], [ "AMOUR", "in_language", "FRENCH" ], [ "AMOUR", "release_year", "2012" ], [ "AN UNFORGETTABLE SUMMER", "in_language", "FRENCH" ], [ "AN UNFORGETTABLE SUMMER", "release_year", "1994" ], [ "BASTARDS", "directed_by", "CLAIRE DENIS" ], [ "BASTARDS", "in_language", "FRENCH" ], [ "BASTARDS", "written_by", "CLAIRE DENIS" ], [ "BEAU TRAVAIL", "directed_by", "CLAIRE DENIS" ], [ "BEAU TRAVAIL", "in_language", "FRENCH" ], [ "BEAU TRAVAIL", "written_by", "CLAIRE DENIS" ], [ "BREAKING WIND", "release_year", "2012" ], [ "CAMILLE REWINDS", "in_language", "FRENCH" ], [ "CAMILLE REWINDS", "release_year", "2012" ], [ "CHARLIE CHAN AT MONTE CARLO", "directed_by", "EUGENE FORDE" ], [ "CHARLIE CHAN AT MONTE CARLO", "has_tags", "EUGENE FORDE" ], [ "CHARLIE CHAN AT MONTE CARLO", "in_language", "FRENCH" ], [ "CHARLIE CHAN AT MONTE CARLO", "starred_actors", "WARNER OLAND" ], [ "CHARLIE CHAN IN LONDON", "directed_by", "EUGENE FORDE" ], [ "CHARLIE CHAN IN LONDON", "has_tags", "EUGENE FORDE" ], [ "CHARLIE CHAN IN LONDON", "starred_actors", "WARNER OLAND" ], [ "CHOCOLAT", "directed_by", "CLAIRE DENIS" ], [ "CHOCOLAT", "has_tags", "CLAIRE DENIS" ], [ "CHOCOLAT", "has_tags", "FRENCH" ], [ "CHOCOLAT", "in_language", "FRENCH" ], [ "CHOCOLAT", "written_by", "CLAIRE DENIS" ], [ "EDEN", "in_language", "FRENCH" ], [ "EDEN", "release_year", "2012" ], [ "ENGLISH VINGLISH", "in_language", "FRENCH" ], [ "ENGLISH VINGLISH", "release_year", "2012" ], [ "FAREWELL, MY QUEEN", "in_language", "FRENCH" ], [ "FAREWELL, MY QUEEN", "release_year", "2012" ], [ "FARINELLI", "in_language", "FRENCH" ], [ "FARINELLI", "release_year", "1994" ], [ "HANNAH ARENDT", "in_language", "FRENCH" ], [ "HANNAH ARENDT", "release_year", "2012" ], [ "HAPPINESS NEVER COMES ALONE", "in_language", "FRENCH" ], [ "HAPPINESS NEVER COMES ALONE", "release_year", "2012" ], [ "I CAN'T SLEEP", "directed_by", "CLAIRE DENIS" ], [ "I CAN'T SLEEP", "in_language", "FRENCH" ], [ "I CAN'T SLEEP", "release_year", "1994" ], [ "I CAN'T SLEEP", "written_by", "CLAIRE DENIS" ], [ "I DO", "has_tags", "FRENCH" ], [ "I DO", "in_language", "FRENCH" ], [ "I DO", "release_year", "2012" ], [ "IN THE HOUSE", "in_language", "FRENCH" ], [ "IN THE HOUSE", "release_year", "2012" ], [ "L'ENFER", "in_language", "FRENCH" ], [ "L'ENFER", "release_year", "1994" ], [ "LES MISÉRABLES", "in_language", "FRENCH" ], [ "LES MISÉRABLES", "release_year", "2012" ], [ "LIFE OF PI", "in_language", "FRENCH" ], [ "LIFE OF PI", "release_year", "2012" ], [ "LOL", "in_language", "FRENCH" ], [ "LOL", "release_year", "2012" ], [ "MINA TANNENBAUM", "in_language", "FRENCH" ], [ "MINA TANNENBAUM", "release_year", "1994" ], [ "MY FATHER THE HERO", "in_language", "FRENCH" ], [ "MY FATHER THE HERO", "release_year", "1994" ], [ "MY WAY", "in_language", "FRENCH" ], [ "MY WAY", "release_year", "2012" ], [ "ON THE ROAD", "in_language", "FRENCH" ], [ "ON THE ROAD", "release_year", "2012" ], [ "OUR CHILDREN", "in_language", "FRENCH" ], [ "OUR CHILDREN", "release_year", "2012" ], [ "PAULETTE", "in_language", "FRENCH" ], [ "PAULETTE", "release_year", "2012" ], [ "POPULAIRE", "in_language", "FRENCH" ], [ "POPULAIRE", "release_year", "2012" ], [ "RED LIGHTS", "has_tags", "FRENCH" ], [ "RED LIGHTS", "in_language", "FRENCH" ], [ "RED LIGHTS", "release_year", "2012" ], [ "RENOIR", "in_language", "FRENCH" ], [ "RENOIR", "release_year", "2012" ], [ "RUST AND BONE", "in_language", "FRENCH" ], [ "RUST AND BONE", "release_year", "2012" ], [ "SEE HOW THEY FALL", "in_language", "FRENCH" ], [ "SEE HOW THEY FALL", "release_year", "1994" ], [ "SEXUAL CHRONICLES OF A FRENCH FAMILY", "in_language", "FRENCH" ], [ "SEXUAL CHRONICLES OF A FRENCH FAMILY", "release_year", "2012" ], [ "SIMON KILLER", "in_language", "FRENCH" ], [ "SIMON KILLER", "release_year", "2012" ], [ "SOMETHING IN THE AIR", "in_language", "FRENCH" ], [ "SOMETHING IN THE AIR", "release_year", "2012" ], [ "THE ARTIST AND THE MODEL", "in_language", "FRENCH" ], [ "THE ARTIST AND THE MODEL", "release_year", "2012" ], [ "THE GIRL", "in_language", "FRENCH" ], [ "THE GIRL", "release_year", "2012" ], [ "THE MAN WHO LAUGHS", "in_language", "FRENCH" ], [ "THE MAN WHO LAUGHS", "release_year", "2012" ], [ "THE OTHER SON", "in_language", "FRENCH" ], [ "THE OTHER SON", "release_year", "2012" ], [ "THE SUICIDE SHOP", "in_language", "FRENCH" ], [ "THE SUICIDE SHOP", "release_year", "2012" ], [ "THREE WORLDS", "in_language", "FRENCH" ], [ "THREE WORLDS", "release_year", "2012" ], [ "TROUBLE EVERY DAY", "directed_by", "CLAIRE DENIS" ], [ "TROUBLE EVERY DAY", "in_language", "FRENCH" ], [ "TROUBLE EVERY DAY", "written_by", "CLAIRE DENIS" ], [ "TRUE LIES", "in_language", "FRENCH" ], [ "TRUE LIES", "release_year", "1994" ], [ "WHAT'S IN A NAME?", "has_tags", "FRENCH" ], [ "WHAT'S IN A NAME?", "in_language", "FRENCH" ], [ "WHAT'S IN A NAME?", "release_year", "2012" ], [ "WHITE MATERIAL", "directed_by", "CLAIRE DENIS" ], [ "WHITE MATERIAL", "has_tags", "CLAIRE DENIS" ], [ "WHITE MATERIAL", "in_language", "FRENCH" ], [ "WHITE MATERIAL", "written_by", "CLAIRE DENIS" ], [ "WILD REEDS", "in_language", "FRENCH" ], [ "WILD REEDS", "release_year", "1994" ], [ "YOU AIN'T SEEN NOTHIN' YET", "in_language", "FRENCH" ], [ "YOU AIN'T SEEN NOTHIN' YET", "release_year", "2012" ], [ "ZARAFA", "in_language", "FRENCH" ], [ "ZARAFA", "release_year", "2012" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36522, 1934 24749, A STUDY IN SCARLET 26614, ANNA MAY WONG 9764, BABE RUTH 10045, BD-R 29180, CHU CHIN CHOW 17924, REGINALD DENNY 23170, THE LOST PATROL 34208, THE PRIDE OF THE YANKEES src, edge_attr, dst 24749, has_tags, 10045 24749, starred_actors, 26614 29180, release_year, 36522 29180, starred_actors, 26614 23170, release_year, 36522 23170, starred_actors, 17924 34208, has_tags, 10045 34208, starred_actors, 9764 Question: For what reason are ANNA MAY WONG, BABE RUTH, and REGINALD DENNY associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ANNA MAY WONG", "BABE RUTH", "REGINALD DENNY" ], "valid_edges": [ [ "A STUDY IN SCARLET", "has_tags", "BD-R" ], [ "A STUDY IN SCARLET", "starred_actors", "ANNA MAY WONG" ], [ "CHU CHIN CHOW", "release_year", "1934" ], [ "CHU CHIN CHOW", "starred_actors", "ANNA MAY WONG" ], [ "THE LOST PATROL", "release_year", "1934" ], [ "THE LOST PATROL", "starred_actors", "REGINALD DENNY" ], [ "THE PRIDE OF THE YANKEES", "has_tags", "BD-R" ], [ "THE PRIDE OF THE YANKEES", "starred_actors", "BABE RUTH" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10193, ALLEN C. MILLER 10045, BD-R 22072, BEN JOHNSON 16823, BITE THE BULLET 11476, DEE WALLACE 34935, DILLINGER 23807, DOCTOR X 23540, E.T. THE EXTRA-TERRESTRIAL 26730, STEVEN SPIELBERG 18706, THE LAST PICTURE SHOW 28697, THE SUGARLAND EXPRESS 16504, THE TOWN THAT DREADED SUNDOWN src, edge_attr, dst 16823, has_tags, 10045 16823, starred_actors, 22072 34935, has_tags, 10045 34935, starred_actors, 22072 23807, has_tags, 10045 23807, written_by, 10193 23540, directed_by, 26730 23540, has_tags, 26730 23540, starred_actors, 11476 18706, has_tags, 10045 18706, starred_actors, 22072 28697, directed_by, 26730 28697, starred_actors, 22072 28697, written_by, 26730 16504, has_tags, 10045 16504, starred_actors, 22072 Question: For what reason are ALLEN C. MILLER, BEN JOHNSON, and DEE WALLACE associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ALLEN C. MILLER", "BEN JOHNSON", "DEE WALLACE" ], "valid_edges": [ [ "BITE THE BULLET", "has_tags", "BD-R" ], [ "BITE THE BULLET", "starred_actors", "BEN JOHNSON" ], [ "DILLINGER", "has_tags", "BD-R" ], [ "DILLINGER", "starred_actors", "BEN JOHNSON" ], [ "DOCTOR X", "has_tags", "BD-R" ], [ "DOCTOR X", "written_by", "ALLEN C. MILLER" ], [ "E.T. THE EXTRA-TERRESTRIAL", "directed_by", "STEVEN SPIELBERG" ], [ "E.T. THE EXTRA-TERRESTRIAL", "has_tags", "STEVEN SPIELBERG" ], [ "E.T. THE EXTRA-TERRESTRIAL", "starred_actors", "DEE WALLACE" ], [ "THE LAST PICTURE SHOW", "has_tags", "BD-R" ], [ "THE LAST PICTURE SHOW", "starred_actors", "BEN JOHNSON" ], [ "THE SUGARLAND EXPRESS", "directed_by", "STEVEN SPIELBERG" ], [ "THE SUGARLAND EXPRESS", "starred_actors", "BEN JOHNSON" ], [ "THE SUGARLAND EXPRESS", "written_by", "STEVEN SPIELBERG" ], [ "THE TOWN THAT DREADED SUNDOWN", "has_tags", "BD-R" ], [ "THE TOWN THAT DREADED SUNDOWN", "starred_actors", "BEN JOHNSON" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 658, 2012 22041, A BULLET FOR THE GENERAL 28463, AFTER THE FOX 30332, AMOUR 20546, ANZIO 3449, APARTMENT 1303 3D 30204, BAFFLED! 33711, CAESAR MUST DIE 5840, CERTIFIED COPY 13888, CITY OF THE LIVING DEAD 15275, CONVERSATION PIECE 11096, DANNY GLOVER 16041, DJANGO UNCHAINED 34275, DR. GOLDFOOT AND THE GIRL BOMBS 37267, DREAMGIRLS 31783, ENGLISH 32892, ENGLISH VINGLISH 7740, FOREIGN LETTERS 8046, GOSFORD PARK 23081, HEAVEN 35319, HOPE SPRINGS 28169, IN THE CUT 25854, INTERVISTA 16200, ITALIAN 38160, JOURNEY TO ITALY 14601, LES MISÉRABLES 27996, LOCKOUT 34611, ME AND YOU 8368, MUSHROOMING 15145, MYSTERY 769, MYSTERY TRAIN 5744, OFFENDER 21677, ON THE ROAD 8509, PASSION 738, PLOT OF FEAR 38043, PUSHER 35746, REALITY 32487, SAPPHIRE 430, SHANGHAI 29238, SHOESHINE 6119, SLEUTH 8436, SPIRITS OF THE DEAD 29427, STARCRASH 40067, STOLEN 22826, TAKEN 2 30456, TEDDY BEAR 31479, TEOREMA 9091, THE ADVENTURES OF PICASSO 15568, THE CANTERBURY TALES 38918, THE FAMILY 38614, THE IMPOSSIBLE 4091, THE LADY VANISHES 28107, THE LAST KISS 12269, THE MOTEL LIFE 37910, THE MOUNTAIN OF THE CANNIBAL GOD 18162, THE RAVEN 18274, THE ROSE TATTOO 25030, THE UNKNOWN WOMAN 14962, THE WATCHER IN THE WOODS 3437, THE WOMAN IN BLACK 15504, THE WORDS 6598, TO ROME WITH LOVE 33119, TOM EYEN 26367, WAR AND PEACE 28211, WHAT HAVE YOU DONE TO SOLANGE? src, edge_attr, dst 658, has_tags, 11096 22041, in_language, 31783 22041, in_language, 16200 28463, in_language, 31783 28463, in_language, 16200 30332, in_language, 31783 30332, release_year, 658 20546, in_language, 31783 20546, in_language, 16200 3449, in_language, 31783 3449, release_year, 658 30204, has_genre, 15145 30204, in_language, 31783 33711, in_language, 16200 33711, release_year, 658 5840, in_language, 31783 5840, in_language, 16200 13888, has_tags, 16200 13888, in_language, 31783 13888, in_language, 16200 15275, in_language, 31783 15275, in_language, 16200 16041, in_language, 31783 16041, release_year, 658 34275, in_language, 31783 34275, in_language, 16200 37267, starred_actors, 11096 37267, written_by, 33119 32892, in_language, 31783 32892, release_year, 658 7740, in_language, 31783 7740, release_year, 658 8046, has_genre, 15145 8046, in_language, 31783 23081, in_language, 31783 23081, in_language, 16200 35319, in_language, 31783 35319, release_year, 658 28169, has_genre, 15145 28169, in_language, 31783 25854, in_language, 31783 25854, in_language, 16200 38160, in_language, 31783 38160, in_language, 16200 14601, in_language, 31783 14601, release_year, 658 27996, in_language, 31783 27996, release_year, 658 34611, in_language, 16200 34611, release_year, 658 8368, release_year, 658 769, in_language, 31783 769, in_language, 16200 5744, in_language, 31783 5744, release_year, 658 21677, in_language, 31783 21677, release_year, 658 8509, in_language, 31783 8509, release_year, 658 738, has_genre, 15145 738, in_language, 16200 38043, in_language, 31783 38043, release_year, 658 35746, in_language, 16200 35746, release_year, 658 32487, has_genre, 15145 32487, in_language, 31783 430, has_genre, 15145 430, release_year, 658 29238, in_language, 31783 29238, in_language, 16200 6119, has_genre, 15145 6119, has_tags, 15145 6119, in_language, 16200 8436, has_genre, 15145 8436, in_language, 31783 8436, in_language, 16200 29427, in_language, 31783 29427, in_language, 16200 40067, has_genre, 15145 40067, release_year, 658 22826, in_language, 31783 22826, release_year, 658 30456, in_language, 31783 30456, release_year, 658 31479, has_genre, 15145 31479, in_language, 16200 9091, in_language, 31783 9091, in_language, 16200 15568, in_language, 31783 15568, in_language, 16200 38918, in_language, 31783 38918, in_language, 16200 38614, in_language, 31783 38614, release_year, 658 4091, has_genre, 15145 4091, in_language, 31783 28107, in_language, 31783 28107, in_language, 16200 12269, has_genre, 15145 12269, release_year, 658 37910, in_language, 31783 37910, in_language, 16200 18162, has_genre, 15145 18162, release_year, 658 18274, in_language, 31783 18274, in_language, 16200 25030, has_genre, 15145 25030, in_language, 16200 14962, has_genre, 15145 14962, in_language, 31783 3437, in_language, 31783 3437, release_year, 658 15504, has_genre, 15145 15504, release_year, 658 6598, in_language, 16200 6598, release_year, 658 26367, in_language, 31783 26367, in_language, 16200 28211, has_genre, 15145 28211, in_language, 16200 Question: How are MUSHROOMING, SPIRITS OF THE DEAD, and TOM EYEN related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "MUSHROOMING", "SPIRITS OF THE DEAD", "TOM EYEN" ], "valid_edges": [ [ "2012", "has_tags", "DANNY GLOVER" ], [ "A BULLET FOR THE GENERAL", "in_language", "ENGLISH" ], [ "A BULLET FOR THE GENERAL", "in_language", "ITALIAN" ], [ "AFTER THE FOX", "in_language", "ENGLISH" ], [ "AFTER THE FOX", "in_language", "ITALIAN" ], [ "AMOUR", "in_language", "ENGLISH" ], [ "AMOUR", "release_year", "2012" ], [ "ANZIO", "in_language", "ENGLISH" ], [ "ANZIO", "in_language", "ITALIAN" ], [ "APARTMENT 1303 3D", "in_language", "ENGLISH" ], [ "APARTMENT 1303 3D", "release_year", "2012" ], [ "BAFFLED!", "has_genre", "MYSTERY" ], [ "BAFFLED!", "in_language", "ENGLISH" ], [ "CAESAR MUST DIE", "in_language", "ITALIAN" ], [ "CAESAR MUST DIE", "release_year", "2012" ], [ "CERTIFIED COPY", "in_language", "ENGLISH" ], [ "CERTIFIED COPY", "in_language", "ITALIAN" ], [ "CITY OF THE LIVING DEAD", "has_tags", "ITALIAN" ], [ "CITY OF THE LIVING DEAD", "in_language", "ENGLISH" ], [ "CITY OF THE LIVING DEAD", "in_language", "ITALIAN" ], [ "CONVERSATION PIECE", "in_language", "ENGLISH" ], [ "CONVERSATION PIECE", "in_language", "ITALIAN" ], [ "DJANGO UNCHAINED", "in_language", "ENGLISH" ], [ "DJANGO UNCHAINED", "release_year", "2012" ], [ "DR. GOLDFOOT AND THE GIRL BOMBS", "in_language", "ENGLISH" ], [ "DR. GOLDFOOT AND THE GIRL BOMBS", "in_language", "ITALIAN" ], [ "DREAMGIRLS", "starred_actors", "DANNY GLOVER" ], [ "DREAMGIRLS", "written_by", "TOM EYEN" ], [ "ENGLISH VINGLISH", "in_language", "ENGLISH" ], [ "ENGLISH VINGLISH", "release_year", "2012" ], [ "FOREIGN LETTERS", "in_language", "ENGLISH" ], [ "FOREIGN LETTERS", "release_year", "2012" ], [ "GOSFORD PARK", "has_genre", "MYSTERY" ], [ "GOSFORD PARK", "in_language", "ENGLISH" ], [ "HEAVEN", "in_language", "ENGLISH" ], [ "HEAVEN", "in_language", "ITALIAN" ], [ "HOPE SPRINGS", "in_language", "ENGLISH" ], [ "HOPE SPRINGS", "release_year", "2012" ], [ "IN THE CUT", "has_genre", "MYSTERY" ], [ "IN THE CUT", "in_language", "ENGLISH" ], [ "INTERVISTA", "in_language", "ENGLISH" ], [ "INTERVISTA", "in_language", "ITALIAN" ], [ "JOURNEY TO ITALY", "in_language", "ENGLISH" ], [ "JOURNEY TO ITALY", "in_language", "ITALIAN" ], [ "LES MISÉRABLES", "in_language", "ENGLISH" ], [ "LES MISÉRABLES", "release_year", "2012" ], [ "LOCKOUT", "in_language", "ENGLISH" ], [ "LOCKOUT", "release_year", "2012" ], [ "ME AND YOU", "in_language", "ITALIAN" ], [ "ME AND YOU", "release_year", "2012" ], [ "MUSHROOMING", "release_year", "2012" ], [ "MYSTERY TRAIN", "in_language", "ENGLISH" ], [ "MYSTERY TRAIN", "in_language", "ITALIAN" ], [ "OFFENDER", "in_language", "ENGLISH" ], [ "OFFENDER", "release_year", "2012" ], [ "ON THE ROAD", "in_language", "ENGLISH" ], [ "ON THE ROAD", "release_year", "2012" ], [ "PASSION", "in_language", "ENGLISH" ], [ "PASSION", "release_year", "2012" ], [ "PLOT OF FEAR", "has_genre", "MYSTERY" ], [ "PLOT OF FEAR", "in_language", "ITALIAN" ], [ "PUSHER", "in_language", "ENGLISH" ], [ "PUSHER", "release_year", "2012" ], [ "REALITY", "in_language", "ITALIAN" ], [ "REALITY", "release_year", "2012" ], [ "SAPPHIRE", "has_genre", "MYSTERY" ], [ "SAPPHIRE", "in_language", "ENGLISH" ], [ "SHANGHAI", "has_genre", "MYSTERY" ], [ "SHANGHAI", "release_year", "2012" ], [ "SHOESHINE", "in_language", "ENGLISH" ], [ "SHOESHINE", "in_language", "ITALIAN" ], [ "SLEUTH", "has_genre", "MYSTERY" ], [ "SLEUTH", "has_tags", "MYSTERY" ], [ "SLEUTH", "in_language", "ITALIAN" ], [ "SPIRITS OF THE DEAD", "has_genre", "MYSTERY" ], [ "SPIRITS OF THE DEAD", "in_language", "ENGLISH" ], [ "SPIRITS OF THE DEAD", "in_language", "ITALIAN" ], [ "STARCRASH", "in_language", "ENGLISH" ], [ "STARCRASH", "in_language", "ITALIAN" ], [ "STOLEN", "has_genre", "MYSTERY" ], [ "STOLEN", "release_year", "2012" ], [ "TAKEN 2", "in_language", "ENGLISH" ], [ "TAKEN 2", "release_year", "2012" ], [ "TEDDY BEAR", "in_language", "ENGLISH" ], [ "TEDDY BEAR", "release_year", "2012" ], [ "TEOREMA", "has_genre", "MYSTERY" ], [ "TEOREMA", "in_language", "ITALIAN" ], [ "THE ADVENTURES OF PICASSO", "in_language", "ENGLISH" ], [ "THE ADVENTURES OF PICASSO", "in_language", "ITALIAN" ], [ "THE CANTERBURY TALES", "in_language", "ENGLISH" ], [ "THE CANTERBURY TALES", "in_language", "ITALIAN" ], [ "THE FAMILY", "in_language", "ENGLISH" ], [ "THE FAMILY", "in_language", "ITALIAN" ], [ "THE IMPOSSIBLE", "in_language", "ENGLISH" ], [ "THE IMPOSSIBLE", "release_year", "2012" ], [ "THE LADY VANISHES", "has_genre", "MYSTERY" ], [ "THE LADY VANISHES", "in_language", "ENGLISH" ], [ "THE LAST KISS", "in_language", "ENGLISH" ], [ "THE LAST KISS", "in_language", "ITALIAN" ], [ "THE MOTEL LIFE", "has_genre", "MYSTERY" ], [ "THE MOTEL LIFE", "release_year", "2012" ], [ "THE MOUNTAIN OF THE CANNIBAL GOD", "in_language", "ENGLISH" ], [ "THE MOUNTAIN OF THE CANNIBAL GOD", "in_language", "ITALIAN" ], [ "THE RAVEN", "has_genre", "MYSTERY" ], [ "THE RAVEN", "release_year", "2012" ], [ "THE ROSE TATTOO", "in_language", "ENGLISH" ], [ "THE ROSE TATTOO", "in_language", "ITALIAN" ], [ "THE UNKNOWN WOMAN", "has_genre", "MYSTERY" ], [ "THE UNKNOWN WOMAN", "in_language", "ITALIAN" ], [ "THE WATCHER IN THE WOODS", "has_genre", "MYSTERY" ], [ "THE WATCHER IN THE WOODS", "in_language", "ENGLISH" ], [ "THE WOMAN IN BLACK", "in_language", "ENGLISH" ], [ "THE WOMAN IN BLACK", "release_year", "2012" ], [ "THE WORDS", "has_genre", "MYSTERY" ], [ "THE WORDS", "release_year", "2012" ], [ "TO ROME WITH LOVE", "in_language", "ITALIAN" ], [ "TO ROME WITH LOVE", "release_year", "2012" ], [ "WAR AND PEACE", "in_language", "ENGLISH" ], [ "WAR AND PEACE", "in_language", "ITALIAN" ], [ "WHAT HAVE YOU DONE TO SOLANGE?", "has_genre", "MYSTERY" ], [ "WHAT HAVE YOU DONE TO SOLANGE?", "in_language", "ITALIAN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6776, 2000 25611, 4 FOR TEXAS 8221, A MAN ESCAPED 37987, A ROOM WITH A VIEW 21271, ALL THE PRETTY HORSES 10045, BD-R 6942, BEDAZZLED 39085, BILLY ELLIOT 16823, BITE THE BULLET 5809, BUCK AND THE PREACHER 35953, BUTCH CASSIDY AND THE SUNDANCE KID 7432, CHEYENNE AUTUMN 26781, CIMARRON 26931, COOL HAND LUKE 21286, DAVID COPPERFIELD 16041, DJANGO UNCHAINED 31564, ENGLAND 34004, FAIL SAFE 23299, GET CARTER 565, GREENFINGERS 20941, HAMLET 35856, HEARTS OF THE WEST 11980, HEAVEN'S GATE 39972, HOLLOW MAN 5870, HORROR 5779, JEFFREY BOAM 33417, JOHNNY GUITAR 27312, MAIL ORDER BRIDE 37887, MAN OF THE WEST 27954, MIDNIGHT EXPRESS 9564, MONTE WALSH 38294, MRS. MINIVER 15797, MY DARLING CLEMENTINE 7730, NEVADA SMITH 14797, O BROTHER, WHERE ART THOU? 27893, POSSESSED 30919, PRISON 4848, RIDE THE HIGH COUNTRY 36102, RIO BRAVO 18821, RUN OF THE ARROW 27807, SHAFT 15270, SHOOT-OUT AT MEDICINE BEND 3226, STAGECOACH 420, SUPPORT YOUR LOCAL SHERIFF! 35403, TEARS OF THE BLACK TIGER 7763, THE CHEYENNE SOCIAL CLUB 25685, THE CLAIM 26351, THE DEAD ZONE 21845, THE DEADLY COMPANIONS 21435, THE GOOD, THE BAD AND THE UGLY 15600, THE HALLELUJAH TRAIL 26955, THE HOLIDAY 31283, THE HOUND OF THE BASKERVILLES 9210, THE LION IN WINTER 28552, THE MAGNIFICENT SEVEN 36235, THE MAN WHO SHOT LIBERTY VALANCE 39232, THE NAKED SPUR 11902, THE OUTLAW JOSEY WALES 4624, THE OX-BOW INCIDENT 19768, THE PROFESSIONALS 27611, THE SEARCHERS 18433, THE WILD BUNCH 36026, WESTERN src, edge_attr, dst 25611, has_genre, 36026 25611, has_tags, 10045 8221, has_tags, 10045 8221, has_tags, 30919 37987, has_tags, 10045 37987, has_tags, 31564 21271, has_genre, 36026 21271, release_year, 6776 6942, has_tags, 10045 6942, release_year, 6776 39085, has_tags, 31564 39085, release_year, 6776 16823, has_genre, 36026 16823, has_tags, 10045 5809, has_genre, 36026 5809, has_tags, 10045 35953, has_genre, 36026 35953, has_tags, 10045 35953, has_tags, 36026 7432, has_genre, 36026 7432, has_tags, 10045 26781, has_genre, 36026 26781, has_tags, 10045 26931, has_tags, 10045 26931, has_tags, 30919 21286, has_tags, 10045 21286, release_year, 6776 16041, has_genre, 36026 16041, has_tags, 10045 16041, has_tags, 36026 34004, has_tags, 10045 34004, release_year, 6776 23299, has_tags, 10045 23299, release_year, 6776 565, has_tags, 31564 565, has_tags, 30919 565, release_year, 6776 20941, has_tags, 10045 20941, release_year, 6776 35856, has_genre, 36026 35856, has_tags, 10045 11980, has_tags, 10045 11980, has_tags, 36026 39972, has_tags, 10045 39972, release_year, 6776 33417, has_genre, 36026 33417, has_tags, 10045 33417, has_tags, 36026 27312, has_genre, 36026 27312, has_tags, 10045 37887, has_genre, 36026 37887, has_tags, 10045 37887, has_tags, 36026 27954, has_tags, 10045 27954, has_tags, 30919 9564, has_genre, 36026 9564, has_tags, 10045 38294, has_tags, 10045 38294, has_tags, 31564 15797, has_genre, 36026 15797, has_tags, 10045 7730, has_genre, 36026 7730, has_tags, 10045 14797, has_tags, 10045 14797, release_year, 6776 27893, has_tags, 10045 27893, release_year, 6776 30919, has_genre, 5870 30919, has_tags, 30919 4848, has_genre, 36026 4848, has_tags, 10045 36102, has_genre, 36026 36102, has_tags, 10045 36102, has_tags, 36026 18821, has_genre, 36026 18821, has_tags, 10045 27807, has_tags, 10045 27807, release_year, 6776 15270, has_genre, 36026 15270, has_tags, 10045 3226, has_genre, 36026 3226, has_tags, 10045 3226, has_tags, 36026 420, has_genre, 36026 420, has_tags, 10045 420, has_tags, 36026 35403, has_tags, 36026 35403, release_year, 6776 7763, has_genre, 36026 7763, has_tags, 10045 25685, has_genre, 36026 25685, release_year, 6776 26351, has_genre, 5870 26351, written_by, 5779 21845, has_genre, 36026 21845, has_tags, 10045 21435, has_genre, 36026 21435, has_tags, 10045 21435, has_tags, 36026 15600, has_genre, 36026 15600, has_tags, 10045 15600, has_tags, 36026 26955, has_tags, 10045 26955, has_tags, 31564 31283, has_tags, 10045 31283, release_year, 6776 9210, has_tags, 10045 9210, has_tags, 31564 28552, has_genre, 36026 28552, has_tags, 10045 28552, has_tags, 36026 36235, has_genre, 36026 36235, has_tags, 10045 36235, has_tags, 36026 39232, has_genre, 36026 39232, has_tags, 10045 11902, has_genre, 36026 11902, has_tags, 10045 11902, has_tags, 36026 4624, has_genre, 36026 4624, has_tags, 10045 4624, has_tags, 36026 19768, has_genre, 36026 19768, has_tags, 10045 27611, has_genre, 36026 27611, has_tags, 10045 27611, has_tags, 36026 18433, has_genre, 36026 18433, has_tags, 10045 18433, has_tags, 36026 Question: In what context are GREENFINGERS, JEFFREY BOAM, and RIO BRAVO connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "GREENFINGERS", "JEFFREY BOAM", "RIO BRAVO" ], "valid_edges": [ [ "4 FOR TEXAS", "has_genre", "WESTERN" ], [ "4 FOR TEXAS", "has_tags", "BD-R" ], [ "A MAN ESCAPED", "has_tags", "BD-R" ], [ "A MAN ESCAPED", "has_tags", "PRISON" ], [ "A ROOM WITH A VIEW", "has_tags", "BD-R" ], [ "A ROOM WITH A VIEW", "has_tags", "ENGLAND" ], [ "ALL THE PRETTY HORSES", "has_genre", "WESTERN" ], [ "ALL THE PRETTY HORSES", "release_year", "2000" ], [ "BEDAZZLED", "has_tags", "BD-R" ], [ "BEDAZZLED", "release_year", "2000" ], [ "BILLY ELLIOT", "has_tags", "ENGLAND" ], [ "BILLY ELLIOT", "release_year", "2000" ], [ "BITE THE BULLET", "has_genre", "WESTERN" ], [ "BITE THE BULLET", "has_tags", "BD-R" ], [ "BUCK AND THE PREACHER", "has_genre", "WESTERN" ], [ "BUCK AND THE PREACHER", "has_tags", "BD-R" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_genre", "WESTERN" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "BD-R" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "WESTERN" ], [ "CHEYENNE AUTUMN", "has_genre", "WESTERN" ], [ "CHEYENNE AUTUMN", "has_tags", "BD-R" ], [ "CIMARRON", "has_genre", "WESTERN" ], [ "CIMARRON", "has_tags", "BD-R" ], [ "COOL HAND LUKE", "has_tags", "BD-R" ], [ "COOL HAND LUKE", "has_tags", "PRISON" ], [ "DAVID COPPERFIELD", "has_tags", "BD-R" ], [ "DAVID COPPERFIELD", "release_year", "2000" ], [ "DJANGO UNCHAINED", "has_genre", "WESTERN" ], [ "DJANGO UNCHAINED", "has_tags", "BD-R" ], [ "DJANGO UNCHAINED", "has_tags", "WESTERN" ], [ "FAIL SAFE", "has_tags", "BD-R" ], [ "FAIL SAFE", "release_year", "2000" ], [ "GET CARTER", "has_tags", "BD-R" ], [ "GET CARTER", "release_year", "2000" ], [ "GREENFINGERS", "has_tags", "ENGLAND" ], [ "GREENFINGERS", "has_tags", "PRISON" ], [ "GREENFINGERS", "release_year", "2000" ], [ "HAMLET", "has_tags", "BD-R" ], [ "HAMLET", "release_year", "2000" ], [ "HEARTS OF THE WEST", "has_genre", "WESTERN" ], [ "HEARTS OF THE WEST", "has_tags", "BD-R" ], [ "HEAVEN'S GATE", "has_tags", "BD-R" ], [ "HEAVEN'S GATE", "has_tags", "WESTERN" ], [ "HOLLOW MAN", "has_tags", "BD-R" ], [ "HOLLOW MAN", "release_year", "2000" ], [ "JOHNNY GUITAR", "has_genre", "WESTERN" ], [ "JOHNNY GUITAR", "has_tags", "BD-R" ], [ "JOHNNY GUITAR", "has_tags", "WESTERN" ], [ "MAIL ORDER BRIDE", "has_genre", "WESTERN" ], [ "MAIL ORDER BRIDE", "has_tags", "BD-R" ], [ "MAN OF THE WEST", "has_genre", "WESTERN" ], [ "MAN OF THE WEST", "has_tags", "BD-R" ], [ "MAN OF THE WEST", "has_tags", "WESTERN" ], [ "MIDNIGHT EXPRESS", "has_tags", "BD-R" ], [ "MIDNIGHT EXPRESS", "has_tags", "PRISON" ], [ "MONTE WALSH", "has_genre", "WESTERN" ], [ "MONTE WALSH", "has_tags", "BD-R" ], [ "MRS. MINIVER", "has_tags", "BD-R" ], [ "MRS. MINIVER", "has_tags", "ENGLAND" ], [ "MY DARLING CLEMENTINE", "has_genre", "WESTERN" ], [ "MY DARLING CLEMENTINE", "has_tags", "BD-R" ], [ "NEVADA SMITH", "has_genre", "WESTERN" ], [ "NEVADA SMITH", "has_tags", "BD-R" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "BD-R" ], [ "O BROTHER, WHERE ART THOU?", "release_year", "2000" ], [ "POSSESSED", "has_tags", "BD-R" ], [ "POSSESSED", "release_year", "2000" ], [ "PRISON", "has_genre", "HORROR" ], [ "PRISON", "has_tags", "PRISON" ], [ "RIDE THE HIGH COUNTRY", "has_genre", "WESTERN" ], [ "RIDE THE HIGH COUNTRY", "has_tags", "BD-R" ], [ "RIO BRAVO", "has_genre", "WESTERN" ], [ "RIO BRAVO", "has_tags", "BD-R" ], [ "RIO BRAVO", "has_tags", "WESTERN" ], [ "RUN OF THE ARROW", "has_genre", "WESTERN" ], [ "RUN OF THE ARROW", "has_tags", "BD-R" ], [ "SHAFT", "has_tags", "BD-R" ], [ "SHAFT", "release_year", "2000" ], [ "SHOOT-OUT AT MEDICINE BEND", "has_genre", "WESTERN" ], [ "SHOOT-OUT AT MEDICINE BEND", "has_tags", "BD-R" ], [ "STAGECOACH", "has_genre", "WESTERN" ], [ "STAGECOACH", "has_tags", "BD-R" ], [ "STAGECOACH", "has_tags", "WESTERN" ], [ "SUPPORT YOUR LOCAL SHERIFF!", "has_genre", "WESTERN" ], [ "SUPPORT YOUR LOCAL SHERIFF!", "has_tags", "BD-R" ], [ "SUPPORT YOUR LOCAL SHERIFF!", "has_tags", "WESTERN" ], [ "TEARS OF THE BLACK TIGER", "has_tags", "WESTERN" ], [ "TEARS OF THE BLACK TIGER", "release_year", "2000" ], [ "THE CHEYENNE SOCIAL CLUB", "has_genre", "WESTERN" ], [ "THE CHEYENNE SOCIAL CLUB", "has_tags", "BD-R" ], [ "THE CLAIM", "has_genre", "WESTERN" ], [ "THE CLAIM", "release_year", "2000" ], [ "THE DEAD ZONE", "has_genre", "HORROR" ], [ "THE DEAD ZONE", "written_by", "JEFFREY BOAM" ], [ "THE DEADLY COMPANIONS", "has_genre", "WESTERN" ], [ "THE DEADLY COMPANIONS", "has_tags", "BD-R" ], [ "THE GOOD, THE BAD AND THE UGLY", "has_genre", "WESTERN" ], [ "THE GOOD, THE BAD AND THE UGLY", "has_tags", "BD-R" ], [ "THE GOOD, THE BAD AND THE UGLY", "has_tags", "WESTERN" ], [ "THE HALLELUJAH TRAIL", "has_genre", "WESTERN" ], [ "THE HALLELUJAH TRAIL", "has_tags", "BD-R" ], [ "THE HALLELUJAH TRAIL", "has_tags", "WESTERN" ], [ "THE HOLIDAY", "has_tags", "BD-R" ], [ "THE HOLIDAY", "has_tags", "ENGLAND" ], [ "THE HOUND OF THE BASKERVILLES", "has_tags", "BD-R" ], [ "THE HOUND OF THE BASKERVILLES", "release_year", "2000" ], [ "THE LION IN WINTER", "has_tags", "BD-R" ], [ "THE LION IN WINTER", "has_tags", "ENGLAND" ], [ "THE MAGNIFICENT SEVEN", "has_genre", "WESTERN" ], [ "THE MAGNIFICENT SEVEN", "has_tags", "BD-R" ], [ "THE MAGNIFICENT SEVEN", "has_tags", "WESTERN" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_genre", "WESTERN" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "BD-R" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "WESTERN" ], [ "THE NAKED SPUR", "has_genre", "WESTERN" ], [ "THE NAKED SPUR", "has_tags", "BD-R" ], [ "THE OUTLAW JOSEY WALES", "has_genre", "WESTERN" ], [ "THE OUTLAW JOSEY WALES", "has_tags", "BD-R" ], [ "THE OUTLAW JOSEY WALES", "has_tags", "WESTERN" ], [ "THE OX-BOW INCIDENT", "has_genre", "WESTERN" ], [ "THE OX-BOW INCIDENT", "has_tags", "BD-R" ], [ "THE OX-BOW INCIDENT", "has_tags", "WESTERN" ], [ "THE PROFESSIONALS", "has_genre", "WESTERN" ], [ "THE PROFESSIONALS", "has_tags", "BD-R" ], [ "THE SEARCHERS", "has_genre", "WESTERN" ], [ "THE SEARCHERS", "has_tags", "BD-R" ], [ "THE SEARCHERS", "has_tags", "WESTERN" ], [ "THE WILD BUNCH", "has_genre", "WESTERN" ], [ "THE WILD BUNCH", "has_tags", "BD-R" ], [ "THE WILD BUNCH", "has_tags", "WESTERN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10045, BD-R 8156, BYE BYE BRAVERMAN 30463, COMEDY 7393, CRIME AND PUNISHMENT 3463, DARE 5324, DAVID BRIND 36212, DRAMA 35646, MENAHEM GOLAN 28063, OVER THE BROOKLYN BRIDGE 18490, OVER THE TOP 36130, WALLACE MARKFIELD src, edge_attr, dst 8156, has_genre, 30463 8156, has_tags, 10045 8156, written_by, 36130 7393, directed_by, 35646 7393, has_tags, 10045 7393, written_by, 35646 3463, has_genre, 36212 3463, written_by, 5324 28063, directed_by, 35646 28063, has_genre, 30463 28063, has_tags, 35646 18490, directed_by, 35646 18490, has_genre, 36212 18490, has_tags, 35646 Question: In what context are DAVID BRIND, MENAHEM GOLAN, and WALLACE MARKFIELD connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DAVID BRIND", "MENAHEM GOLAN", "WALLACE MARKFIELD" ], "valid_edges": [ [ "BYE BYE BRAVERMAN", "has_genre", "COMEDY" ], [ "BYE BYE BRAVERMAN", "has_tags", "BD-R" ], [ "BYE BYE BRAVERMAN", "written_by", "WALLACE MARKFIELD" ], [ "CRIME AND PUNISHMENT", "directed_by", "MENAHEM GOLAN" ], [ "CRIME AND PUNISHMENT", "has_tags", "BD-R" ], [ "CRIME AND PUNISHMENT", "written_by", "MENAHEM GOLAN" ], [ "DARE", "has_genre", "DRAMA" ], [ "DARE", "written_by", "DAVID BRIND" ], [ "OVER THE BROOKLYN BRIDGE", "directed_by", "MENAHEM GOLAN" ], [ "OVER THE BROOKLYN BRIDGE", "has_genre", "COMEDY" ], [ "OVER THE BROOKLYN BRIDGE", "has_tags", "MENAHEM GOLAN" ], [ "OVER THE TOP", "directed_by", "MENAHEM GOLAN" ], [ "OVER THE TOP", "has_genre", "DRAMA" ], [ "OVER THE TOP", "has_tags", "MENAHEM GOLAN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29036, A MIDSUMMER NIGHT'S DREAM 10045, BD-R 17939, BURT REYNOLDS 1040, CAPTAIN BLOOD 12331, DAMES 28094, DELIVERANCE 6044, DICK POWELL 36196, DR. EHRLICH'S MAGIC BULLET 4057, FOOTLIGHT PARADE 24124, GAMBIT 20693, GONE WITH THE WIND 17323, KEVIN KLINE 26649, KISMET 36261, LAST VEGAS 18367, MICHAEL HOFFMAN 6972, OLIVIA DE HAVILLAND 4261, SALLY FIELD 94, SATAN MET A LADY 14350, SMOKEY AND THE BANDIT 17988, THE BAD AND THE BEAUTIFUL 7639, THE CHARGE OF THE LIGHT BRIGADE 16732, THE END 20658, THE LIFE OF EMILE ZOLA 33513, THE MAN WHO LOVED WOMEN 12160, THE PRIVATE LIVES OF ELIZABETH AND ESSEX 4784, THE SNAKE PIT 10474, WILLIAM DIETERLE src, edge_attr, dst 29036, directed_by, 18367 29036, directed_by, 10474 29036, has_tags, 10045 29036, has_tags, 6972 29036, has_tags, 10474 29036, starred_actors, 6044 29036, starred_actors, 17323 29036, written_by, 18367 1040, has_tags, 10045 1040, has_tags, 6972 1040, starred_actors, 6972 12331, has_tags, 10045 12331, starred_actors, 6044 28094, has_tags, 10045 28094, has_tags, 17939 28094, starred_actors, 17939 36196, directed_by, 10474 36196, has_tags, 10045 36196, has_tags, 10474 4057, has_tags, 10045 4057, starred_actors, 6044 24124, directed_by, 18367 24124, has_tags, 10045 20693, has_tags, 10045 20693, has_tags, 6972 26649, directed_by, 10474 26649, has_tags, 10045 36261, starred_actors, 17323 94, directed_by, 10474 94, has_tags, 10045 14350, has_tags, 10045 14350, starred_actors, 17939 14350, starred_actors, 4261 17988, has_tags, 10045 17988, starred_actors, 6044 7639, has_tags, 10045 7639, starred_actors, 6972 16732, directed_by, 17939 16732, has_tags, 10045 16732, starred_actors, 17939 16732, starred_actors, 4261 20658, directed_by, 10474 20658, has_tags, 10045 20658, has_tags, 10474 33513, has_tags, 10045 33513, starred_actors, 17939 12160, has_tags, 10045 12160, starred_actors, 6972 4784, has_tags, 10045 4784, has_tags, 6972 4784, starred_actors, 6972 Question: For what reason are BD-R, BURT REYNOLDS, and LAST VEGAS associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BD-R", "BURT REYNOLDS", "LAST VEGAS" ], "valid_edges": [ [ "A MIDSUMMER NIGHT'S DREAM", "directed_by", "MICHAEL HOFFMAN" ], [ "A MIDSUMMER NIGHT'S DREAM", "directed_by", "WILLIAM DIETERLE" ], [ "A MIDSUMMER NIGHT'S DREAM", "has_tags", "BD-R" ], [ "A MIDSUMMER NIGHT'S DREAM", "has_tags", "OLIVIA DE HAVILLAND" ], [ "A MIDSUMMER NIGHT'S DREAM", "has_tags", "WILLIAM DIETERLE" ], [ "A MIDSUMMER NIGHT'S DREAM", "starred_actors", "DICK POWELL" ], [ "A MIDSUMMER NIGHT'S DREAM", "starred_actors", "KEVIN KLINE" ], [ "A MIDSUMMER NIGHT'S DREAM", "written_by", "MICHAEL HOFFMAN" ], [ "CAPTAIN BLOOD", "has_tags", "BD-R" ], [ "CAPTAIN BLOOD", "has_tags", "OLIVIA DE HAVILLAND" ], [ "CAPTAIN BLOOD", "starred_actors", "OLIVIA DE HAVILLAND" ], [ "DAMES", "has_tags", "BD-R" ], [ "DAMES", "starred_actors", "DICK POWELL" ], [ "DELIVERANCE", "has_tags", "BD-R" ], [ "DELIVERANCE", "has_tags", "BURT REYNOLDS" ], [ "DELIVERANCE", "starred_actors", "BURT REYNOLDS" ], [ "DR. EHRLICH'S MAGIC BULLET", "directed_by", "WILLIAM DIETERLE" ], [ "DR. EHRLICH'S MAGIC BULLET", "has_tags", "BD-R" ], [ "DR. EHRLICH'S MAGIC BULLET", "has_tags", "WILLIAM DIETERLE" ], [ "FOOTLIGHT PARADE", "has_tags", "BD-R" ], [ "FOOTLIGHT PARADE", "starred_actors", "DICK POWELL" ], [ "GAMBIT", "directed_by", "MICHAEL HOFFMAN" ], [ "GAMBIT", "has_tags", "BD-R" ], [ "GONE WITH THE WIND", "has_tags", "BD-R" ], [ "GONE WITH THE WIND", "has_tags", "OLIVIA DE HAVILLAND" ], [ "KISMET", "directed_by", "WILLIAM DIETERLE" ], [ "KISMET", "has_tags", "BD-R" ], [ "LAST VEGAS", "starred_actors", "KEVIN KLINE" ], [ "SATAN MET A LADY", "directed_by", "WILLIAM DIETERLE" ], [ "SATAN MET A LADY", "has_tags", "BD-R" ], [ "SMOKEY AND THE BANDIT", "has_tags", "BD-R" ], [ "SMOKEY AND THE BANDIT", "starred_actors", "BURT REYNOLDS" ], [ "SMOKEY AND THE BANDIT", "starred_actors", "SALLY FIELD" ], [ "THE BAD AND THE BEAUTIFUL", "has_tags", "BD-R" ], [ "THE BAD AND THE BEAUTIFUL", "starred_actors", "DICK POWELL" ], [ "THE CHARGE OF THE LIGHT BRIGADE", "has_tags", "BD-R" ], [ "THE CHARGE OF THE LIGHT BRIGADE", "starred_actors", "OLIVIA DE HAVILLAND" ], [ "THE END", "directed_by", "BURT REYNOLDS" ], [ "THE END", "has_tags", "BD-R" ], [ "THE END", "starred_actors", "BURT REYNOLDS" ], [ "THE END", "starred_actors", "SALLY FIELD" ], [ "THE LIFE OF EMILE ZOLA", "directed_by", "WILLIAM DIETERLE" ], [ "THE LIFE OF EMILE ZOLA", "has_tags", "BD-R" ], [ "THE LIFE OF EMILE ZOLA", "has_tags", "WILLIAM DIETERLE" ], [ "THE MAN WHO LOVED WOMEN", "has_tags", "BD-R" ], [ "THE MAN WHO LOVED WOMEN", "starred_actors", "BURT REYNOLDS" ], [ "THE PRIVATE LIVES OF ELIZABETH AND ESSEX", "has_tags", "BD-R" ], [ "THE PRIVATE LIVES OF ELIZABETH AND ESSEX", "starred_actors", "OLIVIA DE HAVILLAND" ], [ "THE SNAKE PIT", "has_tags", "BD-R" ], [ "THE SNAKE PIT", "has_tags", "OLIVIA DE HAVILLAND" ], [ "THE SNAKE PIT", "starred_actors", "OLIVIA DE HAVILLAND" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 30172, 1964 8486, 1999 658, 2012 15145, MYSTERY 38226, RESOLUTION 430, SHANGHAI 34833, SIMON WEST 40067, STOLEN 4157, THE BEST MAN 24173, THE EXPENDABLES 2 598, THE GENERAL'S DAUGHTER 33864, THE MOON-SPINNERS 12269, THE MOTEL LIFE 18162, THE RAVEN 15504, THE WORDS src, edge_attr, dst 38226, release_year, 658 430, has_genre, 15145 430, release_year, 658 40067, has_genre, 15145 40067, release_year, 658 4157, release_year, 30172 4157, release_year, 8486 24173, directed_by, 34833 24173, has_tags, 34833 24173, release_year, 658 598, directed_by, 34833 598, has_genre, 15145 598, has_tags, 34833 598, release_year, 8486 33864, release_year, 30172 12269, has_genre, 15145 12269, release_year, 658 18162, has_genre, 15145 18162, release_year, 658 15504, has_genre, 15145 15504, release_year, 658 Question: In what context are RESOLUTION, THE GENERAL'S DAUGHTER, and THE MOON-SPINNERS connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "RESOLUTION", "THE GENERAL'S DAUGHTER", "THE MOON-SPINNERS" ], "valid_edges": [ [ "RESOLUTION", "release_year", "2012" ], [ "SHANGHAI", "has_genre", "MYSTERY" ], [ "SHANGHAI", "release_year", "2012" ], [ "STOLEN", "has_genre", "MYSTERY" ], [ "STOLEN", "release_year", "2012" ], [ "THE BEST MAN", "release_year", "1964" ], [ "THE BEST MAN", "release_year", "1999" ], [ "THE EXPENDABLES 2", "directed_by", "SIMON WEST" ], [ "THE EXPENDABLES 2", "has_tags", "SIMON WEST" ], [ "THE EXPENDABLES 2", "release_year", "2012" ], [ "THE GENERAL'S DAUGHTER", "directed_by", "SIMON WEST" ], [ "THE GENERAL'S DAUGHTER", "has_genre", "MYSTERY" ], [ "THE GENERAL'S DAUGHTER", "has_tags", "SIMON WEST" ], [ "THE GENERAL'S DAUGHTER", "release_year", "1999" ], [ "THE MOON-SPINNERS", "release_year", "1964" ], [ "THE MOTEL LIFE", "has_genre", "MYSTERY" ], [ "THE MOTEL LIFE", "release_year", "2012" ], [ "THE RAVEN", "has_genre", "MYSTERY" ], [ "THE RAVEN", "release_year", "2012" ], [ "THE WORDS", "has_genre", "MYSTERY" ], [ "THE WORDS", "release_year", "2012" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 18366, 1960 6925, 1966 16160, COME DRINK WITH ME 24508, DAVID SWIFT 12903, DISNEY 24638, ENCHANTED 35596, HAYLEY MILLS 21518, HONEY, I SHRUNK THE KIDS 21580, KIDS 1989, KING HU 4303, NEW YORK CITY 21773, POLLYANNA 18762, SEQUEL 34600, SPIDER-MAN 38117, SPIDER-MAN 2 2980, SUPERHERO 8061, SWISS FAMILY ROBINSON 14774, THAT DARN CAT! 24357, THE PARENT TRAP 26382, YOU'RE A BIG BOY NOW src, edge_attr, dst 16160, directed_by, 1989 16160, release_year, 6925 16160, written_by, 1989 24638, has_tags, 12903 24638, has_tags, 4303 21518, has_tags, 12903 21518, has_tags, 21580 21580, has_tags, 4303 21773, directed_by, 24508 21773, has_tags, 24508 21773, has_tags, 12903 21773, has_tags, 35596 21773, release_year, 18366 21773, starred_actors, 35596 21773, written_by, 24508 34600, has_tags, 4303 34600, has_tags, 18762 34600, has_tags, 2980 38117, has_tags, 4303 38117, has_tags, 18762 38117, has_tags, 2980 8061, has_tags, 12903 8061, release_year, 18366 14774, has_tags, 12903 14774, has_tags, 35596 14774, starred_actors, 35596 24357, directed_by, 24508 24357, has_tags, 24508 24357, has_tags, 12903 24357, has_tags, 35596 24357, starred_actors, 35596 24357, written_by, 24508 26382, has_tags, 4303 26382, release_year, 6925 Question: In what context are KING HU, NEW YORK CITY, and POLLYANNA connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "KING HU", "NEW YORK CITY", "POLLYANNA" ], "valid_edges": [ [ "COME DRINK WITH ME", "directed_by", "KING HU" ], [ "COME DRINK WITH ME", "release_year", "1966" ], [ "COME DRINK WITH ME", "written_by", "KING HU" ], [ "ENCHANTED", "has_tags", "DISNEY" ], [ "ENCHANTED", "has_tags", "NEW YORK CITY" ], [ "HONEY, I SHRUNK THE KIDS", "has_tags", "DISNEY" ], [ "HONEY, I SHRUNK THE KIDS", "has_tags", "KIDS" ], [ "KIDS", "has_tags", "NEW YORK CITY" ], [ "POLLYANNA", "directed_by", "DAVID SWIFT" ], [ "POLLYANNA", "has_tags", "DAVID SWIFT" ], [ "POLLYANNA", "has_tags", "DISNEY" ], [ "POLLYANNA", "has_tags", "HAYLEY MILLS" ], [ "POLLYANNA", "release_year", "1960" ], [ "POLLYANNA", "starred_actors", "HAYLEY MILLS" ], [ "POLLYANNA", "written_by", "DAVID SWIFT" ], [ "SPIDER-MAN", "has_tags", "NEW YORK CITY" ], [ "SPIDER-MAN", "has_tags", "SEQUEL" ], [ "SPIDER-MAN", "has_tags", "SUPERHERO" ], [ "SPIDER-MAN 2", "has_tags", "NEW YORK CITY" ], [ "SPIDER-MAN 2", "has_tags", "SEQUEL" ], [ "SPIDER-MAN 2", "has_tags", "SUPERHERO" ], [ "SWISS FAMILY ROBINSON", "has_tags", "DISNEY" ], [ "SWISS FAMILY ROBINSON", "release_year", "1960" ], [ "THAT DARN CAT!", "has_tags", "DISNEY" ], [ "THAT DARN CAT!", "has_tags", "HAYLEY MILLS" ], [ "THAT DARN CAT!", "starred_actors", "HAYLEY MILLS" ], [ "THE PARENT TRAP", "directed_by", "DAVID SWIFT" ], [ "THE PARENT TRAP", "has_tags", "DAVID SWIFT" ], [ "THE PARENT TRAP", "has_tags", "DISNEY" ], [ "THE PARENT TRAP", "has_tags", "HAYLEY MILLS" ], [ "THE PARENT TRAP", "starred_actors", "HAYLEY MILLS" ], [ "THE PARENT TRAP", "written_by", "DAVID SWIFT" ], [ "YOU'RE A BIG BOY NOW", "has_tags", "NEW YORK CITY" ], [ "YOU'RE A BIG BOY NOW", "release_year", "1966" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26310, 1947 36163, 1967 6721, 1972 19131, BONNIE AND CLYDE 11767, HUNGRY HILL 19536, TERENCE YOUNG 39072, THE MAN WHO QUIT SMOKING 25837, THE PERILS OF PAULINE 19255, THE VALACHI PAPERS 499, WAIT UNTIL DARK src, edge_attr, dst 19131, release_year, 36163 11767, release_year, 26310 11767, written_by, 19536 39072, release_year, 6721 25837, release_year, 26310 25837, release_year, 36163 19255, directed_by, 19536 19255, release_year, 6721 499, directed_by, 19536 499, has_tags, 19536 499, release_year, 36163 Question: In what context are BONNIE AND CLYDE, HUNGRY HILL, and THE MAN WHO QUIT SMOKING connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BONNIE AND CLYDE", "HUNGRY HILL", "THE MAN WHO QUIT SMOKING" ], "valid_edges": [ [ "BONNIE AND CLYDE", "release_year", "1967" ], [ "HUNGRY HILL", "release_year", "1947" ], [ "HUNGRY HILL", "written_by", "TERENCE YOUNG" ], [ "THE MAN WHO QUIT SMOKING", "release_year", "1972" ], [ "THE PERILS OF PAULINE", "release_year", "1947" ], [ "THE PERILS OF PAULINE", "release_year", "1967" ], [ "THE VALACHI PAPERS", "directed_by", "TERENCE YOUNG" ], [ "THE VALACHI PAPERS", "release_year", "1972" ], [ "WAIT UNTIL DARK", "directed_by", "TERENCE YOUNG" ], [ "WAIT UNTIL DARK", "has_tags", "TERENCE YOUNG" ], [ "WAIT UNTIL DARK", "release_year", "1967" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6253, 1936 18132, 1938 11112, 1939 11, 1940 21931, 1941 26423, 1950 6216, 1952 25717, 1953 1567, 1954 14004, 1955 33637, 1959 3863, 1962 4981, 1965 27810, 1968 39813, 1971 4763, ADVENTURE 39045, ALFRED HITCHCOCK 9677, ANATOMY OF A MURDER 13999, ANDREW V. MCLAGLEN 5661, ANTHONY MANN 35990, ARTHUR KENNEDY 4816, BANDOLERO! 10045, BD-R 3204, BEND OF THE RIVER 3706, BEULAH BONDI 36479, BORN TO DANCE 16749, BROKEN ARROW 29246, CARBINE WILLIAMS 35148, CLARENCE BROWN 14728, CLASSIC 19585, COME LIVE WITH ME 30463, COMEDY 21423, DEAR BRIGITTE 7159, DESTRY RIDES AGAIN 36212, DRAMA 10509, FAMILY 8406, FIRECREEK 13009, FOOLS' PARADE 23668, FRANK CAPRA 27953, GEORGE KENNEDY 18850, GEORGE STEVENS 11565, GOOD 34149, HENRY FONDA 38940, HENRY KOSTER 27350, HITCHCOCK 1331, IT'S A WONDERFUL LIFE 26280, IT'S A WONDERFUL WORLD 7736, JAMES STEWART 2818, JEAN ARTHUR 13255, JOHN FORD 12435, JOHN WAYNE 26627, MADE FOR EACH OTHER 27297, MAGIC TOWN 31669, MARGARET SULLAVAN 36999, MAUREEN O'HARA 20920, MR. HOBBS TAKES A VACATION 26086, MR. SMITH GOES TO WASHINGTON 28476, MURDER 24593, MUSICAL 37497, NATIONAL FILM REGISTRY 35223, NIGHT PASSAGE 23166, NO TIME FOR COMEDY 15311, OF HUMAN HEARTS 9638, ON OUR MERRY WAY 14982, PAULETTE GODDARD 23008, PETER FERDINANDO 19648, POT O' GOLD 37135, REAR WINDOW 7098, SHENANDOAH 38066, SHIRLEY JONES 26381, STRATEGIC AIR COMMAND 11290, TAKE HER, SHE'S MINE 7763, THE CHEYENNE SOCIAL CLUB 27995, THE FAR COUNTRY 32820, THE FBI STORY 757, THE FLIGHT OF THE PHOENIX 26752, THE GLENN MILLER STORY 17394, THE MAN FROM LARAMIE 36235, THE MAN WHO SHOT LIBERTY VALANCE 1533, THE MORTAL STORM 39232, THE NAKED SPUR 28172, THE PHILADELPHIA STORY 2555, THE RARE BREED 31357, THE SHOOTIST 30253, THE SHOP AROUND THE CORNER 32860, THE SHOPWORN ANGEL 24811, THRILLER 32490, THUNDER BAY 4149, TONY 37207, TWO RODE TOGETHER 7957, VERTIGO 13631, VIVACIOUS LADY 22214, WAR 36026, WESTERN 14809, WIFE VS. SECRETARY 26441, WINCHESTER '73 8184, YOU CAN'T TAKE IT WITH YOU 23675, ZERO FOR CONDUCT src, edge_attr, dst 9677, has_genre, 36212 9677, has_tags, 10045 9677, has_tags, 7736 9677, has_tags, 28476 9677, release_year, 33637 9677, starred_actors, 7736 4816, directed_by, 13999 4816, has_tags, 10045 4816, release_year, 27810 4816, starred_actors, 27953 4816, starred_actors, 7736 3204, directed_by, 5661 3204, has_genre, 36026 3204, has_tags, 5661 3204, has_tags, 7736 3204, release_year, 6216 3204, starred_actors, 35990 3204, starred_actors, 7736 36479, has_genre, 30463 36479, has_genre, 24593 36479, has_imdb_rating, 11565 36479, release_year, 6253 36479, starred_actors, 7736 16749, has_genre, 36212 16749, has_genre, 36026 16749, release_year, 26423 16749, starred_actors, 7736 29246, has_genre, 36212 29246, release_year, 6216 29246, starred_actors, 7736 19585, directed_by, 35148 19585, has_genre, 30463 19585, has_tags, 35148 19585, release_year, 21931 19585, starred_actors, 7736 21423, directed_by, 38940 21423, has_genre, 30463 21423, has_genre, 10509 21423, has_tags, 30463 21423, release_year, 4981 21423, starred_actors, 7736 7159, has_genre, 36026 7159, has_tags, 7736 7159, has_tags, 37497 7159, release_year, 11112 7159, starred_actors, 7736 8406, has_genre, 36026 8406, release_year, 27810 8406, starred_actors, 34149 8406, starred_actors, 7736 13009, has_genre, 36212 13009, release_year, 39813 13009, starred_actors, 27953 13009, starred_actors, 7736 1331, directed_by, 23668 1331, has_genre, 36212 1331, has_genre, 10509 1331, has_tags, 14728 1331, has_tags, 36212 1331, has_tags, 10509 1331, has_tags, 23668 1331, has_tags, 7736 1331, starred_actors, 7736 1331, written_by, 23668 26280, has_genre, 30463 26280, release_year, 11112 26280, starred_actors, 7736 26627, has_genre, 36212 26627, release_year, 11112 26627, release_year, 39813 26627, starred_actors, 7736 27297, has_genre, 30463 27297, starred_actors, 7736 20920, directed_by, 38940 20920, has_genre, 30463 20920, has_tags, 38940 20920, release_year, 3863 20920, starred_actors, 7736 20920, starred_actors, 36999 26086, directed_by, 23668 26086, has_genre, 36212 26086, has_tags, 10045 26086, has_tags, 36212 26086, has_tags, 23668 26086, has_tags, 7736 26086, has_tags, 2818 26086, has_tags, 37497 26086, release_year, 11112 26086, starred_actors, 7736 26086, starred_actors, 2818 35223, has_genre, 36026 35223, starred_actors, 7736 23166, has_genre, 30463 23166, has_genre, 36212 23166, release_year, 11 23166, starred_actors, 7736 15311, directed_by, 35148 15311, has_genre, 36212 15311, release_year, 18132 15311, starred_actors, 3706 15311, starred_actors, 7736 9638, directed_by, 18850 9638, has_genre, 30463 9638, starred_actors, 34149 9638, starred_actors, 7736 9638, starred_actors, 14982 19648, has_genre, 30463 19648, has_genre, 24593 19648, has_tags, 7736 19648, release_year, 21931 19648, starred_actors, 7736 19648, starred_actors, 14982 37135, directed_by, 39045 37135, has_genre, 24811 37135, has_tags, 39045 37135, has_tags, 14728 37135, has_tags, 27350 37135, has_tags, 7736 37135, has_tags, 28476 37135, has_tags, 37497 37135, has_tags, 24811 37135, release_year, 1567 37135, starred_actors, 7736 7098, directed_by, 13999 7098, has_genre, 22214 7098, has_tags, 13999 7098, has_tags, 7736 7098, release_year, 4981 7098, starred_actors, 7736 26381, directed_by, 5661 26381, has_genre, 22214 26381, release_year, 14004 26381, starred_actors, 7736 11290, directed_by, 38940 11290, has_genre, 30463 11290, starred_actors, 7736 7763, has_genre, 30463 7763, has_genre, 36026 7763, has_tags, 10045 7763, starred_actors, 34149 7763, starred_actors, 7736 7763, starred_actors, 38066 27995, directed_by, 5661 27995, has_genre, 4763 27995, has_tags, 5661 27995, release_year, 1567 27995, starred_actors, 7736 32820, has_genre, 36212 32820, release_year, 33637 32820, starred_actors, 7736 757, has_genre, 36212 757, has_tags, 7736 757, release_year, 4981 757, starred_actors, 7736 26752, directed_by, 5661 26752, has_tags, 5661 26752, has_tags, 7736 26752, release_year, 1567 26752, starred_actors, 7736 17394, directed_by, 5661 17394, has_genre, 36026 17394, has_tags, 5661 17394, release_year, 14004 17394, starred_actors, 35990 17394, starred_actors, 7736 36235, directed_by, 13255 36235, has_genre, 36026 36235, has_tags, 10045 36235, has_tags, 7736 36235, has_tags, 13255 36235, has_tags, 12435 36235, has_tags, 37497 36235, has_tags, 36026 36235, release_year, 3863 36235, starred_actors, 7736 36235, starred_actors, 12435 1533, has_genre, 36212 1533, release_year, 11 1533, starred_actors, 7736 1533, starred_actors, 31669 39232, directed_by, 5661 39232, has_genre, 36026 39232, has_tags, 5661 39232, has_tags, 10045 39232, has_tags, 7736 39232, release_year, 25717 39232, starred_actors, 7736 28172, has_genre, 30463 28172, has_tags, 10045 28172, has_tags, 7736 28172, has_tags, 37497 28172, release_year, 11 28172, starred_actors, 7736 2555, directed_by, 13999 2555, has_genre, 36026 2555, starred_actors, 7736 2555, starred_actors, 36999 31357, has_genre, 36026 31357, has_tags, 12435 31357, starred_actors, 7736 31357, starred_actors, 12435 30253, has_genre, 30463 30253, has_tags, 10045 30253, has_tags, 7736 30253, has_tags, 37497 30253, release_year, 11 30253, starred_actors, 7736 30253, starred_actors, 31669 32860, has_genre, 36212 32860, has_genre, 22214 32860, release_year, 18132 32860, starred_actors, 7736 32860, starred_actors, 31669 32490, directed_by, 5661 32490, has_genre, 4763 32490, release_year, 25717 32490, starred_actors, 7736 4149, has_genre, 36212 4149, starred_actors, 23008 37207, directed_by, 13255 37207, has_genre, 36026 37207, starred_actors, 7736 37207, starred_actors, 38066 7957, directed_by, 39045 7957, has_genre, 24811 7957, has_tags, 39045 7957, has_tags, 14728 7957, has_tags, 27350 7957, has_tags, 7736 7957, starred_actors, 7736 13631, directed_by, 18850 13631, has_genre, 30463 13631, has_tags, 18850 13631, release_year, 18132 13631, starred_actors, 3706 13631, starred_actors, 7736 14809, directed_by, 35148 14809, has_genre, 30463 14809, has_tags, 35148 14809, has_tags, 7736 14809, release_year, 6253 26441, directed_by, 5661 26441, has_genre, 36026 26441, has_tags, 5661 26441, release_year, 26423 26441, starred_actors, 7736 8184, directed_by, 23668 8184, has_genre, 30463 8184, has_imdb_rating, 11565 8184, has_tags, 23668 8184, has_tags, 7736 8184, release_year, 18132 8184, starred_actors, 7736 8184, starred_actors, 2818 23675, has_tags, 10045 Question: For what reason are JAMES STEWART, PETER FERDINANDO, and ZERO FOR CONDUCT associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JAMES STEWART", "PETER FERDINANDO", "ZERO FOR CONDUCT" ], "valid_edges": [ [ "ANATOMY OF A MURDER", "has_genre", "DRAMA" ], [ "ANATOMY OF A MURDER", "has_tags", "BD-R" ], [ "ANATOMY OF A MURDER", "has_tags", "JAMES STEWART" ], [ "ANATOMY OF A MURDER", "has_tags", "MURDER" ], [ "ANATOMY OF A MURDER", "release_year", "1959" ], [ "ANATOMY OF A MURDER", "starred_actors", "JAMES STEWART" ], [ "BANDOLERO!", "directed_by", "ANDREW V. MCLAGLEN" ], [ "BANDOLERO!", "has_tags", "BD-R" ], [ "BANDOLERO!", "release_year", "1968" ], [ "BANDOLERO!", "starred_actors", "GEORGE KENNEDY" ], [ "BANDOLERO!", "starred_actors", "JAMES STEWART" ], [ "BEND OF THE RIVER", "directed_by", "ANTHONY MANN" ], [ "BEND OF THE RIVER", "has_genre", "WESTERN" ], [ "BEND OF THE RIVER", "has_tags", "ANTHONY MANN" ], [ "BEND OF THE RIVER", "has_tags", "JAMES STEWART" ], [ "BEND OF THE RIVER", "release_year", "1952" ], [ "BEND OF THE RIVER", "starred_actors", "ARTHUR KENNEDY" ], [ "BEND OF THE RIVER", "starred_actors", "JAMES STEWART" ], [ "BORN TO DANCE", "has_genre", "COMEDY" ], [ "BORN TO DANCE", "has_genre", "MUSICAL" ], [ "BORN TO DANCE", "has_imdb_rating", "GOOD" ], [ "BORN TO DANCE", "release_year", "1936" ], [ "BORN TO DANCE", "starred_actors", "JAMES STEWART" ], [ "BROKEN ARROW", "has_genre", "DRAMA" ], [ "BROKEN ARROW", "has_genre", "WESTERN" ], [ "BROKEN ARROW", "release_year", "1950" ], [ "BROKEN ARROW", "starred_actors", "JAMES STEWART" ], [ "CARBINE WILLIAMS", "has_genre", "DRAMA" ], [ "CARBINE WILLIAMS", "release_year", "1952" ], [ "CARBINE WILLIAMS", "starred_actors", "JAMES STEWART" ], [ "COME LIVE WITH ME", "directed_by", "CLARENCE BROWN" ], [ "COME LIVE WITH ME", "has_genre", "COMEDY" ], [ "COME LIVE WITH ME", "has_tags", "CLARENCE BROWN" ], [ "COME LIVE WITH ME", "release_year", "1941" ], [ "COME LIVE WITH ME", "starred_actors", "JAMES STEWART" ], [ "DEAR BRIGITTE", "directed_by", "HENRY KOSTER" ], [ "DEAR BRIGITTE", "has_genre", "COMEDY" ], [ "DEAR BRIGITTE", "has_genre", "FAMILY" ], [ "DEAR BRIGITTE", "has_tags", "COMEDY" ], [ "DEAR BRIGITTE", "release_year", "1965" ], [ "DEAR BRIGITTE", "starred_actors", "JAMES STEWART" ], [ "DESTRY RIDES AGAIN", "has_genre", "WESTERN" ], [ "DESTRY RIDES AGAIN", "has_tags", "JAMES STEWART" ], [ "DESTRY RIDES AGAIN", "has_tags", "NATIONAL FILM REGISTRY" ], [ "DESTRY RIDES AGAIN", "release_year", "1939" ], [ "DESTRY RIDES AGAIN", "starred_actors", "JAMES STEWART" ], [ "FIRECREEK", "has_genre", "WESTERN" ], [ "FIRECREEK", "release_year", "1968" ], [ "FIRECREEK", "starred_actors", "HENRY FONDA" ], [ "FIRECREEK", "starred_actors", "JAMES STEWART" ], [ "FOOLS' PARADE", "has_genre", "DRAMA" ], [ "FOOLS' PARADE", "release_year", "1971" ], [ "FOOLS' PARADE", "starred_actors", "GEORGE KENNEDY" ], [ "FOOLS' PARADE", "starred_actors", "JAMES STEWART" ], [ "IT'S A WONDERFUL LIFE", "directed_by", "FRANK CAPRA" ], [ "IT'S A WONDERFUL LIFE", "has_genre", "DRAMA" ], [ "IT'S A WONDERFUL LIFE", "has_genre", "FAMILY" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "CLASSIC" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "DRAMA" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "FAMILY" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "FRANK CAPRA" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "JAMES STEWART" ], [ "IT'S A WONDERFUL LIFE", "starred_actors", "JAMES STEWART" ], [ "IT'S A WONDERFUL LIFE", "written_by", "FRANK CAPRA" ], [ "IT'S A WONDERFUL WORLD", "has_genre", "COMEDY" ], [ "IT'S A WONDERFUL WORLD", "release_year", "1939" ], [ "IT'S A WONDERFUL WORLD", "starred_actors", "JAMES STEWART" ], [ "MADE FOR EACH OTHER", "has_genre", "DRAMA" ], [ "MADE FOR EACH OTHER", "release_year", "1939" ], [ "MADE FOR EACH OTHER", "release_year", "1971" ], [ "MADE FOR EACH OTHER", "starred_actors", "JAMES STEWART" ], [ "MAGIC TOWN", "has_genre", "COMEDY" ], [ "MAGIC TOWN", "starred_actors", "JAMES STEWART" ], [ "MR. HOBBS TAKES A VACATION", "directed_by", "HENRY KOSTER" ], [ "MR. HOBBS TAKES A VACATION", "has_genre", "COMEDY" ], [ "MR. HOBBS TAKES A VACATION", "has_tags", "HENRY KOSTER" ], [ "MR. HOBBS TAKES A VACATION", "release_year", "1962" ], [ "MR. HOBBS TAKES A VACATION", "starred_actors", "JAMES STEWART" ], [ "MR. HOBBS TAKES A VACATION", "starred_actors", "MAUREEN O'HARA" ], [ "MR. SMITH GOES TO WASHINGTON", "directed_by", "FRANK CAPRA" ], [ "MR. SMITH GOES TO WASHINGTON", "has_genre", "DRAMA" ], [ "MR. SMITH GOES TO WASHINGTON", "has_tags", "BD-R" ], [ "MR. SMITH GOES TO WASHINGTON", "has_tags", "DRAMA" ], [ "MR. SMITH GOES TO WASHINGTON", "has_tags", "FRANK CAPRA" ], [ "MR. SMITH GOES TO WASHINGTON", "has_tags", "JAMES STEWART" ], [ "MR. SMITH GOES TO WASHINGTON", "has_tags", "JEAN ARTHUR" ], [ "MR. SMITH GOES TO WASHINGTON", "has_tags", "NATIONAL FILM REGISTRY" ], [ "MR. SMITH GOES TO WASHINGTON", "release_year", "1939" ], [ "MR. SMITH GOES TO WASHINGTON", "starred_actors", "JAMES STEWART" ], [ "MR. SMITH GOES TO WASHINGTON", "starred_actors", "JEAN ARTHUR" ], [ "NIGHT PASSAGE", "has_genre", "WESTERN" ], [ "NIGHT PASSAGE", "starred_actors", "JAMES STEWART" ], [ "NO TIME FOR COMEDY", "has_genre", "COMEDY" ], [ "NO TIME FOR COMEDY", "has_genre", "DRAMA" ], [ "NO TIME FOR COMEDY", "release_year", "1940" ], [ "NO TIME FOR COMEDY", "starred_actors", "JAMES STEWART" ], [ "OF HUMAN HEARTS", "directed_by", "CLARENCE BROWN" ], [ "OF HUMAN HEARTS", "has_genre", "DRAMA" ], [ "OF HUMAN HEARTS", "release_year", "1938" ], [ "OF HUMAN HEARTS", "starred_actors", "BEULAH BONDI" ], [ "OF HUMAN HEARTS", "starred_actors", "JAMES STEWART" ], [ "ON OUR MERRY WAY", "directed_by", "GEORGE STEVENS" ], [ "ON OUR MERRY WAY", "has_genre", "COMEDY" ], [ "ON OUR MERRY WAY", "starred_actors", "HENRY FONDA" ], [ "ON OUR MERRY WAY", "starred_actors", "JAMES STEWART" ], [ "ON OUR MERRY WAY", "starred_actors", "PAULETTE GODDARD" ], [ "POT O' GOLD", "has_genre", "COMEDY" ], [ "POT O' GOLD", "has_genre", "MUSICAL" ], [ "POT O' GOLD", "has_tags", "JAMES STEWART" ], [ "POT O' GOLD", "release_year", "1941" ], [ "POT O' GOLD", "starred_actors", "JAMES STEWART" ], [ "POT O' GOLD", "starred_actors", "PAULETTE GODDARD" ], [ "REAR WINDOW", "directed_by", "ALFRED HITCHCOCK" ], [ "REAR WINDOW", "has_genre", "THRILLER" ], [ "REAR WINDOW", "has_tags", "ALFRED HITCHCOCK" ], [ "REAR WINDOW", "has_tags", "CLASSIC" ], [ "REAR WINDOW", "has_tags", "HITCHCOCK" ], [ "REAR WINDOW", "has_tags", "JAMES STEWART" ], [ "REAR WINDOW", "has_tags", "MURDER" ], [ "REAR WINDOW", "has_tags", "NATIONAL FILM REGISTRY" ], [ "REAR WINDOW", "has_tags", "THRILLER" ], [ "REAR WINDOW", "release_year", "1954" ], [ "REAR WINDOW", "starred_actors", "JAMES STEWART" ], [ "SHENANDOAH", "directed_by", "ANDREW V. MCLAGLEN" ], [ "SHENANDOAH", "has_genre", "WAR" ], [ "SHENANDOAH", "has_tags", "ANDREW V. MCLAGLEN" ], [ "SHENANDOAH", "has_tags", "JAMES STEWART" ], [ "SHENANDOAH", "release_year", "1965" ], [ "SHENANDOAH", "starred_actors", "JAMES STEWART" ], [ "STRATEGIC AIR COMMAND", "directed_by", "ANTHONY MANN" ], [ "STRATEGIC AIR COMMAND", "has_genre", "WAR" ], [ "STRATEGIC AIR COMMAND", "release_year", "1955" ], [ "STRATEGIC AIR COMMAND", "starred_actors", "JAMES STEWART" ], [ "TAKE HER, SHE'S MINE", "directed_by", "HENRY KOSTER" ], [ "TAKE HER, SHE'S MINE", "has_genre", "COMEDY" ], [ "TAKE HER, SHE'S MINE", "starred_actors", "JAMES STEWART" ], [ "THE CHEYENNE SOCIAL CLUB", "has_genre", "COMEDY" ], [ "THE CHEYENNE SOCIAL CLUB", "has_genre", "WESTERN" ], [ "THE CHEYENNE SOCIAL CLUB", "has_tags", "BD-R" ], [ "THE CHEYENNE SOCIAL CLUB", "starred_actors", "HENRY FONDA" ], [ "THE CHEYENNE SOCIAL CLUB", "starred_actors", "JAMES STEWART" ], [ "THE CHEYENNE SOCIAL CLUB", "starred_actors", "SHIRLEY JONES" ], [ "THE FAR COUNTRY", "directed_by", "ANTHONY MANN" ], [ "THE FAR COUNTRY", "has_genre", "ADVENTURE" ], [ "THE FAR COUNTRY", "has_tags", "ANTHONY MANN" ], [ "THE FAR COUNTRY", "release_year", "1954" ], [ "THE FAR COUNTRY", "starred_actors", "JAMES STEWART" ], [ "THE FBI STORY", "has_genre", "DRAMA" ], [ "THE FBI STORY", "release_year", "1959" ], [ "THE FBI STORY", "starred_actors", "JAMES STEWART" ], [ "THE FLIGHT OF THE PHOENIX", "has_genre", "DRAMA" ], [ "THE FLIGHT OF THE PHOENIX", "has_tags", "JAMES STEWART" ], [ "THE FLIGHT OF THE PHOENIX", "release_year", "1965" ], [ "THE FLIGHT OF THE PHOENIX", "starred_actors", "JAMES STEWART" ], [ "THE GLENN MILLER STORY", "directed_by", "ANTHONY MANN" ], [ "THE GLENN MILLER STORY", "has_tags", "ANTHONY MANN" ], [ "THE GLENN MILLER STORY", "has_tags", "JAMES STEWART" ], [ "THE GLENN MILLER STORY", "release_year", "1954" ], [ "THE GLENN MILLER STORY", "starred_actors", "JAMES STEWART" ], [ "THE MAN FROM LARAMIE", "directed_by", "ANTHONY MANN" ], [ "THE MAN FROM LARAMIE", "has_genre", "WESTERN" ], [ "THE MAN FROM LARAMIE", "has_tags", "ANTHONY MANN" ], [ "THE MAN FROM LARAMIE", "release_year", "1955" ], [ "THE MAN FROM LARAMIE", "starred_actors", "ARTHUR KENNEDY" ], [ "THE MAN FROM LARAMIE", "starred_actors", "JAMES STEWART" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "directed_by", "JOHN FORD" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_genre", "WESTERN" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "BD-R" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "JAMES STEWART" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "JOHN FORD" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "JOHN WAYNE" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "WESTERN" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "release_year", "1962" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "starred_actors", "JAMES STEWART" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "starred_actors", "JOHN WAYNE" ], [ "THE MORTAL STORM", "has_genre", "DRAMA" ], [ "THE MORTAL STORM", "release_year", "1940" ], [ "THE MORTAL STORM", "starred_actors", "JAMES STEWART" ], [ "THE MORTAL STORM", "starred_actors", "MARGARET SULLAVAN" ], [ "THE NAKED SPUR", "directed_by", "ANTHONY MANN" ], [ "THE NAKED SPUR", "has_genre", "WESTERN" ], [ "THE NAKED SPUR", "has_tags", "ANTHONY MANN" ], [ "THE NAKED SPUR", "has_tags", "BD-R" ], [ "THE NAKED SPUR", "has_tags", "JAMES STEWART" ], [ "THE NAKED SPUR", "release_year", "1953" ], [ "THE NAKED SPUR", "starred_actors", "JAMES STEWART" ], [ "THE PHILADELPHIA STORY", "has_genre", "COMEDY" ], [ "THE PHILADELPHIA STORY", "has_tags", "BD-R" ], [ "THE PHILADELPHIA STORY", "has_tags", "JAMES STEWART" ], [ "THE PHILADELPHIA STORY", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE PHILADELPHIA STORY", "release_year", "1940" ], [ "THE PHILADELPHIA STORY", "starred_actors", "JAMES STEWART" ], [ "THE RARE BREED", "directed_by", "ANDREW V. MCLAGLEN" ], [ "THE RARE BREED", "has_genre", "WESTERN" ], [ "THE RARE BREED", "starred_actors", "JAMES STEWART" ], [ "THE RARE BREED", "starred_actors", "MAUREEN O'HARA" ], [ "THE SHOOTIST", "has_genre", "WESTERN" ], [ "THE SHOOTIST", "has_tags", "JOHN WAYNE" ], [ "THE SHOOTIST", "starred_actors", "JAMES STEWART" ], [ "THE SHOOTIST", "starred_actors", "JOHN WAYNE" ], [ "THE SHOP AROUND THE CORNER", "has_genre", "COMEDY" ], [ "THE SHOP AROUND THE CORNER", "has_tags", "BD-R" ], [ "THE SHOP AROUND THE CORNER", "has_tags", "JAMES STEWART" ], [ "THE SHOP AROUND THE CORNER", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE SHOP AROUND THE CORNER", "release_year", "1940" ], [ "THE SHOP AROUND THE CORNER", "starred_actors", "JAMES STEWART" ], [ "THE SHOP AROUND THE CORNER", "starred_actors", "MARGARET SULLAVAN" ], [ "THE SHOPWORN ANGEL", "has_genre", "DRAMA" ], [ "THE SHOPWORN ANGEL", "has_genre", "WAR" ], [ "THE SHOPWORN ANGEL", "release_year", "1938" ], [ "THE SHOPWORN ANGEL", "starred_actors", "JAMES STEWART" ], [ "THE SHOPWORN ANGEL", "starred_actors", "MARGARET SULLAVAN" ], [ "THUNDER BAY", "directed_by", "ANTHONY MANN" ], [ "THUNDER BAY", "has_genre", "ADVENTURE" ], [ "THUNDER BAY", "release_year", "1953" ], [ "THUNDER BAY", "starred_actors", "JAMES STEWART" ], [ "TONY", "has_genre", "DRAMA" ], [ "TONY", "starred_actors", "PETER FERDINANDO" ], [ "TWO RODE TOGETHER", "directed_by", "JOHN FORD" ], [ "TWO RODE TOGETHER", "has_genre", "WESTERN" ], [ "TWO RODE TOGETHER", "starred_actors", "JAMES STEWART" ], [ "TWO RODE TOGETHER", "starred_actors", "SHIRLEY JONES" ], [ "VERTIGO", "directed_by", "ALFRED HITCHCOCK" ], [ "VERTIGO", "has_genre", "THRILLER" ], [ "VERTIGO", "has_tags", "ALFRED HITCHCOCK" ], [ "VERTIGO", "has_tags", "CLASSIC" ], [ "VERTIGO", "has_tags", "HITCHCOCK" ], [ "VERTIGO", "has_tags", "JAMES STEWART" ], [ "VERTIGO", "starred_actors", "JAMES STEWART" ], [ "VIVACIOUS LADY", "directed_by", "GEORGE STEVENS" ], [ "VIVACIOUS LADY", "has_genre", "COMEDY" ], [ "VIVACIOUS LADY", "has_tags", "GEORGE STEVENS" ], [ "VIVACIOUS LADY", "release_year", "1938" ], [ "VIVACIOUS LADY", "starred_actors", "BEULAH BONDI" ], [ "VIVACIOUS LADY", "starred_actors", "JAMES STEWART" ], [ "WIFE VS. SECRETARY", "directed_by", "CLARENCE BROWN" ], [ "WIFE VS. SECRETARY", "has_genre", "COMEDY" ], [ "WIFE VS. SECRETARY", "has_tags", "CLARENCE BROWN" ], [ "WIFE VS. SECRETARY", "has_tags", "JAMES STEWART" ], [ "WIFE VS. SECRETARY", "release_year", "1936" ], [ "WINCHESTER '73", "directed_by", "ANTHONY MANN" ], [ "WINCHESTER '73", "has_genre", "WESTERN" ], [ "WINCHESTER '73", "has_tags", "ANTHONY MANN" ], [ "WINCHESTER '73", "release_year", "1950" ], [ "WINCHESTER '73", "starred_actors", "JAMES STEWART" ], [ "YOU CAN'T TAKE IT WITH YOU", "directed_by", "FRANK CAPRA" ], [ "YOU CAN'T TAKE IT WITH YOU", "has_genre", "COMEDY" ], [ "YOU CAN'T TAKE IT WITH YOU", "has_imdb_rating", "GOOD" ], [ "YOU CAN'T TAKE IT WITH YOU", "has_tags", "FRANK CAPRA" ], [ "YOU CAN'T TAKE IT WITH YOU", "has_tags", "JAMES STEWART" ], [ "YOU CAN'T TAKE IT WITH YOU", "release_year", "1938" ], [ "YOU CAN'T TAKE IT WITH YOU", "starred_actors", "JAMES STEWART" ], [ "YOU CAN'T TAKE IT WITH YOU", "starred_actors", "JEAN ARTHUR" ], [ "ZERO FOR CONDUCT", "has_tags", "BD-R" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 7977, 1969 27938, BRIGITTE BARDOT 27948, BRUCE DAVISON 28933, LAST SUMMER 12165, SHALAKO 8153, THE HANOI HILTON 18187, ULZANA'S RAID 22214, WAR 36026, WESTERN src, edge_attr, dst 7977, has_genre, 22214 28933, release_year, 7977 28933, starred_actors, 27948 12165, has_genre, 36026 12165, starred_actors, 27938 8153, has_genre, 22214 18187, has_genre, 36026 18187, starred_actors, 27948 Question: How are BRIGITTE BARDOT, BRUCE DAVISON, and THE HANOI HILTON related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BRIGITTE BARDOT", "BRUCE DAVISON", "THE HANOI HILTON" ], "valid_edges": [ [ "1969", "has_genre", "WAR" ], [ "LAST SUMMER", "release_year", "1969" ], [ "LAST SUMMER", "starred_actors", "BRUCE DAVISON" ], [ "SHALAKO", "has_genre", "WESTERN" ], [ "SHALAKO", "starred_actors", "BRIGITTE BARDOT" ], [ "THE HANOI HILTON", "has_genre", "WAR" ], [ "ULZANA'S RAID", "has_genre", "WESTERN" ], [ "ULZANA'S RAID", "starred_actors", "BRUCE DAVISON" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35935, 2002 35845, 2006 30496, EMMETT'S MARK 36222, FEARLESS 35711, HARRY DEAN STANTON 19637, INLAND EMPIRE 31899, KEITH SNYDER 26470, NATIONALISM 7083, SONNY src, edge_attr, dst 30496, directed_by, 31899 30496, release_year, 35935 30496, written_by, 31899 36222, has_tags, 26470 36222, release_year, 35845 19637, has_tags, 35711 19637, release_year, 35845 7083, release_year, 35935 7083, starred_actors, 35711 Question: How are HARRY DEAN STANTON, KEITH SNYDER, and NATIONALISM related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "HARRY DEAN STANTON", "KEITH SNYDER", "NATIONALISM" ], "valid_edges": [ [ "EMMETT'S MARK", "directed_by", "KEITH SNYDER" ], [ "EMMETT'S MARK", "release_year", "2002" ], [ "EMMETT'S MARK", "written_by", "KEITH SNYDER" ], [ "FEARLESS", "has_tags", "NATIONALISM" ], [ "FEARLESS", "release_year", "2006" ], [ "INLAND EMPIRE", "has_tags", "HARRY DEAN STANTON" ], [ "INLAND EMPIRE", "release_year", "2006" ], [ "SONNY", "release_year", "2002" ], [ "SONNY", "starred_actors", "HARRY DEAN STANTON" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1097, 2003 20497, BEN AFFLECK 26583, BOUNCE 31208, DAREDEVIL 13799, DIABOLIQUE 37448, DON ROOS 35535, GIGLI 533, GRETA SCACCHI 25010, JENNIFER LOPEZ 21861, JERSEY GIRL 60, PAYCHECK 2196, SHATTERED 24811, THRILLER src, edge_attr, dst 26583, directed_by, 37448 26583, starred_actors, 20497 26583, written_by, 37448 31208, has_tags, 20497 31208, release_year, 1097 31208, starred_actors, 20497 13799, has_genre, 24811 13799, written_by, 37448 35535, has_tags, 20497 35535, has_tags, 25010 35535, release_year, 1097 35535, starred_actors, 20497 21861, has_tags, 20497 21861, has_tags, 25010 60, has_tags, 20497 60, release_year, 1097 60, starred_actors, 20497 2196, has_genre, 24811 2196, starred_actors, 533 Question: How are DON ROOS, GIGLI, and GRETA SCACCHI related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DON ROOS", "GIGLI", "GRETA SCACCHI" ], "valid_edges": [ [ "BOUNCE", "directed_by", "DON ROOS" ], [ "BOUNCE", "starred_actors", "BEN AFFLECK" ], [ "BOUNCE", "written_by", "DON ROOS" ], [ "DAREDEVIL", "has_tags", "BEN AFFLECK" ], [ "DAREDEVIL", "release_year", "2003" ], [ "DAREDEVIL", "starred_actors", "BEN AFFLECK" ], [ "DIABOLIQUE", "has_genre", "THRILLER" ], [ "DIABOLIQUE", "written_by", "DON ROOS" ], [ "GIGLI", "has_tags", "BEN AFFLECK" ], [ "GIGLI", "has_tags", "JENNIFER LOPEZ" ], [ "GIGLI", "release_year", "2003" ], [ "GIGLI", "starred_actors", "BEN AFFLECK" ], [ "JERSEY GIRL", "has_tags", "BEN AFFLECK" ], [ "JERSEY GIRL", "has_tags", "JENNIFER LOPEZ" ], [ "PAYCHECK", "has_tags", "BEN AFFLECK" ], [ "PAYCHECK", "release_year", "2003" ], [ "PAYCHECK", "starred_actors", "BEN AFFLECK" ], [ "SHATTERED", "has_genre", "THRILLER" ], [ "SHATTERED", "starred_actors", "GRETA SCACCHI" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17687, AMERICA'S SWEETHEARTS 24598, CHRISTMAS WITH THE KRANKS 30463, COMEDY 23734, COUPE DE VILLE 36212, DRAMA 13308, FREEDOMLAND 28038, HAPPY GO LOVELY 22891, JOE ROTH 21683, PARIS TROUT 9956, PETER DEXTER src, edge_attr, dst 17687, directed_by, 22891 17687, has_genre, 30463 24598, directed_by, 22891 24598, has_genre, 30463 23734, directed_by, 22891 23734, has_genre, 30463 23734, has_genre, 36212 13308, directed_by, 22891 13308, has_genre, 36212 28038, has_genre, 30463 21683, has_genre, 36212 21683, written_by, 9956 Question: How are HAPPY GO LOVELY, JOE ROTH, and PETER DEXTER related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "HAPPY GO LOVELY", "JOE ROTH", "PETER DEXTER" ], "valid_edges": [ [ "AMERICA'S SWEETHEARTS", "directed_by", "JOE ROTH" ], [ "AMERICA'S SWEETHEARTS", "has_genre", "COMEDY" ], [ "CHRISTMAS WITH THE KRANKS", "directed_by", "JOE ROTH" ], [ "CHRISTMAS WITH THE KRANKS", "has_genre", "COMEDY" ], [ "COUPE DE VILLE", "directed_by", "JOE ROTH" ], [ "COUPE DE VILLE", "has_genre", "COMEDY" ], [ "COUPE DE VILLE", "has_genre", "DRAMA" ], [ "FREEDOMLAND", "directed_by", "JOE ROTH" ], [ "FREEDOMLAND", "has_genre", "DRAMA" ], [ "HAPPY GO LOVELY", "has_genre", "COMEDY" ], [ "PARIS TROUT", "has_genre", "DRAMA" ], [ "PARIS TROUT", "written_by", "PETER DEXTER" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 7841, 1987 8486, 1999 6252, A CHINESE GHOST STORY 31344, A LEAGUE OF THEIR OWN 36420, A TAXING WOMAN 27451, ADDICTED TO LOVE 16054, ADVENTURES IN BABYSITTING 18051, AFTER HOURS 3473, AMAZON WOMEN ON THE MOON 1546, AN AMERICAN WEREWOLF IN LONDON 17761, BABY BOOM 37155, BACHELOR PARTY VEGAS 2069, BACK TO THE BEACH 34587, BAD TASTE 24579, BEVERLY HILLS COP II 7462, BEYOND THERAPY 18646, BIG SHOTS 7101, BLIND DATE 8781, BORN IN EAST L.A. 15416, BOYFRIENDS AND GIRLFRIENDS 32043, BROADCAST NEWS 30182, BURGLAR 29437, CAN'T BUY ME LOVE 10710, CLAIRE BLOOM 30463, COMEDY 19984, CREEPSHOW 2 5277, CRITICAL CONDITION 17866, CROSS MY HEART 12629, DATE WITH AN ANGEL 2382, DESPERATELY SEEKING SUSAN 37748, DONALD FAISON 31407, DRAGNET 32705, ERNEST GOES TO CAMP 16661, EVIL DEAD II 21763, GOOD MORNING, VIETNAM 11469, GRIFFIN DUNNE 32384, HAMLET GOES BUSINESS 12085, HAPPY NEW YEAR 28307, HARRY AND THE HENDERSONS 24557, HEAD OFFICE 36859, HELLO AGAIN 37602, HOLLYWOOD SHUFFLE 24940, HOPE AND GLORY 31686, HOT PURSUIT 23849, HOUSEKEEPING 9007, HUNK 16321, INNERSPACE 1166, ISHTAR 21514, JAMES FOLEY 25024, KEN FINKLEMAN 20866, LEIF 30420, LEONARD PART 6 39520, LETHAL WEAPON 28811, LIKE FATHER LIKE SON 1130, LISA PICARD IS FAMOUS 11952, MADONNA 7423, MAID TO ORDER 22842, MAKING MR. RIGHT 32481, MANNEQUIN 33763, MOONSTRUCK 16298, MORGAN STEWART'S COMING HOME 7353, MOVIE 43 36631, MUNCHIES 20549, NADINE 19632, NEXT DAY AIR 36424, OUTRAGEOUS FORTUNE 253, OVERBOARD 16172, PRACTICAL MAGIC 12939, PROJECT X 15214, RADIO DAYS 21462, RAISING ARIZONA 2855, REAL MEN 20748, RECKLESS 10717, RENT-A-COP 9184, RETURN TO HORROR HIGH 39429, ROXANNE 11041, SILENT NIGHT, DEADLY NIGHT PART 2 16951, STAKEOUT 3563, SUMMER SCHOOL 4755, SURF NAZIS MUST DIE 26790, SWEPT AWAY 32018, TEEN WOLF TOO 10020, THE ACCIDENTAL HUSBAND 27730, THE ALLNIGHTER 10194, THE BRAVE LITTLE TOASTER 38918, THE FAMILY 11787, THE HAUNTING 33993, THE MONSTER SQUAD 20674, THE NEXT BEST THING 17411, THE PICK-UP ARTIST 29641, THE PRINCESS BRIDE 27344, THE SQUEEZE 14621, THE WITCHES OF EASTWICK 32233, THREE O'CLOCK HIGH 26294, THROW MOMMA FROM THE TRAIN 22559, TIN MEN 36468, TOUGH GUYS DON'T DANCE 23874, TRIPPIN' 35371, UPTOWN GIRLS 6124, WALK LIKE A MAN 16913, WHO'S THAT GIRL 6981, WISH YOU WERE HERE src, edge_attr, dst 6252, has_genre, 30463 6252, release_year, 7841 31344, has_genre, 30463 31344, has_tags, 11952 31344, starred_actors, 11952 36420, has_genre, 30463 36420, release_year, 7841 27451, directed_by, 11469 27451, has_genre, 30463 27451, has_tags, 30463 16054, has_genre, 30463 16054, release_year, 7841 18051, has_genre, 30463 18051, starred_actors, 11469 3473, has_genre, 30463 3473, release_year, 7841 1546, has_genre, 30463 1546, has_tags, 11469 1546, starred_actors, 11469 17761, has_genre, 30463 17761, release_year, 7841 37155, has_genre, 30463 37155, starred_actors, 37748 2069, has_genre, 30463 2069, release_year, 7841 34587, has_genre, 30463 34587, release_year, 7841 24579, has_genre, 30463 24579, release_year, 7841 7462, has_genre, 30463 7462, release_year, 7841 18646, has_genre, 30463 18646, release_year, 7841 7101, has_genre, 30463 7101, release_year, 7841 8781, has_genre, 30463 8781, release_year, 7841 15416, has_genre, 30463 15416, release_year, 7841 32043, has_genre, 30463 32043, release_year, 7841 30182, has_genre, 30463 30182, release_year, 7841 29437, has_genre, 30463 29437, release_year, 7841 19984, has_genre, 30463 19984, release_year, 7841 5277, has_genre, 30463 5277, release_year, 7841 17866, has_genre, 30463 17866, release_year, 7841 12629, has_genre, 30463 12629, release_year, 7841 2382, has_genre, 30463 2382, has_tags, 11952 2382, starred_actors, 11952 31407, has_genre, 30463 31407, release_year, 7841 32705, has_genre, 30463 32705, release_year, 7841 16661, has_genre, 30463 16661, release_year, 7841 21763, has_genre, 30463 21763, release_year, 7841 32384, has_genre, 30463 32384, has_tags, 30463 32384, release_year, 7841 12085, has_genre, 30463 12085, release_year, 7841 28307, has_genre, 30463 28307, has_tags, 30463 28307, release_year, 7841 24557, directed_by, 25024 24557, has_genre, 30463 24557, written_by, 25024 36859, has_genre, 30463 36859, release_year, 7841 37602, has_genre, 30463 37602, release_year, 7841 24940, has_genre, 30463 24940, release_year, 7841 31686, has_genre, 30463 31686, release_year, 7841 23849, has_genre, 30463 23849, release_year, 7841 9007, has_genre, 30463 9007, release_year, 7841 16321, has_genre, 30463 16321, release_year, 7841 1166, has_genre, 30463 1166, release_year, 7841 20866, has_genre, 30463 20866, release_year, 7841 30420, has_genre, 30463 30420, release_year, 7841 39520, has_tags, 30463 39520, release_year, 7841 28811, has_genre, 30463 28811, release_year, 7841 1130, directed_by, 11469 1130, has_genre, 30463 1130, starred_actors, 11469 7423, has_genre, 30463 7423, release_year, 7841 22842, has_genre, 30463 22842, release_year, 7841 32481, has_genre, 30463 32481, release_year, 7841 33763, has_genre, 30463 33763, release_year, 7841 16298, has_genre, 30463 16298, release_year, 7841 7353, directed_by, 11469 7353, has_genre, 30463 36631, has_genre, 30463 36631, release_year, 7841 20549, has_genre, 30463 20549, release_year, 7841 19632, has_genre, 30463 19632, starred_actors, 37748 36424, has_genre, 30463 36424, release_year, 7841 253, has_genre, 30463 253, release_year, 7841 16172, directed_by, 11469 16172, has_genre, 30463 12939, has_genre, 30463 12939, release_year, 7841 15214, has_genre, 30463 15214, release_year, 7841 21462, has_genre, 30463 21462, has_tags, 30463 21462, release_year, 7841 2855, has_genre, 30463 2855, has_tags, 30463 2855, release_year, 7841 20748, directed_by, 21514 20748, has_genre, 30463 10717, has_genre, 30463 10717, release_year, 7841 9184, has_genre, 30463 9184, release_year, 7841 39429, has_genre, 30463 39429, release_year, 7841 11041, has_genre, 30463 11041, release_year, 7841 16951, has_genre, 30463 16951, release_year, 7841 3563, has_genre, 30463 3563, has_tags, 30463 3563, release_year, 7841 4755, has_genre, 30463 4755, release_year, 7841 26790, has_genre, 30463 26790, has_tags, 11952 26790, starred_actors, 11952 32018, has_genre, 30463 32018, release_year, 7841 10020, directed_by, 11469 10020, has_genre, 30463 27730, has_genre, 30463 27730, release_year, 7841 10194, has_genre, 30463 10194, release_year, 7841 38918, has_genre, 30463 38918, release_year, 7841 11787, release_year, 8486 11787, starred_actors, 10710 33993, has_genre, 30463 33993, release_year, 7841 20674, has_genre, 30463 20674, has_tags, 11952 20674, starred_actors, 11952 17411, has_genre, 30463 17411, release_year, 7841 29641, has_genre, 30463 29641, has_tags, 30463 29641, release_year, 7841 27344, has_genre, 30463 27344, release_year, 7841 14621, has_genre, 30463 14621, release_year, 7841 32233, has_genre, 30463 32233, release_year, 7841 26294, has_genre, 30463 26294, has_tags, 30463 26294, release_year, 7841 22559, has_genre, 30463 22559, release_year, 7841 36468, has_genre, 30463 36468, release_year, 7841 23874, has_genre, 30463 23874, release_year, 8486 23874, starred_actors, 37748 35371, has_genre, 30463 35371, starred_actors, 37748 6124, has_genre, 30463 6124, release_year, 7841 16913, directed_by, 21514 16913, has_genre, 30463 16913, has_tags, 21514 16913, has_tags, 11952 16913, release_year, 7841 16913, starred_actors, 11469 16913, starred_actors, 11952 16913, written_by, 25024 6981, has_genre, 30463 6981, release_year, 7841 Question: For what reason are CLAIRE BLOOM, DONALD FAISON, and WHO'S THAT GIRL associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CLAIRE BLOOM", "DONALD FAISON", "WHO'S THAT GIRL" ], "valid_edges": [ [ "A CHINESE GHOST STORY", "has_genre", "COMEDY" ], [ "A CHINESE GHOST STORY", "release_year", "1987" ], [ "A LEAGUE OF THEIR OWN", "has_genre", "COMEDY" ], [ "A LEAGUE OF THEIR OWN", "has_tags", "MADONNA" ], [ "A LEAGUE OF THEIR OWN", "starred_actors", "MADONNA" ], [ "A TAXING WOMAN", "has_genre", "COMEDY" ], [ "A TAXING WOMAN", "release_year", "1987" ], [ "ADDICTED TO LOVE", "directed_by", "GRIFFIN DUNNE" ], [ "ADDICTED TO LOVE", "has_genre", "COMEDY" ], [ "ADDICTED TO LOVE", "has_tags", "COMEDY" ], [ "ADVENTURES IN BABYSITTING", "has_genre", "COMEDY" ], [ "ADVENTURES IN BABYSITTING", "release_year", "1987" ], [ "AFTER HOURS", "has_genre", "COMEDY" ], [ "AFTER HOURS", "starred_actors", "GRIFFIN DUNNE" ], [ "AMAZON WOMEN ON THE MOON", "has_genre", "COMEDY" ], [ "AMAZON WOMEN ON THE MOON", "release_year", "1987" ], [ "AN AMERICAN WEREWOLF IN LONDON", "has_genre", "COMEDY" ], [ "AN AMERICAN WEREWOLF IN LONDON", "has_tags", "GRIFFIN DUNNE" ], [ "AN AMERICAN WEREWOLF IN LONDON", "starred_actors", "GRIFFIN DUNNE" ], [ "BABY BOOM", "has_genre", "COMEDY" ], [ "BABY BOOM", "release_year", "1987" ], [ "BACHELOR PARTY VEGAS", "has_genre", "COMEDY" ], [ "BACHELOR PARTY VEGAS", "starred_actors", "DONALD FAISON" ], [ "BACK TO THE BEACH", "has_genre", "COMEDY" ], [ "BACK TO THE BEACH", "release_year", "1987" ], [ "BAD TASTE", "has_genre", "COMEDY" ], [ "BAD TASTE", "release_year", "1987" ], [ "BEVERLY HILLS COP II", "has_genre", "COMEDY" ], [ "BEVERLY HILLS COP II", "release_year", "1987" ], [ "BEYOND THERAPY", "has_genre", "COMEDY" ], [ "BEYOND THERAPY", "release_year", "1987" ], [ "BIG SHOTS", "has_genre", "COMEDY" ], [ "BIG SHOTS", "release_year", "1987" ], [ "BLIND DATE", "has_genre", "COMEDY" ], [ "BLIND DATE", "release_year", "1987" ], [ "BORN IN EAST L.A.", "has_genre", "COMEDY" ], [ "BORN IN EAST L.A.", "release_year", "1987" ], [ "BOYFRIENDS AND GIRLFRIENDS", "has_genre", "COMEDY" ], [ "BOYFRIENDS AND GIRLFRIENDS", "release_year", "1987" ], [ "BROADCAST NEWS", "has_genre", "COMEDY" ], [ "BROADCAST NEWS", "release_year", "1987" ], [ "BURGLAR", "has_genre", "COMEDY" ], [ "BURGLAR", "release_year", "1987" ], [ "CAN'T BUY ME LOVE", "has_genre", "COMEDY" ], [ "CAN'T BUY ME LOVE", "release_year", "1987" ], [ "CREEPSHOW 2", "has_genre", "COMEDY" ], [ "CREEPSHOW 2", "release_year", "1987" ], [ "CRITICAL CONDITION", "has_genre", "COMEDY" ], [ "CRITICAL CONDITION", "release_year", "1987" ], [ "CROSS MY HEART", "has_genre", "COMEDY" ], [ "CROSS MY HEART", "release_year", "1987" ], [ "DATE WITH AN ANGEL", "has_genre", "COMEDY" ], [ "DATE WITH AN ANGEL", "release_year", "1987" ], [ "DESPERATELY SEEKING SUSAN", "has_genre", "COMEDY" ], [ "DESPERATELY SEEKING SUSAN", "has_tags", "MADONNA" ], [ "DESPERATELY SEEKING SUSAN", "starred_actors", "MADONNA" ], [ "DRAGNET", "has_genre", "COMEDY" ], [ "DRAGNET", "release_year", "1987" ], [ "ERNEST GOES TO CAMP", "has_genre", "COMEDY" ], [ "ERNEST GOES TO CAMP", "release_year", "1987" ], [ "EVIL DEAD II", "has_genre", "COMEDY" ], [ "EVIL DEAD II", "release_year", "1987" ], [ "GOOD MORNING, VIETNAM", "has_genre", "COMEDY" ], [ "GOOD MORNING, VIETNAM", "release_year", "1987" ], [ "HAMLET GOES BUSINESS", "has_genre", "COMEDY" ], [ "HAMLET GOES BUSINESS", "has_tags", "COMEDY" ], [ "HAMLET GOES BUSINESS", "release_year", "1987" ], [ "HAPPY NEW YEAR", "has_genre", "COMEDY" ], [ "HAPPY NEW YEAR", "release_year", "1987" ], [ "HARRY AND THE HENDERSONS", "has_genre", "COMEDY" ], [ "HARRY AND THE HENDERSONS", "has_tags", "COMEDY" ], [ "HARRY AND THE HENDERSONS", "release_year", "1987" ], [ "HEAD OFFICE", "directed_by", "KEN FINKLEMAN" ], [ "HEAD OFFICE", "has_genre", "COMEDY" ], [ "HEAD OFFICE", "written_by", "KEN FINKLEMAN" ], [ "HELLO AGAIN", "has_genre", "COMEDY" ], [ "HELLO AGAIN", "release_year", "1987" ], [ "HOLLYWOOD SHUFFLE", "has_genre", "COMEDY" ], [ "HOLLYWOOD SHUFFLE", "release_year", "1987" ], [ "HOPE AND GLORY", "has_genre", "COMEDY" ], [ "HOPE AND GLORY", "release_year", "1987" ], [ "HOT PURSUIT", "has_genre", "COMEDY" ], [ "HOT PURSUIT", "release_year", "1987" ], [ "HOUSEKEEPING", "has_genre", "COMEDY" ], [ "HOUSEKEEPING", "release_year", "1987" ], [ "HUNK", "has_genre", "COMEDY" ], [ "HUNK", "release_year", "1987" ], [ "INNERSPACE", "has_genre", "COMEDY" ], [ "INNERSPACE", "release_year", "1987" ], [ "ISHTAR", "has_genre", "COMEDY" ], [ "ISHTAR", "release_year", "1987" ], [ "LEIF", "has_genre", "COMEDY" ], [ "LEIF", "release_year", "1987" ], [ "LEONARD PART 6", "has_genre", "COMEDY" ], [ "LEONARD PART 6", "release_year", "1987" ], [ "LETHAL WEAPON", "has_tags", "COMEDY" ], [ "LETHAL WEAPON", "release_year", "1987" ], [ "LIKE FATHER LIKE SON", "has_genre", "COMEDY" ], [ "LIKE FATHER LIKE SON", "release_year", "1987" ], [ "LISA PICARD IS FAMOUS", "directed_by", "GRIFFIN DUNNE" ], [ "LISA PICARD IS FAMOUS", "has_genre", "COMEDY" ], [ "LISA PICARD IS FAMOUS", "starred_actors", "GRIFFIN DUNNE" ], [ "MAID TO ORDER", "has_genre", "COMEDY" ], [ "MAID TO ORDER", "release_year", "1987" ], [ "MAKING MR. RIGHT", "has_genre", "COMEDY" ], [ "MAKING MR. RIGHT", "release_year", "1987" ], [ "MANNEQUIN", "has_genre", "COMEDY" ], [ "MANNEQUIN", "release_year", "1987" ], [ "MOONSTRUCK", "has_genre", "COMEDY" ], [ "MOONSTRUCK", "release_year", "1987" ], [ "MORGAN STEWART'S COMING HOME", "has_genre", "COMEDY" ], [ "MORGAN STEWART'S COMING HOME", "release_year", "1987" ], [ "MOVIE 43", "directed_by", "GRIFFIN DUNNE" ], [ "MOVIE 43", "has_genre", "COMEDY" ], [ "MUNCHIES", "has_genre", "COMEDY" ], [ "MUNCHIES", "release_year", "1987" ], [ "NADINE", "has_genre", "COMEDY" ], [ "NADINE", "release_year", "1987" ], [ "NEXT DAY AIR", "has_genre", "COMEDY" ], [ "NEXT DAY AIR", "starred_actors", "DONALD FAISON" ], [ "OUTRAGEOUS FORTUNE", "has_genre", "COMEDY" ], [ "OUTRAGEOUS FORTUNE", "release_year", "1987" ], [ "OVERBOARD", "has_genre", "COMEDY" ], [ "OVERBOARD", "release_year", "1987" ], [ "PRACTICAL MAGIC", "directed_by", "GRIFFIN DUNNE" ], [ "PRACTICAL MAGIC", "has_genre", "COMEDY" ], [ "PROJECT X", "has_genre", "COMEDY" ], [ "PROJECT X", "release_year", "1987" ], [ "RADIO DAYS", "has_genre", "COMEDY" ], [ "RADIO DAYS", "release_year", "1987" ], [ "RAISING ARIZONA", "has_genre", "COMEDY" ], [ "RAISING ARIZONA", "has_tags", "COMEDY" ], [ "RAISING ARIZONA", "release_year", "1987" ], [ "REAL MEN", "has_genre", "COMEDY" ], [ "REAL MEN", "has_tags", "COMEDY" ], [ "REAL MEN", "release_year", "1987" ], [ "RECKLESS", "directed_by", "JAMES FOLEY" ], [ "RECKLESS", "has_genre", "COMEDY" ], [ "RENT-A-COP", "has_genre", "COMEDY" ], [ "RENT-A-COP", "release_year", "1987" ], [ "RETURN TO HORROR HIGH", "has_genre", "COMEDY" ], [ "RETURN TO HORROR HIGH", "release_year", "1987" ], [ "ROXANNE", "has_genre", "COMEDY" ], [ "ROXANNE", "release_year", "1987" ], [ "SILENT NIGHT, DEADLY NIGHT PART 2", "has_genre", "COMEDY" ], [ "SILENT NIGHT, DEADLY NIGHT PART 2", "release_year", "1987" ], [ "STAKEOUT", "has_genre", "COMEDY" ], [ "STAKEOUT", "release_year", "1987" ], [ "SUMMER SCHOOL", "has_genre", "COMEDY" ], [ "SUMMER SCHOOL", "has_tags", "COMEDY" ], [ "SUMMER SCHOOL", "release_year", "1987" ], [ "SURF NAZIS MUST DIE", "has_genre", "COMEDY" ], [ "SURF NAZIS MUST DIE", "release_year", "1987" ], [ "SWEPT AWAY", "has_genre", "COMEDY" ], [ "SWEPT AWAY", "has_tags", "MADONNA" ], [ "SWEPT AWAY", "starred_actors", "MADONNA" ], [ "TEEN WOLF TOO", "has_genre", "COMEDY" ], [ "TEEN WOLF TOO", "release_year", "1987" ], [ "THE ACCIDENTAL HUSBAND", "directed_by", "GRIFFIN DUNNE" ], [ "THE ACCIDENTAL HUSBAND", "has_genre", "COMEDY" ], [ "THE ALLNIGHTER", "has_genre", "COMEDY" ], [ "THE ALLNIGHTER", "release_year", "1987" ], [ "THE BRAVE LITTLE TOASTER", "has_genre", "COMEDY" ], [ "THE BRAVE LITTLE TOASTER", "release_year", "1987" ], [ "THE FAMILY", "has_genre", "COMEDY" ], [ "THE FAMILY", "release_year", "1987" ], [ "THE HAUNTING", "release_year", "1999" ], [ "THE HAUNTING", "starred_actors", "CLAIRE BLOOM" ], [ "THE MONSTER SQUAD", "has_genre", "COMEDY" ], [ "THE MONSTER SQUAD", "release_year", "1987" ], [ "THE NEXT BEST THING", "has_genre", "COMEDY" ], [ "THE NEXT BEST THING", "has_tags", "MADONNA" ], [ "THE NEXT BEST THING", "starred_actors", "MADONNA" ], [ "THE PICK-UP ARTIST", "has_genre", "COMEDY" ], [ "THE PICK-UP ARTIST", "release_year", "1987" ], [ "THE PRINCESS BRIDE", "has_genre", "COMEDY" ], [ "THE PRINCESS BRIDE", "has_tags", "COMEDY" ], [ "THE PRINCESS BRIDE", "release_year", "1987" ], [ "THE SQUEEZE", "has_genre", "COMEDY" ], [ "THE SQUEEZE", "release_year", "1987" ], [ "THE WITCHES OF EASTWICK", "has_genre", "COMEDY" ], [ "THE WITCHES OF EASTWICK", "release_year", "1987" ], [ "THREE O'CLOCK HIGH", "has_genre", "COMEDY" ], [ "THREE O'CLOCK HIGH", "release_year", "1987" ], [ "THROW MOMMA FROM THE TRAIN", "has_genre", "COMEDY" ], [ "THROW MOMMA FROM THE TRAIN", "has_tags", "COMEDY" ], [ "THROW MOMMA FROM THE TRAIN", "release_year", "1987" ], [ "TIN MEN", "has_genre", "COMEDY" ], [ "TIN MEN", "release_year", "1987" ], [ "TOUGH GUYS DON'T DANCE", "has_genre", "COMEDY" ], [ "TOUGH GUYS DON'T DANCE", "release_year", "1987" ], [ "TRIPPIN'", "has_genre", "COMEDY" ], [ "TRIPPIN'", "release_year", "1999" ], [ "TRIPPIN'", "starred_actors", "DONALD FAISON" ], [ "UPTOWN GIRLS", "has_genre", "COMEDY" ], [ "UPTOWN GIRLS", "starred_actors", "DONALD FAISON" ], [ "WALK LIKE A MAN", "has_genre", "COMEDY" ], [ "WALK LIKE A MAN", "release_year", "1987" ], [ "WHO'S THAT GIRL", "directed_by", "JAMES FOLEY" ], [ "WHO'S THAT GIRL", "has_genre", "COMEDY" ], [ "WHO'S THAT GIRL", "has_tags", "JAMES FOLEY" ], [ "WHO'S THAT GIRL", "has_tags", "MADONNA" ], [ "WHO'S THAT GIRL", "release_year", "1987" ], [ "WHO'S THAT GIRL", "starred_actors", "GRIFFIN DUNNE" ], [ "WHO'S THAT GIRL", "starred_actors", "MADONNA" ], [ "WHO'S THAT GIRL", "written_by", "KEN FINKLEMAN" ], [ "WISH YOU WERE HERE", "has_genre", "COMEDY" ], [ "WISH YOU WERE HERE", "release_year", "1987" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 33908, BARBARA BEDFORD 35148, CLARENCE BROWN 28508, CONQUEST 36066, FANTASY 22582, THE LAST OF THE MOHICANS 13189, THE LOST CONTINENT 29314, TONY BECKLEY 17666, WACLAW GASIOROWSKI src, edge_attr, dst 28508, directed_by, 35148 28508, has_genre, 36066 28508, written_by, 17666 22582, directed_by, 35148 22582, starred_actors, 33908 13189, has_genre, 36066 13189, starred_actors, 29314 Question: How are BARBARA BEDFORD, TONY BECKLEY, and WACLAW GASIOROWSKI related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BARBARA BEDFORD", "TONY BECKLEY", "WACLAW GASIOROWSKI" ], "valid_edges": [ [ "CONQUEST", "directed_by", "CLARENCE BROWN" ], [ "CONQUEST", "has_genre", "FANTASY" ], [ "CONQUEST", "written_by", "WACLAW GASIOROWSKI" ], [ "THE LAST OF THE MOHICANS", "directed_by", "CLARENCE BROWN" ], [ "THE LAST OF THE MOHICANS", "starred_actors", "BARBARA BEDFORD" ], [ "THE LOST CONTINENT", "has_genre", "FANTASY" ], [ "THE LOST CONTINENT", "starred_actors", "TONY BECKLEY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 30113, 101 DALMATIANS 1006, 1996 6094, A CLOCKWORK ORANGE 17822, AMY HOLDEN JONES 14271, BEETHOVEN 14561, BEETHOVEN'S 2ND 20510, BONNIE HUNT 30523, CHEAPER BY THE DOZEN 32379, CHEAPER BY THE DOZEN 2 10509, FAMILY 18521, FLY AWAY HOME 39198, GETTING AWAY WITH MURDER 4798, JINGLE ALL THE WAY 14017, JURASSIC PARK 12949, KAZAAM 6577, SHILOH 9735, SPECIAL EFFECTS 13976, THE ADVENTURES OF PINOCCHIO 14846, THE RICH MAN'S WIFE 6923, THE WHOLE WIDE WORLD 26509, VIOLENCE src, edge_attr, dst 30113, has_genre, 10509 30113, release_year, 1006 6094, has_tags, 14271 6094, has_tags, 26509 14271, has_genre, 10509 14271, has_tags, 20510 14271, has_tags, 10509 14271, starred_actors, 20510 14271, written_by, 17822 14561, has_genre, 10509 14561, has_tags, 20510 14561, starred_actors, 20510 30523, has_genre, 10509 30523, has_tags, 20510 30523, has_tags, 10509 30523, starred_actors, 20510 32379, has_genre, 10509 32379, starred_actors, 20510 18521, has_genre, 10509 18521, release_year, 1006 39198, release_year, 1006 39198, starred_actors, 20510 4798, has_genre, 10509 4798, release_year, 1006 14017, has_tags, 9735 14017, has_tags, 26509 12949, has_genre, 10509 12949, release_year, 1006 6577, has_genre, 10509 6577, release_year, 1006 13976, has_genre, 10509 13976, release_year, 1006 14846, directed_by, 17822 14846, release_year, 1006 14846, written_by, 17822 6923, release_year, 1006 Question: How are BEETHOVEN, SPECIAL EFFECTS, and THE WHOLE WIDE WORLD related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BEETHOVEN", "SPECIAL EFFECTS", "THE WHOLE WIDE WORLD" ], "valid_edges": [ [ "101 DALMATIANS", "has_genre", "FAMILY" ], [ "101 DALMATIANS", "release_year", "1996" ], [ "A CLOCKWORK ORANGE", "has_tags", "BEETHOVEN" ], [ "A CLOCKWORK ORANGE", "has_tags", "VIOLENCE" ], [ "BEETHOVEN", "has_genre", "FAMILY" ], [ "BEETHOVEN", "has_tags", "BONNIE HUNT" ], [ "BEETHOVEN", "has_tags", "FAMILY" ], [ "BEETHOVEN", "starred_actors", "BONNIE HUNT" ], [ "BEETHOVEN", "written_by", "AMY HOLDEN JONES" ], [ "BEETHOVEN'S 2ND", "has_genre", "FAMILY" ], [ "BEETHOVEN'S 2ND", "has_tags", "BONNIE HUNT" ], [ "BEETHOVEN'S 2ND", "starred_actors", "BONNIE HUNT" ], [ "CHEAPER BY THE DOZEN", "has_genre", "FAMILY" ], [ "CHEAPER BY THE DOZEN", "has_tags", "BONNIE HUNT" ], [ "CHEAPER BY THE DOZEN", "has_tags", "FAMILY" ], [ "CHEAPER BY THE DOZEN", "starred_actors", "BONNIE HUNT" ], [ "CHEAPER BY THE DOZEN 2", "has_genre", "FAMILY" ], [ "CHEAPER BY THE DOZEN 2", "starred_actors", "BONNIE HUNT" ], [ "FLY AWAY HOME", "has_genre", "FAMILY" ], [ "FLY AWAY HOME", "release_year", "1996" ], [ "GETTING AWAY WITH MURDER", "release_year", "1996" ], [ "GETTING AWAY WITH MURDER", "starred_actors", "BONNIE HUNT" ], [ "JINGLE ALL THE WAY", "has_genre", "FAMILY" ], [ "JINGLE ALL THE WAY", "release_year", "1996" ], [ "JURASSIC PARK", "has_tags", "SPECIAL EFFECTS" ], [ "JURASSIC PARK", "has_tags", "VIOLENCE" ], [ "KAZAAM", "has_genre", "FAMILY" ], [ "KAZAAM", "release_year", "1996" ], [ "SHILOH", "has_genre", "FAMILY" ], [ "SHILOH", "release_year", "1996" ], [ "THE ADVENTURES OF PINOCCHIO", "has_genre", "FAMILY" ], [ "THE ADVENTURES OF PINOCCHIO", "release_year", "1996" ], [ "THE RICH MAN'S WIFE", "directed_by", "AMY HOLDEN JONES" ], [ "THE RICH MAN'S WIFE", "release_year", "1996" ], [ "THE RICH MAN'S WIFE", "written_by", "AMY HOLDEN JONES" ], [ "THE WHOLE WIDE WORLD", "release_year", "1996" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29145, 10 ITEMS OR LESS 26310, 1947 35845, 2006 21892, 48 SHADES 14242, A FRIEND OF MINE 24039, A GOOD YEAR 8198, A PRAIRIE HOME COMPANION 18514, ACCEPTED 32926, ALIEN AUTOPSY 38447, ALWAYS LEAVE THEM LAUGHING 27024, AMERICAN DREAMZ 23409, AN IDEAL HUSBAND 4963, ANN HARDING 24855, ANOTHER GAY MOVIE 17890, AQUAMARINE 24301, ART SCHOOL CONFIDENTIAL 17133, AS YOU LIKE IT 37155, BACHELOR PARTY VEGAS 36792, BANDIDAS 39257, BARNYARD 34728, BEAUTIFUL OHIO 26356, BEAUTY IN TROUBLE 37161, BEERFEST 38736, BIG MOMMA'S HOUSE 2 5099, BIG NOTHING 31778, BLACK SHEEP 17021, BLIND DATING 26553, BONNEVILLE 36479, BORN TO DANCE 5823, BROTHER BEAR 2 33196, CARS 16659, CASINO ROYALE 7830, CATCH AND RELEASE 18748, CATTLE CALL 11009, CHICKEN RUN 2297, CHRISTMAS EVE 21625, CLERKS II 18016, CLICK 30463, COMEDY 18440, CONFETTI 7685, DATE MOVIE 38345, DECK THE HALLS 29485, DELIRIOUS 3362, DIKKENEK 12012, DON DEFORE 8573, DR. DOLITTLE 3 22658, EMPLOYEE OF THE MONTH 10100, EVERYONE'S HERO 5515, EVIL BONG 8262, FAMILY LAW 13893, FIDO 18217, FIND ME GUILTY 2287, FLUSHED AWAY 40137, FOR YOUR CONSIDERATION 28514, GRANDMA'S BOY 17057, GRAVE DECISIONS 28826, GRAY MATTERS 14375, HIGH SCHOOL MUSICAL 12053, HONEYMOON 15660, HOOT 38589, I DO 16161, I WANT SOMEONE TO EAT CHEESE WITH 10554, I-SEE-YOU.COM 10625, IDIOCRACY 14226, IT HAPPENED ON FIFTH AVENUE 9624, IT'S A BOY GIRL THING 18276, JOHN TUCKER MUST DIE 7986, JUST MY LUCK 26486, KEEPING UP WITH THE STEINS 36745, LAST HOLIDAY 30776, LET'S GO TO PRISON 38412, LIFE WITH FATHER 24376, LITTLE MISS SUNSHINE 34385, LIVE FREE OR DIE 17372, LOL 39979, MADEA'S FAMILY REUNION 27297, MAGIC TOWN 10502, MAN ABOUT TOWN 27801, MAN OF THE YEAR 24324, MATERIAL GIRLS 30166, MONSIEUR VERDOUX 9173, MONSTER HOUSE 26612, MY FAVORITE BRUNETTE 19983, MY SUPER EX-GIRLFRIEND 1268, NACHO LIBRE 3027, NIGHT AT THE MUSEUM 39115, NINA'S HEAVENLY DELIGHTS 13261, OPEN SEASON 24150, OUTSOURCED 17365, OVER THE HEDGE 16124, PENELOPE 2629, PHAT GIRLZ 776, PITER FM 2814, PUCCINI FOR BEGINNERS 31713, ROAD TO RIO 30518, ROMANCE ON THE HIGH SEAS 7011, ROY DEL RUTH 33108, RUNNING SCARED 5766, RUNNING WITH SCISSORS 29696, RV 9228, SCARY MOVIE 4 31315, SCENES OF A SEXUAL NATURE 21609, SCHOOL FOR SCOUNDRELS 24726, SCOOP 26416, SHE'S THE MAN 28126, SHEITAN 3237, SIXTY SIX 38752, SLEEPING DOGS LIE 26930, SLITHER 31073, SLUMMING 10804, SOMETHING IN THE WIND 35507, SONG OF THE THIN MAN 28005, SOUTHLAND TALES 26020, STARTER FOR 10 39786, STICK IT 8998, SWING TIME 38498, TAXIDERMIA 37498, TENACIOUS D IN THE PICK OF DESTINY 23870, THE ANIMAL KINGDOM 15243, THE ART OF CRYING 11415, THE ART OF NEGATIVE THINKING 8318, THE BACHELOR AND THE BOBBY-SOXER 38597, THE BENCHWARMERS 28719, THE BISHOP'S WIFE 21024, THE BOSS OF IT ALL 26285, THE BREAK-UP 36932, THE CAIMAN 3251, THE CURIOSITY OF CHANCE 2102, THE DARWIN AWARDS 22346, THE DEVIL WEARS PRADA 22882, THE DOG PROBLEM 17991, THE EGG AND I 7404, THE EX 16464, THE FOOT FIST WAY 4060, THE GROOMSMEN 15420, THE HISTORY BOYS 26955, THE HOLIDAY 28107, THE LAST KISS 9355, THE MARSH 32781, THE OH IN OHIO 25837, THE PERILS OF PAULINE 21400, THE PINK PANTHER 18162, THE RAVEN 11383, THE SCIENCE OF SLEEP 30746, THE SECRET LIFE OF WALTER MITTY 15558, THE SIN OF HAROLD DIDDLEBOCK 14580, THE TREATMENT 4542, THE VALET 31313, THE WEST POINT STORY 1772, THE WILD 18500, TONY HAYGARTH 12051, UNACCOMPANIED MINORS 36753, VENUS 3778, VICTOR MOORE 31364, WE'RE NOT MARRIED! 20986, WEDDING DAZE 36581, YOU, ME AND DUPREE 14841, ZIEGFELD FOLLIES src, edge_attr, dst 29145, has_genre, 30463 29145, has_tags, 30463 29145, release_year, 35845 21892, has_genre, 30463 21892, release_year, 35845 14242, has_genre, 30463 14242, release_year, 35845 24039, has_genre, 30463 24039, release_year, 35845 8198, has_genre, 30463 8198, release_year, 35845 18514, has_genre, 30463 18514, release_year, 35845 32926, has_genre, 30463 32926, release_year, 35845 38447, directed_by, 7011 38447, has_genre, 30463 27024, has_genre, 30463 27024, has_tags, 30463 27024, release_year, 35845 23409, has_genre, 30463 23409, has_tags, 30463 23409, release_year, 26310 24855, has_genre, 30463 24855, release_year, 35845 17890, has_genre, 30463 17890, release_year, 35845 24301, has_genre, 30463 24301, release_year, 35845 17133, has_genre, 30463 17133, release_year, 35845 37155, has_genre, 30463 37155, release_year, 35845 36792, has_genre, 30463 36792, release_year, 35845 39257, has_genre, 30463 39257, release_year, 35845 34728, has_genre, 30463 34728, release_year, 35845 26356, has_genre, 30463 26356, release_year, 35845 37161, has_genre, 30463 37161, release_year, 35845 38736, has_genre, 30463 38736, release_year, 35845 5099, has_genre, 30463 5099, has_tags, 30463 5099, release_year, 35845 31778, has_genre, 30463 31778, has_tags, 30463 31778, release_year, 35845 17021, has_genre, 30463 17021, release_year, 35845 26553, has_genre, 30463 26553, release_year, 35845 36479, directed_by, 7011 36479, has_genre, 30463 5823, has_genre, 30463 5823, release_year, 35845 33196, has_genre, 30463 33196, has_tags, 30463 33196, release_year, 35845 16659, has_genre, 30463 16659, release_year, 35845 7830, has_genre, 30463 7830, release_year, 35845 18748, has_genre, 30463 18748, release_year, 35845 11009, has_genre, 30463 11009, starred_actors, 18500 2297, has_genre, 30463 2297, release_year, 26310 21625, has_genre, 30463 21625, has_tags, 30463 21625, release_year, 35845 18016, has_genre, 30463 18016, has_tags, 30463 18016, release_year, 35845 18440, has_genre, 30463 18440, release_year, 35845 7685, has_genre, 30463 7685, has_tags, 30463 7685, release_year, 35845 38345, has_genre, 30463 38345, release_year, 35845 29485, has_genre, 30463 29485, release_year, 35845 3362, has_genre, 30463 3362, release_year, 35845 8573, has_genre, 30463 8573, release_year, 35845 22658, has_genre, 30463 22658, has_tags, 30463 22658, release_year, 35845 10100, has_genre, 30463 10100, release_year, 35845 5515, has_genre, 30463 5515, release_year, 35845 8262, has_genre, 30463 8262, release_year, 35845 13893, has_genre, 30463 13893, has_tags, 30463 13893, release_year, 35845 18217, has_genre, 30463 18217, release_year, 35845 2287, has_genre, 30463 2287, release_year, 35845 40137, has_genre, 30463 40137, release_year, 35845 28514, has_genre, 30463 28514, release_year, 35845 17057, has_genre, 30463 17057, release_year, 35845 28826, has_genre, 30463 28826, release_year, 35845 14375, has_genre, 30463 14375, release_year, 35845 12053, has_genre, 30463 12053, release_year, 26310 15660, has_genre, 30463 15660, release_year, 35845 38589, has_genre, 30463 38589, release_year, 35845 16161, has_genre, 30463 16161, release_year, 35845 10554, has_genre, 30463 10554, release_year, 35845 10625, has_genre, 30463 10625, release_year, 35845 14226, directed_by, 7011 14226, has_genre, 30463 14226, has_tags, 7011 14226, release_year, 26310 14226, starred_actors, 4963 14226, starred_actors, 12012 14226, starred_actors, 3778 9624, has_genre, 30463 9624, release_year, 35845 18276, has_genre, 30463 18276, release_year, 35845 7986, has_genre, 30463 7986, release_year, 35845 26486, has_genre, 30463 26486, release_year, 35845 36745, has_genre, 30463 36745, release_year, 35845 30776, has_genre, 30463 30776, release_year, 35845 38412, has_genre, 30463 38412, release_year, 26310 24376, has_genre, 30463 24376, has_tags, 30463 24376, release_year, 35845 34385, has_genre, 30463 34385, release_year, 35845 17372, has_genre, 30463 17372, release_year, 35845 39979, has_genre, 30463 39979, release_year, 35845 27297, has_genre, 30463 27297, release_year, 26310 10502, has_genre, 30463 10502, release_year, 35845 27801, has_genre, 30463 27801, has_tags, 30463 27801, release_year, 35845 24324, has_genre, 30463 24324, release_year, 35845 30166, has_genre, 30463 30166, release_year, 26310 9173, has_genre, 30463 9173, release_year, 35845 26612, has_genre, 30463 26612, release_year, 26310 19983, has_genre, 30463 19983, release_year, 35845 1268, has_genre, 30463 1268, has_tags, 30463 1268, release_year, 35845 3027, has_genre, 30463 3027, release_year, 35845 39115, has_genre, 30463 39115, release_year, 35845 13261, has_genre, 30463 13261, has_tags, 30463 13261, release_year, 35845 24150, has_genre, 30463 24150, has_tags, 30463 24150, release_year, 35845 17365, has_genre, 30463 17365, release_year, 35845 16124, has_genre, 30463 16124, release_year, 35845 2629, has_genre, 30463 2629, release_year, 35845 776, has_genre, 30463 776, release_year, 35845 2814, has_genre, 30463 2814, release_year, 35845 31713, has_genre, 30463 31713, release_year, 26310 30518, has_genre, 30463 30518, starred_actors, 12012 33108, has_genre, 30463 33108, release_year, 35845 5766, has_genre, 30463 5766, release_year, 35845 29696, has_genre, 30463 29696, has_tags, 30463 29696, release_year, 35845 9228, has_genre, 30463 9228, release_year, 35845 31315, has_genre, 30463 31315, release_year, 35845 21609, has_genre, 30463 21609, has_tags, 30463 21609, release_year, 35845 24726, has_genre, 30463 24726, release_year, 35845 26416, has_genre, 30463 26416, release_year, 35845 28126, has_genre, 30463 28126, release_year, 35845 3237, has_genre, 30463 3237, release_year, 35845 38752, has_genre, 30463 38752, release_year, 35845 26930, has_genre, 30463 26930, has_tags, 30463 26930, release_year, 35845 31073, has_genre, 30463 31073, release_year, 35845 10804, has_genre, 30463 10804, release_year, 26310 35507, has_genre, 30463 35507, release_year, 26310 28005, has_genre, 30463 28005, has_tags, 30463 28005, release_year, 35845 26020, has_genre, 30463 26020, has_tags, 30463 26020, release_year, 35845 39786, has_genre, 30463 39786, release_year, 35845 8998, has_genre, 30463 8998, starred_actors, 3778 38498, has_genre, 30463 38498, release_year, 35845 37498, has_genre, 30463 37498, has_tags, 30463 37498, release_year, 35845 23870, has_genre, 30463 23870, starred_actors, 4963 15243, has_genre, 30463 15243, release_year, 35845 11415, has_genre, 30463 11415, release_year, 35845 8318, has_genre, 30463 8318, release_year, 26310 38597, has_genre, 30463 38597, release_year, 35845 28719, has_genre, 30463 28719, release_year, 26310 21024, has_genre, 30463 21024, release_year, 35845 26285, has_genre, 30463 26285, has_tags, 30463 26285, release_year, 35845 36932, has_genre, 30463 36932, release_year, 35845 3251, has_genre, 30463 3251, release_year, 35845 2102, has_genre, 30463 2102, release_year, 35845 22346, has_genre, 30463 22346, has_tags, 30463 22346, release_year, 35845 22882, has_genre, 30463 22882, release_year, 35845 17991, has_genre, 30463 17991, release_year, 26310 7404, has_genre, 30463 7404, release_year, 35845 16464, has_genre, 30463 16464, release_year, 35845 4060, has_genre, 30463 4060, release_year, 35845 15420, has_genre, 30463 15420, release_year, 35845 26955, has_genre, 30463 26955, release_year, 35845 28107, has_genre, 30463 28107, release_year, 35845 9355, release_year, 35845 32781, has_genre, 30463 32781, release_year, 35845 25837, has_genre, 30463 25837, release_year, 26310 21400, has_genre, 30463 21400, release_year, 35845 18162, has_genre, 30463 18162, release_year, 35845 11383, has_genre, 30463 11383, release_year, 35845 30746, has_genre, 30463 30746, release_year, 26310 15558, has_genre, 30463 15558, release_year, 26310 14580, has_genre, 30463 14580, release_year, 35845 4542, has_genre, 30463 4542, has_tags, 30463 4542, release_year, 35845 31313, directed_by, 7011 31313, has_genre, 30463 1772, has_genre, 30463 1772, release_year, 35845 12051, has_genre, 30463 12051, release_year, 35845 36753, has_genre, 30463 36753, release_year, 35845 31364, has_genre, 30463 31364, starred_actors, 3778 20986, has_genre, 30463 20986, release_year, 35845 36581, has_genre, 30463 36581, release_year, 35845 14841, directed_by, 7011 14841, has_genre, 30463 Question: For what reason are IT HAPPENED ON FIFTH AVENUE, THE MARSH, and TONY HAYGARTH associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "IT HAPPENED ON FIFTH AVENUE", "THE MARSH", "TONY HAYGARTH" ], "valid_edges": [ [ "10 ITEMS OR LESS", "has_genre", "COMEDY" ], [ "10 ITEMS OR LESS", "has_tags", "COMEDY" ], [ "10 ITEMS OR LESS", "release_year", "2006" ], [ "48 SHADES", "has_genre", "COMEDY" ], [ "48 SHADES", "release_year", "2006" ], [ "A FRIEND OF MINE", "has_genre", "COMEDY" ], [ "A FRIEND OF MINE", "release_year", "2006" ], [ "A GOOD YEAR", "has_genre", "COMEDY" ], [ "A GOOD YEAR", "release_year", "2006" ], [ "A PRAIRIE HOME COMPANION", "has_genre", "COMEDY" ], [ "A PRAIRIE HOME COMPANION", "release_year", "2006" ], [ "ACCEPTED", "has_genre", "COMEDY" ], [ "ACCEPTED", "release_year", "2006" ], [ "ALIEN AUTOPSY", "has_genre", "COMEDY" ], [ "ALIEN AUTOPSY", "release_year", "2006" ], [ "ALWAYS LEAVE THEM LAUGHING", "directed_by", "ROY DEL RUTH" ], [ "ALWAYS LEAVE THEM LAUGHING", "has_genre", "COMEDY" ], [ "AMERICAN DREAMZ", "has_genre", "COMEDY" ], [ "AMERICAN DREAMZ", "has_tags", "COMEDY" ], [ "AMERICAN DREAMZ", "release_year", "2006" ], [ "AN IDEAL HUSBAND", "has_genre", "COMEDY" ], [ "AN IDEAL HUSBAND", "has_tags", "COMEDY" ], [ "AN IDEAL HUSBAND", "release_year", "1947" ], [ "ANOTHER GAY MOVIE", "has_genre", "COMEDY" ], [ "ANOTHER GAY MOVIE", "release_year", "2006" ], [ "AQUAMARINE", "has_genre", "COMEDY" ], [ "AQUAMARINE", "release_year", "2006" ], [ "ART SCHOOL CONFIDENTIAL", "has_genre", "COMEDY" ], [ "ART SCHOOL CONFIDENTIAL", "release_year", "2006" ], [ "AS YOU LIKE IT", "has_genre", "COMEDY" ], [ "AS YOU LIKE IT", "release_year", "2006" ], [ "BACHELOR PARTY VEGAS", "has_genre", "COMEDY" ], [ "BACHELOR PARTY VEGAS", "release_year", "2006" ], [ "BANDIDAS", "has_genre", "COMEDY" ], [ "BANDIDAS", "release_year", "2006" ], [ "BARNYARD", "has_genre", "COMEDY" ], [ "BARNYARD", "release_year", "2006" ], [ "BEAUTIFUL OHIO", "has_genre", "COMEDY" ], [ "BEAUTIFUL OHIO", "release_year", "2006" ], [ "BEAUTY IN TROUBLE", "has_genre", "COMEDY" ], [ "BEAUTY IN TROUBLE", "release_year", "2006" ], [ "BEERFEST", "has_genre", "COMEDY" ], [ "BEERFEST", "release_year", "2006" ], [ "BIG MOMMA'S HOUSE 2", "has_genre", "COMEDY" ], [ "BIG MOMMA'S HOUSE 2", "release_year", "2006" ], [ "BIG NOTHING", "has_genre", "COMEDY" ], [ "BIG NOTHING", "has_tags", "COMEDY" ], [ "BIG NOTHING", "release_year", "2006" ], [ "BLACK SHEEP", "has_genre", "COMEDY" ], [ "BLACK SHEEP", "has_tags", "COMEDY" ], [ "BLACK SHEEP", "release_year", "2006" ], [ "BLIND DATING", "has_genre", "COMEDY" ], [ "BLIND DATING", "release_year", "2006" ], [ "BONNEVILLE", "has_genre", "COMEDY" ], [ "BONNEVILLE", "release_year", "2006" ], [ "BORN TO DANCE", "directed_by", "ROY DEL RUTH" ], [ "BORN TO DANCE", "has_genre", "COMEDY" ], [ "BROTHER BEAR 2", "has_genre", "COMEDY" ], [ "BROTHER BEAR 2", "release_year", "2006" ], [ "CARS", "has_genre", "COMEDY" ], [ "CARS", "has_tags", "COMEDY" ], [ "CARS", "release_year", "2006" ], [ "CASINO ROYALE", "has_genre", "COMEDY" ], [ "CASINO ROYALE", "release_year", "2006" ], [ "CATCH AND RELEASE", "has_genre", "COMEDY" ], [ "CATCH AND RELEASE", "release_year", "2006" ], [ "CATTLE CALL", "has_genre", "COMEDY" ], [ "CATTLE CALL", "release_year", "2006" ], [ "CHICKEN RUN", "has_genre", "COMEDY" ], [ "CHICKEN RUN", "starred_actors", "TONY HAYGARTH" ], [ "CHRISTMAS EVE", "has_genre", "COMEDY" ], [ "CHRISTMAS EVE", "release_year", "1947" ], [ "CLERKS II", "has_genre", "COMEDY" ], [ "CLERKS II", "has_tags", "COMEDY" ], [ "CLERKS II", "release_year", "2006" ], [ "CLICK", "has_genre", "COMEDY" ], [ "CLICK", "has_tags", "COMEDY" ], [ "CLICK", "release_year", "2006" ], [ "CONFETTI", "has_genre", "COMEDY" ], [ "CONFETTI", "release_year", "2006" ], [ "DATE MOVIE", "has_genre", "COMEDY" ], [ "DATE MOVIE", "has_tags", "COMEDY" ], [ "DATE MOVIE", "release_year", "2006" ], [ "DECK THE HALLS", "has_genre", "COMEDY" ], [ "DECK THE HALLS", "release_year", "2006" ], [ "DELIRIOUS", "has_genre", "COMEDY" ], [ "DELIRIOUS", "release_year", "2006" ], [ "DIKKENEK", "has_genre", "COMEDY" ], [ "DIKKENEK", "release_year", "2006" ], [ "DR. DOLITTLE 3", "has_genre", "COMEDY" ], [ "DR. DOLITTLE 3", "release_year", "2006" ], [ "EMPLOYEE OF THE MONTH", "has_genre", "COMEDY" ], [ "EMPLOYEE OF THE MONTH", "has_tags", "COMEDY" ], [ "EMPLOYEE OF THE MONTH", "release_year", "2006" ], [ "EVERYONE'S HERO", "has_genre", "COMEDY" ], [ "EVERYONE'S HERO", "release_year", "2006" ], [ "EVIL BONG", "has_genre", "COMEDY" ], [ "EVIL BONG", "release_year", "2006" ], [ "FAMILY LAW", "has_genre", "COMEDY" ], [ "FAMILY LAW", "release_year", "2006" ], [ "FIDO", "has_genre", "COMEDY" ], [ "FIDO", "has_tags", "COMEDY" ], [ "FIDO", "release_year", "2006" ], [ "FIND ME GUILTY", "has_genre", "COMEDY" ], [ "FIND ME GUILTY", "release_year", "2006" ], [ "FLUSHED AWAY", "has_genre", "COMEDY" ], [ "FLUSHED AWAY", "release_year", "2006" ], [ "FOR YOUR CONSIDERATION", "has_genre", "COMEDY" ], [ "FOR YOUR CONSIDERATION", "release_year", "2006" ], [ "GRANDMA'S BOY", "has_genre", "COMEDY" ], [ "GRANDMA'S BOY", "release_year", "2006" ], [ "GRAVE DECISIONS", "has_genre", "COMEDY" ], [ "GRAVE DECISIONS", "release_year", "2006" ], [ "GRAY MATTERS", "has_genre", "COMEDY" ], [ "GRAY MATTERS", "release_year", "2006" ], [ "HIGH SCHOOL MUSICAL", "has_genre", "COMEDY" ], [ "HIGH SCHOOL MUSICAL", "release_year", "2006" ], [ "HONEYMOON", "has_genre", "COMEDY" ], [ "HONEYMOON", "release_year", "1947" ], [ "HOOT", "has_genre", "COMEDY" ], [ "HOOT", "release_year", "2006" ], [ "I DO", "has_genre", "COMEDY" ], [ "I DO", "release_year", "2006" ], [ "I WANT SOMEONE TO EAT CHEESE WITH", "has_genre", "COMEDY" ], [ "I WANT SOMEONE TO EAT CHEESE WITH", "release_year", "2006" ], [ "I-SEE-YOU.COM", "has_genre", "COMEDY" ], [ "I-SEE-YOU.COM", "release_year", "2006" ], [ "IDIOCRACY", "has_genre", "COMEDY" ], [ "IDIOCRACY", "release_year", "2006" ], [ "IT HAPPENED ON FIFTH AVENUE", "directed_by", "ROY DEL RUTH" ], [ "IT HAPPENED ON FIFTH AVENUE", "has_genre", "COMEDY" ], [ "IT HAPPENED ON FIFTH AVENUE", "has_tags", "ROY DEL RUTH" ], [ "IT HAPPENED ON FIFTH AVENUE", "release_year", "1947" ], [ "IT HAPPENED ON FIFTH AVENUE", "starred_actors", "ANN HARDING" ], [ "IT HAPPENED ON FIFTH AVENUE", "starred_actors", "DON DEFORE" ], [ "IT HAPPENED ON FIFTH AVENUE", "starred_actors", "VICTOR MOORE" ], [ "IT'S A BOY GIRL THING", "has_genre", "COMEDY" ], [ "IT'S A BOY GIRL THING", "release_year", "2006" ], [ "JOHN TUCKER MUST DIE", "has_genre", "COMEDY" ], [ "JOHN TUCKER MUST DIE", "release_year", "2006" ], [ "JUST MY LUCK", "has_genre", "COMEDY" ], [ "JUST MY LUCK", "release_year", "2006" ], [ "KEEPING UP WITH THE STEINS", "has_genre", "COMEDY" ], [ "KEEPING UP WITH THE STEINS", "release_year", "2006" ], [ "LAST HOLIDAY", "has_genre", "COMEDY" ], [ "LAST HOLIDAY", "release_year", "2006" ], [ "LET'S GO TO PRISON", "has_genre", "COMEDY" ], [ "LET'S GO TO PRISON", "release_year", "2006" ], [ "LIFE WITH FATHER", "has_genre", "COMEDY" ], [ "LIFE WITH FATHER", "release_year", "1947" ], [ "LITTLE MISS SUNSHINE", "has_genre", "COMEDY" ], [ "LITTLE MISS SUNSHINE", "has_tags", "COMEDY" ], [ "LITTLE MISS SUNSHINE", "release_year", "2006" ], [ "LIVE FREE OR DIE", "has_genre", "COMEDY" ], [ "LIVE FREE OR DIE", "release_year", "2006" ], [ "LOL", "has_genre", "COMEDY" ], [ "LOL", "release_year", "2006" ], [ "MADEA'S FAMILY REUNION", "has_genre", "COMEDY" ], [ "MADEA'S FAMILY REUNION", "release_year", "2006" ], [ "MAGIC TOWN", "has_genre", "COMEDY" ], [ "MAGIC TOWN", "release_year", "1947" ], [ "MAN ABOUT TOWN", "has_genre", "COMEDY" ], [ "MAN ABOUT TOWN", "release_year", "2006" ], [ "MAN OF THE YEAR", "has_genre", "COMEDY" ], [ "MAN OF THE YEAR", "has_tags", "COMEDY" ], [ "MAN OF THE YEAR", "release_year", "2006" ], [ "MATERIAL GIRLS", "has_genre", "COMEDY" ], [ "MATERIAL GIRLS", "release_year", "2006" ], [ "MONSIEUR VERDOUX", "has_genre", "COMEDY" ], [ "MONSIEUR VERDOUX", "release_year", "1947" ], [ "MONSTER HOUSE", "has_genre", "COMEDY" ], [ "MONSTER HOUSE", "release_year", "2006" ], [ "MY FAVORITE BRUNETTE", "has_genre", "COMEDY" ], [ "MY FAVORITE BRUNETTE", "release_year", "1947" ], [ "MY SUPER EX-GIRLFRIEND", "has_genre", "COMEDY" ], [ "MY SUPER EX-GIRLFRIEND", "release_year", "2006" ], [ "NACHO LIBRE", "has_genre", "COMEDY" ], [ "NACHO LIBRE", "has_tags", "COMEDY" ], [ "NACHO LIBRE", "release_year", "2006" ], [ "NIGHT AT THE MUSEUM", "has_genre", "COMEDY" ], [ "NIGHT AT THE MUSEUM", "release_year", "2006" ], [ "NINA'S HEAVENLY DELIGHTS", "has_genre", "COMEDY" ], [ "NINA'S HEAVENLY DELIGHTS", "release_year", "2006" ], [ "OPEN SEASON", "has_genre", "COMEDY" ], [ "OPEN SEASON", "has_tags", "COMEDY" ], [ "OPEN SEASON", "release_year", "2006" ], [ "OUTSOURCED", "has_genre", "COMEDY" ], [ "OUTSOURCED", "has_tags", "COMEDY" ], [ "OUTSOURCED", "release_year", "2006" ], [ "OVER THE HEDGE", "has_genre", "COMEDY" ], [ "OVER THE HEDGE", "release_year", "2006" ], [ "PENELOPE", "has_genre", "COMEDY" ], [ "PENELOPE", "release_year", "2006" ], [ "PHAT GIRLZ", "has_genre", "COMEDY" ], [ "PHAT GIRLZ", "release_year", "2006" ], [ "PITER FM", "has_genre", "COMEDY" ], [ "PITER FM", "release_year", "2006" ], [ "PUCCINI FOR BEGINNERS", "has_genre", "COMEDY" ], [ "PUCCINI FOR BEGINNERS", "release_year", "2006" ], [ "ROAD TO RIO", "has_genre", "COMEDY" ], [ "ROAD TO RIO", "release_year", "1947" ], [ "ROMANCE ON THE HIGH SEAS", "has_genre", "COMEDY" ], [ "ROMANCE ON THE HIGH SEAS", "starred_actors", "DON DEFORE" ], [ "RUNNING SCARED", "has_genre", "COMEDY" ], [ "RUNNING SCARED", "release_year", "2006" ], [ "RUNNING WITH SCISSORS", "has_genre", "COMEDY" ], [ "RUNNING WITH SCISSORS", "release_year", "2006" ], [ "RV", "has_genre", "COMEDY" ], [ "RV", "has_tags", "COMEDY" ], [ "RV", "release_year", "2006" ], [ "SCARY MOVIE 4", "has_genre", "COMEDY" ], [ "SCARY MOVIE 4", "release_year", "2006" ], [ "SCENES OF A SEXUAL NATURE", "has_genre", "COMEDY" ], [ "SCENES OF A SEXUAL NATURE", "release_year", "2006" ], [ "SCHOOL FOR SCOUNDRELS", "has_genre", "COMEDY" ], [ "SCHOOL FOR SCOUNDRELS", "has_tags", "COMEDY" ], [ "SCHOOL FOR SCOUNDRELS", "release_year", "2006" ], [ "SCOOP", "has_genre", "COMEDY" ], [ "SCOOP", "release_year", "2006" ], [ "SHE'S THE MAN", "has_genre", "COMEDY" ], [ "SHE'S THE MAN", "release_year", "2006" ], [ "SHEITAN", "has_genre", "COMEDY" ], [ "SHEITAN", "release_year", "2006" ], [ "SIXTY SIX", "has_genre", "COMEDY" ], [ "SIXTY SIX", "release_year", "2006" ], [ "SLEEPING DOGS LIE", "has_genre", "COMEDY" ], [ "SLEEPING DOGS LIE", "release_year", "2006" ], [ "SLITHER", "has_genre", "COMEDY" ], [ "SLITHER", "has_tags", "COMEDY" ], [ "SLITHER", "release_year", "2006" ], [ "SLUMMING", "has_genre", "COMEDY" ], [ "SLUMMING", "release_year", "2006" ], [ "SOMETHING IN THE WIND", "has_genre", "COMEDY" ], [ "SOMETHING IN THE WIND", "release_year", "1947" ], [ "SONG OF THE THIN MAN", "has_genre", "COMEDY" ], [ "SONG OF THE THIN MAN", "release_year", "1947" ], [ "SOUTHLAND TALES", "has_genre", "COMEDY" ], [ "SOUTHLAND TALES", "has_tags", "COMEDY" ], [ "SOUTHLAND TALES", "release_year", "2006" ], [ "STARTER FOR 10", "has_genre", "COMEDY" ], [ "STARTER FOR 10", "has_tags", "COMEDY" ], [ "STARTER FOR 10", "release_year", "2006" ], [ "STICK IT", "has_genre", "COMEDY" ], [ "STICK IT", "release_year", "2006" ], [ "SWING TIME", "has_genre", "COMEDY" ], [ "SWING TIME", "starred_actors", "VICTOR MOORE" ], [ "TAXIDERMIA", "has_genre", "COMEDY" ], [ "TAXIDERMIA", "release_year", "2006" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "has_genre", "COMEDY" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "has_tags", "COMEDY" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "release_year", "2006" ], [ "THE ANIMAL KINGDOM", "has_genre", "COMEDY" ], [ "THE ANIMAL KINGDOM", "starred_actors", "ANN HARDING" ], [ "THE ART OF CRYING", "has_genre", "COMEDY" ], [ "THE ART OF CRYING", "release_year", "2006" ], [ "THE ART OF NEGATIVE THINKING", "has_genre", "COMEDY" ], [ "THE ART OF NEGATIVE THINKING", "release_year", "2006" ], [ "THE BACHELOR AND THE BOBBY-SOXER", "has_genre", "COMEDY" ], [ "THE BACHELOR AND THE BOBBY-SOXER", "release_year", "1947" ], [ "THE BENCHWARMERS", "has_genre", "COMEDY" ], [ "THE BENCHWARMERS", "release_year", "2006" ], [ "THE BISHOP'S WIFE", "has_genre", "COMEDY" ], [ "THE BISHOP'S WIFE", "release_year", "1947" ], [ "THE BOSS OF IT ALL", "has_genre", "COMEDY" ], [ "THE BOSS OF IT ALL", "release_year", "2006" ], [ "THE BREAK-UP", "has_genre", "COMEDY" ], [ "THE BREAK-UP", "has_tags", "COMEDY" ], [ "THE BREAK-UP", "release_year", "2006" ], [ "THE CAIMAN", "has_genre", "COMEDY" ], [ "THE CAIMAN", "release_year", "2006" ], [ "THE CURIOSITY OF CHANCE", "has_genre", "COMEDY" ], [ "THE CURIOSITY OF CHANCE", "release_year", "2006" ], [ "THE DARWIN AWARDS", "has_genre", "COMEDY" ], [ "THE DARWIN AWARDS", "release_year", "2006" ], [ "THE DEVIL WEARS PRADA", "has_genre", "COMEDY" ], [ "THE DEVIL WEARS PRADA", "has_tags", "COMEDY" ], [ "THE DEVIL WEARS PRADA", "release_year", "2006" ], [ "THE DOG PROBLEM", "has_genre", "COMEDY" ], [ "THE DOG PROBLEM", "release_year", "2006" ], [ "THE EGG AND I", "has_genre", "COMEDY" ], [ "THE EGG AND I", "release_year", "1947" ], [ "THE EX", "has_genre", "COMEDY" ], [ "THE EX", "release_year", "2006" ], [ "THE FOOT FIST WAY", "has_genre", "COMEDY" ], [ "THE FOOT FIST WAY", "release_year", "2006" ], [ "THE GROOMSMEN", "has_genre", "COMEDY" ], [ "THE GROOMSMEN", "release_year", "2006" ], [ "THE HISTORY BOYS", "has_genre", "COMEDY" ], [ "THE HISTORY BOYS", "release_year", "2006" ], [ "THE HOLIDAY", "has_genre", "COMEDY" ], [ "THE HOLIDAY", "release_year", "2006" ], [ "THE LAST KISS", "has_genre", "COMEDY" ], [ "THE LAST KISS", "release_year", "2006" ], [ "THE MARSH", "release_year", "2006" ], [ "THE OH IN OHIO", "has_genre", "COMEDY" ], [ "THE OH IN OHIO", "release_year", "2006" ], [ "THE PERILS OF PAULINE", "has_genre", "COMEDY" ], [ "THE PERILS OF PAULINE", "release_year", "1947" ], [ "THE PINK PANTHER", "has_genre", "COMEDY" ], [ "THE PINK PANTHER", "release_year", "2006" ], [ "THE RAVEN", "has_genre", "COMEDY" ], [ "THE RAVEN", "release_year", "2006" ], [ "THE SCIENCE OF SLEEP", "has_genre", "COMEDY" ], [ "THE SCIENCE OF SLEEP", "release_year", "2006" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "COMEDY" ], [ "THE SECRET LIFE OF WALTER MITTY", "release_year", "1947" ], [ "THE SIN OF HAROLD DIDDLEBOCK", "has_genre", "COMEDY" ], [ "THE SIN OF HAROLD DIDDLEBOCK", "release_year", "1947" ], [ "THE TREATMENT", "has_genre", "COMEDY" ], [ "THE TREATMENT", "release_year", "2006" ], [ "THE VALET", "has_genre", "COMEDY" ], [ "THE VALET", "has_tags", "COMEDY" ], [ "THE VALET", "release_year", "2006" ], [ "THE WEST POINT STORY", "directed_by", "ROY DEL RUTH" ], [ "THE WEST POINT STORY", "has_genre", "COMEDY" ], [ "THE WILD", "has_genre", "COMEDY" ], [ "THE WILD", "release_year", "2006" ], [ "UNACCOMPANIED MINORS", "has_genre", "COMEDY" ], [ "UNACCOMPANIED MINORS", "release_year", "2006" ], [ "VENUS", "has_genre", "COMEDY" ], [ "VENUS", "release_year", "2006" ], [ "WE'RE NOT MARRIED!", "has_genre", "COMEDY" ], [ "WE'RE NOT MARRIED!", "starred_actors", "VICTOR MOORE" ], [ "WEDDING DAZE", "has_genre", "COMEDY" ], [ "WEDDING DAZE", "release_year", "2006" ], [ "YOU, ME AND DUPREE", "has_genre", "COMEDY" ], [ "YOU, ME AND DUPREE", "release_year", "2006" ], [ "ZIEGFELD FOLLIES", "directed_by", "ROY DEL RUTH" ], [ "ZIEGFELD FOLLIES", "has_genre", "COMEDY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36096, CARROLL O'CONNOR 30463, COMEDY 16632, DOCTORS' WIVES 36212, DRAMA 6012, FRENCH 7569, IN THE BEGINNING 26924, JEAN DUJARDIN 1372, RETURN TO ME 39795, THE ARTIST 4632, XAVIER GIANNOLI src, edge_attr, dst 16632, has_genre, 36212 16632, starred_actors, 36096 7569, directed_by, 4632 7569, has_genre, 36212 7569, in_language, 6012 7569, written_by, 4632 1372, has_genre, 30463 1372, has_genre, 36212 1372, starred_actors, 36096 39795, has_genre, 30463 39795, has_genre, 36212 39795, has_tags, 36212 39795, has_tags, 6012 39795, has_tags, 26924 39795, in_language, 6012 39795, starred_actors, 26924 Question: For what reason are CARROLL O'CONNOR, JEAN DUJARDIN, and XAVIER GIANNOLI associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CARROLL O'CONNOR", "JEAN DUJARDIN", "XAVIER GIANNOLI" ], "valid_edges": [ [ "DOCTORS' WIVES", "has_genre", "DRAMA" ], [ "DOCTORS' WIVES", "starred_actors", "CARROLL O'CONNOR" ], [ "IN THE BEGINNING", "directed_by", "XAVIER GIANNOLI" ], [ "IN THE BEGINNING", "has_genre", "DRAMA" ], [ "IN THE BEGINNING", "in_language", "FRENCH" ], [ "IN THE BEGINNING", "written_by", "XAVIER GIANNOLI" ], [ "RETURN TO ME", "has_genre", "COMEDY" ], [ "RETURN TO ME", "has_genre", "DRAMA" ], [ "RETURN TO ME", "starred_actors", "CARROLL O'CONNOR" ], [ "THE ARTIST", "has_genre", "COMEDY" ], [ "THE ARTIST", "has_genre", "DRAMA" ], [ "THE ARTIST", "has_tags", "DRAMA" ], [ "THE ARTIST", "has_tags", "FRENCH" ], [ "THE ARTIST", "has_tags", "JEAN DUJARDIN" ], [ "THE ARTIST", "in_language", "FRENCH" ], [ "THE ARTIST", "starred_actors", "JEAN DUJARDIN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 11953, ALAN JOHNSON 30463, COMEDY 30164, THE CLOSET 17571, THE INTERNSHIP 3640, TO BE OR NOT TO BE src, edge_attr, dst 30164, has_genre, 30463 30164, has_tags, 30463 17571, has_genre, 30463 3640, directed_by, 11953 3640, has_genre, 30463 3640, has_tags, 30463 Question: In what context are ALAN JOHNSON, THE CLOSET, and THE INTERNSHIP connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ALAN JOHNSON", "THE CLOSET", "THE INTERNSHIP" ], "valid_edges": [ [ "THE CLOSET", "has_genre", "COMEDY" ], [ "THE CLOSET", "has_tags", "COMEDY" ], [ "THE INTERNSHIP", "has_genre", "COMEDY" ], [ "TO BE OR NOT TO BE", "directed_by", "ALAN JOHNSON" ], [ "TO BE OR NOT TO BE", "has_genre", "COMEDY" ], [ "TO BE OR NOT TO BE", "has_tags", "COMEDY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 658, 2012 15907, CHINA 274, COCKNEYS VS ZOMBIES 8585, DEATH BY CHINA 4709, GREAT EXPECTATIONS 36, JAVIER BARDEM 7566, KAHAANI 17319, LONDON 19118, MUSEUM HOURS 3339, MY BROTHER THE DEVIL 38131, PARAMBRATA CHATTERJEE 29281, PLOT 20985, RALPH FIENNES 20187, SKYFALL 16103, THE AVENGERS 22733, THE DARK KNIGHT RISES 9918, TO THE WONDER 23853, WRATH OF THE TITANS src, edge_attr, dst 274, has_tags, 17319 274, release_year, 658 8585, has_tags, 15907 8585, release_year, 658 4709, release_year, 658 4709, starred_actors, 20985 7566, release_year, 658 7566, starred_actors, 38131 19118, release_year, 658 3339, has_tags, 17319 3339, release_year, 658 20187, has_tags, 15907 20187, has_tags, 36 20187, has_tags, 17319 20187, has_tags, 29281 20187, has_tags, 20985 20187, release_year, 658 20187, starred_actors, 36 20187, starred_actors, 20985 16103, has_tags, 20985 16103, release_year, 658 16103, starred_actors, 20985 22733, has_tags, 29281 22733, release_year, 658 9918, release_year, 658 9918, starred_actors, 36 23853, release_year, 658 23853, starred_actors, 20985 Question: In what context are MUSEUM HOURS, PARAMBRATA CHATTERJEE, and SKYFALL connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "MUSEUM HOURS", "PARAMBRATA CHATTERJEE", "SKYFALL" ], "valid_edges": [ [ "COCKNEYS VS ZOMBIES", "has_tags", "LONDON" ], [ "COCKNEYS VS ZOMBIES", "release_year", "2012" ], [ "DEATH BY CHINA", "has_tags", "CHINA" ], [ "DEATH BY CHINA", "release_year", "2012" ], [ "GREAT EXPECTATIONS", "release_year", "2012" ], [ "GREAT EXPECTATIONS", "starred_actors", "RALPH FIENNES" ], [ "KAHAANI", "release_year", "2012" ], [ "KAHAANI", "starred_actors", "PARAMBRATA CHATTERJEE" ], [ "MUSEUM HOURS", "release_year", "2012" ], [ "MY BROTHER THE DEVIL", "has_tags", "LONDON" ], [ "MY BROTHER THE DEVIL", "release_year", "2012" ], [ "SKYFALL", "has_tags", "CHINA" ], [ "SKYFALL", "has_tags", "JAVIER BARDEM" ], [ "SKYFALL", "has_tags", "LONDON" ], [ "SKYFALL", "has_tags", "PLOT" ], [ "SKYFALL", "has_tags", "RALPH FIENNES" ], [ "SKYFALL", "release_year", "2012" ], [ "SKYFALL", "starred_actors", "JAVIER BARDEM" ], [ "SKYFALL", "starred_actors", "RALPH FIENNES" ], [ "THE AVENGERS", "has_tags", "RALPH FIENNES" ], [ "THE AVENGERS", "release_year", "2012" ], [ "THE AVENGERS", "starred_actors", "RALPH FIENNES" ], [ "THE DARK KNIGHT RISES", "has_tags", "PLOT" ], [ "THE DARK KNIGHT RISES", "release_year", "2012" ], [ "TO THE WONDER", "release_year", "2012" ], [ "TO THE WONDER", "starred_actors", "JAVIER BARDEM" ], [ "WRATH OF THE TITANS", "release_year", "2012" ], [ "WRATH OF THE TITANS", "starred_actors", "RALPH FIENNES" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26619, ADELAIDE KANE 11475, ALEXANDER NEVSKY 5870, HORROR 37146, MAGIC MAN 13937, RHIAN RAMOS 6427, THE PURGE 15562, THE ROAD 24811, THRILLER src, edge_attr, dst 37146, has_genre, 24811 37146, starred_actors, 11475 6427, has_genre, 5870 6427, has_genre, 24811 6427, starred_actors, 26619 15562, has_genre, 5870 15562, starred_actors, 13937 Question: For what reason are ADELAIDE KANE, ALEXANDER NEVSKY, and RHIAN RAMOS associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ADELAIDE KANE", "ALEXANDER NEVSKY", "RHIAN RAMOS" ], "valid_edges": [ [ "MAGIC MAN", "has_genre", "THRILLER" ], [ "MAGIC MAN", "starred_actors", "ALEXANDER NEVSKY" ], [ "THE PURGE", "has_genre", "HORROR" ], [ "THE PURGE", "has_genre", "THRILLER" ], [ "THE PURGE", "starred_actors", "ADELAIDE KANE" ], [ "THE ROAD", "has_genre", "HORROR" ], [ "THE ROAD", "starred_actors", "RHIAN RAMOS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1567, 1954 7841, 1987 12954, BEAR'S KISS 10218, BLACK WIDOW 35452, BOPE 30265, BRAZIL 39480, CHARLTON HESTON 34528, DARK CITY 31254, ELITE SQUAD 36066, FANTASY 37039, ORIGINAL 27643, PLANET OF THE APES 8379, ROMANCE 7394, SOME KIND OF WONDERFUL 6260, SPIRITED AWAY 19351, THE COUNT OF MONTE CRISTO 27995, THE FAR COUNTRY 36977, THE GIRL WHO LEAPT THROUGH TIME 29048, THE NAKED JUNGLE 29641, THE PRINCESS BRIDE 28776, THE WIZARD OF OZ src, edge_attr, dst 12954, has_genre, 36066 12954, has_genre, 8379 10218, release_year, 1567 10218, release_year, 7841 30265, has_tags, 36066 34528, has_tags, 37039 34528, starred_actors, 39480 31254, has_tags, 35452 31254, has_tags, 30265 27643, has_tags, 39480 27643, has_tags, 37039 27643, starred_actors, 39480 7394, has_genre, 8379 7394, has_tags, 8379 7394, release_year, 7841 6260, has_tags, 36066 6260, has_tags, 37039 19351, has_genre, 8379 19351, release_year, 1567 27995, has_genre, 8379 27995, release_year, 1567 36977, has_tags, 37039 36977, has_tags, 8379 29048, release_year, 1567 29048, starred_actors, 39480 29641, has_tags, 36066 29641, has_tags, 37039 29641, has_tags, 8379 29641, release_year, 7841 28776, has_genre, 36066 28776, has_tags, 36066 28776, has_tags, 37039 Question: In what context are BOPE, THE NAKED JUNGLE, and THE PRINCESS BRIDE connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BOPE", "THE NAKED JUNGLE", "THE PRINCESS BRIDE" ], "valid_edges": [ [ "BEAR'S KISS", "has_genre", "FANTASY" ], [ "BEAR'S KISS", "has_genre", "ROMANCE" ], [ "BLACK WIDOW", "release_year", "1954" ], [ "BLACK WIDOW", "release_year", "1987" ], [ "BRAZIL", "has_tags", "FANTASY" ], [ "DARK CITY", "has_tags", "ORIGINAL" ], [ "DARK CITY", "starred_actors", "CHARLTON HESTON" ], [ "ELITE SQUAD", "has_tags", "BOPE" ], [ "ELITE SQUAD", "has_tags", "BRAZIL" ], [ "PLANET OF THE APES", "has_tags", "CHARLTON HESTON" ], [ "PLANET OF THE APES", "has_tags", "ORIGINAL" ], [ "PLANET OF THE APES", "starred_actors", "CHARLTON HESTON" ], [ "SOME KIND OF WONDERFUL", "has_genre", "ROMANCE" ], [ "SOME KIND OF WONDERFUL", "has_tags", "ROMANCE" ], [ "SOME KIND OF WONDERFUL", "release_year", "1987" ], [ "SPIRITED AWAY", "has_tags", "FANTASY" ], [ "SPIRITED AWAY", "has_tags", "ORIGINAL" ], [ "THE COUNT OF MONTE CRISTO", "has_genre", "ROMANCE" ], [ "THE COUNT OF MONTE CRISTO", "release_year", "1954" ], [ "THE FAR COUNTRY", "has_genre", "ROMANCE" ], [ "THE FAR COUNTRY", "release_year", "1954" ], [ "THE GIRL WHO LEAPT THROUGH TIME", "has_tags", "ORIGINAL" ], [ "THE GIRL WHO LEAPT THROUGH TIME", "has_tags", "ROMANCE" ], [ "THE NAKED JUNGLE", "release_year", "1954" ], [ "THE NAKED JUNGLE", "starred_actors", "CHARLTON HESTON" ], [ "THE PRINCESS BRIDE", "has_tags", "FANTASY" ], [ "THE PRINCESS BRIDE", "has_tags", "ORIGINAL" ], [ "THE PRINCESS BRIDE", "has_tags", "ROMANCE" ], [ "THE PRINCESS BRIDE", "release_year", "1987" ], [ "THE WIZARD OF OZ", "has_genre", "FANTASY" ], [ "THE WIZARD OF OZ", "has_tags", "FANTASY" ], [ "THE WIZARD OF OZ", "has_tags", "ORIGINAL" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3702, 1995 1006, 1996 658, 2012 30870, BEAUTIFUL CREATURES 17794, BERNARDO BERTOLUCCI 38196, CHAIN REACTION 7349, EMPIRE RECORDS 39351, HEAVY 29418, JEREMY IRONS 14601, LES MISÉRABLES 14931, LIBERAL ARTS 9640, LIV TYLER 34611, ME AND YOU 38043, PUSHER 15348, RACHEL WEISZ 29038, STEALING BEAUTY 35366, THE BOURNE LEGACY 10924, THE PEBBLE AND THE PENGUIN 15504, THE WORDS src, edge_attr, dst 30870, starred_actors, 29418 30870, starred_actors, 15348 38196, release_year, 1006 38196, starred_actors, 15348 7349, has_tags, 9640 7349, release_year, 3702 39351, release_year, 3702 39351, starred_actors, 9640 14601, release_year, 3702 14601, release_year, 658 14931, release_year, 658 34611, directed_by, 17794 34611, release_year, 658 34611, written_by, 17794 38043, release_year, 1006 38043, release_year, 658 29038, directed_by, 17794 29038, has_tags, 17794 29038, has_tags, 29418 29038, has_tags, 9640 29038, has_tags, 15348 29038, release_year, 1006 29038, written_by, 17794 35366, has_tags, 15348 35366, release_year, 658 10924, release_year, 3702 15504, has_tags, 29418 15504, release_year, 658 15504, starred_actors, 29418 Question: How are LIBERAL ARTS, STEALING BEAUTY, and THE PEBBLE AND THE PENGUIN related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "LIBERAL ARTS", "STEALING BEAUTY", "THE PEBBLE AND THE PENGUIN" ], "valid_edges": [ [ "BEAUTIFUL CREATURES", "starred_actors", "JEREMY IRONS" ], [ "BEAUTIFUL CREATURES", "starred_actors", "RACHEL WEISZ" ], [ "CHAIN REACTION", "release_year", "1996" ], [ "CHAIN REACTION", "starred_actors", "RACHEL WEISZ" ], [ "EMPIRE RECORDS", "has_tags", "LIV TYLER" ], [ "EMPIRE RECORDS", "release_year", "1995" ], [ "HEAVY", "release_year", "1995" ], [ "HEAVY", "starred_actors", "LIV TYLER" ], [ "LES MISÉRABLES", "release_year", "1995" ], [ "LES MISÉRABLES", "release_year", "2012" ], [ "LIBERAL ARTS", "release_year", "2012" ], [ "ME AND YOU", "directed_by", "BERNARDO BERTOLUCCI" ], [ "ME AND YOU", "release_year", "2012" ], [ "ME AND YOU", "written_by", "BERNARDO BERTOLUCCI" ], [ "PUSHER", "release_year", "1996" ], [ "PUSHER", "release_year", "2012" ], [ "STEALING BEAUTY", "directed_by", "BERNARDO BERTOLUCCI" ], [ "STEALING BEAUTY", "has_tags", "BERNARDO BERTOLUCCI" ], [ "STEALING BEAUTY", "has_tags", "JEREMY IRONS" ], [ "STEALING BEAUTY", "has_tags", "LIV TYLER" ], [ "STEALING BEAUTY", "has_tags", "RACHEL WEISZ" ], [ "STEALING BEAUTY", "release_year", "1996" ], [ "STEALING BEAUTY", "written_by", "BERNARDO BERTOLUCCI" ], [ "THE BOURNE LEGACY", "has_tags", "RACHEL WEISZ" ], [ "THE BOURNE LEGACY", "release_year", "2012" ], [ "THE PEBBLE AND THE PENGUIN", "release_year", "1995" ], [ "THE WORDS", "has_tags", "JEREMY IRONS" ], [ "THE WORDS", "release_year", "2012" ], [ "THE WORDS", "starred_actors", "JEREMY IRONS" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 33637, 1959 35845, 2006 27261, 2009 8198, A PRAIRIE HOME COMPANION 22517, A SERIOUS MAN 6283, CARGO 25011, CHILDREN OF GLORY 40097, DARK COMEDY 24943, ETHAN COEN 21123, FARGO 18223, MINNESOTA 4078, NIGHT OF THE GHOULS 32482, NIGHT TRAIN 38358, OBSERVE AND REPORT 26258, PARIS, JE T'AIME 3942, SALVAGE 38498, TAXIDERMIA src, edge_attr, dst 8198, has_tags, 18223 8198, release_year, 35845 22517, directed_by, 24943 22517, has_tags, 40097 22517, has_tags, 24943 22517, has_tags, 18223 22517, release_year, 27261 22517, written_by, 24943 6283, release_year, 35845 6283, release_year, 27261 25011, release_year, 35845 21123, directed_by, 24943 21123, has_tags, 40097 21123, has_tags, 18223 21123, written_by, 24943 4078, release_year, 33637 32482, release_year, 33637 32482, release_year, 27261 38358, has_tags, 40097 38358, release_year, 27261 26258, directed_by, 24943 26258, release_year, 35845 26258, written_by, 24943 3942, release_year, 35845 3942, release_year, 27261 38498, has_tags, 40097 38498, release_year, 35845 Question: How are A SERIOUS MAN, CHILDREN OF GLORY, and NIGHT OF THE GHOULS related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "A SERIOUS MAN", "CHILDREN OF GLORY", "NIGHT OF THE GHOULS" ], "valid_edges": [ [ "A PRAIRIE HOME COMPANION", "has_tags", "MINNESOTA" ], [ "A PRAIRIE HOME COMPANION", "release_year", "2006" ], [ "A SERIOUS MAN", "directed_by", "ETHAN COEN" ], [ "A SERIOUS MAN", "has_tags", "DARK COMEDY" ], [ "A SERIOUS MAN", "has_tags", "ETHAN COEN" ], [ "A SERIOUS MAN", "has_tags", "MINNESOTA" ], [ "A SERIOUS MAN", "release_year", "2009" ], [ "A SERIOUS MAN", "written_by", "ETHAN COEN" ], [ "CARGO", "release_year", "2006" ], [ "CARGO", "release_year", "2009" ], [ "CHILDREN OF GLORY", "release_year", "2006" ], [ "FARGO", "directed_by", "ETHAN COEN" ], [ "FARGO", "has_tags", "DARK COMEDY" ], [ "FARGO", "has_tags", "MINNESOTA" ], [ "FARGO", "written_by", "ETHAN COEN" ], [ "NIGHT OF THE GHOULS", "release_year", "1959" ], [ "NIGHT TRAIN", "release_year", "1959" ], [ "NIGHT TRAIN", "release_year", "2009" ], [ "OBSERVE AND REPORT", "has_tags", "DARK COMEDY" ], [ "OBSERVE AND REPORT", "release_year", "2009" ], [ "PARIS, JE T'AIME", "directed_by", "ETHAN COEN" ], [ "PARIS, JE T'AIME", "release_year", "2006" ], [ "PARIS, JE T'AIME", "written_by", "ETHAN COEN" ], [ "SALVAGE", "release_year", "2006" ], [ "SALVAGE", "release_year", "2009" ], [ "TAXIDERMIA", "has_tags", "DARK COMEDY" ], [ "TAXIDERMIA", "release_year", "2006" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3384, 1935 38258, BRIGHT LIGHTS 230, CARNIVAL IN FLANDERS 30463, COMEDY 6012, FRENCH 22175, I'M REED FISH 14601, LES MISÉRABLES 11142, LUCREZIA BORGIA 30602, PRINCESSE TAM-TAM 25591, THE TRIPLETS OF BELLEVILLE 19429, TONI 1796, ZACKARY ADLER src, edge_attr, dst 38258, release_year, 3384 230, has_genre, 30463 230, in_language, 6012 230, release_year, 3384 22175, directed_by, 1796 22175, has_genre, 30463 22175, written_by, 1796 14601, in_language, 6012 14601, release_year, 3384 11142, in_language, 6012 11142, release_year, 3384 30602, in_language, 6012 30602, release_year, 3384 25591, has_genre, 30463 25591, has_tags, 6012 25591, in_language, 6012 19429, in_language, 6012 19429, release_year, 3384 Question: In what context are BRIGHT LIGHTS, THE TRIPLETS OF BELLEVILLE, and ZACKARY ADLER connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BRIGHT LIGHTS", "THE TRIPLETS OF BELLEVILLE", "ZACKARY ADLER" ], "valid_edges": [ [ "BRIGHT LIGHTS", "release_year", "1935" ], [ "CARNIVAL IN FLANDERS", "has_genre", "COMEDY" ], [ "CARNIVAL IN FLANDERS", "in_language", "FRENCH" ], [ "CARNIVAL IN FLANDERS", "release_year", "1935" ], [ "I'M REED FISH", "directed_by", "ZACKARY ADLER" ], [ "I'M REED FISH", "has_genre", "COMEDY" ], [ "I'M REED FISH", "written_by", "ZACKARY ADLER" ], [ "LES MISÉRABLES", "in_language", "FRENCH" ], [ "LES MISÉRABLES", "release_year", "1935" ], [ "LUCREZIA BORGIA", "in_language", "FRENCH" ], [ "LUCREZIA BORGIA", "release_year", "1935" ], [ "PRINCESSE TAM-TAM", "in_language", "FRENCH" ], [ "PRINCESSE TAM-TAM", "release_year", "1935" ], [ "THE TRIPLETS OF BELLEVILLE", "has_genre", "COMEDY" ], [ "THE TRIPLETS OF BELLEVILLE", "has_tags", "FRENCH" ], [ "THE TRIPLETS OF BELLEVILLE", "in_language", "FRENCH" ], [ "TONI", "in_language", "FRENCH" ], [ "TONI", "release_year", "1935" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 19721, 300 24716, 40 GUNS TO APACHE PASS 25570, BEAUTY AND THE BEAST 36066, FANTASY 6012, FRENCH 31172, KING 14181, ROGER ALLERS 36026, WESTERN src, edge_attr, dst 19721, has_genre, 36066 19721, has_tags, 31172 24716, has_genre, 36026 25570, has_genre, 36066 25570, has_tags, 36066 25570, in_language, 6012 25570, written_by, 14181 36026, in_language, 6012 Question: For what reason are 40 GUNS TO APACHE PASS, KING, and ROGER ALLERS associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "40 GUNS TO APACHE PASS", "KING", "ROGER ALLERS" ], "valid_edges": [ [ "300", "has_genre", "FANTASY" ], [ "300", "has_tags", "KING" ], [ "40 GUNS TO APACHE PASS", "has_genre", "WESTERN" ], [ "BEAUTY AND THE BEAST", "has_genre", "FANTASY" ], [ "BEAUTY AND THE BEAST", "has_tags", "FANTASY" ], [ "BEAUTY AND THE BEAST", "in_language", "FRENCH" ], [ "BEAUTY AND THE BEAST", "written_by", "ROGER ALLERS" ], [ "WESTERN", "in_language", "FRENCH" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37484, 2004 2043, 9 SONGS 5321, A GOOD WOMAN 38203, A HOLE IN MY HEART 20026, A HOME AT THE END OF THE WORLD 5441, A LOVE SONG FOR BOBBY LONG 11398, A MOMENT TO REMEMBER 20576, A WORLD WITHOUT THIEVES 27020, AGAINST THE ROPES 1698, ALFIE 34789, BAD EDUCATION 18380, BEFORE SUNSET 1815, BEFORE THE FALL 2137, BEING JULIA 20294, BIRTH 2856, BROTHERS 20489, CHANGING TIMES 30885, CLOSER 10272, CONFESSIONS OF A TEENAGE DRAMA QUEEN 32049, CRASH 34180, CRUEL INTENTIONS 3 15696, DAY AND NIGHT 27982, DEAR FRANKIE 16961, DIRTY FILTHY LOVE 15779, DORIAN BLUES 1441, DOWN TO THE BONE 36212, DRAMA 1329, ENVY 5924, EROS 15635, ETHAN MAO 5501, EVERYDAY PEOPLE 32706, FIRST LOVE 15080, FLIGHT OF THE PHOENIX 13263, FREEZE FRAME 3175, FRIDAY NIGHT LIGHTS 21640, GARDEN STATE 16914, GILLES' WIFE 28999, GREG SPOTTISWOOD 17567, HARRY + MAX 9621, HAWAII, OSLO 23477, HAWKING 4840, HEAD IN THE CLOUDS 1044, HOTEL RWANDA 20303, HOUSE OF D 8377, ICE MEN 6753, IMAGINARY HEROES 38426, IRON JAWED ANGELS 21861, JERSEY GIRL 8849, KEANE 34731, KINSEY 926, LADDER 49 30600, LADIES IN LAVENDER 37237, LAND OF PLENTY 5251, LIGHTNING BUG 9188, LIGHTNING STRIKES TWICE 11689, LOOK AT ME 12292, MARIE AND BRUCE 20283, MEAN CREEK 831, MELINDA AND MELINDA 33998, MICKEY 28532, MILLION DOLLAR BABY 13143, MILLIONS 4168, MIRACLE 34674, MY SUMMER OF LOVE 26817, MYSTERIOUS SKIN 20433, NEW POLICE STORY 25709, NOBODY KNOWS 37353, NOEL 4132, OMAGH 11031, OUT OF REACH 13268, OYSTER FARMER 29275, P.S. 28047, PALINDROMES 12683, PRIMER 35167, PRIVATE 28125, RAINCOAT 5693, RAISING HELEN 33617, RED DUST 31114, SAINT RALPH 11313, SAVED! 2135, SAVING FACE 12902, SHE HATE ME 36797, SIDEWAYS 12464, SILVER CITY 32387, SIMON 7717, SPANGLISH 10978, STAGE BEAUTY 8374, STRIP SEARCH 24987, SUMMER STORM 6439, THE AVIATOR 16499, THE BEAUTIFUL COUNTRY 5686, THE BRIDGE OF SAN LUIS REY 33022, THE CHORUS 18130, THE CLEARING 21465, THE DOOR IN THE FLOOR 19685, THE FINAL CUT 15429, THE FORGOTTEN 14807, THE GOODBYE GIRL 38765, THE HOLY GIRL 8435, THE KEYS TO THE HOUSE 11711, THE LIBERTINE 28217, THE LIFE AQUATIC WITH STEVE ZISSOU 36024, THE LIZARD 38433, THE MERCHANT OF VENICE 11555, THE NOTEBOOK 34751, THE PASSION OF THE CHRIST 7537, THE RETURNED 15768, THE TERMINAL 25426, THE WOODSMAN 16413, TROPICAL MALADY 29947, TURTLES CAN FLY 32733, VANITY FAIR 7577, VEER-ZAARA 22949, VERA DRAKE 37859, WE DON'T LIVE HERE ANYMORE 21897, WHEN WILL I BE LOVED 7055, WICKER PARK 18720, WILBY WONDERFUL 32096, WILD SIDE 7208, WINTER SOLSTICE src, edge_attr, dst 2043, has_genre, 36212 2043, release_year, 37484 5321, has_genre, 36212 5321, release_year, 37484 38203, has_genre, 36212 38203, release_year, 37484 20026, has_genre, 36212 20026, release_year, 37484 5441, has_genre, 36212 5441, release_year, 37484 11398, has_genre, 36212 11398, release_year, 37484 20576, has_genre, 36212 20576, release_year, 37484 27020, has_genre, 36212 27020, release_year, 37484 1698, has_genre, 36212 1698, release_year, 37484 34789, has_genre, 36212 34789, has_tags, 36212 34789, release_year, 37484 18380, has_genre, 36212 18380, release_year, 37484 1815, has_genre, 36212 1815, release_year, 37484 2137, has_genre, 36212 2137, release_year, 37484 20294, has_genre, 36212 20294, release_year, 37484 2856, has_genre, 36212 2856, release_year, 37484 20489, has_genre, 36212 20489, release_year, 37484 30885, has_genre, 36212 30885, has_tags, 36212 30885, release_year, 37484 10272, has_tags, 36212 10272, release_year, 37484 32049, has_genre, 36212 32049, release_year, 37484 34180, has_genre, 36212 34180, release_year, 37484 15696, has_genre, 36212 15696, has_tags, 36212 15696, release_year, 37484 27982, has_genre, 36212 27982, release_year, 37484 16961, has_genre, 36212 16961, release_year, 37484 15779, has_genre, 36212 15779, release_year, 37484 1441, has_genre, 36212 1441, release_year, 37484 1329, has_genre, 36212 1329, release_year, 37484 5924, has_genre, 36212 5924, release_year, 37484 15635, has_genre, 36212 15635, release_year, 37484 5501, has_genre, 36212 5501, release_year, 37484 32706, has_genre, 36212 32706, release_year, 37484 15080, has_genre, 36212 15080, release_year, 37484 13263, has_genre, 36212 13263, release_year, 37484 3175, has_genre, 36212 3175, has_tags, 36212 3175, release_year, 37484 21640, has_genre, 36212 21640, release_year, 37484 16914, has_genre, 36212 16914, release_year, 37484 17567, has_genre, 36212 17567, release_year, 37484 9621, has_genre, 36212 9621, release_year, 37484 23477, has_genre, 36212 23477, release_year, 37484 4840, has_genre, 36212 4840, release_year, 37484 1044, has_genre, 36212 1044, has_tags, 36212 1044, release_year, 37484 20303, has_genre, 36212 20303, release_year, 37484 8377, release_year, 37484 8377, starred_actors, 28999 6753, has_genre, 36212 6753, release_year, 37484 38426, has_genre, 36212 38426, release_year, 37484 21861, has_genre, 36212 21861, has_tags, 36212 21861, release_year, 37484 8849, has_genre, 36212 8849, release_year, 37484 34731, has_genre, 36212 34731, release_year, 37484 926, has_genre, 36212 926, release_year, 37484 30600, has_genre, 36212 30600, release_year, 37484 37237, has_genre, 36212 37237, release_year, 37484 5251, has_genre, 36212 5251, release_year, 37484 9188, has_genre, 36212 11689, has_genre, 36212 11689, release_year, 37484 12292, has_genre, 36212 12292, release_year, 37484 20283, has_genre, 36212 20283, has_tags, 36212 20283, release_year, 37484 831, has_genre, 36212 831, release_year, 37484 33998, has_genre, 36212 33998, release_year, 37484 28532, has_genre, 36212 28532, has_tags, 36212 28532, release_year, 37484 13143, has_genre, 36212 13143, release_year, 37484 4168, has_genre, 36212 4168, release_year, 37484 34674, has_genre, 36212 34674, has_tags, 36212 34674, release_year, 37484 26817, has_genre, 36212 26817, release_year, 37484 20433, has_genre, 36212 20433, release_year, 37484 25709, has_genre, 36212 25709, release_year, 37484 37353, has_genre, 36212 37353, has_tags, 36212 37353, release_year, 37484 4132, has_genre, 36212 4132, release_year, 37484 11031, has_genre, 36212 11031, release_year, 37484 13268, has_genre, 36212 13268, release_year, 37484 29275, has_genre, 36212 29275, release_year, 37484 28047, has_genre, 36212 28047, release_year, 37484 12683, has_genre, 36212 12683, release_year, 37484 35167, has_genre, 36212 35167, release_year, 37484 28125, has_genre, 36212 28125, release_year, 37484 5693, has_genre, 36212 5693, release_year, 37484 33617, has_genre, 36212 33617, release_year, 37484 31114, has_genre, 36212 31114, release_year, 37484 11313, has_genre, 36212 11313, release_year, 37484 2135, has_genre, 36212 2135, release_year, 37484 12902, has_genre, 36212 12902, release_year, 37484 36797, has_genre, 36212 36797, release_year, 37484 12464, has_genre, 36212 12464, release_year, 37484 32387, has_genre, 36212 32387, release_year, 37484 7717, has_genre, 36212 7717, release_year, 37484 10978, has_genre, 36212 10978, release_year, 37484 8374, has_genre, 36212 8374, release_year, 37484 24987, has_genre, 36212 24987, release_year, 37484 6439, has_genre, 36212 6439, has_tags, 36212 6439, release_year, 37484 16499, has_genre, 36212 16499, has_tags, 36212 16499, release_year, 37484 5686, has_genre, 36212 5686, release_year, 37484 33022, has_genre, 36212 33022, has_tags, 36212 33022, release_year, 37484 18130, has_genre, 36212 18130, release_year, 37484 21465, has_genre, 36212 21465, has_tags, 36212 21465, release_year, 37484 19685, has_genre, 36212 19685, release_year, 37484 15429, has_genre, 36212 15429, release_year, 37484 14807, has_genre, 36212 14807, release_year, 37484 38765, has_genre, 36212 38765, release_year, 37484 8435, has_genre, 36212 8435, release_year, 37484 11711, has_genre, 36212 11711, release_year, 37484 28217, has_genre, 36212 28217, release_year, 37484 36024, has_genre, 36212 36024, release_year, 37484 38433, has_genre, 36212 38433, release_year, 37484 11555, has_genre, 36212 11555, release_year, 37484 34751, has_genre, 36212 34751, release_year, 37484 7537, has_genre, 36212 7537, release_year, 37484 15768, has_genre, 36212 15768, has_tags, 36212 15768, release_year, 37484 25426, has_genre, 36212 25426, has_tags, 36212 25426, release_year, 37484 16413, has_genre, 36212 16413, release_year, 37484 29947, has_genre, 36212 29947, release_year, 37484 32733, has_genre, 36212 32733, release_year, 37484 7577, has_genre, 36212 7577, release_year, 37484 22949, has_genre, 36212 22949, release_year, 37484 37859, has_genre, 36212 37859, release_year, 37484 21897, has_genre, 36212 21897, release_year, 37484 7055, has_genre, 36212 7055, release_year, 37484 18720, has_genre, 36212 18720, release_year, 37484 32096, has_genre, 36212 32096, release_year, 37484 7208, has_genre, 36212 7208, release_year, 37484 Question: For what reason are EVERYDAY PEOPLE, GREG SPOTTISWOOD, and LIGHTNING STRIKES TWICE associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "EVERYDAY PEOPLE", "GREG SPOTTISWOOD", "LIGHTNING STRIKES TWICE" ], "valid_edges": [ [ "9 SONGS", "has_genre", "DRAMA" ], [ "9 SONGS", "release_year", "2004" ], [ "A GOOD WOMAN", "has_genre", "DRAMA" ], [ "A GOOD WOMAN", "release_year", "2004" ], [ "A HOLE IN MY HEART", "has_genre", "DRAMA" ], [ "A HOLE IN MY HEART", "release_year", "2004" ], [ "A HOME AT THE END OF THE WORLD", "has_genre", "DRAMA" ], [ "A HOME AT THE END OF THE WORLD", "release_year", "2004" ], [ "A LOVE SONG FOR BOBBY LONG", "has_genre", "DRAMA" ], [ "A LOVE SONG FOR BOBBY LONG", "release_year", "2004" ], [ "A MOMENT TO REMEMBER", "has_genre", "DRAMA" ], [ "A MOMENT TO REMEMBER", "release_year", "2004" ], [ "A WORLD WITHOUT THIEVES", "has_genre", "DRAMA" ], [ "A WORLD WITHOUT THIEVES", "release_year", "2004" ], [ "AGAINST THE ROPES", "has_genre", "DRAMA" ], [ "AGAINST THE ROPES", "release_year", "2004" ], [ "ALFIE", "has_genre", "DRAMA" ], [ "ALFIE", "release_year", "2004" ], [ "BAD EDUCATION", "has_genre", "DRAMA" ], [ "BAD EDUCATION", "has_tags", "DRAMA" ], [ "BAD EDUCATION", "release_year", "2004" ], [ "BEFORE SUNSET", "has_genre", "DRAMA" ], [ "BEFORE SUNSET", "release_year", "2004" ], [ "BEFORE THE FALL", "has_genre", "DRAMA" ], [ "BEFORE THE FALL", "release_year", "2004" ], [ "BEING JULIA", "has_genre", "DRAMA" ], [ "BEING JULIA", "release_year", "2004" ], [ "BIRTH", "has_genre", "DRAMA" ], [ "BIRTH", "release_year", "2004" ], [ "BROTHERS", "has_genre", "DRAMA" ], [ "BROTHERS", "release_year", "2004" ], [ "CHANGING TIMES", "has_genre", "DRAMA" ], [ "CHANGING TIMES", "release_year", "2004" ], [ "CLOSER", "has_genre", "DRAMA" ], [ "CLOSER", "has_tags", "DRAMA" ], [ "CLOSER", "release_year", "2004" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_tags", "DRAMA" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "release_year", "2004" ], [ "CRASH", "has_genre", "DRAMA" ], [ "CRASH", "release_year", "2004" ], [ "CRUEL INTENTIONS 3", "has_genre", "DRAMA" ], [ "CRUEL INTENTIONS 3", "release_year", "2004" ], [ "DAY AND NIGHT", "has_genre", "DRAMA" ], [ "DAY AND NIGHT", "has_tags", "DRAMA" ], [ "DAY AND NIGHT", "release_year", "2004" ], [ "DEAR FRANKIE", "has_genre", "DRAMA" ], [ "DEAR FRANKIE", "release_year", "2004" ], [ "DIRTY FILTHY LOVE", "has_genre", "DRAMA" ], [ "DIRTY FILTHY LOVE", "release_year", "2004" ], [ "DORIAN BLUES", "has_genre", "DRAMA" ], [ "DORIAN BLUES", "release_year", "2004" ], [ "DOWN TO THE BONE", "has_genre", "DRAMA" ], [ "DOWN TO THE BONE", "release_year", "2004" ], [ "ENVY", "has_genre", "DRAMA" ], [ "ENVY", "release_year", "2004" ], [ "EROS", "has_genre", "DRAMA" ], [ "EROS", "release_year", "2004" ], [ "ETHAN MAO", "has_genre", "DRAMA" ], [ "ETHAN MAO", "release_year", "2004" ], [ "EVERYDAY PEOPLE", "has_genre", "DRAMA" ], [ "EVERYDAY PEOPLE", "release_year", "2004" ], [ "FIRST LOVE", "has_genre", "DRAMA" ], [ "FIRST LOVE", "release_year", "2004" ], [ "FLIGHT OF THE PHOENIX", "has_genre", "DRAMA" ], [ "FLIGHT OF THE PHOENIX", "release_year", "2004" ], [ "FREEZE FRAME", "has_genre", "DRAMA" ], [ "FREEZE FRAME", "release_year", "2004" ], [ "FRIDAY NIGHT LIGHTS", "has_genre", "DRAMA" ], [ "FRIDAY NIGHT LIGHTS", "has_tags", "DRAMA" ], [ "FRIDAY NIGHT LIGHTS", "release_year", "2004" ], [ "GARDEN STATE", "has_genre", "DRAMA" ], [ "GARDEN STATE", "release_year", "2004" ], [ "GILLES' WIFE", "has_genre", "DRAMA" ], [ "GILLES' WIFE", "release_year", "2004" ], [ "HARRY + MAX", "has_genre", "DRAMA" ], [ "HARRY + MAX", "release_year", "2004" ], [ "HAWAII, OSLO", "has_genre", "DRAMA" ], [ "HAWAII, OSLO", "release_year", "2004" ], [ "HAWKING", "has_genre", "DRAMA" ], [ "HAWKING", "release_year", "2004" ], [ "HEAD IN THE CLOUDS", "has_genre", "DRAMA" ], [ "HEAD IN THE CLOUDS", "release_year", "2004" ], [ "HOTEL RWANDA", "has_genre", "DRAMA" ], [ "HOTEL RWANDA", "has_tags", "DRAMA" ], [ "HOTEL RWANDA", "release_year", "2004" ], [ "HOUSE OF D", "has_genre", "DRAMA" ], [ "HOUSE OF D", "release_year", "2004" ], [ "ICE MEN", "release_year", "2004" ], [ "ICE MEN", "starred_actors", "GREG SPOTTISWOOD" ], [ "IMAGINARY HEROES", "has_genre", "DRAMA" ], [ "IMAGINARY HEROES", "release_year", "2004" ], [ "IRON JAWED ANGELS", "has_genre", "DRAMA" ], [ "IRON JAWED ANGELS", "release_year", "2004" ], [ "JERSEY GIRL", "has_genre", "DRAMA" ], [ "JERSEY GIRL", "has_tags", "DRAMA" ], [ "JERSEY GIRL", "release_year", "2004" ], [ "KEANE", "has_genre", "DRAMA" ], [ "KEANE", "release_year", "2004" ], [ "KINSEY", "has_genre", "DRAMA" ], [ "KINSEY", "release_year", "2004" ], [ "LADDER 49", "has_genre", "DRAMA" ], [ "LADDER 49", "release_year", "2004" ], [ "LADIES IN LAVENDER", "has_genre", "DRAMA" ], [ "LADIES IN LAVENDER", "release_year", "2004" ], [ "LAND OF PLENTY", "has_genre", "DRAMA" ], [ "LAND OF PLENTY", "release_year", "2004" ], [ "LIGHTNING BUG", "has_genre", "DRAMA" ], [ "LIGHTNING BUG", "release_year", "2004" ], [ "LIGHTNING STRIKES TWICE", "has_genre", "DRAMA" ], [ "LOOK AT ME", "has_genre", "DRAMA" ], [ "LOOK AT ME", "release_year", "2004" ], [ "MARIE AND BRUCE", "has_genre", "DRAMA" ], [ "MARIE AND BRUCE", "release_year", "2004" ], [ "MEAN CREEK", "has_genre", "DRAMA" ], [ "MEAN CREEK", "has_tags", "DRAMA" ], [ "MEAN CREEK", "release_year", "2004" ], [ "MELINDA AND MELINDA", "has_genre", "DRAMA" ], [ "MELINDA AND MELINDA", "release_year", "2004" ], [ "MICKEY", "has_genre", "DRAMA" ], [ "MICKEY", "release_year", "2004" ], [ "MILLION DOLLAR BABY", "has_genre", "DRAMA" ], [ "MILLION DOLLAR BABY", "has_tags", "DRAMA" ], [ "MILLION DOLLAR BABY", "release_year", "2004" ], [ "MILLIONS", "has_genre", "DRAMA" ], [ "MILLIONS", "release_year", "2004" ], [ "MIRACLE", "has_genre", "DRAMA" ], [ "MIRACLE", "release_year", "2004" ], [ "MY SUMMER OF LOVE", "has_genre", "DRAMA" ], [ "MY SUMMER OF LOVE", "has_tags", "DRAMA" ], [ "MY SUMMER OF LOVE", "release_year", "2004" ], [ "MYSTERIOUS SKIN", "has_genre", "DRAMA" ], [ "MYSTERIOUS SKIN", "release_year", "2004" ], [ "NEW POLICE STORY", "has_genre", "DRAMA" ], [ "NEW POLICE STORY", "release_year", "2004" ], [ "NOBODY KNOWS", "has_genre", "DRAMA" ], [ "NOBODY KNOWS", "release_year", "2004" ], [ "NOEL", "has_genre", "DRAMA" ], [ "NOEL", "has_tags", "DRAMA" ], [ "NOEL", "release_year", "2004" ], [ "OMAGH", "has_genre", "DRAMA" ], [ "OMAGH", "release_year", "2004" ], [ "OUT OF REACH", "has_genre", "DRAMA" ], [ "OUT OF REACH", "release_year", "2004" ], [ "OYSTER FARMER", "has_genre", "DRAMA" ], [ "OYSTER FARMER", "release_year", "2004" ], [ "P.S.", "has_genre", "DRAMA" ], [ "P.S.", "release_year", "2004" ], [ "PALINDROMES", "has_genre", "DRAMA" ], [ "PALINDROMES", "release_year", "2004" ], [ "PRIMER", "has_genre", "DRAMA" ], [ "PRIMER", "release_year", "2004" ], [ "PRIVATE", "has_genre", "DRAMA" ], [ "PRIVATE", "release_year", "2004" ], [ "RAINCOAT", "has_genre", "DRAMA" ], [ "RAINCOAT", "release_year", "2004" ], [ "RAISING HELEN", "has_genre", "DRAMA" ], [ "RAISING HELEN", "release_year", "2004" ], [ "RED DUST", "has_genre", "DRAMA" ], [ "RED DUST", "release_year", "2004" ], [ "SAINT RALPH", "has_genre", "DRAMA" ], [ "SAINT RALPH", "release_year", "2004" ], [ "SAVED!", "has_genre", "DRAMA" ], [ "SAVED!", "release_year", "2004" ], [ "SAVING FACE", "has_genre", "DRAMA" ], [ "SAVING FACE", "release_year", "2004" ], [ "SHE HATE ME", "has_genre", "DRAMA" ], [ "SHE HATE ME", "release_year", "2004" ], [ "SIDEWAYS", "has_genre", "DRAMA" ], [ "SIDEWAYS", "release_year", "2004" ], [ "SILVER CITY", "has_genre", "DRAMA" ], [ "SILVER CITY", "release_year", "2004" ], [ "SIMON", "has_genre", "DRAMA" ], [ "SIMON", "release_year", "2004" ], [ "SPANGLISH", "has_genre", "DRAMA" ], [ "SPANGLISH", "release_year", "2004" ], [ "STAGE BEAUTY", "has_genre", "DRAMA" ], [ "STAGE BEAUTY", "release_year", "2004" ], [ "STRIP SEARCH", "has_genre", "DRAMA" ], [ "STRIP SEARCH", "release_year", "2004" ], [ "SUMMER STORM", "has_genre", "DRAMA" ], [ "SUMMER STORM", "release_year", "2004" ], [ "THE AVIATOR", "has_genre", "DRAMA" ], [ "THE AVIATOR", "has_tags", "DRAMA" ], [ "THE AVIATOR", "release_year", "2004" ], [ "THE BEAUTIFUL COUNTRY", "has_genre", "DRAMA" ], [ "THE BEAUTIFUL COUNTRY", "has_tags", "DRAMA" ], [ "THE BEAUTIFUL COUNTRY", "release_year", "2004" ], [ "THE BRIDGE OF SAN LUIS REY", "has_genre", "DRAMA" ], [ "THE BRIDGE OF SAN LUIS REY", "release_year", "2004" ], [ "THE CHORUS", "has_genre", "DRAMA" ], [ "THE CHORUS", "has_tags", "DRAMA" ], [ "THE CHORUS", "release_year", "2004" ], [ "THE CLEARING", "has_genre", "DRAMA" ], [ "THE CLEARING", "release_year", "2004" ], [ "THE DOOR IN THE FLOOR", "has_genre", "DRAMA" ], [ "THE DOOR IN THE FLOOR", "has_tags", "DRAMA" ], [ "THE DOOR IN THE FLOOR", "release_year", "2004" ], [ "THE FINAL CUT", "has_genre", "DRAMA" ], [ "THE FINAL CUT", "release_year", "2004" ], [ "THE FORGOTTEN", "has_genre", "DRAMA" ], [ "THE FORGOTTEN", "release_year", "2004" ], [ "THE GOODBYE GIRL", "has_genre", "DRAMA" ], [ "THE GOODBYE GIRL", "release_year", "2004" ], [ "THE HOLY GIRL", "has_genre", "DRAMA" ], [ "THE HOLY GIRL", "release_year", "2004" ], [ "THE KEYS TO THE HOUSE", "has_genre", "DRAMA" ], [ "THE KEYS TO THE HOUSE", "release_year", "2004" ], [ "THE LIBERTINE", "has_genre", "DRAMA" ], [ "THE LIBERTINE", "release_year", "2004" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "has_genre", "DRAMA" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "release_year", "2004" ], [ "THE LIZARD", "has_genre", "DRAMA" ], [ "THE LIZARD", "release_year", "2004" ], [ "THE MERCHANT OF VENICE", "has_genre", "DRAMA" ], [ "THE MERCHANT OF VENICE", "release_year", "2004" ], [ "THE NOTEBOOK", "has_genre", "DRAMA" ], [ "THE NOTEBOOK", "release_year", "2004" ], [ "THE PASSION OF THE CHRIST", "has_genre", "DRAMA" ], [ "THE PASSION OF THE CHRIST", "release_year", "2004" ], [ "THE RETURNED", "has_genre", "DRAMA" ], [ "THE RETURNED", "release_year", "2004" ], [ "THE TERMINAL", "has_genre", "DRAMA" ], [ "THE TERMINAL", "has_tags", "DRAMA" ], [ "THE TERMINAL", "release_year", "2004" ], [ "THE WOODSMAN", "has_genre", "DRAMA" ], [ "THE WOODSMAN", "has_tags", "DRAMA" ], [ "THE WOODSMAN", "release_year", "2004" ], [ "TROPICAL MALADY", "has_genre", "DRAMA" ], [ "TROPICAL MALADY", "release_year", "2004" ], [ "TURTLES CAN FLY", "has_genre", "DRAMA" ], [ "TURTLES CAN FLY", "release_year", "2004" ], [ "VANITY FAIR", "has_genre", "DRAMA" ], [ "VANITY FAIR", "release_year", "2004" ], [ "VEER-ZAARA", "has_genre", "DRAMA" ], [ "VEER-ZAARA", "release_year", "2004" ], [ "VERA DRAKE", "has_genre", "DRAMA" ], [ "VERA DRAKE", "release_year", "2004" ], [ "WE DON'T LIVE HERE ANYMORE", "has_genre", "DRAMA" ], [ "WE DON'T LIVE HERE ANYMORE", "release_year", "2004" ], [ "WHEN WILL I BE LOVED", "has_genre", "DRAMA" ], [ "WHEN WILL I BE LOVED", "release_year", "2004" ], [ "WICKER PARK", "has_genre", "DRAMA" ], [ "WICKER PARK", "release_year", "2004" ], [ "WILBY WONDERFUL", "has_genre", "DRAMA" ], [ "WILBY WONDERFUL", "release_year", "2004" ], [ "WILD SIDE", "has_genre", "DRAMA" ], [ "WILD SIDE", "release_year", "2004" ], [ "WINTER SOLSTICE", "has_genre", "DRAMA" ], [ "WINTER SOLSTICE", "release_year", "2004" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26762, 2008 37549, A CHORUS LINE 4269, A HARD DAY'S NIGHT 8198, A PRAIRIE HOME COMPANION 9152, A STAR IS BORN 27803, AASHIQUI 2 30643, ACROSS THE UNIVERSE 19457, AGING 27061, ALADDIN 6847, ALL THAT JAZZ 26658, ANOTHER CINDERELLA STORY 35145, AUGUST RUSH 39085, BILLY ELLIOT 16023, BLUES BROTHERS 2000 36271, BURLESQUE 24631, CADILLAC RECORDS 21381, CAMP ROCK 5376, CAPE NO. 7 10349, CHICAGO 10327, CHITTY CHITTY BANG BANG 35525, CHRISTMAS ON MARS 39861, CINDERELLA 14657, CSNY/DÉJÀ VU 37267, DREAMGIRLS 16291, EVITA 33716, FAME 409, FARINELLI 5287, FROZEN 14698, GRAFFITI BRIDGE 20263, HAIR 9798, HAIRSPRAY 1292, HEDWIG AND THE ANGRY INCH 10346, HERO WANTED 14375, HIGH SCHOOL MUSICAL 30806, IMAGINAERUM 33279, IN BRUGES 16243, JAILHOUSE ROCK 4492, JESUS CHRIST SUPERSTAR 36940, LABYRINTH 8851, LITTLE SHOP OF HORRORS 5163, MAMMA MIA! 22845, MUSIC 24593, MUSICAL 31661, MY FAIR LADY 29995, NEW YORK, NEW YORK 7019, NORMAN REEDUS 18184, OKLAHOMA! 25899, ONCE 8740, PARIS 36 4806, PETE'S DRAGON 14026, PINOCCHIO 6864, PITCH PERFECT 24736, PROM NIGHT 4005, PURPLE RAIN 3257, RED CANYON 30416, REPO! THE GENETIC OPERA 36575, RHINESTONE 38119, ROUSTABOUT 901, SCHOOL OF ROCK 22068, SOUL MEN 25270, THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT 26008, THE BLUES BROTHERS 888, THE JAZZ SINGER 37562, THE KING AND I 14478, THE LION KING 22217, THE MAMBO KINGS 11189, THE MUPPETS 34124, THE NIGHTMARE BEFORE CHRISTMAS 10721, THE ROCKY HORROR PICTURE SHOW 37901, THE SOUND OF MUSIC 31313, THE WEST POINT STORY 28776, THE WIZARD OF OZ 19447, THE WRESTLER 32562, VICTOR VICTORIA 32589, WERE THE WORLD MINE 4552, WEST SIDE STORY src, edge_attr, dst 37549, has_genre, 22845 37549, has_genre, 24593 4269, has_genre, 22845 4269, has_tags, 22845 4269, has_tags, 24593 8198, has_genre, 22845 8198, has_tags, 24593 9152, has_genre, 22845 9152, has_genre, 24593 9152, has_tags, 24593 27803, has_genre, 22845 27803, has_genre, 24593 30643, has_genre, 24593 30643, has_tags, 22845 30643, has_tags, 24593 27061, has_tags, 22845 27061, has_tags, 24593 6847, has_genre, 22845 6847, has_genre, 24593 6847, has_tags, 24593 26658, has_genre, 24593 26658, release_year, 26762 35145, has_genre, 22845 35145, has_tags, 22845 35145, has_tags, 24593 39085, has_genre, 22845 39085, has_tags, 24593 16023, has_tags, 22845 16023, has_tags, 24593 36271, has_genre, 22845 36271, has_tags, 24593 24631, has_tags, 22845 24631, release_year, 26762 21381, has_genre, 24593 21381, release_year, 26762 5376, has_genre, 22845 5376, release_year, 26762 10349, has_genre, 24593 10349, has_tags, 22845 10349, has_tags, 24593 10327, has_tags, 22845 10327, has_tags, 24593 35525, has_genre, 22845 35525, release_year, 26762 39861, has_genre, 24593 39861, has_tags, 22845 39861, has_tags, 24593 14657, has_genre, 22845 14657, release_year, 26762 37267, has_genre, 22845 37267, has_genre, 24593 37267, has_tags, 24593 16291, has_tags, 22845 16291, has_tags, 24593 33716, has_genre, 22845 33716, has_genre, 24593 33716, has_tags, 22845 409, has_genre, 22845 409, has_tags, 24593 5287, has_tags, 22845 5287, has_tags, 24593 14698, has_genre, 22845 14698, has_genre, 24593 20263, has_genre, 24593 20263, has_tags, 22845 20263, has_tags, 24593 9798, has_genre, 22845 9798, has_genre, 24593 9798, has_tags, 24593 1292, has_genre, 22845 1292, has_tags, 22845 1292, has_tags, 24593 10346, release_year, 26762 10346, starred_actors, 7019 14375, has_tags, 22845 14375, has_tags, 24593 30806, has_genre, 24593 30806, has_tags, 22845 33279, has_tags, 22845 33279, release_year, 26762 16243, has_genre, 22845 16243, has_genre, 24593 4492, has_genre, 22845 4492, has_genre, 24593 4492, has_tags, 24593 36940, has_tags, 22845 36940, has_tags, 24593 8851, has_genre, 24593 8851, has_tags, 22845 8851, has_tags, 24593 5163, has_genre, 24593 5163, has_tags, 24593 5163, release_year, 26762 31661, has_genre, 24593 31661, has_tags, 22845 31661, has_tags, 24593 29995, has_genre, 22845 29995, has_genre, 24593 18184, has_genre, 24593 18184, has_tags, 22845 18184, has_tags, 24593 25899, has_genre, 22845 25899, has_tags, 22845 25899, has_tags, 24593 8740, has_genre, 22845 8740, release_year, 26762 4806, has_tags, 22845 4806, has_tags, 24593 14026, has_tags, 22845 14026, has_tags, 24593 6864, has_genre, 22845 6864, has_tags, 22845 6864, has_tags, 24593 24736, has_tags, 22845 24736, release_year, 26762 4005, has_genre, 22845 4005, has_genre, 24593 3257, release_year, 26762 3257, starred_actors, 7019 30416, has_genre, 24593 30416, has_tags, 24593 30416, release_year, 26762 36575, has_genre, 22845 36575, has_genre, 24593 38119, has_genre, 22845 38119, has_genre, 24593 901, has_genre, 22845 901, has_tags, 22845 901, has_tags, 24593 22068, has_genre, 22845 22068, release_year, 26762 25270, has_genre, 22845 25270, has_tags, 24593 26008, has_tags, 22845 26008, has_tags, 24593 888, has_genre, 22845 888, has_genre, 24593 37562, has_genre, 24593 37562, has_tags, 22845 37562, has_tags, 24593 14478, has_tags, 22845 14478, has_tags, 24593 22217, has_genre, 22845 22217, has_tags, 24593 11189, has_genre, 24593 11189, has_tags, 22845 11189, has_tags, 24593 34124, has_tags, 22845 34124, has_tags, 24593 10721, has_genre, 24593 10721, has_tags, 22845 10721, has_tags, 24593 37901, has_tags, 22845 37901, has_tags, 24593 31313, has_genre, 22845 31313, has_tags, 24593 28776, has_tags, 22845 28776, has_tags, 24593 19447, has_tags, 19457 19447, release_year, 26762 32562, has_genre, 22845 32562, has_genre, 24593 32589, has_tags, 24593 32589, release_year, 26762 4552, has_genre, 24593 4552, has_tags, 22845 4552, has_tags, 24593 Question: For what reason are AGING, HERO WANTED, and NEW YORK, NEW YORK associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "AGING", "HERO WANTED", "NEW YORK, NEW YORK" ], "valid_edges": [ [ "A CHORUS LINE", "has_genre", "MUSIC" ], [ "A CHORUS LINE", "has_genre", "MUSICAL" ], [ "A HARD DAY'S NIGHT", "has_genre", "MUSIC" ], [ "A HARD DAY'S NIGHT", "has_tags", "MUSIC" ], [ "A HARD DAY'S NIGHT", "has_tags", "MUSICAL" ], [ "A PRAIRIE HOME COMPANION", "has_genre", "MUSIC" ], [ "A PRAIRIE HOME COMPANION", "has_tags", "MUSICAL" ], [ "A STAR IS BORN", "has_genre", "MUSIC" ], [ "A STAR IS BORN", "has_genre", "MUSICAL" ], [ "A STAR IS BORN", "has_tags", "MUSICAL" ], [ "AASHIQUI 2", "has_genre", "MUSIC" ], [ "AASHIQUI 2", "has_genre", "MUSICAL" ], [ "ACROSS THE UNIVERSE", "has_genre", "MUSICAL" ], [ "ACROSS THE UNIVERSE", "has_tags", "MUSIC" ], [ "ACROSS THE UNIVERSE", "has_tags", "MUSICAL" ], [ "ALADDIN", "has_tags", "MUSIC" ], [ "ALADDIN", "has_tags", "MUSICAL" ], [ "ALL THAT JAZZ", "has_genre", "MUSIC" ], [ "ALL THAT JAZZ", "has_genre", "MUSICAL" ], [ "ALL THAT JAZZ", "has_tags", "MUSICAL" ], [ "ANOTHER CINDERELLA STORY", "has_genre", "MUSICAL" ], [ "ANOTHER CINDERELLA STORY", "release_year", "2008" ], [ "AUGUST RUSH", "has_genre", "MUSIC" ], [ "AUGUST RUSH", "has_tags", "MUSIC" ], [ "AUGUST RUSH", "has_tags", "MUSICAL" ], [ "BILLY ELLIOT", "has_genre", "MUSIC" ], [ "BILLY ELLIOT", "has_tags", "MUSICAL" ], [ "BLUES BROTHERS 2000", "has_tags", "MUSIC" ], [ "BLUES BROTHERS 2000", "has_tags", "MUSICAL" ], [ "BURLESQUE", "has_genre", "MUSIC" ], [ "BURLESQUE", "has_tags", "MUSICAL" ], [ "CADILLAC RECORDS", "has_tags", "MUSIC" ], [ "CADILLAC RECORDS", "release_year", "2008" ], [ "CAMP ROCK", "has_genre", "MUSICAL" ], [ "CAMP ROCK", "release_year", "2008" ], [ "CAPE NO. 7", "has_genre", "MUSIC" ], [ "CAPE NO. 7", "release_year", "2008" ], [ "CHICAGO", "has_genre", "MUSICAL" ], [ "CHICAGO", "has_tags", "MUSIC" ], [ "CHICAGO", "has_tags", "MUSICAL" ], [ "CHITTY CHITTY BANG BANG", "has_tags", "MUSIC" ], [ "CHITTY CHITTY BANG BANG", "has_tags", "MUSICAL" ], [ "CHRISTMAS ON MARS", "has_genre", "MUSIC" ], [ "CHRISTMAS ON MARS", "release_year", "2008" ], [ "CINDERELLA", "has_genre", "MUSICAL" ], [ "CINDERELLA", "has_tags", "MUSIC" ], [ "CINDERELLA", "has_tags", "MUSICAL" ], [ "CSNY/DÉJÀ VU", "has_genre", "MUSIC" ], [ "CSNY/DÉJÀ VU", "release_year", "2008" ], [ "DREAMGIRLS", "has_genre", "MUSIC" ], [ "DREAMGIRLS", "has_genre", "MUSICAL" ], [ "DREAMGIRLS", "has_tags", "MUSICAL" ], [ "EVITA", "has_tags", "MUSIC" ], [ "EVITA", "has_tags", "MUSICAL" ], [ "FAME", "has_genre", "MUSIC" ], [ "FAME", "has_genre", "MUSICAL" ], [ "FAME", "has_tags", "MUSIC" ], [ "FARINELLI", "has_genre", "MUSIC" ], [ "FARINELLI", "has_tags", "MUSICAL" ], [ "FROZEN", "has_tags", "MUSIC" ], [ "FROZEN", "has_tags", "MUSICAL" ], [ "GRAFFITI BRIDGE", "has_genre", "MUSIC" ], [ "GRAFFITI BRIDGE", "has_genre", "MUSICAL" ], [ "HAIR", "has_genre", "MUSICAL" ], [ "HAIR", "has_tags", "MUSIC" ], [ "HAIR", "has_tags", "MUSICAL" ], [ "HAIRSPRAY", "has_genre", "MUSIC" ], [ "HAIRSPRAY", "has_genre", "MUSICAL" ], [ "HAIRSPRAY", "has_tags", "MUSICAL" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "MUSIC" ], [ "HEDWIG AND THE ANGRY INCH", "has_tags", "MUSIC" ], [ "HEDWIG AND THE ANGRY INCH", "has_tags", "MUSICAL" ], [ "HERO WANTED", "release_year", "2008" ], [ "HERO WANTED", "starred_actors", "NORMAN REEDUS" ], [ "HIGH SCHOOL MUSICAL", "has_tags", "MUSIC" ], [ "HIGH SCHOOL MUSICAL", "has_tags", "MUSICAL" ], [ "IMAGINAERUM", "has_genre", "MUSICAL" ], [ "IMAGINAERUM", "has_tags", "MUSIC" ], [ "IN BRUGES", "has_tags", "MUSIC" ], [ "IN BRUGES", "release_year", "2008" ], [ "JAILHOUSE ROCK", "has_genre", "MUSIC" ], [ "JAILHOUSE ROCK", "has_genre", "MUSICAL" ], [ "JESUS CHRIST SUPERSTAR", "has_genre", "MUSIC" ], [ "JESUS CHRIST SUPERSTAR", "has_genre", "MUSICAL" ], [ "JESUS CHRIST SUPERSTAR", "has_tags", "MUSICAL" ], [ "LABYRINTH", "has_tags", "MUSIC" ], [ "LABYRINTH", "has_tags", "MUSICAL" ], [ "LITTLE SHOP OF HORRORS", "has_genre", "MUSICAL" ], [ "LITTLE SHOP OF HORRORS", "has_tags", "MUSIC" ], [ "LITTLE SHOP OF HORRORS", "has_tags", "MUSICAL" ], [ "MAMMA MIA!", "has_genre", "MUSICAL" ], [ "MAMMA MIA!", "has_tags", "MUSICAL" ], [ "MAMMA MIA!", "release_year", "2008" ], [ "MY FAIR LADY", "has_genre", "MUSICAL" ], [ "MY FAIR LADY", "has_tags", "MUSIC" ], [ "MY FAIR LADY", "has_tags", "MUSICAL" ], [ "NEW YORK, NEW YORK", "has_genre", "MUSIC" ], [ "NEW YORK, NEW YORK", "has_genre", "MUSICAL" ], [ "OKLAHOMA!", "has_genre", "MUSICAL" ], [ "OKLAHOMA!", "has_tags", "MUSIC" ], [ "OKLAHOMA!", "has_tags", "MUSICAL" ], [ "ONCE", "has_genre", "MUSIC" ], [ "ONCE", "has_tags", "MUSIC" ], [ "ONCE", "has_tags", "MUSICAL" ], [ "PARIS 36", "has_genre", "MUSIC" ], [ "PARIS 36", "release_year", "2008" ], [ "PETE'S DRAGON", "has_tags", "MUSIC" ], [ "PETE'S DRAGON", "has_tags", "MUSICAL" ], [ "PINOCCHIO", "has_tags", "MUSIC" ], [ "PINOCCHIO", "has_tags", "MUSICAL" ], [ "PITCH PERFECT", "has_genre", "MUSIC" ], [ "PITCH PERFECT", "has_tags", "MUSIC" ], [ "PITCH PERFECT", "has_tags", "MUSICAL" ], [ "PROM NIGHT", "has_tags", "MUSIC" ], [ "PROM NIGHT", "release_year", "2008" ], [ "PURPLE RAIN", "has_genre", "MUSIC" ], [ "PURPLE RAIN", "has_genre", "MUSICAL" ], [ "RED CANYON", "release_year", "2008" ], [ "RED CANYON", "starred_actors", "NORMAN REEDUS" ], [ "REPO! THE GENETIC OPERA", "has_genre", "MUSICAL" ], [ "REPO! THE GENETIC OPERA", "has_tags", "MUSICAL" ], [ "REPO! THE GENETIC OPERA", "release_year", "2008" ], [ "RHINESTONE", "has_genre", "MUSIC" ], [ "RHINESTONE", "has_genre", "MUSICAL" ], [ "ROUSTABOUT", "has_genre", "MUSIC" ], [ "ROUSTABOUT", "has_genre", "MUSICAL" ], [ "SCHOOL OF ROCK", "has_genre", "MUSIC" ], [ "SCHOOL OF ROCK", "has_tags", "MUSIC" ], [ "SCHOOL OF ROCK", "has_tags", "MUSICAL" ], [ "SOUL MEN", "has_genre", "MUSIC" ], [ "SOUL MEN", "release_year", "2008" ], [ "THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT", "has_genre", "MUSIC" ], [ "THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT", "has_tags", "MUSICAL" ], [ "THE BLUES BROTHERS", "has_tags", "MUSIC" ], [ "THE BLUES BROTHERS", "has_tags", "MUSICAL" ], [ "THE JAZZ SINGER", "has_genre", "MUSIC" ], [ "THE JAZZ SINGER", "has_genre", "MUSICAL" ], [ "THE KING AND I", "has_genre", "MUSICAL" ], [ "THE KING AND I", "has_tags", "MUSIC" ], [ "THE KING AND I", "has_tags", "MUSICAL" ], [ "THE LION KING", "has_tags", "MUSIC" ], [ "THE LION KING", "has_tags", "MUSICAL" ], [ "THE MAMBO KINGS", "has_genre", "MUSIC" ], [ "THE MAMBO KINGS", "has_tags", "MUSICAL" ], [ "THE MUPPETS", "has_genre", "MUSICAL" ], [ "THE MUPPETS", "has_tags", "MUSIC" ], [ "THE MUPPETS", "has_tags", "MUSICAL" ], [ "THE NIGHTMARE BEFORE CHRISTMAS", "has_tags", "MUSIC" ], [ "THE NIGHTMARE BEFORE CHRISTMAS", "has_tags", "MUSICAL" ], [ "THE ROCKY HORROR PICTURE SHOW", "has_genre", "MUSICAL" ], [ "THE ROCKY HORROR PICTURE SHOW", "has_tags", "MUSIC" ], [ "THE ROCKY HORROR PICTURE SHOW", "has_tags", "MUSICAL" ], [ "THE SOUND OF MUSIC", "has_tags", "MUSIC" ], [ "THE SOUND OF MUSIC", "has_tags", "MUSICAL" ], [ "THE WEST POINT STORY", "has_genre", "MUSIC" ], [ "THE WEST POINT STORY", "has_tags", "MUSICAL" ], [ "THE WIZARD OF OZ", "has_tags", "MUSIC" ], [ "THE WIZARD OF OZ", "has_tags", "MUSICAL" ], [ "THE WRESTLER", "has_tags", "AGING" ], [ "THE WRESTLER", "release_year", "2008" ], [ "VICTOR VICTORIA", "has_genre", "MUSIC" ], [ "VICTOR VICTORIA", "has_genre", "MUSICAL" ], [ "WERE THE WORLD MINE", "has_tags", "MUSICAL" ], [ "WERE THE WORLD MINE", "release_year", "2008" ], [ "WEST SIDE STORY", "has_genre", "MUSICAL" ], [ "WEST SIDE STORY", "has_tags", "MUSIC" ], [ "WEST SIDE STORY", "has_tags", "MUSICAL" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26257, 1994 15374, 2005 31413, LASSIE 13383, PRIEST 5181, SHOOTING GALLERY 1374, SLEEP WITH ME 35082, THE EXORCIST 25478, WILLIAM PETER BLATTY src, edge_attr, dst 31413, release_year, 26257 31413, release_year, 15374 13383, release_year, 26257 5181, release_year, 15374 1374, release_year, 26257 35082, has_tags, 13383 35082, written_by, 25478 Question: In what context are SHOOTING GALLERY, SLEEP WITH ME, and WILLIAM PETER BLATTY connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "SHOOTING GALLERY", "SLEEP WITH ME", "WILLIAM PETER BLATTY" ], "valid_edges": [ [ "LASSIE", "release_year", "1994" ], [ "LASSIE", "release_year", "2005" ], [ "PRIEST", "release_year", "1994" ], [ "SHOOTING GALLERY", "release_year", "2005" ], [ "SLEEP WITH ME", "release_year", "1994" ], [ "THE EXORCIST", "has_tags", "PRIEST" ], [ "THE EXORCIST", "written_by", "WILLIAM PETER BLATTY" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36169, BEYOND THE LIGHTS 36212, DRAMA 22981, GEORGE MACKAY 35078, HOW I LIVE NOW 1804, POSTCARDS FROM THE EDGE src, edge_attr, dst 36169, has_genre, 36212 35078, has_genre, 36212 35078, starred_actors, 22981 1804, has_genre, 36212 Question: For what reason are BEYOND THE LIGHTS, GEORGE MACKAY, and POSTCARDS FROM THE EDGE associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BEYOND THE LIGHTS", "GEORGE MACKAY", "POSTCARDS FROM THE EDGE" ], "valid_edges": [ [ "BEYOND THE LIGHTS", "has_genre", "DRAMA" ], [ "HOW I LIVE NOW", "has_genre", "DRAMA" ], [ "HOW I LIVE NOW", "starred_actors", "GEORGE MACKAY" ], [ "POSTCARDS FROM THE EDGE", "has_genre", "DRAMA" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17745, DAVID ZELLNER 36212, DRAMA 19701, HOTELL 29887, KUMIKO, THE TREASURE HUNTER 4092, LISA LANGSETH 34040, SKINHEADS 18052, THIS IS ENGLAND src, edge_attr, dst 19701, directed_by, 4092 19701, has_genre, 36212 19701, written_by, 4092 29887, directed_by, 17745 29887, has_genre, 36212 29887, starred_actors, 17745 29887, written_by, 17745 18052, has_genre, 36212 18052, has_tags, 34040 Question: How are DAVID ZELLNER, LISA LANGSETH, and SKINHEADS related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DAVID ZELLNER", "LISA LANGSETH", "SKINHEADS" ], "valid_edges": [ [ "HOTELL", "directed_by", "LISA LANGSETH" ], [ "HOTELL", "has_genre", "DRAMA" ], [ "HOTELL", "written_by", "LISA LANGSETH" ], [ "KUMIKO, THE TREASURE HUNTER", "directed_by", "DAVID ZELLNER" ], [ "KUMIKO, THE TREASURE HUNTER", "has_genre", "DRAMA" ], [ "KUMIKO, THE TREASURE HUNTER", "starred_actors", "DAVID ZELLNER" ], [ "KUMIKO, THE TREASURE HUNTER", "written_by", "DAVID ZELLNER" ], [ "THIS IS ENGLAND", "has_genre", "DRAMA" ], [ "THIS IS ENGLAND", "has_tags", "SKINHEADS" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1892, 1932 35845, 2006 6718, A FAREWELL TO ARMS 17182, A GATHERING OF EAGLES 29918, AMAZING GRACE 35616, BROKEN LULLABY 8026, END OF THE GAME 31783, ENGLISH 14294, JEWEL ROBBERY 37928, JOE PANTOLIANO 12018, KAY FRANCIS 26649, KISMET 878, PARLIAMENT 21244, RAFFLES 15198, THE HUNCHBACK OF NOTRE DAME 34860, THIS IS THE NIGHT 10133, UNKNOWN 10474, WILLIAM DIETERLE src, edge_attr, dst 6718, in_language, 31783 6718, release_year, 1892 17182, has_imdb_votes, 10133 17182, in_language, 31783 29918, has_tags, 878 29918, release_year, 35845 35616, in_language, 31783 35616, release_year, 1892 8026, has_imdb_votes, 10133 8026, in_language, 31783 14294, directed_by, 10474 14294, has_tags, 10474 14294, in_language, 31783 14294, release_year, 1892 14294, starred_actors, 12018 26649, directed_by, 10474 26649, in_language, 31783 21244, in_language, 31783 21244, starred_actors, 12018 15198, directed_by, 10474 15198, has_tags, 10474 15198, in_language, 31783 34860, in_language, 31783 34860, release_year, 1892 10133, has_tags, 37928 10133, in_language, 31783 10133, release_year, 35845 10133, starred_actors, 37928 Question: How are JEWEL ROBBERY, JOE PANTOLIANO, and PARLIAMENT related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JEWEL ROBBERY", "JOE PANTOLIANO", "PARLIAMENT" ], "valid_edges": [ [ "A FAREWELL TO ARMS", "in_language", "ENGLISH" ], [ "A FAREWELL TO ARMS", "release_year", "1932" ], [ "A GATHERING OF EAGLES", "has_imdb_votes", "UNKNOWN" ], [ "A GATHERING OF EAGLES", "in_language", "ENGLISH" ], [ "AMAZING GRACE", "has_tags", "PARLIAMENT" ], [ "AMAZING GRACE", "release_year", "2006" ], [ "BROKEN LULLABY", "in_language", "ENGLISH" ], [ "BROKEN LULLABY", "release_year", "1932" ], [ "END OF THE GAME", "has_imdb_votes", "UNKNOWN" ], [ "END OF THE GAME", "in_language", "ENGLISH" ], [ "JEWEL ROBBERY", "directed_by", "WILLIAM DIETERLE" ], [ "JEWEL ROBBERY", "has_tags", "WILLIAM DIETERLE" ], [ "JEWEL ROBBERY", "in_language", "ENGLISH" ], [ "JEWEL ROBBERY", "release_year", "1932" ], [ "JEWEL ROBBERY", "starred_actors", "KAY FRANCIS" ], [ "KISMET", "directed_by", "WILLIAM DIETERLE" ], [ "KISMET", "in_language", "ENGLISH" ], [ "RAFFLES", "in_language", "ENGLISH" ], [ "RAFFLES", "starred_actors", "KAY FRANCIS" ], [ "THE HUNCHBACK OF NOTRE DAME", "directed_by", "WILLIAM DIETERLE" ], [ "THE HUNCHBACK OF NOTRE DAME", "has_tags", "WILLIAM DIETERLE" ], [ "THE HUNCHBACK OF NOTRE DAME", "in_language", "ENGLISH" ], [ "THIS IS THE NIGHT", "in_language", "ENGLISH" ], [ "THIS IS THE NIGHT", "release_year", "1932" ], [ "UNKNOWN", "has_tags", "JOE PANTOLIANO" ], [ "UNKNOWN", "in_language", "ENGLISH" ], [ "UNKNOWN", "release_year", "2006" ], [ "UNKNOWN", "starred_actors", "JOE PANTOLIANO" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 4981, 1965 10997, A HIGH WIND IN JAMAICA 15604, CORN ON THE COP 7516, IRV SPECTOR 19754, JAMES COBURN 4922, JOHANNES WEILAND 29056, MAJOR DUNDEE 36899, SHORT 8748, THE GRUFFALO'S CHILD src, edge_attr, dst 10997, release_year, 4981 10997, starred_actors, 19754 15604, directed_by, 7516 15604, has_genre, 36899 15604, release_year, 4981 29056, release_year, 4981 29056, starred_actors, 19754 8748, directed_by, 4922 8748, has_genre, 36899 Question: For what reason are IRV SPECTOR, JAMES COBURN, and JOHANNES WEILAND associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "IRV SPECTOR", "JAMES COBURN", "JOHANNES WEILAND" ], "valid_edges": [ [ "A HIGH WIND IN JAMAICA", "release_year", "1965" ], [ "A HIGH WIND IN JAMAICA", "starred_actors", "JAMES COBURN" ], [ "CORN ON THE COP", "directed_by", "IRV SPECTOR" ], [ "CORN ON THE COP", "has_genre", "SHORT" ], [ "CORN ON THE COP", "release_year", "1965" ], [ "MAJOR DUNDEE", "release_year", "1965" ], [ "MAJOR DUNDEE", "starred_actors", "JAMES COBURN" ], [ "THE GRUFFALO'S CHILD", "directed_by", "JOHANNES WEILAND" ], [ "THE GRUFFALO'S CHILD", "has_genre", "SHORT" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 658, 2012 9952, BRUNO DUMONT 25148, CHICAGO OVERCOAT 36001, HADEWIJCH 22177, TAYLOR SWIFT 34429, THE LORAX 29084, TWENTYNINE PALMS src, edge_attr, dst 658, release_year, 27261 25148, release_year, 27261 36001, directed_by, 9952 36001, has_tags, 9952 36001, release_year, 27261 36001, written_by, 9952 34429, has_tags, 22177 34429, release_year, 658 34429, starred_actors, 22177 29084, directed_by, 9952 29084, written_by, 9952 Question: For what reason are CHICAGO OVERCOAT, TAYLOR SWIFT, and TWENTYNINE PALMS associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CHICAGO OVERCOAT", "TAYLOR SWIFT", "TWENTYNINE PALMS" ], "valid_edges": [ [ "2012", "release_year", "2009" ], [ "CHICAGO OVERCOAT", "release_year", "2009" ], [ "HADEWIJCH", "directed_by", "BRUNO DUMONT" ], [ "HADEWIJCH", "has_tags", "BRUNO DUMONT" ], [ "HADEWIJCH", "release_year", "2009" ], [ "HADEWIJCH", "written_by", "BRUNO DUMONT" ], [ "THE LORAX", "has_tags", "TAYLOR SWIFT" ], [ "THE LORAX", "release_year", "2012" ], [ "THE LORAX", "starred_actors", "TAYLOR SWIFT" ], [ "TWENTYNINE PALMS", "directed_by", "BRUNO DUMONT" ], [ "TWENTYNINE PALMS", "written_by", "BRUNO DUMONT" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13504, 1963 1421, 2013 25594, BAY OF ANGELS 28488, CLAUDE MANN 36212, DRAMA 17034, FLAMING CREATURES 6012, FRENCH 28996, INDIA SONG 4475, JACK SMITH 27245, LONE SURVIVOR 3214, LOVE AND HONOR 23193, PHANTOM 11124, STALINGRAD 30733, SUBMARINE 19442, THE BOOK THIEF 11555, THE NOTEBOOK 22214, WAR src, edge_attr, dst 25594, in_language, 6012 25594, release_year, 13504 25594, starred_actors, 28488 17034, directed_by, 4475 17034, release_year, 13504 17034, written_by, 4475 28996, has_genre, 36212 28996, in_language, 6012 28996, starred_actors, 28488 27245, has_tags, 22214 27245, release_year, 1421 3214, has_genre, 22214 3214, release_year, 1421 23193, has_genre, 22214 23193, has_tags, 30733 23193, release_year, 1421 11124, has_genre, 22214 11124, release_year, 1421 30733, has_genre, 36212 19442, has_genre, 22214 19442, release_year, 1421 11555, has_genre, 22214 11555, release_year, 1421 Question: How are CLAUDE MANN, JACK SMITH, and PHANTOM related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CLAUDE MANN", "JACK SMITH", "PHANTOM" ], "valid_edges": [ [ "BAY OF ANGELS", "in_language", "FRENCH" ], [ "BAY OF ANGELS", "release_year", "1963" ], [ "BAY OF ANGELS", "starred_actors", "CLAUDE MANN" ], [ "FLAMING CREATURES", "directed_by", "JACK SMITH" ], [ "FLAMING CREATURES", "release_year", "1963" ], [ "FLAMING CREATURES", "written_by", "JACK SMITH" ], [ "INDIA SONG", "has_genre", "DRAMA" ], [ "INDIA SONG", "in_language", "FRENCH" ], [ "INDIA SONG", "starred_actors", "CLAUDE MANN" ], [ "LONE SURVIVOR", "has_tags", "WAR" ], [ "LONE SURVIVOR", "release_year", "2013" ], [ "LOVE AND HONOR", "has_genre", "WAR" ], [ "LOVE AND HONOR", "release_year", "2013" ], [ "PHANTOM", "has_genre", "WAR" ], [ "PHANTOM", "has_tags", "SUBMARINE" ], [ "PHANTOM", "release_year", "2013" ], [ "STALINGRAD", "has_genre", "WAR" ], [ "STALINGRAD", "release_year", "2013" ], [ "SUBMARINE", "has_genre", "DRAMA" ], [ "THE BOOK THIEF", "has_genre", "WAR" ], [ "THE BOOK THIEF", "release_year", "2013" ], [ "THE NOTEBOOK", "has_genre", "WAR" ], [ "THE NOTEBOOK", "release_year", "2013" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6925, 1966 17480, 1988 1097, 2003 4390, A PATCH OF BLUE 29089, DUEL AT DIABLO 10709, ELIZABETH HARTMAN 27719, LITTLE NIKITA 21889, OLD SCHOOL 14030, ROGER SPOTTISWOODE 30426, RUNNING ON EMPTY 11262, SHOOT TO KILL 3239, SIDNEY LUMET 1777, SIDNEY POITIER 23639, SPINNING BORIS 36916, THE GROUP 26382, YOU'RE A BIG BOY NOW src, edge_attr, dst 4390, starred_actors, 10709 4390, starred_actors, 1777 29089, release_year, 6925 29089, starred_actors, 1777 27719, release_year, 17480 27719, starred_actors, 1777 21889, release_year, 1097 30426, directed_by, 3239 30426, has_tags, 3239 30426, release_year, 17480 11262, directed_by, 14030 11262, release_year, 17480 11262, starred_actors, 1777 23639, directed_by, 14030 23639, release_year, 1097 36916, directed_by, 3239 36916, release_year, 6925 36916, starred_actors, 10709 26382, release_year, 6925 26382, starred_actors, 10709 Question: In what context are OLD SCHOOL, SHOOT TO KILL, and THE GROUP connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "OLD SCHOOL", "SHOOT TO KILL", "THE GROUP" ], "valid_edges": [ [ "A PATCH OF BLUE", "starred_actors", "ELIZABETH HARTMAN" ], [ "A PATCH OF BLUE", "starred_actors", "SIDNEY POITIER" ], [ "DUEL AT DIABLO", "release_year", "1966" ], [ "DUEL AT DIABLO", "starred_actors", "SIDNEY POITIER" ], [ "LITTLE NIKITA", "release_year", "1988" ], [ "LITTLE NIKITA", "starred_actors", "SIDNEY POITIER" ], [ "OLD SCHOOL", "release_year", "2003" ], [ "RUNNING ON EMPTY", "directed_by", "SIDNEY LUMET" ], [ "RUNNING ON EMPTY", "has_tags", "SIDNEY LUMET" ], [ "RUNNING ON EMPTY", "release_year", "1988" ], [ "SHOOT TO KILL", "directed_by", "ROGER SPOTTISWOODE" ], [ "SHOOT TO KILL", "release_year", "1988" ], [ "SHOOT TO KILL", "starred_actors", "SIDNEY POITIER" ], [ "SPINNING BORIS", "directed_by", "ROGER SPOTTISWOODE" ], [ "SPINNING BORIS", "release_year", "2003" ], [ "THE GROUP", "directed_by", "SIDNEY LUMET" ], [ "THE GROUP", "release_year", "1966" ], [ "THE GROUP", "starred_actors", "ELIZABETH HARTMAN" ], [ "YOU'RE A BIG BOY NOW", "release_year", "1966" ], [ "YOU'RE A BIG BOY NOW", "starred_actors", "ELIZABETH HARTMAN" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29424, 2011 15000, APOLLO 18 25202, BRIAN MILLER 33310, CHESTER ERSKINE 30463, COMEDY 36212, DRAMA 5870, HORROR 11375, THE COBBLER 17991, THE EGG AND I 38108, THE STATION AGENT 28579, THE VISITOR 6617, THOMAS MCCARTHY 36565, WIN WIN src, edge_attr, dst 15000, has_genre, 5870 15000, release_year, 29424 15000, written_by, 25202 11375, directed_by, 6617 11375, has_genre, 30463 11375, has_genre, 36212 11375, written_by, 6617 17991, directed_by, 33310 17991, has_genre, 30463 17991, written_by, 33310 38108, directed_by, 6617 38108, has_genre, 30463 38108, has_genre, 36212 38108, has_tags, 6617 38108, written_by, 6617 28579, directed_by, 6617 28579, has_genre, 36212 28579, has_genre, 5870 28579, has_tags, 6617 28579, written_by, 6617 36565, directed_by, 6617 36565, has_genre, 30463 36565, has_genre, 36212 36565, has_tags, 6617 36565, release_year, 29424 36565, written_by, 6617 Question: In what context are BRIAN MILLER, CHESTER ERSKINE, and THOMAS MCCARTHY connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BRIAN MILLER", "CHESTER ERSKINE", "THOMAS MCCARTHY" ], "valid_edges": [ [ "APOLLO 18", "has_genre", "HORROR" ], [ "APOLLO 18", "release_year", "2011" ], [ "APOLLO 18", "written_by", "BRIAN MILLER" ], [ "THE COBBLER", "directed_by", "THOMAS MCCARTHY" ], [ "THE COBBLER", "has_genre", "COMEDY" ], [ "THE COBBLER", "has_genre", "DRAMA" ], [ "THE COBBLER", "written_by", "THOMAS MCCARTHY" ], [ "THE EGG AND I", "directed_by", "CHESTER ERSKINE" ], [ "THE EGG AND I", "has_genre", "COMEDY" ], [ "THE EGG AND I", "written_by", "CHESTER ERSKINE" ], [ "THE STATION AGENT", "directed_by", "THOMAS MCCARTHY" ], [ "THE STATION AGENT", "has_genre", "COMEDY" ], [ "THE STATION AGENT", "has_genre", "DRAMA" ], [ "THE STATION AGENT", "has_tags", "THOMAS MCCARTHY" ], [ "THE STATION AGENT", "written_by", "THOMAS MCCARTHY" ], [ "THE VISITOR", "directed_by", "THOMAS MCCARTHY" ], [ "THE VISITOR", "has_genre", "DRAMA" ], [ "THE VISITOR", "has_genre", "HORROR" ], [ "THE VISITOR", "has_tags", "THOMAS MCCARTHY" ], [ "THE VISITOR", "written_by", "THOMAS MCCARTHY" ], [ "WIN WIN", "directed_by", "THOMAS MCCARTHY" ], [ "WIN WIN", "has_genre", "COMEDY" ], [ "WIN WIN", "has_genre", "DRAMA" ], [ "WIN WIN", "has_tags", "THOMAS MCCARTHY" ], [ "WIN WIN", "release_year", "2011" ], [ "WIN WIN", "written_by", "THOMAS MCCARTHY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35845, 2006 27261, 2009 658, 2012 12931, ALEX KURTZMAN 17021, BLIND DATING 2020, CARRIERS 27018, CHRIS PINE 20845, EDDIE KAYE THOMAS 24481, FRANCHISE 12209, GENE RODDENBERRY 7986, JUST MY LUCK 22109, LEONARD NIMOY 3352, MIGUEL FERRER 31312, PEOPLE LIKE US 15802, RISE OF THE GUARDIANS 26204, ROBERTO ORCI 12333, SMOKIN' ACES 34989, STAR TREK 23210, STAR TREK INTO DARKNESS 20169, THIS MEANS WAR 33951, WRONG TURN AT TAHOE 30346, ZACHARY QUINTO src, edge_attr, dst 17021, release_year, 35845 17021, starred_actors, 27018 17021, starred_actors, 20845 2020, has_tags, 27018 2020, release_year, 27261 2020, starred_actors, 27018 7986, has_tags, 27018 7986, release_year, 35845 7986, starred_actors, 27018 31312, directed_by, 12931 31312, has_tags, 27018 31312, release_year, 658 31312, starred_actors, 27018 31312, written_by, 12931 31312, written_by, 26204 15802, release_year, 658 15802, starred_actors, 27018 12333, has_tags, 27018 12333, release_year, 35845 34989, has_tags, 27018 34989, has_tags, 24481 34989, has_tags, 22109 34989, has_tags, 34989 34989, has_tags, 30346 34989, release_year, 27261 34989, starred_actors, 27018 34989, starred_actors, 22109 34989, starred_actors, 30346 34989, written_by, 12931 34989, written_by, 12209 34989, written_by, 26204 23210, has_tags, 27018 23210, has_tags, 24481 23210, has_tags, 22109 23210, has_tags, 34989 23210, has_tags, 30346 23210, starred_actors, 27018 23210, starred_actors, 30346 23210, written_by, 12931 23210, written_by, 12209 23210, written_by, 26204 20169, has_tags, 27018 20169, release_year, 658 20169, starred_actors, 27018 33951, release_year, 27261 33951, starred_actors, 3352 Question: In what context are CHRIS PINE, EDDIE KAYE THOMAS, and MIGUEL FERRER connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CHRIS PINE", "EDDIE KAYE THOMAS", "MIGUEL FERRER" ], "valid_edges": [ [ "BLIND DATING", "release_year", "2006" ], [ "BLIND DATING", "starred_actors", "CHRIS PINE" ], [ "BLIND DATING", "starred_actors", "EDDIE KAYE THOMAS" ], [ "CARRIERS", "has_tags", "CHRIS PINE" ], [ "CARRIERS", "release_year", "2009" ], [ "CARRIERS", "starred_actors", "CHRIS PINE" ], [ "JUST MY LUCK", "has_tags", "CHRIS PINE" ], [ "JUST MY LUCK", "release_year", "2006" ], [ "JUST MY LUCK", "starred_actors", "CHRIS PINE" ], [ "PEOPLE LIKE US", "directed_by", "ALEX KURTZMAN" ], [ "PEOPLE LIKE US", "has_tags", "CHRIS PINE" ], [ "PEOPLE LIKE US", "release_year", "2012" ], [ "PEOPLE LIKE US", "starred_actors", "CHRIS PINE" ], [ "PEOPLE LIKE US", "written_by", "ALEX KURTZMAN" ], [ "PEOPLE LIKE US", "written_by", "ROBERTO ORCI" ], [ "RISE OF THE GUARDIANS", "release_year", "2012" ], [ "RISE OF THE GUARDIANS", "starred_actors", "CHRIS PINE" ], [ "SMOKIN' ACES", "has_tags", "CHRIS PINE" ], [ "SMOKIN' ACES", "release_year", "2006" ], [ "STAR TREK", "has_tags", "CHRIS PINE" ], [ "STAR TREK", "has_tags", "FRANCHISE" ], [ "STAR TREK", "has_tags", "LEONARD NIMOY" ], [ "STAR TREK", "has_tags", "STAR TREK" ], [ "STAR TREK", "has_tags", "ZACHARY QUINTO" ], [ "STAR TREK", "release_year", "2009" ], [ "STAR TREK", "starred_actors", "CHRIS PINE" ], [ "STAR TREK", "starred_actors", "LEONARD NIMOY" ], [ "STAR TREK", "starred_actors", "ZACHARY QUINTO" ], [ "STAR TREK", "written_by", "ALEX KURTZMAN" ], [ "STAR TREK", "written_by", "GENE RODDENBERRY" ], [ "STAR TREK", "written_by", "ROBERTO ORCI" ], [ "STAR TREK INTO DARKNESS", "has_tags", "CHRIS PINE" ], [ "STAR TREK INTO DARKNESS", "has_tags", "FRANCHISE" ], [ "STAR TREK INTO DARKNESS", "has_tags", "LEONARD NIMOY" ], [ "STAR TREK INTO DARKNESS", "has_tags", "STAR TREK" ], [ "STAR TREK INTO DARKNESS", "has_tags", "ZACHARY QUINTO" ], [ "STAR TREK INTO DARKNESS", "starred_actors", "CHRIS PINE" ], [ "STAR TREK INTO DARKNESS", "starred_actors", "ZACHARY QUINTO" ], [ "STAR TREK INTO DARKNESS", "written_by", "ALEX KURTZMAN" ], [ "STAR TREK INTO DARKNESS", "written_by", "GENE RODDENBERRY" ], [ "STAR TREK INTO DARKNESS", "written_by", "ROBERTO ORCI" ], [ "THIS MEANS WAR", "has_tags", "CHRIS PINE" ], [ "THIS MEANS WAR", "release_year", "2012" ], [ "THIS MEANS WAR", "starred_actors", "CHRIS PINE" ], [ "WRONG TURN AT TAHOE", "release_year", "2009" ], [ "WRONG TURN AT TAHOE", "starred_actors", "MIGUEL FERRER" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6721, 1972 10825, 1973 39435, 1975 22088, A BRIDGE TOO FAR 21158, A TOUCH OF CLASS 19293, ALL THE PRESIDENT'S MEN 20380, BLUME IN LOVE 35953, BUTCH CASSIDY AND THE SUNDANCE KID 18053, CAPER 24671, DAVID S. WARD 18042, GEORGE ROY HILL 19579, GEORGE SEGAL 10481, GLENDA JACKSON 4680, GROUNDHOG DAY 33571, HAVANA 25768, JEREMIAH JOHNSON 2781, LOST AND FOUND 27102, MELVIN FRANK 37497, NATIONAL FILM REGISTRY 34938, OUT OF AFRICA 2305, PAUL NEWMAN 206, PENNSYLVANIA 34758, ROBERT REDFORD 16146, SNEAKERS 8211, SYDNEY POLLACK 1174, THE CANDIDATE 38254, THE ELECTRIC HORSEMAN 8847, THE GREAT WALDO PEPPER 32636, THE HOT ROCK 7386, THE MILAGRO BEANFIELD WAR 39278, THE STING 32709, THE WAY WE WERE 31876, THIS PROPERTY IS CONDEMNED 25255, THREE DAYS OF THE CONDOR 13447, WILLIAM GOLDMAN src, edge_attr, dst 22088, has_tags, 34758 22088, written_by, 13447 21158, directed_by, 27102 21158, release_year, 10825 21158, starred_actors, 19579 21158, starred_actors, 10481 21158, written_by, 27102 19293, has_tags, 34758 19293, starred_actors, 34758 19293, written_by, 13447 20380, release_year, 10825 20380, starred_actors, 19579 35953, directed_by, 18042 35953, has_tags, 18042 35953, has_tags, 37497 35953, has_tags, 2305 35953, has_tags, 34758 35953, has_tags, 13447 35953, starred_actors, 2305 35953, starred_actors, 34758 35953, written_by, 13447 4680, has_tags, 37497 4680, has_tags, 206 33571, directed_by, 8211 33571, has_tags, 33571 33571, starred_actors, 34758 25768, directed_by, 8211 25768, has_tags, 34758 25768, has_tags, 8211 25768, release_year, 6721 25768, starred_actors, 34758 2781, directed_by, 27102 2781, starred_actors, 19579 2781, starred_actors, 10481 2781, written_by, 27102 34938, directed_by, 8211 34938, has_tags, 34758 34938, has_tags, 8211 34938, starred_actors, 34758 16146, has_tags, 18053 16146, has_tags, 34758 16146, starred_actors, 34758 1174, has_tags, 34758 1174, release_year, 6721 1174, starred_actors, 34758 38254, directed_by, 8211 38254, starred_actors, 34758 8847, directed_by, 18042 8847, release_year, 39435 8847, starred_actors, 34758 8847, written_by, 18042 32636, has_tags, 34758 32636, release_year, 6721 32636, starred_actors, 19579 32636, starred_actors, 34758 32636, written_by, 13447 7386, directed_by, 34758 7386, has_tags, 34758 7386, written_by, 24671 39278, directed_by, 18042 39278, has_tags, 18053 39278, has_tags, 18042 39278, has_tags, 2305 39278, has_tags, 34758 39278, release_year, 10825 39278, starred_actors, 2305 39278, starred_actors, 34758 39278, written_by, 24671 32709, directed_by, 8211 32709, has_tags, 8211 32709, release_year, 10825 32709, starred_actors, 34758 31876, directed_by, 8211 31876, has_tags, 8211 31876, starred_actors, 34758 25255, directed_by, 8211 25255, has_tags, 34758 25255, has_tags, 8211 25255, release_year, 39435 25255, starred_actors, 34758 Question: In what context are A TOUCH OF CLASS, PENNSYLVANIA, and ROBERT REDFORD connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "A TOUCH OF CLASS", "PENNSYLVANIA", "ROBERT REDFORD" ], "valid_edges": [ [ "A BRIDGE TOO FAR", "has_tags", "ROBERT REDFORD" ], [ "A BRIDGE TOO FAR", "written_by", "WILLIAM GOLDMAN" ], [ "A TOUCH OF CLASS", "directed_by", "MELVIN FRANK" ], [ "A TOUCH OF CLASS", "release_year", "1973" ], [ "A TOUCH OF CLASS", "starred_actors", "GEORGE SEGAL" ], [ "A TOUCH OF CLASS", "starred_actors", "GLENDA JACKSON" ], [ "A TOUCH OF CLASS", "written_by", "MELVIN FRANK" ], [ "ALL THE PRESIDENT'S MEN", "has_tags", "ROBERT REDFORD" ], [ "ALL THE PRESIDENT'S MEN", "starred_actors", "ROBERT REDFORD" ], [ "ALL THE PRESIDENT'S MEN", "written_by", "WILLIAM GOLDMAN" ], [ "BLUME IN LOVE", "release_year", "1973" ], [ "BLUME IN LOVE", "starred_actors", "GEORGE SEGAL" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "directed_by", "GEORGE ROY HILL" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "GEORGE ROY HILL" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "PAUL NEWMAN" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "ROBERT REDFORD" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "WILLIAM GOLDMAN" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "starred_actors", "PAUL NEWMAN" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "starred_actors", "ROBERT REDFORD" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "written_by", "WILLIAM GOLDMAN" ], [ "GROUNDHOG DAY", "has_tags", "NATIONAL FILM REGISTRY" ], [ "GROUNDHOG DAY", "has_tags", "PENNSYLVANIA" ], [ "HAVANA", "directed_by", "SYDNEY POLLACK" ], [ "HAVANA", "has_tags", "HAVANA" ], [ "HAVANA", "starred_actors", "ROBERT REDFORD" ], [ "JEREMIAH JOHNSON", "directed_by", "SYDNEY POLLACK" ], [ "JEREMIAH JOHNSON", "has_tags", "ROBERT REDFORD" ], [ "JEREMIAH JOHNSON", "has_tags", "SYDNEY POLLACK" ], [ "JEREMIAH JOHNSON", "release_year", "1972" ], [ "JEREMIAH JOHNSON", "starred_actors", "ROBERT REDFORD" ], [ "LOST AND FOUND", "directed_by", "MELVIN FRANK" ], [ "LOST AND FOUND", "starred_actors", "GEORGE SEGAL" ], [ "LOST AND FOUND", "starred_actors", "GLENDA JACKSON" ], [ "LOST AND FOUND", "written_by", "MELVIN FRANK" ], [ "OUT OF AFRICA", "directed_by", "SYDNEY POLLACK" ], [ "OUT OF AFRICA", "has_tags", "ROBERT REDFORD" ], [ "OUT OF AFRICA", "has_tags", "SYDNEY POLLACK" ], [ "OUT OF AFRICA", "starred_actors", "ROBERT REDFORD" ], [ "SNEAKERS", "has_tags", "CAPER" ], [ "SNEAKERS", "has_tags", "ROBERT REDFORD" ], [ "SNEAKERS", "starred_actors", "ROBERT REDFORD" ], [ "THE CANDIDATE", "has_tags", "ROBERT REDFORD" ], [ "THE CANDIDATE", "release_year", "1972" ], [ "THE CANDIDATE", "starred_actors", "ROBERT REDFORD" ], [ "THE ELECTRIC HORSEMAN", "directed_by", "SYDNEY POLLACK" ], [ "THE ELECTRIC HORSEMAN", "starred_actors", "ROBERT REDFORD" ], [ "THE GREAT WALDO PEPPER", "directed_by", "GEORGE ROY HILL" ], [ "THE GREAT WALDO PEPPER", "release_year", "1975" ], [ "THE GREAT WALDO PEPPER", "starred_actors", "ROBERT REDFORD" ], [ "THE GREAT WALDO PEPPER", "written_by", "GEORGE ROY HILL" ], [ "THE HOT ROCK", "has_tags", "ROBERT REDFORD" ], [ "THE HOT ROCK", "release_year", "1972" ], [ "THE HOT ROCK", "starred_actors", "GEORGE SEGAL" ], [ "THE HOT ROCK", "starred_actors", "ROBERT REDFORD" ], [ "THE HOT ROCK", "written_by", "WILLIAM GOLDMAN" ], [ "THE MILAGRO BEANFIELD WAR", "directed_by", "ROBERT REDFORD" ], [ "THE MILAGRO BEANFIELD WAR", "has_tags", "ROBERT REDFORD" ], [ "THE MILAGRO BEANFIELD WAR", "written_by", "DAVID S. WARD" ], [ "THE STING", "directed_by", "GEORGE ROY HILL" ], [ "THE STING", "has_tags", "CAPER" ], [ "THE STING", "has_tags", "GEORGE ROY HILL" ], [ "THE STING", "has_tags", "PAUL NEWMAN" ], [ "THE STING", "has_tags", "ROBERT REDFORD" ], [ "THE STING", "release_year", "1973" ], [ "THE STING", "starred_actors", "PAUL NEWMAN" ], [ "THE STING", "starred_actors", "ROBERT REDFORD" ], [ "THE STING", "written_by", "DAVID S. WARD" ], [ "THE WAY WE WERE", "directed_by", "SYDNEY POLLACK" ], [ "THE WAY WE WERE", "has_tags", "SYDNEY POLLACK" ], [ "THE WAY WE WERE", "release_year", "1973" ], [ "THE WAY WE WERE", "starred_actors", "ROBERT REDFORD" ], [ "THIS PROPERTY IS CONDEMNED", "directed_by", "SYDNEY POLLACK" ], [ "THIS PROPERTY IS CONDEMNED", "has_tags", "SYDNEY POLLACK" ], [ "THIS PROPERTY IS CONDEMNED", "starred_actors", "ROBERT REDFORD" ], [ "THREE DAYS OF THE CONDOR", "directed_by", "SYDNEY POLLACK" ], [ "THREE DAYS OF THE CONDOR", "has_tags", "ROBERT REDFORD" ], [ "THREE DAYS OF THE CONDOR", "has_tags", "SYDNEY POLLACK" ], [ "THREE DAYS OF THE CONDOR", "release_year", "1975" ], [ "THREE DAYS OF THE CONDOR", "starred_actors", "ROBERT REDFORD" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 31486, 1970 37315, A BRONX TALE 10996, AWAKENINGS 31163, DIRECTORIAL DEBUT 13133, HI, MOM! 2938, JUMPIN' JACK FLASH 21728, MASSACRE 17036, PENNY MARSHALL 17979, ROBERT DE NIRO 20390, SOLDIER BLUE 1797, THE BIRD WITH THE CRYSTAL PLUMAGE src, edge_attr, dst 37315, directed_by, 17979 37315, has_tags, 31163 37315, has_tags, 17979 37315, starred_actors, 17979 10996, directed_by, 17036 10996, has_tags, 17036 10996, has_tags, 17979 10996, starred_actors, 17979 13133, has_tags, 17979 13133, release_year, 31486 13133, starred_actors, 17979 2938, directed_by, 17036 2938, has_tags, 31163 20390, has_tags, 21728 20390, release_year, 31486 1797, has_tags, 31163 1797, release_year, 31486 Question: In what context are HI, MOM!, JUMPIN' JACK FLASH, and MASSACRE connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "HI, MOM!", "JUMPIN' JACK FLASH", "MASSACRE" ], "valid_edges": [ [ "A BRONX TALE", "directed_by", "ROBERT DE NIRO" ], [ "A BRONX TALE", "has_tags", "DIRECTORIAL DEBUT" ], [ "A BRONX TALE", "has_tags", "ROBERT DE NIRO" ], [ "A BRONX TALE", "starred_actors", "ROBERT DE NIRO" ], [ "AWAKENINGS", "directed_by", "PENNY MARSHALL" ], [ "AWAKENINGS", "has_tags", "PENNY MARSHALL" ], [ "AWAKENINGS", "has_tags", "ROBERT DE NIRO" ], [ "AWAKENINGS", "starred_actors", "ROBERT DE NIRO" ], [ "HI, MOM!", "has_tags", "ROBERT DE NIRO" ], [ "HI, MOM!", "release_year", "1970" ], [ "HI, MOM!", "starred_actors", "ROBERT DE NIRO" ], [ "JUMPIN' JACK FLASH", "directed_by", "PENNY MARSHALL" ], [ "JUMPIN' JACK FLASH", "has_tags", "DIRECTORIAL DEBUT" ], [ "SOLDIER BLUE", "has_tags", "MASSACRE" ], [ "SOLDIER BLUE", "release_year", "1970" ], [ "THE BIRD WITH THE CRYSTAL PLUMAGE", "has_tags", "DIRECTORIAL DEBUT" ], [ "THE BIRD WITH THE CRYSTAL PLUMAGE", "release_year", "1970" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13464, 10 THINGS I HATE ABOUT YOU 8486, 1999 5620, 200 CIGARETTES 30146, A CHRISTMAS CAROL 38367, A MAP OF THE WORLD 27672, A ROOM FOR ROMEO BRASS 5152, A SLIPPING-DOWN LIFE 30464, A WALK ON THE MOON 35603, AGNES BROWNE 30284, ALL ABOUT MY MOTHER 17254, AMERICAN BEAUTY 20033, ANGEL 17481, ANGELA'S ASHES 29422, ANNA AND THE KING 17320, ANY GIVEN SUNDAY 25586, ARLINGTON ROAD 7908, AUDITION 9669, AUDREY WELLS 26205, BEING JOHN MALKOVICH 2067, BETWEEN YOUR LEGS 8900, BICENTENNIAL MAN 37569, BOYS DON'T CRY 21035, BRINGING OUT THE DEAD 7918, BROKEDOWN PALACE 3291, CATFISH IN BLACK BEAN SAUCE 30463, COMEDY 23710, CRADLE WILL ROCK 32140, CRAZY IN ALABAMA 27377, CRUEL INTENTIONS 13007, DETERRENCE 36212, DRAMA 12319, DREAMING OF JOSEPH LEES 7568, EAST IS EAST 3893, ED WOOD 34555, FLAWLESS 17478, FOOLISH 9161, FOR LOVE OF THE GAME 5820, FOREVER MINE 131, GINA GERSHON 22532, GIRL, INTERRUPTED 9527, GLEN OR GLENDA 35657, GLORIA 10457, GOYA IN BORDEAUX 19204, GUINEVERE 34201, HERMAN SHUMLIN 27446, IN TOO DEEP 35335, IT ALL STARTS TODAY 4912, JAKOB THE LIAR 14391, JOE THE KING 27249, JUDY BERLIN 21224, KIKUJIRO 22333, KING OF COMEDY 18023, LIBERTY HEIGHTS 7104, LIFE 21197, LIGHT IT UP 4052, LIMBO 28092, MAGNOLIA 37867, MAN ON THE MOON 6649, MANSFIELD PARK 6559, MESSAGE IN A BOTTLE 30008, MISS JULIE 19598, MOLLY 14977, MOLOCH 9235, MR. NOBODY 16428, MUMFORD 3018, MUSIC OF THE HEART 12944, MY LIFE WITHOUT ME 33718, MYSTERY, ALASKA 493, ONE MAN'S HERO 18987, ONEGIN 35341, ORFEU 35054, PLAY IT TO THE BONE 21386, POLA X 10039, PUPS 16964, PUSHING TIN 9963, RANDOM HEARTS 14786, REUBEN, REUBEN 27631, RIDE WITH THE DEVIL 12234, RKO 281 27556, ROGUE TRADER 8379, ROMANCE 30403, RUDOLPH GREY 36349, SARAH POLLEY 15252, SCREWED IN TALLINN 36012, SHOWGIRLS 36167, SOFT FRUIT 1469, SOPHIE'S WORLD 37429, STEPHEN REA 32984, SWEET AND LOWDOWN 18005, TAKE THIS WALTZ 4157, THE BEST MAN 27111, THE BIG KAHUNA 22372, THE CIDER HOUSE RULES 6150, THE CONFESSION 165, THE CRYING GAME 25509, THE DEBT 791, THE DEEP END OF THE OCEAN 8141, THE END OF THE AFFAIR 14220, THE FIVE SENSES 12748, THE GLASS AGENCY 35367, THE GREEN MILE 16209, THE HI-LINE 12439, THE INSIDER 34986, THE JOYRIDERS 37562, THE KING AND I 13703, THE LAW OF ENCLOSURES 9799, THE LOST SON 27045, THE MISSION 5098, THE MOMENT AFTER 37200, THE STORY OF US 9301, THE STRAIGHT STORY 11235, THE SUBURBANS 13405, THE THIRD MIRACLE 12026, THE TIC CODE 12801, THE VIRGIN SUICIDES 39253, THE WAR ZONE 14983, THE WINSLOW BOY 332, TOPSY-TURVY 29271, TOUCH 308, TRUE CRIME 13101, TUMBLEWEEDS 11544, UNDER THE TUSCAN SUN 9202, VARSITY BLUES 30597, WATCH ON THE RHINE 16102, WILDFLOWERS 30288, WISCONSIN DEATH TRIP 6567, WITH FIRE AND SWORD 31862, WONDERLAND src, edge_attr, dst 13464, has_genre, 36212 13464, release_year, 8486 5620, has_genre, 36212 5620, release_year, 8486 30146, has_genre, 36212 30146, release_year, 8486 38367, has_genre, 36212 38367, release_year, 8486 27672, has_genre, 36212 27672, release_year, 8486 5152, has_genre, 36212 5152, release_year, 8486 30464, has_genre, 36212 30464, release_year, 8486 35603, has_genre, 36212 35603, release_year, 8486 30284, has_genre, 36212 30284, release_year, 8486 17254, has_genre, 36212 17254, has_tags, 36212 17254, release_year, 8486 20033, has_genre, 36212 20033, starred_actors, 37429 17481, has_genre, 36212 17481, 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release_year, 8486 165, has_genre, 36212 165, has_tags, 37429 165, starred_actors, 37429 25509, has_genre, 36212 25509, release_year, 8486 791, has_genre, 36212 791, release_year, 8486 8141, has_genre, 36212 8141, release_year, 8486 8141, starred_actors, 37429 14220, has_genre, 36212 14220, release_year, 8486 12748, has_genre, 36212 12748, release_year, 8486 35367, has_genre, 36212 35367, has_tags, 36212 35367, release_year, 8486 16209, has_genre, 36212 16209, release_year, 8486 12439, has_genre, 36212 12439, has_tags, 36212 12439, release_year, 8486 34986, has_genre, 36212 34986, release_year, 8486 37562, has_genre, 36212 37562, release_year, 8486 13703, has_genre, 36212 13703, starred_actors, 36349 9799, has_genre, 36212 9799, release_year, 8486 27045, has_genre, 36212 27045, release_year, 8486 5098, has_genre, 36212 5098, release_year, 8486 37200, has_genre, 36212 37200, has_tags, 36212 37200, release_year, 8486 9301, has_genre, 36212 9301, release_year, 8486 11235, has_genre, 36212 11235, release_year, 8486 13405, has_genre, 36212 13405, release_year, 8486 12026, has_genre, 36212 12026, release_year, 8486 12801, has_genre, 36212 12801, release_year, 8486 39253, has_genre, 36212 39253, release_year, 8486 14983, has_genre, 36212 14983, release_year, 8486 332, has_genre, 36212 332, release_year, 8486 29271, has_genre, 36212 29271, starred_actors, 131 308, has_genre, 36212 308, release_year, 8486 13101, has_genre, 36212 13101, release_year, 8486 11544, directed_by, 9669 11544, has_genre, 36212 11544, written_by, 9669 9202, has_genre, 36212 9202, release_year, 8486 30597, directed_by, 34201 30597, has_genre, 36212 16102, has_genre, 36212 16102, release_year, 8486 30288, has_genre, 36212 30288, release_year, 8486 6567, has_genre, 36212 6567, release_year, 8486 31862, has_genre, 36212 31862, release_year, 8486 Question: How are GUINEVERE, HERMAN SHUMLIN, and RUDOLPH GREY related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

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HEARTS", "has_genre", "DRAMA" ], [ "RANDOM HEARTS", "release_year", "1999" ], [ "REUBEN, REUBEN", "has_genre", "COMEDY" ], [ "REUBEN, REUBEN", "has_genre", "DRAMA" ], [ "REUBEN, REUBEN", "written_by", "HERMAN SHUMLIN" ], [ "RIDE WITH THE DEVIL", "has_genre", "DRAMA" ], [ "RIDE WITH THE DEVIL", "release_year", "1999" ], [ "RKO 281", "has_genre", "DRAMA" ], [ "RKO 281", "release_year", "1999" ], [ "ROGUE TRADER", "has_genre", "DRAMA" ], [ "ROGUE TRADER", "release_year", "1999" ], [ "ROMANCE", "has_genre", "DRAMA" ], [ "ROMANCE", "release_year", "1999" ], [ "SCREWED IN TALLINN", "has_genre", "DRAMA" ], [ "SCREWED IN TALLINN", "release_year", "1999" ], [ "SHOWGIRLS", "has_genre", "DRAMA" ], [ "SHOWGIRLS", "starred_actors", "GINA GERSHON" ], [ "SOFT FRUIT", "has_genre", "DRAMA" ], [ "SOFT FRUIT", "release_year", "1999" ], [ "SOPHIE'S WORLD", "has_genre", "DRAMA" ], [ "SOPHIE'S WORLD", "release_year", "1999" ], [ "SWEET AND LOWDOWN", "has_genre", "DRAMA" ], [ "SWEET AND LOWDOWN", "release_year", "1999" ], [ "TAKE THIS WALTZ", "directed_by", "SARAH POLLEY" ], [ "TAKE THIS WALTZ", "has_genre", "DRAMA" ], [ "TAKE THIS WALTZ", "has_tags", "SARAH POLLEY" ], [ "TAKE THIS WALTZ", "written_by", "SARAH POLLEY" ], [ "THE BEST MAN", "has_genre", "DRAMA" ], [ "THE BEST MAN", "release_year", "1999" ], [ "THE BIG KAHUNA", "has_genre", "DRAMA" ], [ "THE BIG KAHUNA", "release_year", "1999" ], [ "THE CIDER HOUSE RULES", "has_genre", "DRAMA" ], [ "THE CIDER HOUSE RULES", "has_tags", "DRAMA" ], [ "THE CIDER HOUSE RULES", "release_year", "1999" ], [ "THE CONFESSION", "has_genre", "DRAMA" ], [ "THE CONFESSION", "release_year", "1999" ], [ "THE CRYING GAME", "has_genre", "DRAMA" ], [ "THE CRYING GAME", "has_tags", "STEPHEN REA" ], [ "THE CRYING GAME", "starred_actors", "STEPHEN REA" ], [ "THE DEBT", "has_genre", "DRAMA" ], [ "THE DEBT", "release_year", "1999" ], [ "THE DEEP END OF THE OCEAN", "has_genre", "DRAMA" ], [ "THE DEEP END OF THE OCEAN", "release_year", "1999" ], [ "THE END 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"has_genre", "DRAMA" ], [ "THE LOST SON", "release_year", "1999" ], [ "THE MISSION", "has_genre", "DRAMA" ], [ "THE MISSION", "release_year", "1999" ], [ "THE MOMENT AFTER", "has_genre", "DRAMA" ], [ "THE MOMENT AFTER", "release_year", "1999" ], [ "THE STORY OF US", "has_genre", "DRAMA" ], [ "THE STORY OF US", "has_tags", "DRAMA" ], [ "THE STORY OF US", "release_year", "1999" ], [ "THE STRAIGHT STORY", "has_genre", "DRAMA" ], [ "THE STRAIGHT STORY", "release_year", "1999" ], [ "THE SUBURBANS", "has_genre", "DRAMA" ], [ "THE SUBURBANS", "release_year", "1999" ], [ "THE THIRD MIRACLE", "has_genre", "DRAMA" ], [ "THE THIRD MIRACLE", "release_year", "1999" ], [ "THE TIC CODE", "has_genre", "DRAMA" ], [ "THE TIC CODE", "release_year", "1999" ], [ "THE VIRGIN SUICIDES", "has_genre", "DRAMA" ], [ "THE VIRGIN SUICIDES", "release_year", "1999" ], [ "THE WAR ZONE", "has_genre", "DRAMA" ], [ "THE WAR ZONE", "release_year", "1999" ], [ "THE WINSLOW BOY", "has_genre", "DRAMA" ], [ "THE WINSLOW BOY", "release_year", "1999" ], [ "TOPSY-TURVY", "has_genre", "DRAMA" ], [ "TOPSY-TURVY", "release_year", "1999" ], [ "TOUCH", "has_genre", "DRAMA" ], [ "TOUCH", "starred_actors", "GINA GERSHON" ], [ "TRUE CRIME", "has_genre", "DRAMA" ], [ "TRUE CRIME", "release_year", "1999" ], [ "TUMBLEWEEDS", "has_genre", "DRAMA" ], [ "TUMBLEWEEDS", "release_year", "1999" ], [ "UNDER THE TUSCAN SUN", "directed_by", "AUDREY WELLS" ], [ "UNDER THE TUSCAN SUN", "has_genre", "DRAMA" ], [ "UNDER THE TUSCAN SUN", "written_by", "AUDREY WELLS" ], [ "VARSITY BLUES", "has_genre", "DRAMA" ], [ "VARSITY BLUES", "release_year", "1999" ], [ "WATCH ON THE RHINE", "directed_by", "HERMAN SHUMLIN" ], [ "WATCH ON THE RHINE", "has_genre", "DRAMA" ], [ "WILDFLOWERS", "has_genre", "DRAMA" ], [ "WILDFLOWERS", "release_year", "1999" ], [ "WISCONSIN DEATH TRIP", "has_genre", "DRAMA" ], [ "WISCONSIN DEATH TRIP", "release_year", "1999" ], [ "WITH FIRE AND SWORD", "has_genre", "DRAMA" ], [ "WITH FIRE AND SWORD", "release_year", "1999" ], [ "WONDERLAND", "has_genre", "DRAMA" ], [ "WONDERLAND", "release_year", "1999" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13408, 2001 13747, 25 WATTS 1543, 61* 30721, A BEAUTIFUL MIND 19865, A.I. ARTIFICIAL INTELLIGENCE 1538, ALIAS BETTY 4141, AN AMERICAN RHAPSODY 22873, ANGEL EYES 462, AUTUMN SPRING 1156, AVALON 5593, BABY BOY 23952, BANDITS 13418, BARTLEBY 11298, BOLIVIA 20912, BRIDE OF THE WIND 26051, BRIDESHEAD REVISITED 7461, BROTHERHOOD OF THE WOLF 17892, CAMOUFLAGE 29794, CHARLOTTE GRAY 10293, CONSPIRACY 23979, CRAZY/BEAUTIFUL 656, CRUSH 1915, DIL CHAHTA HAI 7281, DON'S PLUM 22255, DONNIE DARKO 8704, DR. DOLITTLE 2 36212, DRAMA 27747, DRIVEN 17266, DUST 19194, ENIGMA 24686, FATE 6915, FOCUS 12664, GHOST WORLD 38300, GLITTER 15389, GYPSY 83 21060, HARVARD MAN 19139, HEARTS IN ATLANTIS 1292, HEDWIG AND THE ANGRY INCH 38901, HIGH HEELS AND LOW LIFES 22858, HISTORY IS MADE AT NIGHT 35625, HUMAN NATURE 10714, I AM SAM 20430, IN THE BEDROOM 23380, INVINCIBLE 23526, JACKPOT 12610, JOE SOMEBODY 31226, JULIE JOHNSON 6206, KABHI KHUSHI KABHIE GHAM... 7699, KINGDOM COME 7888, L.I.E. 19121, LAST ORDERS 18370, LEO CARRILLO 39962, LIFE AS A HOUSE 29734, LITTLE SECRETS 22386, LOST AND DELIRIOUS 17728, MAD LOVE 30062, MANIC 33714, MEAN MACHINE 14565, MONSTER'S BALL 24616, MOSTLY MARTHA 10824, O 32514, ONE 2 KA 4 32186, ONE MAN UP 28044, PAULINE AND PAULETTE 234, PEARL HARBOR 28106, PROZAC NATION 8367, RAIN 28182, RARE BIRDS 38381, ROCK STAR 29441, SEX AND LUCIA 2407, SON OF THE BRIDE 7949, STORYTELLING 27762, SWEET NOVEMBER 15887, TAPE 13270, TEXAS RANGERS 2582, THE AFFAIR OF THE NECKLACE 15795, THE ANNIVERSARY PARTY 33436, THE BANK 267, THE BELIEVER 25674, THE BROTHERS 30854, THE CAT'S MEOW 4946, THE CAVEMAN'S VALENTINE 14993, THE INVISIBLE CIRCUS 23268, THE JIMMY SHOW 4143, THE LAST CASTLE 28107, THE LAST KISS 12566, THE MAJESTIC 23940, THE MAN FROM ELYSIAN FIELDS 22538, THE OTHER SIDE OF HEAVEN 27573, THE OTHERS 39469, THE PORNOGRAPHER 18649, THE RIVER 20728, THE ROYAL TENENBAUMS 23798, THE SHIPPING NEWS 27910, THE UNSAID 38275, THIRTEEN CONVERSATIONS ABOUT ONE THING 25783, TIME OUT 27854, TO THE LEFT OF THE FATHER 35988, TORTILLA SOUP 8974, TREED MURRAY 17093, UNFAIR COMPETITION 6655, UPRISING 35443, VIZONTELE 18892, WAKING LIFE 19926, WORLD TRAVELER 25391, Y TU MAMÁ TAMBIÉN src, edge_attr, dst 13747, has_genre, 36212 13747, release_year, 13408 1543, has_genre, 36212 1543, release_year, 13408 30721, has_genre, 36212 30721, has_tags, 36212 30721, release_year, 13408 19865, has_genre, 36212 19865, release_year, 13408 1538, has_genre, 36212 1538, release_year, 13408 4141, has_genre, 36212 4141, release_year, 13408 22873, has_genre, 36212 22873, release_year, 13408 462, has_genre, 36212 462, release_year, 13408 1156, has_genre, 36212 1156, release_year, 13408 5593, has_genre, 36212 5593, release_year, 13408 23952, has_genre, 36212 23952, release_year, 13408 13418, has_genre, 36212 13418, release_year, 13408 11298, has_genre, 36212 11298, release_year, 13408 20912, has_genre, 36212 20912, release_year, 13408 26051, has_genre, 36212 7461, has_genre, 36212 7461, release_year, 13408 17892, has_genre, 36212 17892, release_year, 13408 29794, has_genre, 36212 29794, release_year, 13408 10293, has_genre, 36212 10293, release_year, 13408 23979, has_genre, 36212 23979, release_year, 13408 656, has_genre, 36212 656, release_year, 13408 1915, has_genre, 36212 1915, release_year, 13408 7281, has_genre, 36212 7281, release_year, 13408 22255, has_genre, 36212 22255, release_year, 13408 8704, release_year, 13408 27747, has_genre, 36212 27747, release_year, 13408 17266, has_genre, 36212 17266, release_year, 13408 19194, has_genre, 36212 19194, release_year, 13408 24686, has_genre, 36212 24686, release_year, 13408 6915, has_genre, 36212 6915, release_year, 13408 12664, has_genre, 36212 12664, release_year, 13408 38300, has_genre, 36212 38300, release_year, 13408 15389, has_genre, 36212 15389, release_year, 13408 21060, has_genre, 36212 21060, release_year, 13408 19139, has_genre, 36212 19139, release_year, 13408 1292, has_genre, 36212 1292, release_year, 13408 38901, has_genre, 36212 38901, release_year, 13408 22858, has_genre, 36212 22858, starred_actors, 18370 35625, has_genre, 36212 35625, release_year, 13408 10714, has_genre, 36212 10714, release_year, 13408 20430, has_genre, 36212 20430, has_tags, 36212 20430, release_year, 13408 23380, has_genre, 36212 23380, release_year, 13408 23526, has_genre, 36212 23526, release_year, 13408 12610, has_genre, 36212 12610, release_year, 13408 31226, has_genre, 36212 31226, release_year, 13408 6206, has_genre, 36212 6206, release_year, 13408 7699, has_genre, 36212 7699, release_year, 13408 7888, has_genre, 36212 7888, release_year, 13408 19121, has_genre, 36212 19121, release_year, 13408 39962, has_genre, 36212 39962, release_year, 13408 29734, has_genre, 36212 29734, release_year, 13408 22386, has_genre, 36212 22386, release_year, 13408 17728, has_genre, 36212 17728, release_year, 13408 30062, has_genre, 36212 30062, release_year, 13408 33714, has_genre, 36212 33714, release_year, 13408 14565, has_genre, 36212 14565, release_year, 13408 24616, has_genre, 36212 24616, release_year, 13408 10824, has_genre, 36212 10824, release_year, 13408 32514, has_genre, 36212 32514, release_year, 13408 32186, has_genre, 36212 32186, release_year, 13408 28044, has_genre, 36212 28044, release_year, 13408 234, has_genre, 36212 234, has_tags, 36212 234, release_year, 13408 28106, has_genre, 36212 28106, release_year, 13408 8367, has_genre, 36212 8367, release_year, 13408 28182, has_genre, 36212 28182, release_year, 13408 38381, has_genre, 36212 38381, release_year, 13408 29441, has_genre, 36212 29441, release_year, 13408 2407, has_genre, 36212 2407, release_year, 13408 7949, has_genre, 36212 7949, release_year, 13408 27762, has_genre, 36212 27762, release_year, 13408 15887, has_genre, 36212 15887, release_year, 13408 13270, has_genre, 36212 13270, release_year, 13408 2582, has_genre, 36212 2582, release_year, 13408 15795, has_genre, 36212 15795, release_year, 13408 33436, has_genre, 36212 33436, release_year, 13408 267, has_genre, 36212 267, release_year, 13408 25674, has_genre, 36212 25674, release_year, 13408 30854, has_genre, 36212 30854, release_year, 13408 4946, has_genre, 36212 4946, release_year, 13408 14993, has_genre, 36212 14993, release_year, 13408 23268, has_genre, 36212 23268, release_year, 13408 4143, has_genre, 36212 4143, release_year, 13408 28107, has_genre, 36212 28107, release_year, 13408 12566, has_genre, 36212 12566, release_year, 13408 23940, has_genre, 36212 23940, release_year, 13408 22538, has_genre, 36212 22538, release_year, 13408 27573, has_tags, 36212 27573, release_year, 13408 39469, has_genre, 36212 39469, release_year, 13408 18649, has_genre, 36212 18649, release_year, 13408 20728, has_genre, 36212 20728, release_year, 13408 23798, has_genre, 36212 23798, release_year, 13408 27910, has_genre, 36212 27910, release_year, 13408 38275, has_genre, 36212 38275, release_year, 13408 25783, has_genre, 36212 25783, release_year, 13408 27854, has_genre, 36212 27854, release_year, 13408 35988, has_genre, 36212 35988, release_year, 13408 8974, has_genre, 36212 8974, release_year, 13408 17093, has_genre, 36212 17093, release_year, 13408 6655, has_genre, 36212 6655, release_year, 13408 35443, has_genre, 36212 35443, release_year, 13408 18892, has_genre, 36212 18892, release_year, 13408 19926, has_genre, 36212 19926, release_year, 13408 25391, has_genre, 36212 25391, has_tags, 36212 25391, release_year, 13408 Question: How are BRIDESHEAD REVISITED, DR. DOLITTLE 2, and LEO CARRILLO related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BRIDESHEAD REVISITED", "DR. DOLITTLE 2", "LEO CARRILLO" ], "valid_edges": [ [ "25 WATTS", "has_genre", "DRAMA" ], [ "25 WATTS", "release_year", "2001" ], [ "61*", "has_genre", "DRAMA" ], [ "61*", "release_year", "2001" ], [ "A BEAUTIFUL MIND", "has_genre", "DRAMA" ], [ "A BEAUTIFUL MIND", "has_tags", "DRAMA" ], [ "A BEAUTIFUL MIND", "release_year", "2001" ], [ "A.I. ARTIFICIAL INTELLIGENCE", "has_genre", "DRAMA" ], [ "A.I. ARTIFICIAL INTELLIGENCE", "release_year", "2001" ], [ "ALIAS BETTY", "has_genre", "DRAMA" ], [ "ALIAS BETTY", "release_year", "2001" ], [ "AN AMERICAN RHAPSODY", "has_genre", "DRAMA" ], [ "AN AMERICAN RHAPSODY", "release_year", "2001" ], [ "ANGEL EYES", "has_genre", "DRAMA" ], [ "ANGEL EYES", "release_year", "2001" ], [ "AUTUMN SPRING", "has_genre", "DRAMA" ], [ "AUTUMN SPRING", "release_year", "2001" ], [ "AVALON", "has_genre", "DRAMA" ], [ "AVALON", "release_year", "2001" ], [ "BABY BOY", "has_genre", "DRAMA" ], [ "BABY BOY", "release_year", "2001" ], [ "BANDITS", "has_genre", "DRAMA" ], [ "BANDITS", "release_year", "2001" ], [ "BARTLEBY", "has_genre", "DRAMA" ], [ "BARTLEBY", "release_year", "2001" ], [ "BOLIVIA", "has_genre", "DRAMA" ], [ "BOLIVIA", "release_year", "2001" ], [ "BRIDE OF THE WIND", "has_genre", "DRAMA" ], [ "BRIDE OF THE WIND", "release_year", "2001" ], [ "BRIDESHEAD REVISITED", "has_genre", "DRAMA" ], [ "BROTHERHOOD OF THE WOLF", "has_genre", "DRAMA" ], [ "BROTHERHOOD OF THE WOLF", "release_year", "2001" ], [ "CAMOUFLAGE", "has_genre", "DRAMA" ], [ "CAMOUFLAGE", "release_year", "2001" ], [ "CHARLOTTE GRAY", "has_genre", "DRAMA" ], [ "CHARLOTTE GRAY", "release_year", "2001" ], [ "CONSPIRACY", "has_genre", "DRAMA" ], [ "CONSPIRACY", "release_year", "2001" ], [ "CRAZY/BEAUTIFUL", "has_genre", "DRAMA" ], [ "CRAZY/BEAUTIFUL", "release_year", "2001" ], [ "CRUSH", "has_genre", "DRAMA" ], [ "CRUSH", "release_year", "2001" ], [ "DIL CHAHTA HAI", "has_genre", "DRAMA" ], [ "DIL CHAHTA HAI", "release_year", "2001" ], [ "DON'S PLUM", "has_genre", "DRAMA" ], [ "DON'S PLUM", "release_year", "2001" ], [ "DONNIE DARKO", "has_genre", "DRAMA" ], [ "DONNIE DARKO", "release_year", "2001" ], [ "DR. DOLITTLE 2", "release_year", "2001" ], [ "DRIVEN", "has_genre", "DRAMA" ], [ "DRIVEN", "release_year", "2001" ], [ "DUST", "has_genre", "DRAMA" ], [ "DUST", "release_year", "2001" ], [ "ENIGMA", "has_genre", "DRAMA" ], [ "ENIGMA", "release_year", "2001" ], [ "FATE", "has_genre", "DRAMA" ], [ "FATE", "release_year", "2001" ], [ "FOCUS", "has_genre", "DRAMA" ], [ "FOCUS", "release_year", "2001" ], [ "GHOST WORLD", "has_genre", "DRAMA" ], [ "GHOST WORLD", "release_year", "2001" ], [ "GLITTER", "has_genre", "DRAMA" ], [ "GLITTER", "release_year", "2001" ], [ "GYPSY 83", "has_genre", "DRAMA" ], [ "GYPSY 83", "release_year", "2001" ], [ "HARVARD MAN", "has_genre", "DRAMA" ], [ "HARVARD MAN", "release_year", "2001" ], [ "HEARTS IN ATLANTIS", "has_genre", "DRAMA" ], [ "HEARTS IN ATLANTIS", "release_year", "2001" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "DRAMA" ], [ "HEDWIG AND THE ANGRY INCH", "release_year", "2001" ], [ "HIGH HEELS AND LOW LIFES", "has_genre", "DRAMA" ], [ "HIGH HEELS AND LOW LIFES", "release_year", "2001" ], [ "HISTORY IS MADE AT NIGHT", "has_genre", "DRAMA" ], [ "HISTORY IS MADE AT NIGHT", "starred_actors", "LEO CARRILLO" ], [ "HUMAN NATURE", "has_genre", "DRAMA" ], [ "HUMAN NATURE", "release_year", "2001" ], [ "I AM SAM", "has_genre", "DRAMA" ], [ "I AM SAM", "release_year", "2001" ], [ "IN THE BEDROOM", "has_genre", "DRAMA" ], [ "IN THE BEDROOM", "has_tags", "DRAMA" ], [ "IN THE BEDROOM", "release_year", "2001" ], [ "INVINCIBLE", "has_genre", "DRAMA" ], [ "INVINCIBLE", "release_year", "2001" ], [ "JACKPOT", "has_genre", "DRAMA" ], [ "JACKPOT", "release_year", "2001" ], [ "JOE SOMEBODY", "has_genre", "DRAMA" ], [ "JOE SOMEBODY", "release_year", "2001" ], [ "JULIE JOHNSON", "has_genre", "DRAMA" ], [ "JULIE JOHNSON", "release_year", "2001" ], [ "KABHI KHUSHI KABHIE GHAM...", "has_genre", "DRAMA" ], [ "KABHI KHUSHI KABHIE GHAM...", "release_year", "2001" ], [ "KINGDOM COME", "has_genre", "DRAMA" ], [ "KINGDOM COME", "release_year", "2001" ], [ "L.I.E.", "has_genre", "DRAMA" ], [ "L.I.E.", "release_year", "2001" ], [ "LAST ORDERS", "has_genre", "DRAMA" ], [ "LAST ORDERS", "release_year", "2001" ], [ "LIFE AS A HOUSE", "has_genre", "DRAMA" ], [ "LIFE AS A HOUSE", "release_year", "2001" ], [ "LITTLE SECRETS", "has_genre", "DRAMA" ], [ "LITTLE SECRETS", "release_year", "2001" ], [ "LOST AND DELIRIOUS", "has_genre", "DRAMA" ], [ "LOST AND DELIRIOUS", "release_year", "2001" ], [ "MAD LOVE", "has_genre", "DRAMA" ], [ "MAD LOVE", "release_year", "2001" ], [ "MANIC", "has_genre", "DRAMA" ], [ "MANIC", "release_year", "2001" ], [ "MEAN MACHINE", "has_genre", "DRAMA" ], [ "MEAN MACHINE", "release_year", "2001" ], [ "MONSTER'S BALL", "has_genre", "DRAMA" ], [ "MONSTER'S BALL", "release_year", "2001" ], [ "MOSTLY MARTHA", "has_genre", "DRAMA" ], [ "MOSTLY MARTHA", "release_year", "2001" ], [ "O", "has_genre", "DRAMA" ], [ "O", "release_year", "2001" ], [ "ONE 2 KA 4", "has_genre", "DRAMA" ], [ "ONE 2 KA 4", "release_year", "2001" ], [ "ONE MAN UP", "has_genre", "DRAMA" ], [ "ONE MAN UP", "release_year", "2001" ], [ "PAULINE AND PAULETTE", "has_genre", "DRAMA" ], [ "PAULINE AND PAULETTE", "release_year", "2001" ], [ "PEARL HARBOR", "has_genre", "DRAMA" ], [ "PEARL HARBOR", "has_tags", "DRAMA" ], [ "PEARL HARBOR", "release_year", "2001" ], [ "PROZAC NATION", "has_genre", "DRAMA" ], [ "PROZAC NATION", "release_year", "2001" ], [ "RAIN", "has_genre", "DRAMA" ], [ "RAIN", "release_year", "2001" ], [ "RARE BIRDS", "has_genre", "DRAMA" ], [ "RARE BIRDS", "release_year", "2001" ], [ "ROCK STAR", "has_genre", "DRAMA" ], [ "ROCK STAR", "release_year", "2001" ], [ "SEX AND LUCIA", "has_genre", "DRAMA" ], [ "SEX AND LUCIA", "release_year", "2001" ], [ "SON OF THE BRIDE", "has_genre", "DRAMA" ], [ "SON OF THE BRIDE", "release_year", "2001" ], [ "STORYTELLING", "has_genre", "DRAMA" ], [ "STORYTELLING", "release_year", "2001" ], [ "SWEET NOVEMBER", "has_genre", "DRAMA" ], [ "SWEET NOVEMBER", "release_year", "2001" ], [ "TAPE", "has_genre", "DRAMA" ], [ "TAPE", "release_year", "2001" ], [ "TEXAS RANGERS", "has_genre", "DRAMA" ], [ "TEXAS RANGERS", "release_year", "2001" ], [ "THE AFFAIR OF THE NECKLACE", "has_genre", "DRAMA" ], [ "THE AFFAIR OF THE NECKLACE", "release_year", "2001" ], [ "THE ANNIVERSARY PARTY", "has_genre", "DRAMA" ], [ "THE ANNIVERSARY PARTY", "release_year", "2001" ], [ "THE BANK", "has_genre", "DRAMA" ], [ "THE BANK", "release_year", "2001" ], [ "THE BELIEVER", "has_genre", "DRAMA" ], [ "THE BELIEVER", "release_year", "2001" ], [ "THE BROTHERS", "has_genre", "DRAMA" ], [ "THE BROTHERS", "release_year", "2001" ], [ "THE CAT'S MEOW", "has_genre", "DRAMA" ], [ "THE CAT'S MEOW", "release_year", "2001" ], [ "THE CAVEMAN'S VALENTINE", "has_genre", "DRAMA" ], [ "THE CAVEMAN'S VALENTINE", "release_year", "2001" ], [ "THE INVISIBLE CIRCUS", "has_genre", "DRAMA" ], [ "THE INVISIBLE CIRCUS", "release_year", "2001" ], [ "THE JIMMY SHOW", "has_genre", "DRAMA" ], [ "THE JIMMY SHOW", "release_year", "2001" ], [ "THE LAST CASTLE", "has_genre", "DRAMA" ], [ "THE LAST CASTLE", "release_year", "2001" ], [ "THE LAST KISS", "has_genre", "DRAMA" ], [ "THE LAST KISS", "release_year", "2001" ], [ "THE MAJESTIC", "has_genre", "DRAMA" ], [ "THE MAJESTIC", "release_year", "2001" ], [ "THE MAN FROM ELYSIAN FIELDS", "has_genre", "DRAMA" ], [ "THE MAN FROM ELYSIAN FIELDS", "release_year", "2001" ], [ "THE OTHER SIDE OF HEAVEN", "has_genre", "DRAMA" ], [ "THE OTHER SIDE OF HEAVEN", "release_year", "2001" ], [ "THE OTHERS", "has_tags", "DRAMA" ], [ "THE OTHERS", "release_year", "2001" ], [ "THE PORNOGRAPHER", "has_genre", "DRAMA" ], [ "THE PORNOGRAPHER", "release_year", "2001" ], [ "THE RIVER", "has_genre", "DRAMA" ], [ "THE RIVER", "release_year", "2001" ], [ "THE ROYAL TENENBAUMS", "has_genre", "DRAMA" ], [ "THE ROYAL TENENBAUMS", "release_year", "2001" ], [ "THE SHIPPING NEWS", "has_genre", "DRAMA" ], [ "THE SHIPPING NEWS", "release_year", "2001" ], [ "THE UNSAID", "has_genre", "DRAMA" ], [ "THE UNSAID", "release_year", "2001" ], [ "THIRTEEN CONVERSATIONS ABOUT ONE THING", "has_genre", "DRAMA" ], [ "THIRTEEN CONVERSATIONS ABOUT ONE THING", "release_year", "2001" ], [ "TIME OUT", "has_genre", "DRAMA" ], [ "TIME OUT", "release_year", "2001" ], [ "TO THE LEFT OF THE FATHER", "has_genre", "DRAMA" ], [ "TO THE LEFT OF THE FATHER", "release_year", "2001" ], [ "TORTILLA SOUP", "has_genre", "DRAMA" ], [ "TORTILLA SOUP", "release_year", "2001" ], [ "TREED MURRAY", "has_genre", "DRAMA" ], [ "TREED MURRAY", "release_year", "2001" ], [ "UNFAIR COMPETITION", "has_genre", "DRAMA" ], [ "UNFAIR COMPETITION", "release_year", "2001" ], [ "UPRISING", "has_genre", "DRAMA" ], [ "UPRISING", "release_year", "2001" ], [ "VIZONTELE", "has_genre", "DRAMA" ], [ "VIZONTELE", "release_year", "2001" ], [ "WAKING LIFE", "has_genre", "DRAMA" ], [ "WAKING LIFE", "release_year", "2001" ], [ "WORLD TRAVELER", "has_genre", "DRAMA" ], [ "WORLD TRAVELER", "release_year", "2001" ], [ "Y TU MAMÁ TAMBIÉN", "has_genre", "DRAMA" ], [ "Y TU MAMÁ TAMBIÉN", "has_tags", "DRAMA" ], [ "Y TU MAMÁ TAMBIÉN", "release_year", "2001" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37608, AUSTRALIA 7795, BEN CHAPLIN 19633, BIRTHDAY GIRL 9700, DINGO 4931, HOW DO YOU KNOW 10942, MIDNIGHT IN PARIS 9336, NICOLE KIDMAN 31494, OWEN WILSON 31134, PARIS src, edge_attr, dst 37608, has_tags, 37608 37608, has_tags, 9336 19633, has_tags, 9336 19633, starred_actors, 7795 19633, starred_actors, 9336 9700, has_tags, 37608 9700, has_tags, 31134 4931, starred_actors, 31494 10942, has_tags, 31494 10942, has_tags, 31134 10942, starred_actors, 31494 Question: In what context are BEN CHAPLIN, DINGO, and HOW DO YOU KNOW connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BEN CHAPLIN", "DINGO", "HOW DO YOU KNOW" ], "valid_edges": [ [ "AUSTRALIA", "has_tags", "AUSTRALIA" ], [ "AUSTRALIA", "has_tags", "NICOLE KIDMAN" ], [ "BIRTHDAY GIRL", "has_tags", "NICOLE KIDMAN" ], [ "BIRTHDAY GIRL", "starred_actors", "BEN CHAPLIN" ], [ "BIRTHDAY GIRL", "starred_actors", "NICOLE KIDMAN" ], [ "DINGO", "has_tags", "AUSTRALIA" ], [ "DINGO", "has_tags", "PARIS" ], [ "HOW DO YOU KNOW", "starred_actors", "OWEN WILSON" ], [ "MIDNIGHT IN PARIS", "has_tags", "OWEN WILSON" ], [ "MIDNIGHT IN PARIS", "has_tags", "PARIS" ], [ "MIDNIGHT IN PARIS", "starred_actors", "OWEN WILSON" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1892, 1932 25221, 1981 35798, 2010 9532, ARE YOU LISTENING? 14984, BLOW OUT 8065, BRIAN DE PALMA 30463, COMEDY 36212, DRAMA 31783, ENGLISH 31955, FAST LIFE 24396, GET SHORTY 9931, JANE GOLDMAN 7690, JOHN LITHGOW 27999, JOHN TRAVOLTA 16959, JUST A GIGOLO 12359, KICK-ASS 29701, MADGE EVANS 15370, MATTHEW VAUGHN 19479, SISTERS 28810, TATTOO 25509, THE DEBT 31970, THE GIRL SAID NO 3437, THE WOMAN IN BLACK 24811, THRILLER 3475, WILLIAM HAINES src, edge_attr, dst 25221, has_genre, 30463 25221, has_genre, 36212 35798, has_tags, 7690 35798, starred_actors, 7690 9532, has_genre, 36212 9532, release_year, 1892 9532, starred_actors, 29701 9532, starred_actors, 3475 14984, directed_by, 8065 14984, has_genre, 24811 14984, has_tags, 8065 14984, release_year, 25221 14984, starred_actors, 7690 14984, starred_actors, 27999 14984, written_by, 8065 31955, has_genre, 30463 31955, release_year, 1892 31955, starred_actors, 29701 31955, starred_actors, 3475 24396, has_genre, 24811 24396, has_tags, 27999 24396, starred_actors, 27999 16959, has_genre, 30463 16959, starred_actors, 3475 12359, directed_by, 15370 12359, has_genre, 30463 12359, has_tags, 15370 12359, release_year, 35798 12359, written_by, 9931 12359, written_by, 15370 19479, directed_by, 8065 19479, has_genre, 24811 19479, has_tags, 8065 19479, written_by, 8065 28810, has_genre, 24811 28810, release_year, 25221 25509, has_genre, 36212 25509, has_genre, 24811 25509, in_language, 31783 25509, release_year, 35798 25509, written_by, 9931 25509, written_by, 15370 31970, has_genre, 30463 31970, starred_actors, 3475 3437, has_genre, 36212 3437, in_language, 31783 3437, written_by, 9931 Question: In what context are BLOW OUT, JANE GOLDMAN, and WILLIAM HAINES connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BLOW OUT", "JANE GOLDMAN", "WILLIAM HAINES" ], "valid_edges": [ [ "1981", "has_genre", "COMEDY" ], [ "1981", "has_genre", "DRAMA" ], [ "2010", "has_tags", "JOHN LITHGOW" ], [ "2010", "starred_actors", "JOHN LITHGOW" ], [ "ARE YOU LISTENING?", "has_genre", "DRAMA" ], [ "ARE YOU LISTENING?", "release_year", "1932" ], [ "ARE YOU LISTENING?", "starred_actors", "MADGE EVANS" ], [ "ARE YOU LISTENING?", "starred_actors", "WILLIAM HAINES" ], [ "BLOW OUT", "directed_by", "BRIAN DE PALMA" ], [ "BLOW OUT", "has_genre", "THRILLER" ], [ "BLOW OUT", "has_tags", "BRIAN DE PALMA" ], [ "BLOW OUT", "release_year", "1981" ], [ "BLOW OUT", "starred_actors", "JOHN LITHGOW" ], [ "BLOW OUT", "starred_actors", "JOHN TRAVOLTA" ], [ "BLOW OUT", "written_by", "BRIAN DE PALMA" ], [ "FAST LIFE", "has_genre", "COMEDY" ], [ "FAST LIFE", "release_year", "1932" ], [ "FAST LIFE", "starred_actors", "MADGE EVANS" ], [ "FAST LIFE", "starred_actors", "WILLIAM HAINES" ], [ "GET SHORTY", "has_genre", "THRILLER" ], [ "GET SHORTY", "has_tags", "JOHN TRAVOLTA" ], [ "GET SHORTY", "starred_actors", "JOHN TRAVOLTA" ], [ "JUST A GIGOLO", "has_genre", "COMEDY" ], [ "JUST A GIGOLO", "starred_actors", "WILLIAM HAINES" ], [ "KICK-ASS", "directed_by", "MATTHEW VAUGHN" ], [ "KICK-ASS", "has_genre", "COMEDY" ], [ "KICK-ASS", "has_tags", "MATTHEW VAUGHN" ], [ "KICK-ASS", "release_year", "2010" ], [ "KICK-ASS", "written_by", "JANE GOLDMAN" ], [ "KICK-ASS", "written_by", "MATTHEW VAUGHN" ], [ "SISTERS", "directed_by", "BRIAN DE PALMA" ], [ "SISTERS", "has_genre", "THRILLER" ], [ "SISTERS", "has_tags", "BRIAN DE PALMA" ], [ "SISTERS", "written_by", "BRIAN DE PALMA" ], [ "TATTOO", "has_genre", "THRILLER" ], [ "TATTOO", "release_year", "1981" ], [ "THE DEBT", "has_genre", "DRAMA" ], [ "THE DEBT", "has_genre", "THRILLER" ], [ "THE DEBT", "in_language", "ENGLISH" ], [ "THE DEBT", "release_year", "2010" ], [ "THE DEBT", "written_by", "JANE GOLDMAN" ], [ "THE DEBT", "written_by", "MATTHEW VAUGHN" ], [ "THE GIRL SAID NO", "has_genre", "COMEDY" ], [ "THE GIRL SAID NO", "starred_actors", "WILLIAM HAINES" ], [ "THE WOMAN IN BLACK", "has_genre", "DRAMA" ], [ "THE WOMAN IN BLACK", "in_language", "ENGLISH" ], [ "THE WOMAN IN BLACK", "written_by", "JANE GOLDMAN" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1678, 12 AND HOLDING 15374, 2005 17315, 2007 33461, 3 NEEDLES 7596, 4 28189, A LITTLE TRIP TO HEAVEN 29838, A SIMPLE TWIST OF FATE 26599, AMERICAN GUN 29881, AMERICANO 2888, AN UNFINISHED LIFE 27981, ANGEL-A 7302, AS COOL AS I AM 38707, ASYLUM 4499, AURORA BOREALIS 30335, BE WITH ME 31574, BEE SEASON 32479, BEWITCHED 37840, BLACK 29183, BREAKFAST ON PLUTO 11547, BROKEBACK MOUNTAIN 7918, BROKEDOWN PALACE 13657, BROKEN FLOWERS 19004, CAKE 29797, CINDERELLA MAN 8188, CLAIRE DANES 29211, COACH CARTER 31346, CONVERSATIONS WITH OTHER WOMEN 23452, DARK HORSE 32232, DIARY OF A MAD BLACK WOMAN 7347, DIRTY 24798, DON'T COME KNOCKING 36212, DRAMA 15272, DUMA 254, EDMOND 37496, ELIZABETHTOWN 24494, ELLIE PARKER 27441, ENTRE SES MAINS 38285, EVERYTHING IS ILLUMINATED 15891, FETCHING CODY 18446, FEVER PITCH 7391, FIERCE PEOPLE 24013, FROZEN LAND 5514, FUNNY PEOPLE 7770, GABRIELLE 16048, GET RICH OR DIE TRYIN' 6129, HAVOC 29188, HEADING SOUTH 31330, HOME 17197, IGBY GOES DOWN 12076, IN HER SHOES 1321, IRON ISLAND 6425, IT'S ALL ABOUT LOVE 15012, JARHEAD 24985, JASON SCHWARTZMAN 17160, JUNEBUG 26406, KINKY BOOTS 4794, LAST DAYS 14601, LES MISÉRABLES 29912, LIE WITH ME 17319, LONDON 3459, LONESOME JIM 35537, LORDS OF DOGTOWN 19802, LOVE 1691, LOVE'S LONG JOURNEY 21036, LOWER CITY 9938, MAN TO MAN 35670, MANDERLAY 14037, MARY 13531, MATCH POINT 570, MAUREEN MEDVED 11837, ME AND YOU AND EVERYONE WE KNOW 34359, MELISSA P. 16393, MISSING IN AMERICA 23481, MOACYR GÓES 38312, MOUTH TO MOUTH 17433, MOZART AND THE WHALE 37073, MRS. PALFREY AT THE CLAREMONT 8747, MUNICH 21030, NANA 25269, NINE LIVES 30931, NORTH COUNTRY 27113, O HOMEM QUE DESAFIOU O DIABO 14234, ODD GIRL OUT 15644, OLIVER TWIST 21568, ON A CLEAR DAY 5023, PARENTHOOD 23964, PENNIES FROM HEAVEN 20164, PRETTY PERSUASION 4584, PROOF 34066, PUZZLEHEAD 3781, QUO VADIS, BABY? 8871, RENT 17151, REVOLVER 27361, RIDING ALONE FOR THOUSANDS OF MILES 313, ROLL BOUNCE 21719, ROMANZO CRIMINALE 26229, ROMEO + JULIET 12153, RUSHMORE 35586, SAHARA 30441, SEPARATE LIES 4635, SERENITY 36273, SEXUAL LIFE 21176, SHOPGIRL 10925, SLOW BURN 15382, SOMETIMES IN APRIL 35843, SPUN 26621, STAY 24849, STEVE MARTIN 38027, SUNFLOWER 5569, SWEET LAND 11773, THANK YOU FOR SMOKING 34274, THE BALLAD OF JACK AND ROSE 17864, THE CHUMSCRUBBER 18142, THE CONSTANT GARDENER 35261, THE DARJEELING LIMITED 16597, THE DYING GAUL 7366, THE EXORCISM OF EMILY ROSE 28948, THE FAMILY STONE 10802, THE GAME OF THEIR LIVES 33315, THE GIRL IN THE CAFÉ 20237, THE ICE HARVEST 35165, THE ITALIAN 30360, THE KING 20223, THE LONGEST YARD 24108, THE MAN 8022, THE NEW WORLD 8970, THE PRINCE OF EGYPT 27029, THE PROPOSITION 19644, THE QUIET 16072, THE RAINMAKER 7237, THE SISTERHOOD OF THE TRAVELING PANTS 32210, THE SQUID AND THE WHALE 21548, THE SUN 31827, THE THING ABOUT MY FOLKS 35215, THE TRACEY FRAGMENTS 7168, THE UPSIDE OF ANGER 39409, THE VIOLIN 21433, THE WAR WITHIN 11407, THE WEATHER MAN 34902, THE WHITE COUNTESS 631, THUMBSUCKER 9970, TICKETS 38564, TO GILLIAN ON HER 37TH BIRTHDAY 20251, TO PAINT OR MAKE LOVE 22342, TRANSAMERICA 36820, TWO FOR THE MONEY 10855, WAH-WAH 7715, WALK THE LINE 39965, WHAT IS IT? src, edge_attr, dst 1678, has_genre, 36212 1678, release_year, 15374 33461, has_genre, 36212 33461, release_year, 15374 7596, has_genre, 36212 7596, release_year, 15374 28189, has_genre, 36212 28189, release_year, 15374 29838, has_genre, 36212 29838, starred_actors, 24849 29838, written_by, 24849 26599, has_genre, 36212 26599, release_year, 15374 29881, has_genre, 36212 29881, release_year, 15374 2888, has_genre, 36212 2888, release_year, 15374 27981, has_genre, 36212 27981, release_year, 15374 7302, has_genre, 36212 7302, starred_actors, 8188 38707, has_genre, 36212 38707, release_year, 15374 4499, has_genre, 36212 4499, release_year, 15374 30335, has_genre, 36212 30335, release_year, 15374 31574, has_genre, 36212 31574, release_year, 15374 32479, has_genre, 36212 32479, release_year, 15374 37840, has_genre, 36212 37840, release_year, 15374 29183, has_genre, 36212 29183, release_year, 15374 11547, has_genre, 36212 11547, release_year, 15374 7918, has_genre, 36212 7918, starred_actors, 8188 13657, has_genre, 36212 13657, has_tags, 36212 13657, release_year, 15374 19004, has_genre, 36212 19004, release_year, 15374 29797, has_genre, 36212 29797, release_year, 15374 29211, has_genre, 36212 29211, release_year, 15374 31346, has_genre, 36212 31346, release_year, 15374 23452, has_genre, 36212 23452, release_year, 15374 32232, has_genre, 36212 32232, release_year, 15374 7347, has_genre, 36212 7347, release_year, 15374 24798, has_genre, 36212 24798, release_year, 15374 15272, has_genre, 36212 15272, release_year, 15374 254, has_genre, 36212 254, release_year, 15374 37496, has_genre, 36212 37496, release_year, 15374 24494, has_genre, 36212 24494, release_year, 15374 27441, has_genre, 36212 27441, release_year, 15374 38285, has_genre, 36212 38285, has_tags, 36212 38285, release_year, 15374 15891, has_genre, 36212 15891, release_year, 15374 18446, has_genre, 36212 18446, release_year, 15374 7391, has_genre, 36212 7391, release_year, 15374 24013, has_genre, 36212 24013, release_year, 15374 5514, has_genre, 36212 5514, has_tags, 36212 5514, has_tags, 24985 7770, has_genre, 36212 7770, release_year, 15374 16048, has_genre, 36212 16048, release_year, 15374 6129, has_genre, 36212 6129, release_year, 15374 29188, has_genre, 36212 29188, release_year, 15374 31330, has_genre, 36212 31330, starred_actors, 24849 17197, has_genre, 36212 17197, has_tags, 8188 17197, starred_actors, 8188 12076, has_genre, 36212 12076, has_tags, 36212 12076, release_year, 15374 1321, has_genre, 36212 1321, release_year, 15374 6425, has_genre, 36212 6425, has_tags, 8188 6425, starred_actors, 8188 15012, has_genre, 36212 15012, release_year, 15374 17160, has_genre, 36212 17160, release_year, 15374 26406, has_genre, 36212 26406, release_year, 15374 4794, has_genre, 36212 4794, release_year, 15374 14601, has_genre, 36212 14601, has_tags, 8188 29912, has_genre, 36212 29912, release_year, 15374 17319, has_genre, 36212 17319, release_year, 15374 3459, has_genre, 36212 3459, release_year, 15374 35537, has_genre, 36212 35537, release_year, 15374 19802, has_genre, 36212 19802, release_year, 15374 1691, has_genre, 36212 1691, release_year, 15374 21036, has_genre, 36212 21036, release_year, 15374 9938, has_genre, 36212 9938, release_year, 15374 35670, has_genre, 36212 35670, release_year, 15374 14037, has_genre, 36212 14037, release_year, 15374 13531, has_genre, 36212 13531, release_year, 15374 11837, has_genre, 36212 11837, release_year, 15374 34359, has_genre, 36212 34359, release_year, 15374 16393, has_genre, 36212 16393, release_year, 15374 38312, has_genre, 36212 38312, has_tags, 36212 38312, release_year, 15374 17433, has_genre, 36212 17433, release_year, 15374 37073, has_genre, 36212 37073, release_year, 15374 8747, has_genre, 36212 8747, release_year, 15374 21030, has_genre, 36212 21030, release_year, 15374 25269, has_genre, 36212 25269, release_year, 15374 30931, has_genre, 36212 30931, release_year, 15374 27113, directed_by, 23481 27113, release_year, 17315 27113, written_by, 23481 14234, has_genre, 36212 14234, release_year, 15374 15644, has_genre, 36212 15644, release_year, 15374 21568, has_genre, 36212 21568, release_year, 15374 5023, has_genre, 36212 5023, has_tags, 24849 5023, starred_actors, 24849 23964, has_genre, 36212 23964, starred_actors, 24849 20164, has_genre, 36212 20164, release_year, 15374 4584, has_genre, 36212 4584, release_year, 15374 34066, has_genre, 36212 34066, release_year, 15374 3781, has_genre, 36212 3781, release_year, 15374 8871, has_genre, 36212 8871, release_year, 15374 17151, has_genre, 36212 17151, release_year, 15374 27361, has_genre, 36212 27361, release_year, 15374 313, has_genre, 36212 313, release_year, 15374 21719, has_genre, 36212 21719, release_year, 15374 26229, has_genre, 36212 26229, has_tags, 8188 26229, starred_actors, 8188 12153, has_genre, 36212 12153, has_tags, 24985 12153, starred_actors, 24985 35586, has_genre, 36212 35586, release_year, 15374 30441, has_genre, 36212 30441, release_year, 15374 4635, has_tags, 36212 4635, release_year, 15374 36273, has_genre, 36212 36273, release_year, 15374 21176, has_genre, 36212 21176, has_tags, 8188 21176, has_tags, 24985 21176, has_tags, 24849 21176, release_year, 15374 21176, starred_actors, 8188 21176, starred_actors, 24985 21176, starred_actors, 24849 21176, written_by, 24849 10925, has_genre, 36212 10925, release_year, 15374 15382, has_genre, 36212 15382, release_year, 15374 35843, has_genre, 36212 35843, has_tags, 24985 35843, starred_actors, 24985 26621, has_genre, 36212 26621, release_year, 15374 38027, has_genre, 36212 38027, release_year, 15374 5569, has_genre, 36212 5569, release_year, 15374 11773, has_genre, 36212 11773, release_year, 15374 34274, has_genre, 36212 34274, release_year, 15374 17864, has_genre, 36212 17864, release_year, 15374 18142, has_genre, 36212 18142, has_tags, 36212 18142, release_year, 15374 35261, has_genre, 36212 35261, has_tags, 24985 35261, starred_actors, 24985 35261, written_by, 24985 16597, has_genre, 36212 16597, release_year, 15374 7366, has_genre, 36212 7366, release_year, 15374 28948, has_genre, 36212 28948, has_tags, 8188 28948, has_tags, 36212 28948, release_year, 15374 28948, starred_actors, 8188 10802, has_genre, 36212 10802, release_year, 15374 33315, has_genre, 36212 33315, release_year, 15374 20237, has_genre, 36212 20237, release_year, 15374 35165, has_genre, 36212 35165, release_year, 15374 30360, has_genre, 36212 30360, release_year, 15374 20223, has_genre, 36212 20223, release_year, 15374 24108, has_genre, 36212 24108, release_year, 15374 8022, has_genre, 36212 8022, release_year, 15374 8970, has_genre, 36212 8970, has_tags, 24849 27029, has_genre, 36212 27029, release_year, 15374 19644, has_genre, 36212 19644, release_year, 15374 16072, has_genre, 36212 16072, has_tags, 8188 16072, starred_actors, 8188 7237, has_genre, 36212 7237, release_year, 15374 32210, has_genre, 36212 32210, has_tags, 36212 32210, release_year, 15374 21548, has_genre, 36212 21548, release_year, 15374 31827, has_genre, 36212 31827, release_year, 15374 35215, has_genre, 36212 35215, release_year, 17315 35215, written_by, 570 7168, has_genre, 36212 7168, release_year, 15374 39409, has_genre, 36212 39409, release_year, 15374 21433, has_genre, 36212 21433, release_year, 15374 11407, has_genre, 36212 11407, release_year, 15374 34902, has_genre, 36212 34902, release_year, 15374 631, has_genre, 36212 631, release_year, 15374 9970, has_genre, 36212 9970, release_year, 15374 38564, has_genre, 36212 38564, starred_actors, 8188 20251, has_genre, 36212 20251, release_year, 15374 22342, has_genre, 36212 22342, release_year, 15374 36820, has_genre, 36212 36820, release_year, 15374 10855, has_genre, 36212 10855, release_year, 15374 7715, has_genre, 36212 7715, release_year, 15374 39965, has_genre, 36212 39965, release_year, 15374 Question: For what reason are MAUREEN MEDVED, MOACYR GÓES, and SHOPGIRL associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "MAUREEN MEDVED", "MOACYR GÓES", "SHOPGIRL" ], "valid_edges": [ [ "12 AND HOLDING", "has_genre", "DRAMA" ], [ "12 AND HOLDING", "release_year", "2005" ], [ "3 NEEDLES", "has_genre", "DRAMA" ], [ "3 NEEDLES", "release_year", "2005" ], [ "4", "has_genre", "DRAMA" ], [ "4", "release_year", "2005" ], [ "A LITTLE TRIP TO HEAVEN", "has_genre", "DRAMA" ], [ "A LITTLE TRIP TO HEAVEN", "release_year", "2005" ], [ "A SIMPLE TWIST OF FATE", "has_genre", "DRAMA" ], [ "A SIMPLE TWIST OF FATE", "starred_actors", "STEVE MARTIN" ], [ "A SIMPLE TWIST OF FATE", "written_by", "STEVE MARTIN" ], [ "AMERICAN GUN", "has_genre", "DRAMA" ], [ "AMERICAN GUN", "release_year", "2005" ], [ "AMERICANO", "has_genre", "DRAMA" ], [ "AMERICANO", "release_year", "2005" ], [ "AN UNFINISHED LIFE", "has_genre", "DRAMA" ], [ "AN UNFINISHED LIFE", "release_year", "2005" ], [ "ANGEL-A", "has_genre", "DRAMA" ], [ "ANGEL-A", "release_year", "2005" ], [ "AS COOL AS I AM", "has_genre", "DRAMA" ], [ "AS COOL AS I AM", "starred_actors", "CLAIRE DANES" ], [ "ASYLUM", "has_genre", "DRAMA" ], [ "ASYLUM", "release_year", "2005" ], [ "AURORA BOREALIS", "has_genre", "DRAMA" ], [ "AURORA BOREALIS", "release_year", "2005" ], [ "BE WITH ME", "has_genre", "DRAMA" ], [ "BE WITH ME", "release_year", "2005" ], [ "BEE SEASON", "has_genre", "DRAMA" ], [ "BEE SEASON", "release_year", "2005" ], [ "BEWITCHED", "has_genre", "DRAMA" ], [ "BEWITCHED", "release_year", "2005" ], [ "BLACK", "has_genre", "DRAMA" ], [ "BLACK", "release_year", "2005" ], [ "BREAKFAST ON PLUTO", "has_genre", "DRAMA" ], [ "BREAKFAST ON PLUTO", "release_year", "2005" ], [ "BROKEBACK MOUNTAIN", "has_genre", "DRAMA" ], [ "BROKEBACK MOUNTAIN", "release_year", "2005" ], [ "BROKEDOWN PALACE", "has_genre", "DRAMA" ], [ "BROKEDOWN PALACE", "starred_actors", "CLAIRE DANES" ], [ "BROKEN FLOWERS", "has_genre", "DRAMA" ], [ "BROKEN FLOWERS", "has_tags", "DRAMA" ], [ "BROKEN FLOWERS", "release_year", "2005" ], [ "CAKE", "has_genre", "DRAMA" ], [ "CAKE", "release_year", "2005" ], [ "CINDERELLA MAN", "has_genre", "DRAMA" ], [ "CINDERELLA MAN", "release_year", "2005" ], [ "COACH CARTER", "has_genre", "DRAMA" ], [ "COACH CARTER", "release_year", "2005" ], [ "CONVERSATIONS WITH OTHER WOMEN", "has_genre", "DRAMA" ], [ "CONVERSATIONS WITH OTHER WOMEN", "release_year", "2005" ], [ "DARK HORSE", "has_genre", "DRAMA" ], [ "DARK HORSE", "release_year", "2005" ], [ "DIARY OF A MAD BLACK WOMAN", "has_genre", "DRAMA" ], [ "DIARY OF A MAD BLACK WOMAN", "release_year", "2005" ], [ "DIRTY", "has_genre", "DRAMA" ], [ "DIRTY", "release_year", "2005" ], [ "DON'T COME KNOCKING", "has_genre", "DRAMA" ], [ "DON'T COME KNOCKING", "release_year", "2005" ], [ "DUMA", "has_genre", "DRAMA" ], [ "DUMA", "release_year", "2005" ], [ "EDMOND", "has_genre", "DRAMA" ], [ "EDMOND", "release_year", "2005" ], [ "ELIZABETHTOWN", "has_genre", "DRAMA" ], [ "ELIZABETHTOWN", "release_year", "2005" ], [ "ELLIE PARKER", "has_genre", "DRAMA" ], [ "ELLIE PARKER", "release_year", "2005" ], [ "ENTRE SES MAINS", "has_genre", "DRAMA" ], [ "ENTRE SES MAINS", "release_year", "2005" ], [ "EVERYTHING IS ILLUMINATED", "has_genre", "DRAMA" ], [ "EVERYTHING IS ILLUMINATED", "has_tags", "DRAMA" ], [ "EVERYTHING IS ILLUMINATED", "release_year", "2005" ], [ "FETCHING CODY", "has_genre", "DRAMA" ], [ "FETCHING CODY", "release_year", "2005" ], [ "FEVER PITCH", "has_genre", "DRAMA" ], [ "FEVER PITCH", "release_year", "2005" ], [ "FIERCE PEOPLE", "has_genre", "DRAMA" ], [ "FIERCE PEOPLE", "release_year", "2005" ], [ "FROZEN LAND", "has_genre", "DRAMA" ], [ "FROZEN LAND", "release_year", "2005" ], [ "FUNNY PEOPLE", "has_genre", "DRAMA" ], [ "FUNNY PEOPLE", "has_tags", "DRAMA" ], [ "FUNNY PEOPLE", "has_tags", "JASON SCHWARTZMAN" ], [ "GABRIELLE", "has_genre", "DRAMA" ], [ "GABRIELLE", "release_year", "2005" ], [ "GET RICH OR DIE TRYIN'", "has_genre", "DRAMA" ], [ "GET RICH OR DIE TRYIN'", "release_year", "2005" ], [ "HAVOC", "has_genre", "DRAMA" ], [ "HAVOC", "release_year", "2005" ], [ "HEADING SOUTH", "has_genre", "DRAMA" ], [ "HEADING SOUTH", "release_year", "2005" ], [ "HOME", "has_genre", "DRAMA" ], [ "HOME", "starred_actors", "STEVE MARTIN" ], [ "IGBY GOES DOWN", "has_genre", "DRAMA" ], [ "IGBY GOES DOWN", "has_tags", "CLAIRE DANES" ], [ "IGBY GOES DOWN", "starred_actors", "CLAIRE DANES" ], [ "IN HER SHOES", "has_genre", "DRAMA" ], [ "IN HER SHOES", "has_tags", "DRAMA" ], [ "IN HER SHOES", "release_year", "2005" ], [ "IRON ISLAND", "has_genre", "DRAMA" ], [ "IRON ISLAND", "release_year", "2005" ], [ "IT'S ALL ABOUT LOVE", "has_genre", "DRAMA" ], [ "IT'S ALL ABOUT LOVE", "has_tags", "CLAIRE DANES" ], [ "IT'S ALL ABOUT LOVE", "starred_actors", "CLAIRE DANES" ], [ "JARHEAD", "has_genre", "DRAMA" ], [ "JARHEAD", "release_year", "2005" ], [ "JUNEBUG", "has_genre", "DRAMA" ], [ "JUNEBUG", "release_year", "2005" ], [ "KINKY BOOTS", "has_genre", "DRAMA" ], [ "KINKY BOOTS", "release_year", "2005" ], [ "LAST DAYS", "has_genre", "DRAMA" ], [ "LAST DAYS", "release_year", "2005" ], [ "LES MISÉRABLES", "has_genre", "DRAMA" ], [ "LES MISÉRABLES", "has_tags", "CLAIRE DANES" ], [ "LIE WITH ME", "has_genre", "DRAMA" ], [ "LIE WITH ME", "release_year", "2005" ], [ "LONDON", "has_genre", "DRAMA" ], [ "LONDON", "release_year", "2005" ], [ "LONESOME JIM", "has_genre", "DRAMA" ], [ "LONESOME JIM", "release_year", "2005" ], [ "LORDS OF DOGTOWN", "has_genre", "DRAMA" ], [ "LORDS OF DOGTOWN", "release_year", "2005" ], [ "LOVE", "has_genre", "DRAMA" ], [ "LOVE", "release_year", "2005" ], [ "LOVE'S LONG JOURNEY", "has_genre", "DRAMA" ], [ "LOVE'S LONG JOURNEY", "release_year", "2005" ], [ "LOWER CITY", "has_genre", "DRAMA" ], [ "LOWER CITY", "release_year", "2005" ], [ "MAN TO MAN", "has_genre", "DRAMA" ], [ "MAN TO MAN", "release_year", "2005" ], [ "MANDERLAY", "has_genre", "DRAMA" ], [ "MANDERLAY", "release_year", "2005" ], [ "MARY", "has_genre", "DRAMA" ], [ "MARY", "release_year", "2005" ], [ "MATCH POINT", "has_genre", "DRAMA" ], [ "MATCH POINT", "release_year", "2005" ], [ "ME AND YOU AND EVERYONE WE KNOW", "has_genre", "DRAMA" ], [ "ME AND YOU AND EVERYONE WE KNOW", "release_year", "2005" ], [ "MELISSA P.", "has_genre", "DRAMA" ], [ "MELISSA P.", "release_year", "2005" ], [ "MISSING IN AMERICA", "has_genre", "DRAMA" ], [ "MISSING IN AMERICA", "release_year", "2005" ], [ "MOUTH TO MOUTH", "has_genre", "DRAMA" ], [ "MOUTH TO MOUTH", "has_tags", "DRAMA" ], [ "MOUTH TO MOUTH", "release_year", "2005" ], [ "MOZART AND THE WHALE", "has_genre", "DRAMA" ], [ "MOZART AND THE WHALE", "release_year", "2005" ], [ "MRS. PALFREY AT THE CLAREMONT", "has_genre", "DRAMA" ], [ "MRS. PALFREY AT THE CLAREMONT", "release_year", "2005" ], [ "MUNICH", "has_genre", "DRAMA" ], [ "MUNICH", "release_year", "2005" ], [ "NANA", "has_genre", "DRAMA" ], [ "NANA", "release_year", "2005" ], [ "NINE LIVES", "has_genre", "DRAMA" ], [ "NINE LIVES", "release_year", "2005" ], [ "NORTH COUNTRY", "has_genre", "DRAMA" ], [ "NORTH COUNTRY", "release_year", "2005" ], [ "O HOMEM QUE DESAFIOU O DIABO", "directed_by", "MOACYR GÓES" ], [ "O HOMEM QUE DESAFIOU O DIABO", "release_year", "2007" ], [ "O HOMEM QUE DESAFIOU O DIABO", "written_by", "MOACYR GÓES" ], [ "ODD GIRL OUT", "has_genre", "DRAMA" ], [ "ODD GIRL OUT", "release_year", "2005" ], [ "OLIVER TWIST", "has_genre", "DRAMA" ], [ "OLIVER TWIST", "release_year", "2005" ], [ "ON A CLEAR DAY", "has_genre", "DRAMA" ], [ "ON A CLEAR DAY", "release_year", "2005" ], [ "PARENTHOOD", "has_genre", "DRAMA" ], [ "PARENTHOOD", "has_tags", "STEVE MARTIN" ], [ "PARENTHOOD", "starred_actors", "STEVE MARTIN" ], [ "PENNIES FROM HEAVEN", "has_genre", "DRAMA" ], [ "PENNIES FROM HEAVEN", "starred_actors", "STEVE MARTIN" ], [ "PRETTY PERSUASION", "has_genre", "DRAMA" ], [ "PRETTY PERSUASION", "release_year", "2005" ], [ "PROOF", "has_genre", "DRAMA" ], [ "PROOF", "release_year", "2005" ], [ "PUZZLEHEAD", "has_genre", "DRAMA" ], [ "PUZZLEHEAD", "release_year", "2005" ], [ "QUO VADIS, BABY?", "has_genre", "DRAMA" ], [ "QUO VADIS, BABY?", "release_year", "2005" ], [ "RENT", "has_genre", "DRAMA" ], [ "RENT", "release_year", "2005" ], [ "REVOLVER", "has_genre", "DRAMA" ], [ "REVOLVER", "release_year", "2005" ], [ "RIDING ALONE FOR THOUSANDS OF MILES", "has_genre", "DRAMA" ], [ "RIDING ALONE FOR THOUSANDS OF MILES", "release_year", "2005" ], [ "ROLL BOUNCE", "has_genre", "DRAMA" ], [ "ROLL BOUNCE", "release_year", "2005" ], [ "ROMANZO CRIMINALE", "has_genre", "DRAMA" ], [ "ROMANZO CRIMINALE", "release_year", "2005" ], [ "ROMEO + JULIET", "has_genre", "DRAMA" ], [ "ROMEO + JULIET", "has_tags", "CLAIRE DANES" ], [ "ROMEO + JULIET", "starred_actors", "CLAIRE DANES" ], [ "RUSHMORE", "has_genre", "DRAMA" ], [ "RUSHMORE", "has_tags", "JASON SCHWARTZMAN" ], [ "RUSHMORE", "starred_actors", "JASON SCHWARTZMAN" ], [ "SAHARA", "has_genre", "DRAMA" ], [ "SAHARA", "release_year", "2005" ], [ "SEPARATE LIES", "has_genre", "DRAMA" ], [ "SEPARATE LIES", "release_year", "2005" ], [ "SERENITY", "has_tags", "DRAMA" ], [ "SERENITY", "release_year", "2005" ], [ "SEXUAL LIFE", "has_genre", "DRAMA" ], [ "SEXUAL LIFE", "release_year", "2005" ], [ "SHOPGIRL", "has_genre", "DRAMA" ], [ "SHOPGIRL", "has_tags", "CLAIRE DANES" ], [ "SHOPGIRL", "has_tags", "JASON SCHWARTZMAN" ], [ "SHOPGIRL", "has_tags", "STEVE MARTIN" ], [ "SHOPGIRL", "release_year", "2005" ], [ "SHOPGIRL", "starred_actors", "CLAIRE DANES" ], [ "SHOPGIRL", "starred_actors", "JASON SCHWARTZMAN" ], [ "SHOPGIRL", "starred_actors", "STEVE MARTIN" ], [ "SHOPGIRL", "written_by", "STEVE MARTIN" ], [ "SLOW BURN", "has_genre", "DRAMA" ], [ "SLOW BURN", "release_year", "2005" ], [ "SOMETIMES IN APRIL", "has_genre", "DRAMA" ], [ "SOMETIMES IN APRIL", "release_year", "2005" ], [ "SPUN", "has_genre", "DRAMA" ], [ "SPUN", "has_tags", "JASON SCHWARTZMAN" ], [ "SPUN", "starred_actors", "JASON SCHWARTZMAN" ], [ "STAY", "has_genre", "DRAMA" ], [ "STAY", "release_year", "2005" ], [ "SUNFLOWER", "has_genre", "DRAMA" ], [ "SUNFLOWER", "release_year", "2005" ], [ "SWEET LAND", "has_genre", "DRAMA" ], [ "SWEET LAND", "release_year", "2005" ], [ "THANK YOU FOR SMOKING", "has_genre", "DRAMA" ], [ "THANK YOU FOR SMOKING", "release_year", "2005" ], [ "THE BALLAD OF JACK AND ROSE", "has_genre", "DRAMA" ], [ "THE BALLAD OF JACK AND ROSE", "release_year", "2005" ], [ "THE CHUMSCRUBBER", "has_genre", "DRAMA" ], [ "THE CHUMSCRUBBER", "release_year", "2005" ], [ "THE CONSTANT GARDENER", "has_genre", "DRAMA" ], [ "THE CONSTANT GARDENER", "has_tags", "DRAMA" ], [ "THE CONSTANT GARDENER", "release_year", "2005" ], [ "THE DARJEELING LIMITED", "has_genre", "DRAMA" ], [ "THE DARJEELING LIMITED", "has_tags", "JASON SCHWARTZMAN" ], [ "THE DARJEELING LIMITED", "starred_actors", "JASON SCHWARTZMAN" ], [ "THE DARJEELING LIMITED", "written_by", "JASON SCHWARTZMAN" ], [ "THE DYING GAUL", "has_genre", "DRAMA" ], [ "THE DYING GAUL", "release_year", "2005" ], [ "THE EXORCISM OF EMILY ROSE", "has_genre", "DRAMA" ], [ "THE EXORCISM OF EMILY ROSE", "release_year", "2005" ], [ "THE FAMILY STONE", "has_genre", "DRAMA" ], [ "THE FAMILY STONE", "has_tags", "CLAIRE DANES" ], [ "THE FAMILY STONE", "has_tags", "DRAMA" ], [ "THE FAMILY STONE", "release_year", "2005" ], [ "THE FAMILY STONE", "starred_actors", "CLAIRE DANES" ], [ "THE GAME OF THEIR LIVES", "has_genre", "DRAMA" ], [ "THE GAME OF THEIR LIVES", "release_year", "2005" ], [ "THE GIRL IN THE CAFÉ", "has_genre", "DRAMA" ], [ "THE GIRL IN THE CAFÉ", "release_year", "2005" ], [ "THE ICE HARVEST", "has_genre", "DRAMA" ], [ "THE ICE HARVEST", "release_year", "2005" ], [ "THE ITALIAN", "has_genre", "DRAMA" ], [ "THE ITALIAN", "release_year", "2005" ], [ "THE KING", "has_genre", "DRAMA" ], [ "THE KING", "release_year", "2005" ], [ "THE LONGEST YARD", "has_genre", "DRAMA" ], [ "THE LONGEST YARD", "release_year", "2005" ], [ "THE MAN", "has_genre", "DRAMA" ], [ "THE MAN", "release_year", "2005" ], [ "THE NEW WORLD", "has_genre", "DRAMA" ], [ "THE NEW WORLD", "release_year", "2005" ], [ "THE PRINCE OF EGYPT", "has_genre", "DRAMA" ], [ "THE PRINCE OF EGYPT", "has_tags", "STEVE MARTIN" ], [ "THE PROPOSITION", "has_genre", "DRAMA" ], [ "THE PROPOSITION", "release_year", "2005" ], [ "THE QUIET", "has_genre", "DRAMA" ], [ "THE QUIET", "release_year", "2005" ], [ "THE RAINMAKER", "has_genre", "DRAMA" ], [ "THE RAINMAKER", "has_tags", "CLAIRE DANES" ], [ "THE RAINMAKER", "starred_actors", "CLAIRE DANES" ], [ "THE SISTERHOOD OF THE TRAVELING PANTS", "has_genre", "DRAMA" ], [ "THE SISTERHOOD OF THE TRAVELING PANTS", "release_year", "2005" ], [ "THE SQUID AND THE WHALE", "has_genre", "DRAMA" ], [ "THE SQUID AND THE WHALE", "has_tags", "DRAMA" ], [ "THE SQUID AND THE WHALE", "release_year", "2005" ], [ "THE SUN", "has_genre", "DRAMA" ], [ "THE SUN", "release_year", "2005" ], [ "THE THING ABOUT MY FOLKS", "has_genre", "DRAMA" ], [ "THE THING ABOUT MY FOLKS", "release_year", "2005" ], [ "THE TRACEY FRAGMENTS", "has_genre", "DRAMA" ], [ "THE TRACEY FRAGMENTS", "release_year", "2007" ], [ "THE TRACEY FRAGMENTS", "written_by", "MAUREEN MEDVED" ], [ "THE UPSIDE OF ANGER", "has_genre", "DRAMA" ], [ "THE UPSIDE OF ANGER", "release_year", "2005" ], [ "THE VIOLIN", "has_genre", "DRAMA" ], [ "THE VIOLIN", "release_year", "2005" ], [ "THE WAR WITHIN", "has_genre", "DRAMA" ], [ "THE WAR WITHIN", "release_year", "2005" ], [ "THE WEATHER MAN", "has_genre", "DRAMA" ], [ "THE WEATHER MAN", "release_year", "2005" ], [ "THE WHITE COUNTESS", "has_genre", "DRAMA" ], [ "THE WHITE COUNTESS", "release_year", "2005" ], [ "THUMBSUCKER", "has_genre", "DRAMA" ], [ "THUMBSUCKER", "release_year", "2005" ], [ "TICKETS", "has_genre", "DRAMA" ], [ "TICKETS", "release_year", "2005" ], [ "TO GILLIAN ON HER 37TH BIRTHDAY", "has_genre", "DRAMA" ], [ "TO GILLIAN ON HER 37TH BIRTHDAY", "starred_actors", "CLAIRE DANES" ], [ "TO PAINT OR MAKE LOVE", "has_genre", "DRAMA" ], [ "TO PAINT OR MAKE LOVE", "release_year", "2005" ], [ "TRANSAMERICA", "has_genre", "DRAMA" ], [ "TRANSAMERICA", "release_year", "2005" ], [ "TWO FOR THE MONEY", "has_genre", "DRAMA" ], [ "TWO FOR THE MONEY", "release_year", "2005" ], [ "WAH-WAH", "has_genre", "DRAMA" ], [ "WAH-WAH", "release_year", "2005" ], [ "WALK THE LINE", "has_genre", "DRAMA" ], [ "WALK THE LINE", "release_year", "2005" ], [ "WHAT IS IT?", "has_genre", "DRAMA" ], [ "WHAT IS IT?", "release_year", "2005" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 31486, 1970 38751, CHRISTOPHER LEE 20884, COUNT DRACULA 15064, EQUINOX 12336, MATTHEW MODINE 33746, SCARS OF DRACULA 26987, TASTE THE BLOOD OF DRACULA 5903, THE BLOOD OF FU MANCHU 22053, THE REAL BLONDE 21526, TRIBES src, edge_attr, dst 20884, has_tags, 38751 20884, release_year, 31486 20884, starred_actors, 38751 15064, release_year, 31486 15064, starred_actors, 12336 33746, release_year, 31486 33746, starred_actors, 38751 26987, has_tags, 38751 26987, release_year, 31486 26987, starred_actors, 38751 5903, starred_actors, 38751 22053, starred_actors, 12336 21526, release_year, 31486 Question: For what reason are THE BLOOD OF FU MANCHU, THE REAL BLONDE, and TRIBES associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "THE BLOOD OF FU MANCHU", "THE REAL BLONDE", "TRIBES" ], "valid_edges": [ [ "COUNT DRACULA", "has_tags", "CHRISTOPHER LEE" ], [ "COUNT DRACULA", "release_year", "1970" ], [ "COUNT DRACULA", "starred_actors", "CHRISTOPHER LEE" ], [ "EQUINOX", "release_year", "1970" ], [ "EQUINOX", "starred_actors", "MATTHEW MODINE" ], [ "SCARS OF DRACULA", "release_year", "1970" ], [ "SCARS OF DRACULA", "starred_actors", "CHRISTOPHER LEE" ], [ "TASTE THE BLOOD OF DRACULA", "has_tags", "CHRISTOPHER LEE" ], [ "TASTE THE BLOOD OF DRACULA", "release_year", "1970" ], [ "TASTE THE BLOOD OF DRACULA", "starred_actors", "CHRISTOPHER LEE" ], [ "THE BLOOD OF FU MANCHU", "starred_actors", "CHRISTOPHER LEE" ], [ "THE REAL BLONDE", "starred_actors", "MATTHEW MODINE" ], [ "TRIBES", "release_year", "1970" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 21775, 06/05 37484, 2004 30265, BRAZIL 6852, CHEECH MARIN 40091, CONTROL ROOM 31783, ENGLISH 19728, EVILENKO 24815, GOING THE DISTANCE 3285, IN MY COUNTRY 15150, KAMIKAZE GIRLS 30600, LADIES IN LAVENDER 2410, MACHETE 10198, MACHUCA 39135, REACHING FOR THE MOON 38241, RING OF DARKNESS 17979, ROBERT DE NIRO 32465, THE FOOTBALL FACTORY 4420, THE HUNTING OF THE PRESIDENT 32925, THE LIFE AND DEATH OF PETER SELLERS 22880, THE MACHINIST 38433, THE MERCHANT OF VENICE 22654, THREE WAY 23737, WALK ON WATER src, edge_attr, dst 21775, in_language, 31783 21775, release_year, 37484 30265, has_tags, 17979 30265, starred_actors, 17979 40091, in_language, 31783 40091, release_year, 37484 19728, in_language, 31783 19728, release_year, 37484 24815, in_language, 31783 24815, release_year, 37484 3285, in_language, 31783 3285, release_year, 37484 15150, in_language, 31783 15150, release_year, 37484 30600, in_language, 31783 30600, release_year, 37484 2410, has_tags, 6852 2410, has_tags, 17979 2410, starred_actors, 17979 10198, in_language, 31783 10198, release_year, 37484 39135, has_tags, 30265 39135, in_language, 31783 38241, in_language, 31783 38241, release_year, 37484 32465, in_language, 31783 32465, release_year, 37484 4420, in_language, 31783 4420, release_year, 37484 32925, in_language, 31783 32925, release_year, 37484 22880, in_language, 31783 22880, release_year, 37484 38433, in_language, 31783 38433, release_year, 37484 22654, release_year, 37484 23737, in_language, 31783 23737, release_year, 37484 Question: In what context are CHEECH MARIN, REACHING FOR THE MOON, and THREE WAY connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CHEECH MARIN", "REACHING FOR THE MOON", "THREE WAY" ], "valid_edges": [ [ "06/05", "in_language", "ENGLISH" ], [ "06/05", "release_year", "2004" ], [ "BRAZIL", "has_tags", "ROBERT DE NIRO" ], [ "BRAZIL", "starred_actors", "ROBERT DE NIRO" ], [ "CONTROL ROOM", "in_language", "ENGLISH" ], [ "CONTROL ROOM", "release_year", "2004" ], [ "EVILENKO", "in_language", "ENGLISH" ], [ "EVILENKO", "release_year", "2004" ], [ "GOING THE DISTANCE", "in_language", "ENGLISH" ], [ "GOING THE DISTANCE", "release_year", "2004" ], [ "IN MY COUNTRY", "in_language", "ENGLISH" ], [ "IN MY COUNTRY", "release_year", "2004" ], [ "KAMIKAZE GIRLS", "in_language", "ENGLISH" ], [ "KAMIKAZE GIRLS", "release_year", "2004" ], [ "LADIES IN LAVENDER", "in_language", "ENGLISH" ], [ "LADIES IN LAVENDER", "release_year", "2004" ], [ "MACHETE", "has_tags", "CHEECH MARIN" ], [ "MACHETE", "has_tags", "ROBERT DE NIRO" ], [ "MACHETE", "starred_actors", "ROBERT DE NIRO" ], [ "MACHUCA", "in_language", "ENGLISH" ], [ "MACHUCA", "release_year", "2004" ], [ "REACHING FOR THE MOON", "has_tags", "BRAZIL" ], [ "REACHING FOR THE MOON", "in_language", "ENGLISH" ], [ "RING OF DARKNESS", "in_language", "ENGLISH" ], [ "RING OF DARKNESS", "release_year", "2004" ], [ "THE FOOTBALL FACTORY", "in_language", "ENGLISH" ], [ "THE FOOTBALL FACTORY", "release_year", "2004" ], [ "THE HUNTING OF THE PRESIDENT", "in_language", "ENGLISH" ], [ "THE HUNTING OF THE PRESIDENT", "release_year", "2004" ], [ "THE LIFE AND DEATH OF PETER SELLERS", "in_language", "ENGLISH" ], [ "THE LIFE AND DEATH OF PETER SELLERS", "release_year", "2004" ], [ "THE MACHINIST", "in_language", "ENGLISH" ], [ "THE MACHINIST", "release_year", "2004" ], [ "THE MERCHANT OF VENICE", "in_language", "ENGLISH" ], [ "THE MERCHANT OF VENICE", "release_year", "2004" ], [ "THREE WAY", "release_year", "2004" ], [ "WALK ON WATER", "in_language", "ENGLISH" ], [ "WALK ON WATER", "release_year", "2004" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26762, 2008 30247, AN EMPRESS AND THE WARRIORS 26260, BLUE SKY 17256, DONNIE YEN 36212, DRAMA 1498, ERMANNO OLMI 10121, IP MAN 38168, IP MAN 2 26301, MARTIAL ARTS 4738, RAMA LAURIE STAGNER 9970, TICKETS 27749, WALKING, WALKING 5052, WING CHUN src, edge_attr, dst 30247, has_genre, 36212 30247, release_year, 26762 30247, starred_actors, 17256 26260, has_genre, 36212 26260, written_by, 4738 10121, has_tags, 17256 10121, has_tags, 10121 10121, has_tags, 26301 10121, has_tags, 5052 10121, release_year, 26762 10121, starred_actors, 17256 38168, has_genre, 36212 38168, has_tags, 17256 38168, has_tags, 10121 38168, has_tags, 26301 38168, has_tags, 5052 38168, starred_actors, 17256 9970, directed_by, 1498 9970, has_genre, 36212 9970, has_tags, 1498 9970, written_by, 1498 27749, directed_by, 1498 27749, has_genre, 36212 27749, written_by, 1498 Question: How are DONNIE YEN, ERMANNO OLMI, and RAMA LAURIE STAGNER related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DONNIE YEN", "ERMANNO OLMI", "RAMA LAURIE STAGNER" ], "valid_edges": [ [ "AN EMPRESS AND THE WARRIORS", "has_genre", "DRAMA" ], [ "AN EMPRESS AND THE WARRIORS", "release_year", "2008" ], [ "AN EMPRESS AND THE WARRIORS", "starred_actors", "DONNIE YEN" ], [ "BLUE SKY", "has_genre", "DRAMA" ], [ "BLUE SKY", "written_by", "RAMA LAURIE STAGNER" ], [ "IP MAN", "has_tags", "DONNIE YEN" ], [ "IP MAN", "has_tags", "IP MAN" ], [ "IP MAN", "has_tags", "MARTIAL ARTS" ], [ "IP MAN", "has_tags", "WING CHUN" ], [ "IP MAN", "release_year", "2008" ], [ "IP MAN", "starred_actors", "DONNIE YEN" ], [ "IP MAN 2", "has_genre", "DRAMA" ], [ "IP MAN 2", "has_tags", "DONNIE YEN" ], [ "IP MAN 2", "has_tags", "IP MAN" ], [ "IP MAN 2", "has_tags", "MARTIAL ARTS" ], [ "IP MAN 2", "has_tags", "WING CHUN" ], [ "IP MAN 2", "starred_actors", "DONNIE YEN" ], [ "TICKETS", "directed_by", "ERMANNO OLMI" ], [ "TICKETS", "has_genre", "DRAMA" ], [ "TICKETS", "has_tags", "ERMANNO OLMI" ], [ "TICKETS", "written_by", "ERMANNO OLMI" ], [ "WALKING, WALKING", "directed_by", "ERMANNO OLMI" ], [ "WALKING, WALKING", "has_genre", "DRAMA" ], [ "WALKING, WALKING", "written_by", "ERMANNO OLMI" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26633, 1989 24438, 1993 1274, ADDAMS FAMILY VALUES 26799, BACK TO THE FUTURE PART II 28679, CANNIBAL WOMEN IN THE AVOCADO JUNGLE OF DEATH 23496, CHRISTOPHER LLOYD 23875, PIANO 3434, SHANNON TWEED 38878, THE DREAM TEAM 19496, THE PIANO 29852, THIRTY TWO SHORT FILMS ABOUT GLENN GOULD src, edge_attr, dst 1274, has_tags, 23496 1274, release_year, 24438 1274, starred_actors, 23496 26799, has_tags, 23496 26799, release_year, 26633 26799, starred_actors, 23496 28679, release_year, 26633 28679, starred_actors, 3434 38878, has_tags, 23496 38878, release_year, 26633 38878, starred_actors, 23496 19496, has_tags, 23875 19496, release_year, 24438 29852, has_tags, 23875 29852, release_year, 24438 Question: For what reason are CHRISTOPHER LLOYD, SHANNON TWEED, and THIRTY TWO SHORT FILMS ABOUT GLENN GOULD associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CHRISTOPHER LLOYD", "SHANNON TWEED", "THIRTY TWO SHORT FILMS ABOUT GLENN GOULD" ], "valid_edges": [ [ "ADDAMS FAMILY VALUES", "has_tags", "CHRISTOPHER LLOYD" ], [ "ADDAMS FAMILY VALUES", "release_year", "1993" ], [ "ADDAMS FAMILY VALUES", "starred_actors", "CHRISTOPHER LLOYD" ], [ "BACK TO THE FUTURE PART II", "has_tags", "CHRISTOPHER LLOYD" ], [ "BACK TO THE FUTURE PART II", "release_year", "1989" ], [ "BACK TO THE FUTURE PART II", "starred_actors", "CHRISTOPHER LLOYD" ], [ "CANNIBAL WOMEN IN THE AVOCADO JUNGLE OF DEATH", "release_year", "1989" ], [ "CANNIBAL WOMEN IN THE AVOCADO JUNGLE OF DEATH", "starred_actors", "SHANNON TWEED" ], [ "THE DREAM TEAM", "has_tags", "CHRISTOPHER LLOYD" ], [ "THE DREAM TEAM", "release_year", "1989" ], [ "THE DREAM TEAM", "starred_actors", "CHRISTOPHER LLOYD" ], [ "THE PIANO", "has_tags", "PIANO" ], [ "THE PIANO", "release_year", "1993" ], [ "THIRTY TWO SHORT FILMS ABOUT GLENN GOULD", "has_tags", "PIANO" ], [ "THIRTY TWO SHORT FILMS ABOUT GLENN GOULD", "release_year", "1993" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24438, 1993 28293, AMMA ASANTE 23223, BELLE 4847, BOXING HELENA 8003, CALAMARI UNION 30463, COMEDY 36212, DRAMA 11065, FATAL INSTINCT 109, JUST WRITE 33442, KARI HEISKANEN 19787, SHERILYN FENN 20345, THE SCENESTERS 24929, THREE OF HEARTS src, edge_attr, dst 23223, directed_by, 28293 23223, has_genre, 36212 4847, has_genre, 36212 4847, release_year, 24438 4847, starred_actors, 19787 8003, has_genre, 30463 8003, has_tags, 30463 8003, starred_actors, 33442 11065, has_genre, 30463 11065, release_year, 24438 11065, starred_actors, 19787 109, has_genre, 30463 109, starred_actors, 19787 20345, has_genre, 30463 20345, starred_actors, 19787 24929, has_genre, 30463 24929, release_year, 24438 24929, starred_actors, 19787 Question: For what reason are AMMA ASANTE, KARI HEISKANEN, and SHERILYN FENN associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "AMMA ASANTE", "KARI HEISKANEN", "SHERILYN FENN" ], "valid_edges": [ [ "BELLE", "directed_by", "AMMA ASANTE" ], [ "BELLE", "has_genre", "DRAMA" ], [ "BOXING HELENA", "has_genre", "DRAMA" ], [ "BOXING HELENA", "release_year", "1993" ], [ "BOXING HELENA", "starred_actors", "SHERILYN FENN" ], [ "CALAMARI UNION", "has_genre", "COMEDY" ], [ "CALAMARI UNION", "has_tags", "COMEDY" ], [ "CALAMARI UNION", "starred_actors", "KARI HEISKANEN" ], [ "FATAL INSTINCT", "has_genre", "COMEDY" ], [ "FATAL INSTINCT", "release_year", "1993" ], [ "FATAL INSTINCT", "starred_actors", "SHERILYN FENN" ], [ "JUST WRITE", "has_genre", "COMEDY" ], [ "JUST WRITE", "starred_actors", "SHERILYN FENN" ], [ "THE SCENESTERS", "has_genre", "COMEDY" ], [ "THE SCENESTERS", "starred_actors", "SHERILYN FENN" ], [ "THREE OF HEARTS", "has_genre", "COMEDY" ], [ "THREE OF HEARTS", "release_year", "1993" ], [ "THREE OF HEARTS", "starred_actors", "SHERILYN FENN" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6776, 2000 30463, COMEDY 6012, FRENCH 15972, JIRA MALIGOOL 39509, MARCEL PAGNOL 8234, THE BAKER'S WIFE 15575, THE IRON LADIES 13003, THE WELL-DIGGER'S DAUGHTER 23886, THE WOG BOY 10434, VINCE COLOSIMO src, edge_attr, dst 8234, directed_by, 39509 8234, has_genre, 30463 8234, has_tags, 39509 8234, in_language, 6012 15575, has_genre, 30463 15575, release_year, 6776 15575, written_by, 15972 13003, directed_by, 39509 13003, has_genre, 30463 13003, has_tags, 39509 13003, in_language, 6012 13003, written_by, 39509 23886, has_genre, 30463 23886, release_year, 6776 23886, starred_actors, 10434 Question: How are JIRA MALIGOOL, MARCEL PAGNOL, and VINCE COLOSIMO related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JIRA MALIGOOL", "MARCEL PAGNOL", "VINCE COLOSIMO" ], "valid_edges": [ [ "THE BAKER'S WIFE", "directed_by", "MARCEL PAGNOL" ], [ "THE BAKER'S WIFE", "has_genre", "COMEDY" ], [ "THE BAKER'S WIFE", "has_tags", "MARCEL PAGNOL" ], [ "THE BAKER'S WIFE", "in_language", "FRENCH" ], [ "THE IRON LADIES", "has_genre", "COMEDY" ], [ "THE IRON LADIES", "release_year", "2000" ], [ "THE IRON LADIES", "written_by", "JIRA MALIGOOL" ], [ "THE WELL-DIGGER'S DAUGHTER", "directed_by", "MARCEL PAGNOL" ], [ "THE WELL-DIGGER'S DAUGHTER", "has_genre", "COMEDY" ], [ "THE WELL-DIGGER'S DAUGHTER", "has_tags", "MARCEL PAGNOL" ], [ "THE WELL-DIGGER'S DAUGHTER", "in_language", "FRENCH" ], [ "THE WELL-DIGGER'S DAUGHTER", "written_by", "MARCEL PAGNOL" ], [ "THE WOG BOY", "has_genre", "COMEDY" ], [ "THE WOG BOY", "release_year", "2000" ], [ "THE WOG BOY", "starred_actors", "VINCE COLOSIMO" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26423, 1950 6216, 1952 39624, 1957 27810, 1968 1006, 1996 13999, ANDREW V. MCLAGLEN 5661, ANTHONY MANN 35990, ARTHUR KENNEDY 4816, BANDOLERO! 3204, BEND OF THE RIVER 16749, BROKEN ARROW 29246, CARBINE WILLIAMS 14087, COMES A HORSEMAN 7159, DESTRY RIDES AGAIN 8406, FIRECREEK 36979, GINA BELLMAN 34477, HARVEY 34149, HENRY FONDA 7736, JAMES STEWART 13255, JOHN FORD 36999, MAUREEN O'HARA 20920, MR. HOBBS TAKES A VACATION 37497, NATIONAL FILM REGISTRY 35223, NIGHT PASSAGE 9638, ON OUR MERRY WAY 7098, SHENANDOAH 38066, SHIRLEY JONES 24498, SILENT TRIGGER 26381, STRATEGIC AIR COMMAND 7763, THE CHEYENNE SOCIAL CLUB 27995, THE FAR COUNTRY 26752, THE GLENN MILLER STORY 17394, THE MAN FROM LARAMIE 36235, THE MAN WHO SHOT LIBERTY VALANCE 39232, THE NAKED SPUR 2555, THE RARE BREED 31357, THE SHOOTIST 935, THE SPIRIT OF ST. LOUIS 32490, THUNDER BAY 37207, TWO RODE TOGETHER 36026, WESTERN 26441, WINCHESTER '73 src, edge_attr, dst 4816, directed_by, 13999 4816, release_year, 27810 4816, starred_actors, 7736 3204, directed_by, 5661 3204, has_genre, 36026 3204, has_tags, 5661 3204, has_tags, 7736 3204, release_year, 6216 3204, starred_actors, 35990 3204, starred_actors, 7736 16749, has_genre, 36026 16749, release_year, 26423 16749, release_year, 1006 16749, starred_actors, 7736 29246, release_year, 6216 29246, starred_actors, 7736 14087, has_genre, 36026 7159, has_genre, 36026 7159, has_tags, 7736 7159, has_tags, 37497 7159, starred_actors, 7736 8406, has_genre, 36026 8406, release_year, 27810 8406, starred_actors, 34149 8406, starred_actors, 7736 34477, has_tags, 7736 34477, release_year, 26423 34477, release_year, 1006 34477, starred_actors, 7736 20920, starred_actors, 7736 20920, starred_actors, 36999 35223, has_genre, 36026 35223, release_year, 39624 35223, starred_actors, 7736 9638, starred_actors, 34149 9638, starred_actors, 7736 7098, directed_by, 13999 7098, has_tags, 13999 7098, has_tags, 7736 7098, starred_actors, 7736 24498, release_year, 1006 24498, starred_actors, 36979 26381, directed_by, 5661 26381, starred_actors, 7736 7763, has_genre, 36026 7763, starred_actors, 34149 7763, starred_actors, 7736 7763, starred_actors, 38066 27995, directed_by, 5661 27995, has_tags, 5661 27995, starred_actors, 7736 26752, directed_by, 5661 26752, has_tags, 5661 26752, has_tags, 7736 26752, starred_actors, 7736 17394, directed_by, 5661 17394, has_genre, 36026 17394, has_tags, 5661 17394, starred_actors, 35990 17394, starred_actors, 7736 36235, directed_by, 13255 36235, has_genre, 36026 36235, has_tags, 7736 36235, has_tags, 13255 36235, has_tags, 37497 36235, has_tags, 36026 36235, starred_actors, 7736 39232, directed_by, 5661 39232, has_genre, 36026 39232, has_tags, 5661 39232, has_tags, 7736 39232, starred_actors, 7736 2555, directed_by, 13999 2555, has_genre, 36026 2555, starred_actors, 7736 2555, starred_actors, 36999 31357, has_genre, 36026 31357, starred_actors, 7736 935, release_year, 39624 935, starred_actors, 7736 32490, directed_by, 5661 32490, starred_actors, 7736 37207, directed_by, 13255 37207, has_genre, 36026 37207, starred_actors, 7736 37207, starred_actors, 38066 26441, directed_by, 5661 26441, has_genre, 36026 26441, has_tags, 5661 26441, release_year, 26423 26441, starred_actors, 7736 Question: For what reason are COMES A HORSEMAN, GINA BELLMAN, and JAMES STEWART associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "COMES A HORSEMAN", "GINA BELLMAN", "JAMES STEWART" ], "valid_edges": [ [ "BANDOLERO!", "directed_by", "ANDREW V. MCLAGLEN" ], [ "BANDOLERO!", "release_year", "1968" ], [ "BANDOLERO!", "starred_actors", "JAMES STEWART" ], [ "BEND OF THE RIVER", "directed_by", "ANTHONY MANN" ], [ "BEND OF THE RIVER", "has_genre", "WESTERN" ], [ "BEND OF THE RIVER", "has_tags", "ANTHONY MANN" ], [ "BEND OF THE RIVER", "has_tags", "JAMES STEWART" ], [ "BEND OF THE RIVER", "release_year", "1952" ], [ "BEND OF THE RIVER", "starred_actors", "ARTHUR KENNEDY" ], [ "BEND OF THE RIVER", "starred_actors", "JAMES STEWART" ], [ "BROKEN ARROW", "has_genre", "WESTERN" ], [ "BROKEN ARROW", "release_year", "1950" ], [ "BROKEN ARROW", "release_year", "1996" ], [ "BROKEN ARROW", "starred_actors", "JAMES STEWART" ], [ "CARBINE WILLIAMS", "release_year", "1952" ], [ "CARBINE WILLIAMS", "starred_actors", "JAMES STEWART" ], [ "COMES A HORSEMAN", "has_genre", "WESTERN" ], [ "DESTRY RIDES AGAIN", "has_genre", "WESTERN" ], [ "DESTRY RIDES AGAIN", "has_tags", "JAMES STEWART" ], [ "DESTRY RIDES AGAIN", "has_tags", "NATIONAL FILM REGISTRY" ], [ "DESTRY RIDES AGAIN", "starred_actors", "JAMES STEWART" ], [ "FIRECREEK", "has_genre", "WESTERN" ], [ "FIRECREEK", "release_year", "1968" ], [ "FIRECREEK", "starred_actors", "HENRY FONDA" ], [ "FIRECREEK", "starred_actors", "JAMES STEWART" ], [ "HARVEY", "has_tags", "JAMES STEWART" ], [ "HARVEY", "release_year", "1950" ], [ "HARVEY", "release_year", "1996" ], [ "HARVEY", "starred_actors", "JAMES STEWART" ], [ "MR. HOBBS TAKES A VACATION", "starred_actors", "JAMES STEWART" ], [ "MR. HOBBS TAKES A VACATION", "starred_actors", "MAUREEN O'HARA" ], [ "NIGHT PASSAGE", "has_genre", "WESTERN" ], [ "NIGHT PASSAGE", "release_year", "1957" ], [ "NIGHT PASSAGE", "starred_actors", "JAMES STEWART" ], [ "ON OUR MERRY WAY", "starred_actors", "HENRY FONDA" ], [ "ON OUR MERRY WAY", "starred_actors", "JAMES STEWART" ], [ "SHENANDOAH", "directed_by", "ANDREW V. MCLAGLEN" ], [ "SHENANDOAH", "has_tags", "ANDREW V. MCLAGLEN" ], [ "SHENANDOAH", "has_tags", "JAMES STEWART" ], [ "SHENANDOAH", "starred_actors", "JAMES STEWART" ], [ "SILENT TRIGGER", "release_year", "1996" ], [ "SILENT TRIGGER", "starred_actors", "GINA BELLMAN" ], [ "STRATEGIC AIR COMMAND", "directed_by", "ANTHONY MANN" ], [ "STRATEGIC AIR COMMAND", "starred_actors", "JAMES STEWART" ], [ "THE CHEYENNE SOCIAL CLUB", "has_genre", "WESTERN" ], [ "THE CHEYENNE SOCIAL CLUB", "starred_actors", "HENRY FONDA" ], [ "THE CHEYENNE SOCIAL CLUB", "starred_actors", "JAMES STEWART" ], [ "THE CHEYENNE SOCIAL CLUB", "starred_actors", "SHIRLEY JONES" ], [ "THE FAR COUNTRY", "directed_by", "ANTHONY MANN" ], [ "THE FAR COUNTRY", "has_tags", "ANTHONY MANN" ], [ "THE FAR COUNTRY", "starred_actors", "JAMES STEWART" ], [ "THE GLENN MILLER STORY", "directed_by", "ANTHONY MANN" ], [ "THE GLENN MILLER STORY", "has_tags", "ANTHONY MANN" ], [ "THE GLENN MILLER STORY", "has_tags", "JAMES STEWART" ], [ "THE GLENN MILLER STORY", "starred_actors", "JAMES STEWART" ], [ "THE MAN FROM LARAMIE", "directed_by", "ANTHONY MANN" ], [ "THE MAN FROM LARAMIE", "has_genre", "WESTERN" ], [ "THE MAN FROM LARAMIE", "has_tags", "ANTHONY MANN" ], [ "THE MAN FROM LARAMIE", "starred_actors", "ARTHUR KENNEDY" ], [ "THE MAN FROM LARAMIE", "starred_actors", "JAMES STEWART" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "directed_by", "JOHN FORD" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_genre", "WESTERN" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "JAMES STEWART" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "JOHN FORD" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "WESTERN" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "starred_actors", "JAMES STEWART" ], [ "THE NAKED SPUR", "directed_by", "ANTHONY MANN" ], [ "THE NAKED SPUR", "has_genre", "WESTERN" ], [ "THE NAKED SPUR", "has_tags", "ANTHONY MANN" ], [ "THE NAKED SPUR", "has_tags", "JAMES STEWART" ], [ "THE NAKED SPUR", "starred_actors", "JAMES STEWART" ], [ "THE RARE BREED", "directed_by", "ANDREW V. MCLAGLEN" ], [ "THE RARE BREED", "has_genre", "WESTERN" ], [ "THE RARE BREED", "starred_actors", "JAMES STEWART" ], [ "THE RARE BREED", "starred_actors", "MAUREEN O'HARA" ], [ "THE SHOOTIST", "has_genre", "WESTERN" ], [ "THE SHOOTIST", "starred_actors", "JAMES STEWART" ], [ "THE SPIRIT OF ST. LOUIS", "release_year", "1957" ], [ "THE SPIRIT OF ST. LOUIS", "starred_actors", "JAMES STEWART" ], [ "THUNDER BAY", "directed_by", "ANTHONY MANN" ], [ "THUNDER BAY", "starred_actors", "JAMES STEWART" ], [ "TWO RODE TOGETHER", "directed_by", "JOHN FORD" ], [ "TWO RODE TOGETHER", "has_genre", "WESTERN" ], [ "TWO RODE TOGETHER", "starred_actors", "JAMES STEWART" ], [ "TWO RODE TOGETHER", "starred_actors", "SHIRLEY JONES" ], [ "WINCHESTER '73", "directed_by", "ANTHONY MANN" ], [ "WINCHESTER '73", "has_genre", "WESTERN" ], [ "WINCHESTER '73", "has_tags", "ANTHONY MANN" ], [ "WINCHESTER '73", "release_year", "1950" ], [ "WINCHESTER '73", "starred_actors", "JAMES STEWART" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 38097, 1985 13408, 2001 31672, A.K. 17638, BRIEF CROSSING 38311, CHAOS 36073, FAT GIRL 6012, FRENCH 35881, GIRLS JUST WANT TO HAVE FUN 2004, JOSEF VON STERNBERG 25785, KISS OF THE DRAGON 26375, MARLENE DIETRICH 1422, MOROCCO 29620, POLICE 27191, RENDEZ-VOUS 8379, ROMANCE 11723, SHOAH 39270, SUBWAY 28368, THE DEVIL IS A WOMAN 35826, THE PEANUT BUTTER SOLUTION 39469, THE PORNOGRAPHER 12294, VAGABOND 29077, WASABI 19257, WINGED MIGRATION src, edge_attr, dst 31672, in_language, 6012 31672, release_year, 38097 17638, in_language, 6012 17638, release_year, 13408 38311, in_language, 6012 38311, release_year, 13408 36073, in_language, 6012 36073, release_year, 13408 35881, release_year, 38097 25785, in_language, 6012 25785, release_year, 13408 1422, directed_by, 2004 1422, has_genre, 8379 1422, has_tags, 2004 1422, has_tags, 26375 1422, starred_actors, 26375 29620, in_language, 6012 29620, release_year, 38097 27191, in_language, 6012 27191, release_year, 38097 8379, in_language, 6012 11723, in_language, 6012 11723, release_year, 38097 39270, in_language, 6012 39270, release_year, 38097 28368, directed_by, 2004 28368, has_genre, 8379 28368, has_tags, 2004 28368, starred_actors, 26375 35826, in_language, 6012 35826, release_year, 38097 39469, in_language, 6012 39469, release_year, 13408 12294, in_language, 6012 12294, release_year, 38097 29077, in_language, 6012 29077, release_year, 13408 19257, in_language, 6012 19257, release_year, 13408 Question: For what reason are GIRLS JUST WANT TO HAVE FUN, JOSEF VON STERNBERG, and THE PORNOGRAPHER associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "GIRLS JUST WANT TO HAVE FUN", "JOSEF VON STERNBERG", "THE PORNOGRAPHER" ], "valid_edges": [ [ "A.K.", "in_language", "FRENCH" ], [ "A.K.", "release_year", "1985" ], [ "BRIEF CROSSING", "in_language", "FRENCH" ], [ "BRIEF CROSSING", "release_year", "2001" ], [ "CHAOS", "in_language", "FRENCH" ], [ "CHAOS", "release_year", "2001" ], [ "FAT GIRL", "in_language", "FRENCH" ], [ "FAT GIRL", "release_year", "2001" ], [ "GIRLS JUST WANT TO HAVE FUN", "release_year", "1985" ], [ "KISS OF THE DRAGON", "in_language", "FRENCH" ], [ "KISS OF THE DRAGON", "release_year", "2001" ], [ "MOROCCO", "directed_by", "JOSEF VON STERNBERG" ], [ "MOROCCO", "has_genre", "ROMANCE" ], [ "MOROCCO", "has_tags", "JOSEF VON STERNBERG" ], [ "MOROCCO", "has_tags", "MARLENE DIETRICH" ], [ "MOROCCO", "starred_actors", "MARLENE DIETRICH" ], [ "POLICE", "in_language", "FRENCH" ], [ "POLICE", "release_year", "1985" ], [ "RENDEZ-VOUS", "in_language", "FRENCH" ], [ "RENDEZ-VOUS", "release_year", "1985" ], [ "ROMANCE", "in_language", "FRENCH" ], [ "SHOAH", "in_language", "FRENCH" ], [ "SHOAH", "release_year", "1985" ], [ "SUBWAY", "in_language", "FRENCH" ], [ "SUBWAY", "release_year", "1985" ], [ "THE DEVIL IS A WOMAN", "directed_by", "JOSEF VON STERNBERG" ], [ "THE DEVIL IS A WOMAN", "has_genre", "ROMANCE" ], [ "THE DEVIL IS A WOMAN", "has_tags", "JOSEF VON STERNBERG" ], [ "THE DEVIL IS A WOMAN", "starred_actors", "MARLENE DIETRICH" ], [ "THE PEANUT BUTTER SOLUTION", "in_language", "FRENCH" ], [ "THE PEANUT BUTTER SOLUTION", "release_year", "1985" ], [ "THE PORNOGRAPHER", "in_language", "FRENCH" ], [ "THE PORNOGRAPHER", "release_year", "2001" ], [ "VAGABOND", "in_language", "FRENCH" ], [ "VAGABOND", "release_year", "1985" ], [ "WASABI", "in_language", "FRENCH" ], [ "WASABI", "release_year", "2001" ], [ "WINGED MIGRATION", "in_language", "FRENCH" ], [ "WINGED MIGRATION", "release_year", "2001" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26277, A FEW GOOD MEN 15184, AARON SORKIN 3522, ANTI-SEMITISM 32020, DANIELA SILVERIO 36212, DRAMA 31621, GENTLEMAN'S AGREEMENT 37734, IDENTIFICATION OF A WOMAN 30221, LAW 5106, THE SOCIAL NETWORK src, edge_attr, dst 26277, has_genre, 36212 26277, has_tags, 15184 26277, has_tags, 36212 26277, has_tags, 30221 26277, written_by, 15184 31621, has_genre, 36212 31621, has_tags, 3522 37734, has_genre, 36212 37734, starred_actors, 32020 5106, has_genre, 36212 5106, has_tags, 15184 5106, has_tags, 30221 5106, written_by, 15184 Question: For what reason are ANTI-SEMITISM, DANIELA SILVERIO, and LAW associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ANTI-SEMITISM", "DANIELA SILVERIO", "LAW" ], "valid_edges": [ [ "A FEW GOOD MEN", "has_genre", "DRAMA" ], [ "A FEW GOOD MEN", "has_tags", "AARON SORKIN" ], [ "A FEW GOOD MEN", "has_tags", "DRAMA" ], [ "A FEW GOOD MEN", "has_tags", "LAW" ], [ "A FEW GOOD MEN", "written_by", "AARON SORKIN" ], [ "GENTLEMAN'S AGREEMENT", "has_genre", "DRAMA" ], [ "GENTLEMAN'S AGREEMENT", "has_tags", "ANTI-SEMITISM" ], [ "IDENTIFICATION OF A WOMAN", "has_genre", "DRAMA" ], [ "IDENTIFICATION OF A WOMAN", "starred_actors", "DANIELA SILVERIO" ], [ "THE SOCIAL NETWORK", "has_genre", "DRAMA" ], [ "THE SOCIAL NETWORK", "has_tags", "AARON SORKIN" ], [ "THE SOCIAL NETWORK", "has_tags", "LAW" ], [ "THE SOCIAL NETWORK", "written_by", "AARON SORKIN" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 32857, ALLISON ANDERS 10045, BD-R 6399, BORDER RADIO 16659, CASINO ROYALE 3138, CHRISTOPHER MELONI 30463, COMEDY 15796, DANIEL CRAIG 36212, DRAMA 18387, FLASHBACKS OF A FOOL 20761, FOUR ROOMS 13081, R 16954, SYLVIA 38039, THE DIARY OF A TEENAGE GIRL 7240, THE GIRL WITH THE DRAGON TATTOO src, edge_attr, dst 6399, directed_by, 32857 6399, has_tags, 32857 6399, has_tags, 10045 6399, written_by, 32857 16659, has_genre, 30463 16659, has_tags, 10045 16659, has_tags, 15796 16659, starred_actors, 15796 18387, has_genre, 36212 18387, has_tags, 13081 18387, starred_actors, 15796 20761, directed_by, 32857 20761, has_genre, 30463 20761, has_tags, 32857 20761, has_tags, 30463 20761, written_by, 32857 16954, has_genre, 36212 16954, has_tags, 15796 16954, starred_actors, 15796 38039, has_genre, 36212 38039, starred_actors, 3138 7240, has_genre, 36212 7240, has_tags, 15796 7240, has_tags, 13081 7240, starred_actors, 15796 Question: For what reason are ALLISON ANDERS, CHRISTOPHER MELONI, and DANIEL CRAIG associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ALLISON ANDERS", "CHRISTOPHER MELONI", "DANIEL CRAIG" ], "valid_edges": [ [ "BORDER RADIO", "directed_by", "ALLISON ANDERS" ], [ "BORDER RADIO", "has_tags", "ALLISON ANDERS" ], [ "BORDER RADIO", "has_tags", "BD-R" ], [ "BORDER RADIO", "written_by", "ALLISON ANDERS" ], [ "CASINO ROYALE", "has_genre", "COMEDY" ], [ "CASINO ROYALE", "has_tags", "BD-R" ], [ "CASINO ROYALE", "has_tags", "DANIEL CRAIG" ], [ "CASINO ROYALE", "starred_actors", "DANIEL CRAIG" ], [ "FLASHBACKS OF A FOOL", "has_genre", "DRAMA" ], [ "FLASHBACKS OF A FOOL", "has_tags", "R" ], [ "FLASHBACKS OF A FOOL", "starred_actors", "DANIEL CRAIG" ], [ "FOUR ROOMS", "directed_by", "ALLISON ANDERS" ], [ "FOUR ROOMS", "has_genre", "COMEDY" ], [ "FOUR ROOMS", "has_tags", "ALLISON ANDERS" ], [ "FOUR ROOMS", "has_tags", "COMEDY" ], [ "FOUR ROOMS", "written_by", "ALLISON ANDERS" ], [ "SYLVIA", "has_genre", "DRAMA" ], [ "SYLVIA", "has_tags", "DANIEL CRAIG" ], [ "SYLVIA", "starred_actors", "DANIEL CRAIG" ], [ "THE DIARY OF A TEENAGE GIRL", "has_genre", "DRAMA" ], [ "THE DIARY OF A TEENAGE GIRL", "starred_actors", "CHRISTOPHER MELONI" ], [ "THE GIRL WITH THE DRAGON TATTOO", "has_genre", "DRAMA" ], [ "THE GIRL WITH THE DRAGON TATTOO", "has_tags", "DANIEL CRAIG" ], [ "THE GIRL WITH THE DRAGON TATTOO", "has_tags", "R" ], [ "THE GIRL WITH THE DRAGON TATTOO", "starred_actors", "DANIEL CRAIG" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 25221, 1981 22892, GORY 29418, JEREMY IRONS 27927, LOU BRESLOW 22845, MUSIC 9638, ON OUR MERRY WAY 22714, OWN 6630, THE EVIL DEAD 25206, THE FRENCH LIEUTENANT'S WOMAN 14478, THE LION KING 38433, THE MERCHANT OF VENICE src, edge_attr, dst 9638, has_genre, 22845 9638, written_by, 27927 6630, has_tags, 22892 6630, has_tags, 22714 6630, release_year, 25221 25206, has_tags, 29418 25206, release_year, 25221 25206, starred_actors, 29418 14478, has_tags, 29418 14478, has_tags, 22845 14478, has_tags, 22714 14478, starred_actors, 29418 38433, has_tags, 22714 38433, starred_actors, 29418 Question: In what context are GORY, JEREMY IRONS, and LOU BRESLOW connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "GORY", "JEREMY IRONS", "LOU BRESLOW" ], "valid_edges": [ [ "ON OUR MERRY WAY", "has_genre", "MUSIC" ], [ "ON OUR MERRY WAY", "written_by", "LOU BRESLOW" ], [ "THE EVIL DEAD", "has_tags", "GORY" ], [ "THE EVIL DEAD", "has_tags", "OWN" ], [ "THE EVIL DEAD", "release_year", "1981" ], [ "THE FRENCH LIEUTENANT'S WOMAN", "has_tags", "JEREMY IRONS" ], [ "THE FRENCH LIEUTENANT'S WOMAN", "release_year", "1981" ], [ "THE FRENCH LIEUTENANT'S WOMAN", "starred_actors", "JEREMY IRONS" ], [ "THE LION KING", "has_tags", "JEREMY IRONS" ], [ "THE LION KING", "has_tags", "MUSIC" ], [ "THE LION KING", "has_tags", "OWN" ], [ "THE LION KING", "starred_actors", "JEREMY IRONS" ], [ "THE MERCHANT OF VENICE", "has_tags", "OWN" ], [ "THE MERCHANT OF VENICE", "starred_actors", "JEREMY IRONS" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26423, 1950 37224, 1990 859, ACTORS 37068, ALFRED E. GREEN 23277, DAYS OF THUNDER 35304, NASCAR 3317, THE JACKIE ROBINSON STORY 1341, TREASURE ISLAND src, edge_attr, dst 23277, has_tags, 35304 23277, release_year, 37224 3317, directed_by, 37068 3317, release_year, 26423 1341, has_tags, 859 1341, release_year, 26423 1341, release_year, 37224 Question: How are ACTORS, ALFRED E. GREEN, and NASCAR related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ACTORS", "ALFRED E. GREEN", "NASCAR" ], "valid_edges": [ [ "DAYS OF THUNDER", "has_tags", "NASCAR" ], [ "DAYS OF THUNDER", "release_year", "1990" ], [ "THE JACKIE ROBINSON STORY", "directed_by", "ALFRED E. GREEN" ], [ "THE JACKIE ROBINSON STORY", "release_year", "1950" ], [ "TREASURE ISLAND", "has_tags", "ACTORS" ], [ "TREASURE ISLAND", "release_year", "1950" ], [ "TREASURE ISLAND", "release_year", "1990" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39435, 1975 3807, FASCISM 16200, ITALIAN 15549, JEFFREY KRAMER 19396, ROMANO MIGLIORINI 39117, SALÒ, OR THE 120 DAYS OF SODOM 1045, SMILE 18637, THE INGLORIOUS BASTARDS src, edge_attr, dst 39117, has_tags, 3807 39117, in_language, 16200 39117, release_year, 39435 1045, directed_by, 15549 1045, release_year, 39435 1045, written_by, 15549 18637, in_language, 16200 18637, written_by, 19396 Question: For what reason are FASCISM, JEFFREY KRAMER, and ROMANO MIGLIORINI associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "FASCISM", "JEFFREY KRAMER", "ROMANO MIGLIORINI" ], "valid_edges": [ [ "SALÒ, OR THE 120 DAYS OF SODOM", "has_tags", "FASCISM" ], [ "SALÒ, OR THE 120 DAYS OF SODOM", "in_language", "ITALIAN" ], [ "SALÒ, OR THE 120 DAYS OF SODOM", "release_year", "1975" ], [ "SMILE", "directed_by", "JEFFREY KRAMER" ], [ "SMILE", "release_year", "1975" ], [ "SMILE", "written_by", "JEFFREY KRAMER" ], [ "THE INGLORIOUS BASTARDS", "in_language", "ITALIAN" ], [ "THE INGLORIOUS BASTARDS", "written_by", "ROMANO MIGLIORINI" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35845, 2006 27261, 2009 1912, BEYOND ALL BOUNDARIES 4197, BLUEBEARD 6283, CARGO 37236, EDWARD DMYTRYK 14735, FINAL DESTINATION 3 24481, FRANCHISE 22215, FRIDAY THE 13TH 15753, HALLOWEEN II 28852, HANNAH FREE 6780, INTO THE STORM 3942, SALVAGE 5812, SAW III 180, SAW VI 9228, SCARY MOVIE 4 34989, STAR TREK 23472, TERMINATOR SALVATION 36692, THE CAINE MUTINY 31206, THE FINAL DESTINATION 24155, WORLD WAR II src, edge_attr, dst 1912, has_tags, 24155 1912, release_year, 27261 4197, directed_by, 37236 4197, release_year, 27261 4197, written_by, 37236 6283, release_year, 35845 6283, release_year, 27261 14735, has_tags, 24481 14735, release_year, 35845 22215, has_tags, 24481 22215, release_year, 27261 15753, has_tags, 24481 15753, release_year, 27261 28852, release_year, 27261 6780, has_tags, 24155 6780, release_year, 27261 3942, release_year, 35845 3942, release_year, 27261 5812, has_tags, 24481 5812, release_year, 35845 180, has_tags, 24481 180, release_year, 27261 9228, has_tags, 24481 9228, release_year, 35845 34989, has_tags, 24481 34989, release_year, 27261 23472, has_tags, 24481 23472, release_year, 27261 36692, directed_by, 37236 36692, has_tags, 37236 36692, has_tags, 24155 31206, has_tags, 24481 31206, release_year, 27261 Question: In what context are FINAL DESTINATION 3, HANNAH FREE, and THE CAINE MUTINY connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "FINAL DESTINATION 3", "HANNAH FREE", "THE CAINE MUTINY" ], "valid_edges": [ [ "BEYOND ALL BOUNDARIES", "has_tags", "WORLD WAR II" ], [ "BEYOND ALL BOUNDARIES", "release_year", "2009" ], [ "BLUEBEARD", "directed_by", "EDWARD DMYTRYK" ], [ "BLUEBEARD", "release_year", "2009" ], [ "BLUEBEARD", "written_by", "EDWARD DMYTRYK" ], [ "CARGO", "release_year", "2006" ], [ "CARGO", "release_year", "2009" ], [ "FINAL DESTINATION 3", "has_tags", "FRANCHISE" ], [ "FINAL DESTINATION 3", "release_year", "2006" ], [ "FRIDAY THE 13TH", "has_tags", "FRANCHISE" ], [ "FRIDAY THE 13TH", "release_year", "2009" ], [ "HALLOWEEN II", "has_tags", "FRANCHISE" ], [ "HALLOWEEN II", "release_year", "2009" ], [ "HANNAH FREE", "release_year", "2009" ], [ "INTO THE STORM", "has_tags", "WORLD WAR II" ], [ "INTO THE STORM", "release_year", "2009" ], [ "SALVAGE", "release_year", "2006" ], [ "SALVAGE", "release_year", "2009" ], [ "SAW III", "has_tags", "FRANCHISE" ], [ "SAW III", "release_year", "2006" ], [ "SAW VI", "has_tags", "FRANCHISE" ], [ "SAW VI", "release_year", "2009" ], [ "SCARY MOVIE 4", "has_tags", "FRANCHISE" ], [ "SCARY MOVIE 4", "release_year", "2006" ], [ "STAR TREK", "has_tags", "FRANCHISE" ], [ "STAR TREK", "release_year", "2009" ], [ "TERMINATOR SALVATION", "has_tags", "FRANCHISE" ], [ "TERMINATOR SALVATION", "release_year", "2009" ], [ "THE CAINE MUTINY", "directed_by", "EDWARD DMYTRYK" ], [ "THE CAINE MUTINY", "has_tags", "EDWARD DMYTRYK" ], [ "THE CAINE MUTINY", "has_tags", "WORLD WAR II" ], [ "THE FINAL DESTINATION", "has_tags", "FRANCHISE" ], [ "THE FINAL DESTINATION", "release_year", "2009" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1892, 1932 33637, 1959 25221, 1981 37172, BELA LUGOSI 34733, CHANDU THE MAGICIAN 33269, ISLAND OF LOST SOULS 12435, JOHN WAYNE 18744, MURDERS IN THE RUE MORGUE 5794, ONLY WHEN I LAUGH 28388, PLAN 9 FROM OUTER SPACE 36102, RIO BRAVO 13251, THE BIG STAMPEDE 35827, THE DEATH KISS 5663, THE HORSE SOLDIERS 7028, THE HURRICANE EXPRESS 26820, THE MUMMY 35444, THE SHADOW OF THE EAGLE 14902, ZOMBIE 33616, ZOMBIE LAKE src, edge_attr, dst 34733, release_year, 1892 34733, starred_actors, 37172 33269, has_tags, 37172 33269, release_year, 1892 33269, starred_actors, 37172 18744, release_year, 1892 18744, starred_actors, 37172 5794, release_year, 25221 28388, has_tags, 37172 28388, has_tags, 14902 28388, release_year, 33637 36102, has_tags, 12435 36102, release_year, 33637 36102, starred_actors, 12435 13251, release_year, 1892 13251, starred_actors, 12435 35827, release_year, 1892 35827, starred_actors, 37172 5663, has_tags, 12435 5663, release_year, 33637 5663, starred_actors, 12435 7028, release_year, 1892 7028, starred_actors, 12435 26820, release_year, 1892 26820, release_year, 33637 35444, has_tags, 12435 35444, release_year, 1892 35444, starred_actors, 12435 33616, has_tags, 14902 33616, release_year, 25221 Question: For what reason are ONLY WHEN I LAUGH, PLAN 9 FROM OUTER SPACE, and THE BIG STAMPEDE associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ONLY WHEN I LAUGH", "PLAN 9 FROM OUTER SPACE", "THE BIG STAMPEDE" ], "valid_edges": [ [ "CHANDU THE MAGICIAN", "release_year", "1932" ], [ "CHANDU THE MAGICIAN", "starred_actors", "BELA LUGOSI" ], [ "ISLAND OF LOST SOULS", "has_tags", "BELA LUGOSI" ], [ "ISLAND OF LOST SOULS", "release_year", "1932" ], [ "ISLAND OF LOST SOULS", "starred_actors", "BELA LUGOSI" ], [ "MURDERS IN THE RUE MORGUE", "release_year", "1932" ], [ "MURDERS IN THE RUE MORGUE", "starred_actors", "BELA LUGOSI" ], [ "ONLY WHEN I LAUGH", "release_year", "1981" ], [ "PLAN 9 FROM OUTER SPACE", "has_tags", "BELA LUGOSI" ], [ "PLAN 9 FROM OUTER SPACE", "has_tags", "ZOMBIE" ], [ "PLAN 9 FROM OUTER SPACE", "release_year", "1959" ], [ "RIO BRAVO", "has_tags", "JOHN WAYNE" ], [ "RIO BRAVO", "release_year", "1959" ], [ "RIO BRAVO", "starred_actors", "JOHN WAYNE" ], [ "THE BIG STAMPEDE", "release_year", "1932" ], [ "THE BIG STAMPEDE", "starred_actors", "JOHN WAYNE" ], [ "THE DEATH KISS", "release_year", "1932" ], [ "THE DEATH KISS", "starred_actors", "BELA LUGOSI" ], [ "THE HORSE SOLDIERS", "has_tags", "JOHN WAYNE" ], [ "THE HORSE SOLDIERS", "release_year", "1959" ], [ "THE HORSE SOLDIERS", "starred_actors", "JOHN WAYNE" ], [ "THE HURRICANE EXPRESS", "release_year", "1932" ], [ "THE HURRICANE EXPRESS", "starred_actors", "JOHN WAYNE" ], [ "THE MUMMY", "release_year", "1932" ], [ "THE MUMMY", "release_year", "1959" ], [ "THE SHADOW OF THE EAGLE", "has_tags", "JOHN WAYNE" ], [ "THE SHADOW OF THE EAGLE", "release_year", "1932" ], [ "THE SHADOW OF THE EAGLE", "starred_actors", "JOHN WAYNE" ], [ "ZOMBIE LAKE", "has_tags", "ZOMBIE" ], [ "ZOMBIE LAKE", "release_year", "1981" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26762, 2008 17521, ACES 'N' EIGHTS 39289, ACTION 39750, ALIENS 10293, CONSPIRACY 33868, DEAN DEVLIN 5148, DEATH RACE 3553, GODZILLA 5870, HORROR 23780, HURT 8842, INDEPENDENCE DAY 27533, IRON MAN 27764, PAINTED SKIN 681, PISTOL WHIPPED 9720, QUANTUM OF SOLACE 12811, RAMBO 31404, ROLAND EMMERICH 6507, SOFIA VASSILIEVA 8325, STARGATE 2820, THE FORBIDDEN KINGDOM 1081, TRANSPORTER 3 8868, VANTAGE POINT 25527, VICE 22588, WANTED 22214, WAR src, edge_attr, dst 17521, has_genre, 39289 17521, release_year, 26762 39750, has_genre, 39289 39750, has_tags, 39289 10293, has_genre, 39289 10293, release_year, 26762 5148, has_genre, 39289 5148, release_year, 26762 3553, directed_by, 31404 3553, has_genre, 5870 3553, has_tags, 3553 3553, has_tags, 31404 3553, written_by, 33868 3553, written_by, 31404 23780, has_genre, 5870 23780, starred_actors, 6507 8842, directed_by, 31404 8842, has_tags, 39750 8842, has_tags, 31404 8842, has_tags, 22214 8842, written_by, 33868 8842, written_by, 31404 27533, has_genre, 39289 27533, has_tags, 39289 27533, release_year, 26762 27764, has_genre, 39289 27764, release_year, 26762 681, has_genre, 39289 681, release_year, 26762 9720, has_genre, 39289 9720, has_tags, 39289 9720, release_year, 26762 12811, has_genre, 39289 12811, has_tags, 39289 12811, release_year, 26762 8325, directed_by, 31404 8325, has_tags, 8325 8325, written_by, 33868 8325, written_by, 31404 2820, has_genre, 39289 2820, release_year, 26762 1081, has_genre, 39289 1081, has_tags, 39289 1081, release_year, 26762 8868, has_genre, 39289 8868, release_year, 26762 25527, has_genre, 39289 25527, release_year, 26762 22588, has_genre, 39289 22588, has_tags, 39289 22588, release_year, 26762 22214, has_genre, 39289 Question: How are DEAN DEVLIN, PAINTED SKIN, and SOFIA VASSILIEVA related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DEAN DEVLIN", "PAINTED SKIN", "SOFIA VASSILIEVA" ], "valid_edges": [ [ "ACES 'N' EIGHTS", "has_genre", "ACTION" ], [ "ACES 'N' EIGHTS", "release_year", "2008" ], [ "ALIENS", "has_genre", "ACTION" ], [ "ALIENS", "has_tags", "ACTION" ], [ "CONSPIRACY", "has_genre", "ACTION" ], [ "CONSPIRACY", "release_year", "2008" ], [ "DEATH RACE", "has_genre", "ACTION" ], [ "DEATH RACE", "release_year", "2008" ], [ "GODZILLA", "directed_by", "ROLAND EMMERICH" ], [ "GODZILLA", "has_genre", "HORROR" ], [ "GODZILLA", "has_tags", "GODZILLA" ], [ "GODZILLA", "has_tags", "ROLAND EMMERICH" ], [ "GODZILLA", "written_by", "DEAN DEVLIN" ], [ "GODZILLA", "written_by", "ROLAND EMMERICH" ], [ "HURT", "has_genre", "HORROR" ], [ "HURT", "starred_actors", "SOFIA VASSILIEVA" ], [ "INDEPENDENCE DAY", "directed_by", "ROLAND EMMERICH" ], [ "INDEPENDENCE DAY", "has_tags", "ALIENS" ], [ "INDEPENDENCE DAY", "has_tags", "ROLAND EMMERICH" ], [ "INDEPENDENCE DAY", "has_tags", "WAR" ], [ "INDEPENDENCE DAY", "written_by", "DEAN DEVLIN" ], [ "INDEPENDENCE DAY", "written_by", "ROLAND EMMERICH" ], [ "IRON MAN", "has_genre", "ACTION" ], [ "IRON MAN", "has_tags", "ACTION" ], [ "IRON MAN", "release_year", "2008" ], [ "PAINTED SKIN", "has_genre", "ACTION" ], [ "PAINTED SKIN", "release_year", "2008" ], [ "PISTOL WHIPPED", "has_genre", "ACTION" ], [ "PISTOL WHIPPED", "release_year", "2008" ], [ "QUANTUM OF SOLACE", "has_genre", "ACTION" ], [ "QUANTUM OF SOLACE", "has_tags", "ACTION" ], [ "QUANTUM OF SOLACE", "release_year", "2008" ], [ "RAMBO", "has_genre", "ACTION" ], [ "RAMBO", "has_tags", "ACTION" ], [ "RAMBO", "release_year", "2008" ], [ "STARGATE", "directed_by", "ROLAND EMMERICH" ], [ "STARGATE", "has_tags", "STARGATE" ], [ "STARGATE", "written_by", "DEAN DEVLIN" ], [ "STARGATE", "written_by", "ROLAND EMMERICH" ], [ "THE FORBIDDEN KINGDOM", "has_genre", "ACTION" ], [ "THE FORBIDDEN KINGDOM", "release_year", "2008" ], [ "TRANSPORTER 3", "has_genre", "ACTION" ], [ "TRANSPORTER 3", "has_tags", "ACTION" ], [ "TRANSPORTER 3", "release_year", "2008" ], [ "VANTAGE POINT", "has_genre", "ACTION" ], [ "VANTAGE POINT", "release_year", "2008" ], [ "VICE", "has_genre", "ACTION" ], [ "VICE", "release_year", "2008" ], [ "WANTED", "has_genre", "ACTION" ], [ "WANTED", "has_tags", "ACTION" ], [ "WANTED", "release_year", "2008" ], [ "WAR", "has_genre", "ACTION" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 8539, 1982 6776, 2000 34054, ADRIENNE BARBEAU 37912, CAT PEOPLE 30260, CREEPSHOW 25730, KENT SMITH 32591, SCREAM 3 31618, SWAMP THING 13494, TROIS 11529, WES CRAVEN src, edge_attr, dst 37912, release_year, 8539 37912, starred_actors, 25730 30260, release_year, 8539 30260, starred_actors, 34054 32591, directed_by, 11529 32591, has_tags, 11529 32591, release_year, 6776 31618, directed_by, 11529 31618, has_tags, 11529 31618, release_year, 8539 31618, starred_actors, 34054 31618, written_by, 11529 13494, release_year, 6776 Question: In what context are KENT SMITH, SWAMP THING, and TROIS connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "KENT SMITH", "SWAMP THING", "TROIS" ], "valid_edges": [ [ "CAT PEOPLE", "release_year", "1982" ], [ "CAT PEOPLE", "starred_actors", "KENT SMITH" ], [ "CREEPSHOW", "release_year", "1982" ], [ "CREEPSHOW", "starred_actors", "ADRIENNE BARBEAU" ], [ "SCREAM 3", "directed_by", "WES CRAVEN" ], [ "SCREAM 3", "has_tags", "WES CRAVEN" ], [ "SCREAM 3", "release_year", "2000" ], [ "SWAMP THING", "directed_by", "WES CRAVEN" ], [ "SWAMP THING", "has_tags", "WES CRAVEN" ], [ "SWAMP THING", "release_year", "1982" ], [ "SWAMP THING", "starred_actors", "ADRIENNE BARBEAU" ], [ "SWAMP THING", "written_by", "WES CRAVEN" ], [ "TROIS", "release_year", "2000" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17480, 1988 35845, 2006 29424, 2011 23250, 50/50 14062, ALL THE BOYS LOVE MANDY LANE 1805, AMBER HEARD 33796, DEMOTED 39870, DRIVE ANGRY 10658, HEARTBREAK HOTEL 25761, JONATHAN LEVINE 13237, PULSE 10133, UNKNOWN src, edge_attr, dst 23250, directed_by, 25761 23250, has_tags, 25761 23250, release_year, 29424 14062, directed_by, 25761 14062, release_year, 35845 14062, starred_actors, 1805 33796, release_year, 29424 39870, has_tags, 1805 39870, release_year, 29424 39870, starred_actors, 1805 10658, release_year, 17480 13237, release_year, 17480 13237, release_year, 35845 10133, release_year, 35845 10133, release_year, 29424 Question: In what context are ALL THE BOYS LOVE MANDY LANE, DEMOTED, and HEARTBREAK HOTEL connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ALL THE BOYS LOVE MANDY LANE", "DEMOTED", "HEARTBREAK HOTEL" ], "valid_edges": [ [ "50/50", "directed_by", "JONATHAN LEVINE" ], [ "50/50", "has_tags", "JONATHAN LEVINE" ], [ "50/50", "release_year", "2011" ], [ "ALL THE BOYS LOVE MANDY LANE", "directed_by", "JONATHAN LEVINE" ], [ "ALL THE BOYS LOVE MANDY LANE", "release_year", "2006" ], [ "ALL THE BOYS LOVE MANDY LANE", "starred_actors", "AMBER HEARD" ], [ "DEMOTED", "release_year", "2011" ], [ "DRIVE ANGRY", "has_tags", "AMBER HEARD" ], [ "DRIVE ANGRY", "release_year", "2011" ], [ "DRIVE ANGRY", "starred_actors", "AMBER HEARD" ], [ "HEARTBREAK HOTEL", "release_year", "1988" ], [ "PULSE", "release_year", "1988" ], [ "PULSE", "release_year", "2006" ], [ "UNKNOWN", "release_year", "2006" ], [ "UNKNOWN", "release_year", "2011" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9177, 1956 20257, ADOLPHE MENJOU 21856, ANASTASIA 35067, BOXING 12366, BUNDLE OF JOY 35437, DAVID BUTLER 38130, ELENA AND HER MEN 1475, HARRY CLORK 15210, INGRID BERGMAN 34119, MAURICE VALENCY 28026, SOMEBODY UP THERE LIKES ME 22837, TEA FOR TWO 13314, THE GIRL HE LEFT BEHIND 1368, THE MILKY WAY 21662, THE VISIT src, edge_attr, dst 21856, has_tags, 15210 21856, release_year, 9177 21856, starred_actors, 15210 12366, release_year, 9177 12366, starred_actors, 20257 38130, release_year, 9177 38130, starred_actors, 15210 28026, has_tags, 35067 28026, release_year, 9177 22837, directed_by, 35437 22837, written_by, 1475 13314, directed_by, 35437 13314, release_year, 9177 1368, has_tags, 35067 1368, starred_actors, 20257 1368, written_by, 1475 21662, starred_actors, 15210 21662, written_by, 34119 Question: For what reason are 1956, HARRY CLORK, and MAURICE VALENCY associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "1956", "HARRY CLORK", "MAURICE VALENCY" ], "valid_edges": [ [ "ANASTASIA", "has_tags", "INGRID BERGMAN" ], [ "ANASTASIA", "release_year", "1956" ], [ "ANASTASIA", "starred_actors", "INGRID BERGMAN" ], [ "BUNDLE OF JOY", "release_year", "1956" ], [ "BUNDLE OF JOY", "starred_actors", "ADOLPHE MENJOU" ], [ "ELENA AND HER MEN", "release_year", "1956" ], [ "ELENA AND HER MEN", "starred_actors", "INGRID BERGMAN" ], [ "SOMEBODY UP THERE LIKES ME", "has_tags", "BOXING" ], [ "SOMEBODY UP THERE LIKES ME", "release_year", "1956" ], [ "TEA FOR TWO", "directed_by", "DAVID BUTLER" ], [ "TEA FOR TWO", "written_by", "HARRY CLORK" ], [ "THE GIRL HE LEFT BEHIND", "directed_by", "DAVID BUTLER" ], [ "THE GIRL HE LEFT BEHIND", "release_year", "1956" ], [ "THE MILKY WAY", "has_tags", "BOXING" ], [ "THE MILKY WAY", "starred_actors", "ADOLPHE MENJOU" ], [ "THE MILKY WAY", "written_by", "HARRY CLORK" ], [ "THE VISIT", "starred_actors", "INGRID BERGMAN" ], [ "THE VISIT", "written_by", "MAURICE VALENCY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 15506, 1933 36163, 1967 1407, 42ND STREET 15460, CLAMBAKE 28538, DANCING LADY 27897, DOCTOR DOLITTLE 28372, FLIRTATION WALK 20824, FLYING DOWN TO RIO 4057, FOOTLIGHT PARADE 12817, FRANK BORZAGE 9762, GOING HOLLYWOOD 28905, GOLD DIGGERS OF 1933 12843, HOW TO SUCCEED IN BUSINESS WITHOUT REALLY TRYING 26727, I EVEN MET HAPPY GYPSIES 24411, LADY BE GOOD 22149, LIONEL BARRYMORE 31195, LOOKING FORWARD 8151, MAN'S CASTLE 24593, MUSICAL 20443, NIGHT FLIGHT 23990, SECRETS 5384, STAGE DOOR CANTEEN 23817, STATE FAIR 32813, THE HAPPIEST MILLIONAIRE 29621, THE STRANGER'S RETURN 34585, THE YOUNG GIRLS OF ROCHEFORT 25218, THOROUGHLY MODERN MILLIE src, edge_attr, dst 1407, has_genre, 24593 1407, release_year, 15506 15460, has_genre, 24593 15460, release_year, 36163 28538, has_genre, 24593 28538, release_year, 15506 27897, has_tags, 24593 27897, release_year, 36163 28372, directed_by, 12817 28372, has_genre, 24593 20824, has_genre, 24593 20824, release_year, 15506 4057, has_genre, 24593 4057, has_tags, 24593 4057, release_year, 15506 9762, has_genre, 24593 9762, release_year, 15506 28905, has_genre, 24593 28905, release_year, 15506 12843, has_genre, 24593 12843, has_tags, 24593 12843, release_year, 36163 26727, release_year, 36163 24411, has_genre, 24593 24411, starred_actors, 22149 31195, release_year, 15506 31195, starred_actors, 22149 8151, directed_by, 12817 8151, has_tags, 12817 8151, release_year, 15506 20443, release_year, 15506 20443, starred_actors, 22149 23990, directed_by, 12817 23990, has_tags, 12817 23990, release_year, 15506 5384, directed_by, 12817 5384, has_genre, 24593 23817, has_genre, 24593 23817, release_year, 15506 32813, has_genre, 24593 32813, release_year, 36163 29621, release_year, 15506 29621, starred_actors, 22149 34585, has_genre, 24593 34585, has_tags, 24593 34585, release_year, 36163 25218, has_genre, 24593 25218, release_year, 36163 Question: In what context are FLIRTATION WALK, I EVEN MET HAPPY GYPSIES, and LOOKING FORWARD connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "FLIRTATION WALK", "I EVEN MET HAPPY GYPSIES", "LOOKING FORWARD" ], "valid_edges": [ [ "42ND STREET", "has_genre", "MUSICAL" ], [ "42ND STREET", "release_year", "1933" ], [ "CLAMBAKE", "has_genre", "MUSICAL" ], [ "CLAMBAKE", "release_year", "1967" ], [ "DANCING LADY", "has_genre", "MUSICAL" ], [ "DANCING LADY", "release_year", "1933" ], [ "DOCTOR DOLITTLE", "has_tags", "MUSICAL" ], [ "DOCTOR DOLITTLE", "release_year", "1967" ], [ "FLIRTATION WALK", "directed_by", "FRANK BORZAGE" ], [ "FLIRTATION WALK", "has_genre", "MUSICAL" ], [ "FLYING DOWN TO RIO", "has_genre", "MUSICAL" ], [ "FLYING DOWN TO RIO", "release_year", "1933" ], [ "FOOTLIGHT PARADE", "has_genre", "MUSICAL" ], [ "FOOTLIGHT PARADE", "has_tags", "MUSICAL" ], [ "FOOTLIGHT PARADE", "release_year", "1933" ], [ "GOING HOLLYWOOD", "has_genre", "MUSICAL" ], [ "GOING HOLLYWOOD", "release_year", "1933" ], [ "GOLD DIGGERS OF 1933", "has_genre", "MUSICAL" ], [ "GOLD DIGGERS OF 1933", "release_year", "1933" ], [ "HOW TO SUCCEED IN BUSINESS WITHOUT REALLY TRYING", "has_genre", "MUSICAL" ], [ "HOW TO SUCCEED IN BUSINESS WITHOUT REALLY TRYING", "has_tags", "MUSICAL" ], [ "HOW TO SUCCEED IN BUSINESS WITHOUT REALLY TRYING", "release_year", "1967" ], [ "I EVEN MET HAPPY GYPSIES", "release_year", "1967" ], [ "LADY BE GOOD", "has_genre", "MUSICAL" ], [ "LADY BE GOOD", "starred_actors", "LIONEL BARRYMORE" ], [ "LOOKING FORWARD", "release_year", "1933" ], [ "LOOKING FORWARD", "starred_actors", "LIONEL BARRYMORE" ], [ "MAN'S CASTLE", "directed_by", "FRANK BORZAGE" ], [ "MAN'S CASTLE", "has_tags", "FRANK BORZAGE" ], [ "MAN'S CASTLE", "release_year", "1933" ], [ "NIGHT FLIGHT", "release_year", "1933" ], [ "NIGHT FLIGHT", "starred_actors", "LIONEL BARRYMORE" ], [ "SECRETS", "directed_by", "FRANK BORZAGE" ], [ "SECRETS", "has_tags", "FRANK BORZAGE" ], [ "SECRETS", "release_year", "1933" ], [ "STAGE DOOR CANTEEN", "directed_by", "FRANK BORZAGE" ], [ "STAGE DOOR CANTEEN", "has_genre", "MUSICAL" ], [ "STATE FAIR", "has_genre", "MUSICAL" ], [ "STATE FAIR", "release_year", "1933" ], [ "THE HAPPIEST MILLIONAIRE", "has_genre", "MUSICAL" ], [ "THE HAPPIEST MILLIONAIRE", "release_year", "1967" ], [ "THE STRANGER'S RETURN", "release_year", "1933" ], [ "THE STRANGER'S RETURN", "starred_actors", "LIONEL BARRYMORE" ], [ "THE YOUNG GIRLS OF ROCHEFORT", "has_genre", "MUSICAL" ], [ "THE YOUNG GIRLS OF ROCHEFORT", "has_tags", "MUSICAL" ], [ "THE YOUNG GIRLS OF ROCHEFORT", "release_year", "1967" ], [ "THOROUGHLY MODERN MILLIE", "has_genre", "MUSICAL" ], [ "THOROUGHLY MODERN MILLIE", "release_year", "1967" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39624, 1957 25423, APRIL LOVE 15729, BLACK RIVER 1578, FUNNY FACE 7972, HEAVEN KNOWS, MR. ALLISON 14375, HIGH SCHOOL MUSICAL 23829, HIGH SCHOOL MUSICAL 2 11051, I AM WAITING 16243, JAILHOUSE ROCK 36874, JAPANESE 20863, LES GIRLS 3960, LOVING YOU 21686, MOONLIGHT SERENADE 24593, MUSICAL 8682, PAL JOEY 6035, PRINCESS RACCOON 16848, SILK STOCKINGS 39568, THE BROADWAY MELODY 27792, THE JOKER IS WILD 34429, THE LORAX 30738, THE PAJAMA GAME 13374, THRONE OF BLOOD 10062, ZAC EFRON src, edge_attr, dst 25423, has_genre, 24593 25423, release_year, 39624 15729, in_language, 36874 15729, release_year, 39624 1578, has_genre, 24593 1578, has_tags, 24593 1578, release_year, 39624 7972, has_tags, 36874 7972, in_language, 36874 7972, release_year, 39624 14375, has_tags, 24593 14375, has_tags, 10062 14375, starred_actors, 10062 23829, has_tags, 24593 23829, starred_actors, 10062 11051, in_language, 36874 11051, release_year, 39624 16243, has_genre, 24593 16243, release_year, 39624 20863, has_genre, 24593 20863, has_tags, 24593 20863, release_year, 39624 3960, has_genre, 24593 3960, release_year, 39624 21686, has_genre, 24593 21686, in_language, 36874 8682, has_genre, 24593 8682, release_year, 39624 6035, has_genre, 24593 6035, in_language, 36874 16848, has_genre, 24593 16848, release_year, 39624 39568, has_genre, 24593 27792, has_genre, 24593 27792, release_year, 39624 34429, starred_actors, 10062 30738, has_genre, 24593 30738, release_year, 39624 13374, has_tags, 36874 13374, in_language, 36874 13374, release_year, 39624 Question: How are HEAVEN KNOWS, MR. ALLISON, THE BROADWAY MELODY, and THE LORAX related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "HEAVEN KNOWS, MR. ALLISON", "THE BROADWAY MELODY", "THE LORAX" ], "valid_edges": [ [ "APRIL LOVE", "has_genre", "MUSICAL" ], [ "APRIL LOVE", "release_year", "1957" ], [ "BLACK RIVER", "in_language", "JAPANESE" ], [ "BLACK RIVER", "release_year", "1957" ], [ "FUNNY FACE", "has_genre", "MUSICAL" ], [ "FUNNY FACE", "has_tags", "MUSICAL" ], [ "FUNNY FACE", "release_year", "1957" ], [ "HEAVEN KNOWS, MR. ALLISON", "has_tags", "JAPANESE" ], [ "HEAVEN KNOWS, MR. ALLISON", "in_language", "JAPANESE" ], [ "HEAVEN KNOWS, MR. ALLISON", "release_year", "1957" ], [ "HIGH SCHOOL MUSICAL", "has_tags", "MUSICAL" ], [ "HIGH SCHOOL MUSICAL", "has_tags", "ZAC EFRON" ], [ "HIGH SCHOOL MUSICAL", "starred_actors", "ZAC EFRON" ], [ "HIGH SCHOOL MUSICAL 2", "has_tags", "MUSICAL" ], [ "HIGH SCHOOL MUSICAL 2", "starred_actors", "ZAC EFRON" ], [ "I AM WAITING", "in_language", "JAPANESE" ], [ "I AM WAITING", "release_year", "1957" ], [ "JAILHOUSE ROCK", "has_genre", "MUSICAL" ], [ "JAILHOUSE ROCK", "release_year", "1957" ], [ "LES GIRLS", "has_genre", "MUSICAL" ], [ "LES GIRLS", "has_tags", "MUSICAL" ], [ "LES GIRLS", "release_year", "1957" ], [ "LOVING YOU", "has_genre", "MUSICAL" ], [ "LOVING YOU", "release_year", "1957" ], [ "MOONLIGHT SERENADE", "has_genre", "MUSICAL" ], [ "MOONLIGHT SERENADE", "in_language", "JAPANESE" ], [ "PAL JOEY", "has_genre", "MUSICAL" ], [ "PAL JOEY", "release_year", "1957" ], [ "PRINCESS RACCOON", "has_genre", "MUSICAL" ], [ "PRINCESS RACCOON", "in_language", "JAPANESE" ], [ "SILK STOCKINGS", "has_genre", "MUSICAL" ], [ "SILK STOCKINGS", "release_year", "1957" ], [ "THE BROADWAY MELODY", "has_genre", "MUSICAL" ], [ "THE JOKER IS WILD", "has_genre", "MUSICAL" ], [ "THE JOKER IS WILD", "release_year", "1957" ], [ "THE LORAX", "starred_actors", "ZAC EFRON" ], [ "THE PAJAMA GAME", "has_genre", "MUSICAL" ], [ "THE PAJAMA GAME", "release_year", "1957" ], [ "THRONE OF BLOOD", "has_tags", "JAPANESE" ], [ "THRONE OF BLOOD", "in_language", "JAPANESE" ], [ "THRONE OF BLOOD", "release_year", "1957" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 31604, 1978 19493, ANDY SAMBERG 8339, BLOODBROTHERS 5571, CLOUDY WITH A CHANCE OF MEATBALLS 14087, COMES A HORSEMAN 22796, HOOPER 34869, HOTEL TRANSYLVANIA 1038, JAMES CAAN 18164, JEFF BRIDGES 17397, KISS ME GOODBYE 26953, ROBERT MULLIGAN 4261, SALLY FIELD 25567, SAME TIME, NEXT YEAR 10896, SONY PICTURES ANIMATION 37759, STAY HUNGRY 23237, SURF'S UP 16732, THE END 5511, WITCH'S NIGHT OUT src, edge_attr, dst 8339, directed_by, 26953 8339, release_year, 31604 5571, has_tags, 19493 5571, has_tags, 10896 5571, starred_actors, 19493 5571, starred_actors, 1038 14087, release_year, 31604 14087, starred_actors, 1038 22796, release_year, 31604 22796, starred_actors, 4261 34869, has_tags, 19493 34869, has_tags, 10896 34869, starred_actors, 19493 17397, directed_by, 26953 17397, has_tags, 1038 17397, has_tags, 18164 17397, has_tags, 4261 17397, starred_actors, 1038 17397, starred_actors, 18164 17397, starred_actors, 4261 25567, directed_by, 26953 25567, has_tags, 26953 25567, release_year, 31604 37759, starred_actors, 18164 37759, starred_actors, 4261 23237, has_tags, 18164 23237, has_tags, 10896 23237, starred_actors, 18164 16732, release_year, 31604 16732, starred_actors, 4261 5511, release_year, 31604 Question: How are KISS ME GOODBYE, SONY PICTURES ANIMATION, and WITCH'S NIGHT OUT related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "KISS ME GOODBYE", "SONY PICTURES ANIMATION", "WITCH'S NIGHT OUT" ], "valid_edges": [ [ "BLOODBROTHERS", "directed_by", "ROBERT MULLIGAN" ], [ "BLOODBROTHERS", "release_year", "1978" ], [ "CLOUDY WITH A CHANCE OF MEATBALLS", "has_tags", "ANDY SAMBERG" ], [ "CLOUDY WITH A CHANCE OF MEATBALLS", "has_tags", "SONY PICTURES ANIMATION" ], [ "CLOUDY WITH A CHANCE OF MEATBALLS", "starred_actors", "ANDY SAMBERG" ], [ "CLOUDY WITH A CHANCE OF MEATBALLS", "starred_actors", "JAMES CAAN" ], [ "COMES A HORSEMAN", "release_year", "1978" ], [ "COMES A HORSEMAN", "starred_actors", "JAMES CAAN" ], [ "HOOPER", "release_year", "1978" ], [ "HOOPER", "starred_actors", "SALLY FIELD" ], [ "HOTEL TRANSYLVANIA", "has_tags", "ANDY SAMBERG" ], [ "HOTEL TRANSYLVANIA", "has_tags", "SONY PICTURES ANIMATION" ], [ "HOTEL TRANSYLVANIA", "starred_actors", "ANDY SAMBERG" ], [ "KISS ME GOODBYE", "directed_by", "ROBERT MULLIGAN" ], [ "KISS ME GOODBYE", "has_tags", "JAMES CAAN" ], [ "KISS ME GOODBYE", "has_tags", "JEFF BRIDGES" ], [ "KISS ME GOODBYE", "has_tags", "SALLY FIELD" ], [ "KISS ME GOODBYE", "starred_actors", "JAMES CAAN" ], [ "KISS ME GOODBYE", "starred_actors", "JEFF BRIDGES" ], [ "KISS ME GOODBYE", "starred_actors", "SALLY FIELD" ], [ "SAME TIME, NEXT YEAR", "directed_by", "ROBERT MULLIGAN" ], [ "SAME TIME, NEXT YEAR", "has_tags", "ROBERT MULLIGAN" ], [ "SAME TIME, NEXT YEAR", "release_year", "1978" ], [ "STAY HUNGRY", "starred_actors", "JEFF BRIDGES" ], [ "STAY HUNGRY", "starred_actors", "SALLY FIELD" ], [ "SURF'S UP", "has_tags", "JEFF BRIDGES" ], [ "SURF'S UP", "has_tags", "SONY PICTURES ANIMATION" ], [ "SURF'S UP", "starred_actors", "JEFF BRIDGES" ], [ "THE END", "release_year", "1978" ], [ "THE END", "starred_actors", "SALLY FIELD" ], [ "WITCH'S NIGHT OUT", "release_year", "1978" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36268, 1980 37484, 2004 15374, 2005 35845, 2006 29424, 2011 39289, ACTION 36853, ALTERED STATES 33134, ANY WHICH WAY YOU CAN 32931, ASSASSINATION GAMES 1743, BAD TIMING 29513, CANNIBAL HOLOCAUST 25738, CHRISTMAS EVIL 13888, CITY OF THE LIVING DEAD 16813, CONTAMINATION 14724, CRIME 32554, CUBE ZERO 9248, DEATH SHIP 1028, DEEPSTAR SIX 9986, DELITTO A PORTA ROMANA 771, DRESSED TO KILL 31653, EATEN ALIVE! 31783, ENGLISH 12394, ERNIE BARBARASH 14623, FADE TO BLACK 22215, FRIDAY THE 13TH 24174, FUN IS BEAUTIFUL 19224, GHOSTS 35657, GLORIA 13041, HAL HOLBROOK 31948, HARVEY KEITEL 1408, HE KNOWS YOU'RE ALONE 2600, HELL OF THE LIVING DEAD 5870, HORROR 24167, INFERNO 16200, ITALIAN 4472, JAMIE LEE CURTIS 24437, MANIAC 1153, MICHAEL CAINE 30047, MOTEL HELL 19825, MOTHER'S DAY 25714, NIGHTMARE CITY 24736, PROM NIGHT 23458, PSYCHOLOGICAL 33108, RUNNING SCARED 6292, SATURN 3 32387, SIMON 5409, SLASHER 7556, SPANISH 5864, THE AWAKENING 34039, THE CHANGELING 27423, THE FOG 5592, THE HEARSE 23688, THE HUNTER 2393, THE ISLAND 24875, THE KIDNAPPING OF THE PRESIDENT 38433, THE MERCHANT OF VENICE 21636, THE OCTAGON 19018, THE SHINING 14962, THE WATCHER IN THE WOODS 24811, THRILLER 34977, TICKING CLOCK 6768, TRISH VAN DEVERE 25262, WINDOWS 21887, WITHOUT WARNING 14902, ZOMBIE 39354, ZOMBIES src, edge_attr, dst 36853, has_genre, 5870 36853, release_year, 36268 33134, has_genre, 39289 33134, release_year, 36268 32931, directed_by, 12394 32931, has_genre, 39289 32931, release_year, 29424 1743, has_genre, 24811 1743, release_year, 36268 1743, starred_actors, 31948 29513, has_tags, 16200 29513, release_year, 36268 25738, has_genre, 5870 25738, release_year, 36268 13888, has_genre, 5870 13888, has_tags, 5870 13888, has_tags, 16200 13888, in_language, 31783 13888, in_language, 16200 13888, release_year, 36268 16813, has_genre, 5870 16813, release_year, 36268 32554, directed_by, 12394 32554, has_genre, 24811 32554, has_tags, 23458 32554, release_year, 37484 32554, written_by, 12394 9248, has_genre, 5870 9248, release_year, 36268 1028, has_genre, 5870 9986, has_genre, 14724 9986, in_language, 16200 9986, release_year, 36268 771, has_genre, 24811 771, has_tags, 1153 771, release_year, 36268 771, starred_actors, 1153 31653, in_language, 16200 31653, release_year, 36268 14623, has_genre, 24811 14623, release_year, 36268 14623, release_year, 35845 22215, has_genre, 5870 22215, has_tags, 5409 22215, release_year, 36268 24174, in_language, 16200 24174, release_year, 36268 35657, has_genre, 14724 35657, has_genre, 24811 35657, in_language, 7556 35657, release_year, 36268 1408, has_genre, 5870 1408, release_year, 36268 2600, has_genre, 5870 2600, has_tags, 14902 2600, has_tags, 39354 2600, in_language, 16200 2600, release_year, 36268 24167, has_genre, 5870 24167, has_genre, 24811 24167, in_language, 16200 24167, release_year, 36268 24437, has_genre, 5870 24437, has_tags, 5409 24437, release_year, 36268 30047, has_genre, 5870 30047, release_year, 36268 19825, has_genre, 5870 19825, has_genre, 24811 19825, release_year, 36268 25714, has_tags, 14902 25714, has_tags, 39354 25714, in_language, 16200 25714, in_language, 7556 25714, release_year, 36268 24736, has_genre, 5870 24736, has_tags, 5409 24736, release_year, 36268 24736, starred_actors, 4472 33108, has_genre, 39289 33108, has_genre, 14724 33108, release_year, 36268 33108, release_year, 35845 6292, has_genre, 24811 6292, release_year, 36268 6292, starred_actors, 31948 32387, release_year, 36268 32387, release_year, 37484 5864, has_genre, 5870 5864, has_tags, 5870 5864, release_year, 36268 5864, release_year, 29424 34039, has_genre, 5870 34039, release_year, 36268 34039, starred_actors, 6768 27423, has_genre, 5870 27423, has_tags, 19224 27423, has_tags, 13041 27423, has_tags, 5870 27423, has_tags, 4472 27423, release_year, 36268 27423, release_year, 15374 27423, starred_actors, 4472 5592, has_genre, 5870 5592, release_year, 36268 5592, starred_actors, 6768 23688, has_genre, 24811 23688, release_year, 36268 23688, release_year, 29424 2393, has_tags, 24811 2393, release_year, 36268 2393, release_year, 15374 2393, starred_actors, 1153 24875, has_genre, 24811 24875, release_year, 36268 24875, starred_actors, 13041 38433, in_language, 31783 38433, release_year, 36268 38433, release_year, 37484 21636, has_genre, 39289 21636, release_year, 36268 19018, has_genre, 5870 19018, has_tags, 19224 19018, has_tags, 5870 19018, has_tags, 23458 19018, release_year, 36268 14962, has_genre, 5870 14962, in_language, 31783 14962, release_year, 36268 34977, directed_by, 12394 34977, has_genre, 39289 34977, release_year, 29424 25262, has_genre, 24811 25262, release_year, 36268 21887, has_genre, 5870 21887, release_year, 36268 Question: In what context are 1980, DEEPSTAR SIX, and ERNIE BARBARASH connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "1980", "DEEPSTAR SIX", "ERNIE BARBARASH" ], "valid_edges": [ [ "ALTERED STATES", "has_genre", "HORROR" ], [ "ALTERED STATES", "release_year", "1980" ], [ "ANY WHICH WAY YOU CAN", "has_genre", "ACTION" ], [ "ANY WHICH WAY YOU CAN", "release_year", "1980" ], [ "ASSASSINATION GAMES", "directed_by", "ERNIE BARBARASH" ], [ "ASSASSINATION GAMES", "has_genre", "ACTION" ], [ "ASSASSINATION GAMES", "release_year", "2011" ], [ "BAD TIMING", "has_genre", "THRILLER" ], [ "BAD TIMING", "release_year", "1980" ], [ "BAD TIMING", "starred_actors", "HARVEY KEITEL" ], [ "CANNIBAL HOLOCAUST", "has_tags", "ITALIAN" ], [ "CANNIBAL HOLOCAUST", "release_year", "1980" ], [ "CHRISTMAS EVIL", "has_genre", "HORROR" ], [ "CHRISTMAS EVIL", "release_year", "1980" ], [ "CITY OF THE LIVING DEAD", "has_genre", "HORROR" ], [ "CITY OF THE LIVING DEAD", "has_tags", "HORROR" ], [ "CITY OF THE LIVING DEAD", "has_tags", "ITALIAN" ], [ "CITY OF THE LIVING DEAD", "in_language", "ENGLISH" ], [ "CITY OF THE LIVING DEAD", "in_language", "ITALIAN" ], [ "CITY OF THE LIVING DEAD", "release_year", "1980" ], [ "CONTAMINATION", "has_genre", "HORROR" ], [ "CONTAMINATION", "release_year", "1980" ], [ "CUBE ZERO", "directed_by", "ERNIE BARBARASH" ], [ "CUBE ZERO", "has_genre", "THRILLER" ], [ "CUBE ZERO", "has_tags", "PSYCHOLOGICAL" ], [ "CUBE ZERO", "release_year", "2004" ], [ "CUBE ZERO", "written_by", "ERNIE BARBARASH" ], [ "DEATH SHIP", "has_genre", "HORROR" ], [ "DEATH SHIP", "release_year", "1980" ], [ "DEEPSTAR SIX", "has_genre", "HORROR" ], [ "DELITTO A PORTA ROMANA", "has_genre", "CRIME" ], [ "DELITTO A PORTA ROMANA", "in_language", "ITALIAN" ], [ "DELITTO A PORTA ROMANA", "release_year", "1980" ], [ "DRESSED TO KILL", "has_genre", "THRILLER" ], [ "DRESSED TO KILL", "has_tags", "MICHAEL CAINE" ], [ "DRESSED TO KILL", "release_year", "1980" ], [ "DRESSED TO KILL", "starred_actors", "MICHAEL CAINE" ], [ "EATEN ALIVE!", "in_language", "ITALIAN" ], [ "EATEN ALIVE!", "release_year", "1980" ], [ "FADE TO BLACK", "has_genre", "THRILLER" ], [ "FADE TO BLACK", "release_year", "1980" ], [ "FADE TO BLACK", "release_year", "2006" ], [ "FRIDAY THE 13TH", "has_genre", "HORROR" ], [ "FRIDAY THE 13TH", "has_tags", "SLASHER" ], [ "FRIDAY THE 13TH", "release_year", "1980" ], [ "FUN IS BEAUTIFUL", "in_language", "ITALIAN" ], [ "FUN IS BEAUTIFUL", "release_year", "1980" ], [ "GLORIA", "has_genre", "CRIME" ], [ "GLORIA", "has_genre", "THRILLER" ], [ "GLORIA", "in_language", "SPANISH" ], [ "GLORIA", "release_year", "1980" ], [ "HE KNOWS YOU'RE ALONE", "has_genre", "HORROR" ], [ "HE KNOWS YOU'RE ALONE", "release_year", "1980" ], [ "HELL OF THE LIVING DEAD", "has_genre", "HORROR" ], [ "HELL OF THE LIVING DEAD", "has_tags", "ZOMBIE" ], [ "HELL OF THE LIVING DEAD", "has_tags", "ZOMBIES" ], [ "HELL OF THE LIVING DEAD", "in_language", "ITALIAN" ], [ "HELL OF THE LIVING DEAD", "release_year", "1980" ], [ "INFERNO", "has_genre", "HORROR" ], [ "INFERNO", "has_genre", "THRILLER" ], [ "INFERNO", "in_language", "ITALIAN" ], [ "INFERNO", "release_year", "1980" ], [ "MANIAC", "has_genre", "HORROR" ], [ "MANIAC", "has_tags", "SLASHER" ], [ "MANIAC", "release_year", "1980" ], [ "MOTEL HELL", "has_genre", "HORROR" ], [ "MOTEL HELL", "release_year", "1980" ], [ "MOTHER'S DAY", "has_genre", "HORROR" ], [ "MOTHER'S DAY", "has_genre", "THRILLER" ], [ "MOTHER'S DAY", "release_year", "1980" ], [ "NIGHTMARE CITY", "has_tags", "ZOMBIE" ], [ "NIGHTMARE CITY", "has_tags", "ZOMBIES" ], [ "NIGHTMARE CITY", "in_language", "ITALIAN" ], [ "NIGHTMARE CITY", "in_language", "SPANISH" ], [ "NIGHTMARE CITY", "release_year", "1980" ], [ "PROM NIGHT", "has_genre", "HORROR" ], [ "PROM NIGHT", "has_tags", "SLASHER" ], [ "PROM NIGHT", "release_year", "1980" ], [ "PROM NIGHT", "starred_actors", "JAMIE LEE CURTIS" ], [ "RUNNING SCARED", "has_genre", "ACTION" ], [ "RUNNING SCARED", "has_genre", "CRIME" ], [ "RUNNING SCARED", "release_year", "1980" ], [ "RUNNING SCARED", "release_year", "2006" ], [ "SATURN 3", "has_genre", "THRILLER" ], [ "SATURN 3", "release_year", "1980" ], [ "SATURN 3", "starred_actors", "HARVEY KEITEL" ], [ "SIMON", "release_year", "1980" ], [ "SIMON", "release_year", "2004" ], [ "THE AWAKENING", "has_genre", "HORROR" ], [ "THE AWAKENING", "has_tags", "HORROR" ], [ "THE AWAKENING", "release_year", "1980" ], [ "THE AWAKENING", "release_year", "2011" ], [ "THE CHANGELING", "has_genre", "HORROR" ], [ "THE CHANGELING", "release_year", "1980" ], [ "THE CHANGELING", "starred_actors", "TRISH VAN DEVERE" ], [ "THE FOG", "has_genre", "HORROR" ], [ "THE FOG", "has_tags", "GHOSTS" ], [ "THE FOG", "has_tags", "HAL HOLBROOK" ], [ "THE FOG", "has_tags", "HORROR" ], [ "THE FOG", "has_tags", "JAMIE LEE CURTIS" ], [ "THE FOG", "release_year", "1980" ], [ "THE FOG", "release_year", "2005" ], [ "THE FOG", "starred_actors", "JAMIE LEE CURTIS" ], [ "THE HEARSE", "has_genre", "HORROR" ], [ "THE HEARSE", "release_year", "1980" ], [ "THE HEARSE", "starred_actors", "TRISH VAN DEVERE" ], [ "THE HUNTER", "has_genre", "THRILLER" ], [ "THE HUNTER", "release_year", "1980" ], [ "THE HUNTER", "release_year", "2011" ], [ "THE ISLAND", "has_tags", "THRILLER" ], [ "THE ISLAND", "release_year", "1980" ], [ "THE ISLAND", "release_year", "2005" ], [ "THE ISLAND", "starred_actors", "MICHAEL CAINE" ], [ "THE KIDNAPPING OF THE PRESIDENT", "has_genre", "THRILLER" ], [ "THE KIDNAPPING OF THE PRESIDENT", "release_year", "1980" ], [ "THE KIDNAPPING OF THE PRESIDENT", "starred_actors", "HAL HOLBROOK" ], [ "THE MERCHANT OF VENICE", "in_language", "ENGLISH" ], [ "THE MERCHANT OF VENICE", "release_year", "1980" ], [ "THE MERCHANT OF VENICE", "release_year", "2004" ], [ "THE OCTAGON", "has_genre", "ACTION" ], [ "THE OCTAGON", "release_year", "1980" ], [ "THE SHINING", "has_genre", "HORROR" ], [ "THE SHINING", "has_tags", "GHOSTS" ], [ "THE SHINING", "has_tags", "HORROR" ], [ "THE SHINING", "has_tags", "PSYCHOLOGICAL" ], [ "THE SHINING", "release_year", "1980" ], [ "THE WATCHER IN THE WOODS", "has_genre", "HORROR" ], [ "THE WATCHER IN THE WOODS", "in_language", "ENGLISH" ], [ "THE WATCHER IN THE WOODS", "release_year", "1980" ], [ "TICKING CLOCK", "directed_by", "ERNIE BARBARASH" ], [ "TICKING CLOCK", "has_genre", "ACTION" ], [ "TICKING CLOCK", "release_year", "2011" ], [ "WINDOWS", "has_genre", "THRILLER" ], [ "WINDOWS", "release_year", "1980" ], [ "WITHOUT WARNING", "has_genre", "HORROR" ], [ "WITHOUT WARNING", "release_year", "1980" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 31196, 1974 9538, DON SIEGEL 31376, HARRY AND TONTO 23458, PSYCHOLOGICAL 16380, THE BLACK WINDMILL 28677, THE CONVERSATION 6513, THE VILLAGE 37550, TWO MULES FOR SISTER SARA src, edge_attr, dst 31376, release_year, 31196 16380, directed_by, 9538 16380, release_year, 31196 28677, has_tags, 23458 28677, release_year, 31196 6513, has_tags, 23458 37550, directed_by, 9538 37550, has_tags, 9538 Question: How are HARRY AND TONTO, THE VILLAGE, and TWO MULES FOR SISTER SARA related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "HARRY AND TONTO", "THE VILLAGE", "TWO MULES FOR SISTER SARA" ], "valid_edges": [ [ "HARRY AND TONTO", "release_year", "1974" ], [ "THE BLACK WINDMILL", "directed_by", "DON SIEGEL" ], [ "THE BLACK WINDMILL", "release_year", "1974" ], [ "THE CONVERSATION", "has_tags", "PSYCHOLOGICAL" ], [ "THE CONVERSATION", "release_year", "1974" ], [ "THE VILLAGE", "has_tags", "PSYCHOLOGICAL" ], [ "TWO MULES FOR SISTER SARA", "directed_by", "DON SIEGEL" ], [ "TWO MULES FOR SISTER SARA", "has_tags", "DON SIEGEL" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 8486, 1999 30284, ALL ABOUT MY MOTHER 13445, BAHAMAS 10045, BD-R 4592, BEAU TRAVAIL 2067, BETWEEN YOUR LEGS 16659, CASINO ROYALE 19200, CRIMINAL LOVERS 17072, FAREWELL, HOME SWEET HOME 6012, FRENCH 23299, GET CARTER 35657, GLORIA 10457, GOYA IN BORDEAUX 5722, HUMAN RESOURCES 35335, IT ALL STARTS TODAY 9866, MY LITTLE BUSINESS 37006, NO ONE WRITES TO THE COLONEL 23816, NOBODY KNOWS ANYBODY 21386, POLA X 33958, RACHAEL LEIGH COOK 8379, ROMANCE 4126, ROSETTA 11432, SECOND SKIN 3631, SET ME FREE 38502, SHE'S ALL THAT 21147, SOLAS 7556, SPANISH 6150, THE CONFESSION 16209, THE HI-LINE 9799, THE LOST SON 29990, THE NAMELESS 37903, THE NINTH GATE 3569, WHY NOT ME? src, edge_attr, dst 30284, has_tags, 7556 30284, in_language, 7556 30284, release_year, 8486 4592, in_language, 6012 4592, release_year, 8486 2067, in_language, 7556 2067, release_year, 8486 16659, has_tags, 13445 16659, has_tags, 10045 19200, has_tags, 6012 19200, in_language, 6012 19200, release_year, 8486 17072, in_language, 6012 17072, release_year, 8486 23299, has_tags, 10045 23299, starred_actors, 33958 35657, in_language, 7556 35657, release_year, 8486 10457, in_language, 7556 10457, release_year, 8486 5722, in_language, 6012 5722, release_year, 8486 35335, in_language, 6012 35335, release_year, 8486 9866, in_language, 6012 9866, release_year, 8486 37006, in_language, 7556 37006, release_year, 8486 23816, in_language, 7556 23816, release_year, 8486 21386, in_language, 6012 21386, release_year, 8486 8379, in_language, 6012 8379, release_year, 8486 4126, in_language, 6012 4126, release_year, 8486 11432, in_language, 7556 11432, release_year, 8486 3631, in_language, 6012 3631, release_year, 8486 38502, has_tags, 33958 38502, release_year, 8486 38502, starred_actors, 33958 21147, in_language, 7556 21147, release_year, 8486 6150, in_language, 6012 6150, release_year, 8486 16209, release_year, 8486 16209, starred_actors, 33958 9799, in_language, 6012 9799, release_year, 8486 29990, in_language, 7556 29990, release_year, 8486 37903, in_language, 6012 37903, in_language, 7556 37903, release_year, 8486 3569, has_tags, 6012 3569, in_language, 6012 3569, release_year, 8486 Question: In what context are BAHAMAS, RACHAEL LEIGH COOK, and THE NINTH GATE connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BAHAMAS", "RACHAEL LEIGH COOK", "THE NINTH GATE" ], "valid_edges": [ [ "ALL ABOUT MY MOTHER", "has_tags", "SPANISH" ], [ "ALL ABOUT MY MOTHER", "in_language", "SPANISH" ], [ "ALL ABOUT MY MOTHER", "release_year", "1999" ], [ "BEAU TRAVAIL", "in_language", "FRENCH" ], [ "BEAU TRAVAIL", "release_year", "1999" ], [ "BETWEEN YOUR LEGS", "in_language", "SPANISH" ], [ "BETWEEN YOUR LEGS", "release_year", "1999" ], [ "CASINO ROYALE", "has_tags", "BAHAMAS" ], [ "CASINO ROYALE", "has_tags", "BD-R" ], [ "CRIMINAL LOVERS", "has_tags", "FRENCH" ], [ "CRIMINAL LOVERS", "in_language", "FRENCH" ], [ "CRIMINAL LOVERS", "release_year", "1999" ], [ "FAREWELL, HOME SWEET HOME", "in_language", "FRENCH" ], [ "FAREWELL, HOME SWEET HOME", "release_year", "1999" ], [ "GET CARTER", "has_tags", "BD-R" ], [ "GET CARTER", "starred_actors", "RACHAEL LEIGH COOK" ], [ "GLORIA", "in_language", "SPANISH" ], [ "GLORIA", "release_year", "1999" ], [ "GOYA IN BORDEAUX", "in_language", "SPANISH" ], [ "GOYA IN BORDEAUX", "release_year", "1999" ], [ "HUMAN RESOURCES", "in_language", "FRENCH" ], [ "HUMAN RESOURCES", "release_year", "1999" ], [ "IT ALL STARTS TODAY", "in_language", "FRENCH" ], [ "IT ALL STARTS TODAY", "release_year", "1999" ], [ "MY LITTLE BUSINESS", "in_language", "FRENCH" ], [ "MY LITTLE BUSINESS", "release_year", "1999" ], [ "NO ONE WRITES TO THE COLONEL", "in_language", "SPANISH" ], [ "NO ONE WRITES TO THE COLONEL", "release_year", "1999" ], [ "NOBODY KNOWS ANYBODY", "in_language", "SPANISH" ], [ "NOBODY KNOWS ANYBODY", "release_year", "1999" ], [ "POLA X", "in_language", "FRENCH" ], [ "POLA X", "release_year", "1999" ], [ "ROMANCE", "in_language", "FRENCH" ], [ "ROMANCE", "release_year", "1999" ], [ "ROSETTA", "in_language", "FRENCH" ], [ "ROSETTA", "release_year", "1999" ], [ "SECOND SKIN", "in_language", "SPANISH" ], [ "SECOND SKIN", "release_year", "1999" ], [ "SET ME FREE", "in_language", "FRENCH" ], [ "SET ME FREE", "release_year", "1999" ], [ "SHE'S ALL THAT", "has_tags", "RACHAEL LEIGH COOK" ], [ "SHE'S ALL THAT", "release_year", "1999" ], [ "SHE'S ALL THAT", "starred_actors", "RACHAEL LEIGH COOK" ], [ "SOLAS", "in_language", "SPANISH" ], [ "SOLAS", "release_year", "1999" ], [ "THE CONFESSION", "in_language", "FRENCH" ], [ "THE CONFESSION", "release_year", "1999" ], [ "THE HI-LINE", "release_year", "1999" ], [ "THE HI-LINE", "starred_actors", "RACHAEL LEIGH COOK" ], [ "THE LOST SON", "in_language", "FRENCH" ], [ "THE LOST SON", "release_year", "1999" ], [ "THE NAMELESS", "in_language", "SPANISH" ], [ "THE NAMELESS", "release_year", "1999" ], [ "THE NINTH GATE", "in_language", "FRENCH" ], [ "THE NINTH GATE", "in_language", "SPANISH" ], [ "THE NINTH GATE", "release_year", "1999" ], [ "WHY NOT ME?", "has_tags", "FRENCH" ], [ "WHY NOT ME?", "in_language", "FRENCH" ], [ "WHY NOT ME?", "release_year", "1999" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 7977, 1969 39435, 1975 13211, CALIBER 9 906, FERNANDO DI LEO 10387, FRITZ LANG 39145, FURY 16200, ITALIAN 16430, KIDNAP SYNDICATE 20195, NAKED VIOLENCE 13806, NORMAN KRASNA 19487, OVERLORD 1985, SEVEN BEAUTIES 28423, SHOOT FIRST, DIE LATER 35043, SYLVIA SIDNEY 405, THE HIDING PLACE 22214, WAR 39783, YOU AND ME 1088, YOU ONLY LIVE ONCE src, edge_attr, dst 7977, has_genre, 22214 13211, directed_by, 906 13211, in_language, 16200 13211, written_by, 906 39145, directed_by, 10387 39145, has_genre, 22214 39145, has_tags, 10387 39145, has_tags, 22214 39145, starred_actors, 35043 39145, written_by, 10387 39145, written_by, 13806 16430, directed_by, 906 16430, in_language, 16200 16430, release_year, 39435 16430, written_by, 906 20195, directed_by, 906 20195, in_language, 16200 20195, release_year, 7977 20195, written_by, 906 19487, has_genre, 22214 19487, release_year, 39435 1985, has_genre, 22214 1985, release_year, 39435 28423, directed_by, 906 28423, in_language, 16200 28423, written_by, 906 405, has_genre, 22214 405, release_year, 39435 39783, directed_by, 10387 39783, has_tags, 10387 39783, starred_actors, 35043 39783, written_by, 13806 1088, directed_by, 10387 1088, has_tags, 10387 1088, starred_actors, 35043 Question: For what reason are FERNANDO DI LEO, OVERLORD, and SYLVIA SIDNEY associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "FERNANDO DI LEO", "OVERLORD", "SYLVIA SIDNEY" ], "valid_edges": [ [ "1969", "has_genre", "WAR" ], [ "CALIBER 9", "directed_by", "FERNANDO DI LEO" ], [ "CALIBER 9", "in_language", "ITALIAN" ], [ "CALIBER 9", "written_by", "FERNANDO DI LEO" ], [ "FURY", "directed_by", "FRITZ LANG" ], [ "FURY", "has_genre", "WAR" ], [ "FURY", "has_tags", "FRITZ LANG" ], [ "FURY", "has_tags", "WAR" ], [ "FURY", "starred_actors", "SYLVIA SIDNEY" ], [ "FURY", "written_by", "FRITZ LANG" ], [ "FURY", "written_by", "NORMAN KRASNA" ], [ "KIDNAP SYNDICATE", "directed_by", "FERNANDO DI LEO" ], [ "KIDNAP SYNDICATE", "in_language", "ITALIAN" ], [ "KIDNAP SYNDICATE", "release_year", "1975" ], [ "KIDNAP SYNDICATE", "written_by", "FERNANDO DI LEO" ], [ "NAKED VIOLENCE", "directed_by", "FERNANDO DI LEO" ], [ "NAKED VIOLENCE", "in_language", "ITALIAN" ], [ "NAKED VIOLENCE", "release_year", "1969" ], [ "NAKED VIOLENCE", "written_by", "FERNANDO DI LEO" ], [ "OVERLORD", "has_genre", "WAR" ], [ "OVERLORD", "release_year", "1975" ], [ "SEVEN BEAUTIES", "has_genre", "WAR" ], [ "SEVEN BEAUTIES", "release_year", "1975" ], [ "SHOOT FIRST, DIE LATER", "directed_by", "FERNANDO DI LEO" ], [ "SHOOT FIRST, DIE LATER", "in_language", "ITALIAN" ], [ "SHOOT FIRST, DIE LATER", "written_by", "FERNANDO DI LEO" ], [ "THE HIDING PLACE", "has_genre", "WAR" ], [ "THE HIDING PLACE", "release_year", "1975" ], [ "YOU AND ME", "directed_by", "FRITZ LANG" ], [ "YOU AND ME", "has_tags", "FRITZ LANG" ], [ "YOU AND ME", "starred_actors", "SYLVIA SIDNEY" ], [ "YOU AND ME", "written_by", "NORMAN KRASNA" ], [ "YOU ONLY LIVE ONCE", "directed_by", "FRITZ LANG" ], [ "YOU ONLY LIVE ONCE", "has_tags", "FRITZ LANG" ], [ "YOU ONLY LIVE ONCE", "starred_actors", "SYLVIA SIDNEY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35747, 1408 15374, 2005 17315, 2007 38712, 30 DAYS OF NIGHT 2960, ARENA 31464, BALLS OF FURY 7664, CLEANER 29211, COACH CARTER 4928, GRACIE 184, GUY X 17696, JOSH HARTNETT 34241, MAGICIANS 17433, MOZART AND THE WHALE 8324, RESURRECTING THE CHAMP 4695, ROBERT WEBB 13814, SAMUEL L. JACKSON 32404, SPORT 25192, STEEP 18707, THE COMEBACKS 27636, THE FINAL SEASON 334, THE GAME PLAN 36410, THE GREATEST GAME EVER PLAYED 20223, THE LONGEST YARD 24108, THE MAN 36820, TWO FOR THE MONEY src, edge_attr, dst 35747, has_tags, 13814 35747, release_year, 17315 38712, has_tags, 17696 38712, release_year, 17315 38712, starred_actors, 17696 2960, has_genre, 32404 2960, starred_actors, 13814 31464, has_genre, 32404 31464, release_year, 17315 7664, release_year, 17315 7664, starred_actors, 13814 29211, has_genre, 32404 29211, has_tags, 13814 29211, release_year, 15374 29211, starred_actors, 13814 4928, has_genre, 32404 4928, release_year, 17315 184, release_year, 15374 34241, has_tags, 34241 34241, release_year, 17315 34241, starred_actors, 4695 17433, release_year, 15374 17433, starred_actors, 17696 8324, has_genre, 32404 8324, has_tags, 17696 8324, has_tags, 13814 8324, release_year, 17315 8324, starred_actors, 17696 8324, starred_actors, 13814 25192, has_genre, 32404 25192, release_year, 17315 18707, has_genre, 32404 18707, release_year, 17315 27636, has_genre, 32404 27636, release_year, 17315 334, has_genre, 32404 334, release_year, 17315 36410, has_genre, 32404 36410, release_year, 15374 20223, has_genre, 32404 20223, release_year, 15374 24108, has_tags, 13814 24108, release_year, 15374 24108, starred_actors, 13814 36820, has_genre, 32404 36820, release_year, 15374 Question: For what reason are GUY X, RESURRECTING THE CHAMP, and ROBERT WEBB associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "GUY X", "RESURRECTING THE CHAMP", "ROBERT WEBB" ], "valid_edges": [ [ "1408", "has_tags", "SAMUEL L. JACKSON" ], [ "1408", "release_year", "2007" ], [ "30 DAYS OF NIGHT", "has_tags", "JOSH HARTNETT" ], [ "30 DAYS OF NIGHT", "release_year", "2007" ], [ "30 DAYS OF NIGHT", "starred_actors", "JOSH HARTNETT" ], [ "ARENA", "has_genre", "SPORT" ], [ "ARENA", "starred_actors", "SAMUEL L. JACKSON" ], [ "BALLS OF FURY", "has_genre", "SPORT" ], [ "BALLS OF FURY", "release_year", "2007" ], [ "CLEANER", "release_year", "2007" ], [ "CLEANER", "starred_actors", "SAMUEL L. JACKSON" ], [ "COACH CARTER", "has_genre", "SPORT" ], [ "COACH CARTER", "has_tags", "SAMUEL L. JACKSON" ], [ "COACH CARTER", "release_year", "2005" ], [ "COACH CARTER", "starred_actors", "SAMUEL L. JACKSON" ], [ "GRACIE", "has_genre", "SPORT" ], [ "GRACIE", "release_year", "2007" ], [ "GUY X", "release_year", "2005" ], [ "MAGICIANS", "has_tags", "MAGICIANS" ], [ "MAGICIANS", "release_year", "2007" ], [ "MAGICIANS", "starred_actors", "ROBERT WEBB" ], [ "MOZART AND THE WHALE", "release_year", "2005" ], [ "MOZART AND THE WHALE", "starred_actors", "JOSH HARTNETT" ], [ "RESURRECTING THE CHAMP", "has_genre", "SPORT" ], [ "RESURRECTING THE CHAMP", "has_tags", "JOSH HARTNETT" ], [ "RESURRECTING THE CHAMP", "has_tags", "SAMUEL L. JACKSON" ], [ "RESURRECTING THE CHAMP", "release_year", "2007" ], [ "RESURRECTING THE CHAMP", "starred_actors", "JOSH HARTNETT" ], [ "RESURRECTING THE CHAMP", "starred_actors", "SAMUEL L. JACKSON" ], [ "STEEP", "has_genre", "SPORT" ], [ "STEEP", "release_year", "2007" ], [ "THE COMEBACKS", "has_genre", "SPORT" ], [ "THE COMEBACKS", "release_year", "2007" ], [ "THE FINAL SEASON", "has_genre", "SPORT" ], [ "THE FINAL SEASON", "release_year", "2007" ], [ "THE GAME PLAN", "has_genre", "SPORT" ], [ "THE GAME PLAN", "release_year", "2007" ], [ "THE GREATEST GAME EVER PLAYED", "has_genre", "SPORT" ], [ "THE GREATEST GAME EVER PLAYED", "release_year", "2005" ], [ "THE LONGEST YARD", "has_genre", "SPORT" ], [ "THE LONGEST YARD", "release_year", "2005" ], [ "THE MAN", "has_tags", "SAMUEL L. JACKSON" ], [ "THE MAN", "release_year", "2005" ], [ "THE MAN", "starred_actors", "SAMUEL L. JACKSON" ], [ "TWO FOR THE MONEY", "has_genre", "SPORT" ], [ "TWO FOR THE MONEY", "release_year", "2005" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10997, A HIGH WIND IN JAMAICA 1148, CONFESSIONS 36212, DRAMA 17080, FIVE MINUTES OF HEAVEN 3369, GUY HIBBERT src, edge_attr, dst 10997, has_genre, 36212 1148, has_genre, 36212 17080, has_genre, 36212 17080, written_by, 3369 Question: How are A HIGH WIND IN JAMAICA, CONFESSIONS, and GUY HIBBERT related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "A HIGH WIND IN JAMAICA", "CONFESSIONS", "GUY HIBBERT" ], "valid_edges": [ [ "A HIGH WIND IN JAMAICA", "has_genre", "DRAMA" ], [ "CONFESSIONS", "has_genre", "DRAMA" ], [ "FIVE MINUTES OF HEAVEN", "has_genre", "DRAMA" ], [ "FIVE MINUTES OF HEAVEN", "written_by", "GUY HIBBERT" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26633, 1989 37224, 1990 10702, 1991 24438, 1993 3702, 1995 1006, 1996 4763, ADVENTURE 24177, ANIMATION 4329, ANNETTE BENING 26799, BACK TO THE FUTURE PART II 19219, BACK TO THE FUTURE PART III 34596, BLUE IN THE FACE 13903, BRIGHT LIGHTS, BIG CITY 9980, CASUALTIES OF WAR 23496, CHRISTOPHER LLOYD 30463, COMEDY 3160, DOC HOLLYWOOD 36212, DRAMA 26053, FOR LOVE OR MONEY 5585, GREEDY 17539, LEA THOMPSON 12766, LIFE WITH MIKEY 14951, LIGHT OF DAY 14985, MARS ATTACKS! 5678, MICHAEL J. FOX 27601, MICHAEL OLIVER 22398, MIDNIGHT MADNESS 22714, OWN 25436, PROBLEM CHILD 32090, ROBERT ZEMECKIS 32533, SCIENCE FICTION 22847, STUART LITTLE 20756, TEEN WOLF 2633, THE AMERICAN PRESIDENT 21684, THE FRIGHTENERS 39873, THE GOLDEN BOWL 32102, THE HARD WAY 38127, THOMAS F. WILSON 28129, TIME 6351, TIME TRAVEL src, edge_attr, dst 26799, directed_by, 32090 26799, has_genre, 4763 26799, has_tags, 4763 26799, has_tags, 23496 26799, has_tags, 17539 26799, has_tags, 5678 26799, has_tags, 22714 26799, has_tags, 32090 26799, has_tags, 32533 26799, has_tags, 28129 26799, has_tags, 6351 26799, release_year, 26633 26799, starred_actors, 23496 26799, starred_actors, 17539 26799, starred_actors, 5678 26799, starred_actors, 38127 26799, written_by, 32090 19219, directed_by, 32090 19219, has_genre, 4763 19219, has_tags, 4763 19219, has_tags, 23496 19219, has_tags, 17539 19219, has_tags, 5678 19219, has_tags, 22714 19219, has_tags, 32090 19219, has_tags, 32533 19219, has_tags, 28129 19219, has_tags, 6351 19219, release_year, 37224 19219, starred_actors, 23496 19219, starred_actors, 5678 19219, starred_actors, 38127 19219, written_by, 32090 34596, has_genre, 30463 34596, release_year, 3702 34596, starred_actors, 5678 13903, has_genre, 36212 13903, starred_actors, 5678 9980, has_genre, 36212 9980, release_year, 26633 9980, starred_actors, 5678 3160, has_genre, 30463 3160, has_tags, 30463 3160, has_tags, 5678 3160, release_year, 10702 3160, starred_actors, 5678 26053, has_genre, 30463 26053, has_tags, 5678 26053, release_year, 24438 26053, starred_actors, 5678 5585, has_genre, 30463 5585, has_tags, 5678 5585, starred_actors, 5678 12766, has_genre, 30463 12766, has_tags, 5678 12766, release_year, 24438 12766, starred_actors, 5678 14951, has_genre, 36212 14951, starred_actors, 5678 14985, has_genre, 30463 14985, has_tags, 24177 14985, has_tags, 4329 14985, has_tags, 30463 14985, has_tags, 5678 14985, release_year, 1006 14985, starred_actors, 4329 22398, has_genre, 30463 22398, has_tags, 5678 22398, starred_actors, 5678 25436, has_genre, 30463 25436, release_year, 37224 25436, starred_actors, 27601 22847, has_genre, 24177 22847, has_genre, 30463 22847, has_tags, 24177 22847, has_tags, 30463 22847, has_tags, 5678 22847, starred_actors, 5678 20756, has_genre, 30463 20756, has_tags, 30463 20756, has_tags, 5678 20756, starred_actors, 5678 2633, has_genre, 30463 2633, has_genre, 36212 2633, has_tags, 4329 2633, has_tags, 36212 2633, release_year, 3702 2633, starred_actors, 4329 2633, starred_actors, 5678 21684, has_genre, 30463 21684, has_tags, 5678 21684, release_year, 1006 21684, starred_actors, 5678 39873, has_genre, 36212 32102, has_genre, 30463 32102, has_genre, 36212 32102, has_tags, 5678 32102, release_year, 10702 32102, starred_actors, 5678 Question: How are MICHAEL J. FOX, MICHAEL OLIVER, and THE GOLDEN BOWL related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "MICHAEL J. FOX", "MICHAEL OLIVER", "THE GOLDEN BOWL" ], "valid_edges": [ [ "BACK TO THE FUTURE PART II", "directed_by", "ROBERT ZEMECKIS" ], [ "BACK TO THE FUTURE PART II", "has_genre", "ADVENTURE" ], [ "BACK TO THE FUTURE PART II", "has_tags", "ADVENTURE" ], [ "BACK TO THE FUTURE PART II", "has_tags", "CHRISTOPHER LLOYD" ], [ "BACK TO THE FUTURE PART II", "has_tags", "LEA THOMPSON" ], [ "BACK TO THE FUTURE PART II", "has_tags", "MICHAEL J. FOX" ], [ "BACK TO THE FUTURE PART II", "has_tags", "OWN" ], [ "BACK TO THE FUTURE PART II", "has_tags", "ROBERT ZEMECKIS" ], [ "BACK TO THE FUTURE PART II", "has_tags", "SCIENCE FICTION" ], [ "BACK TO THE FUTURE PART II", "has_tags", "TIME" ], [ "BACK TO THE FUTURE PART II", "has_tags", "TIME TRAVEL" ], [ "BACK TO THE FUTURE PART II", "release_year", "1989" ], [ "BACK TO THE FUTURE PART II", "starred_actors", "CHRISTOPHER LLOYD" ], [ "BACK TO THE FUTURE PART II", "starred_actors", "LEA THOMPSON" ], [ "BACK TO THE FUTURE PART II", "starred_actors", "MICHAEL J. FOX" ], [ "BACK TO THE FUTURE PART II", "starred_actors", "THOMAS F. WILSON" ], [ "BACK TO THE FUTURE PART II", "written_by", "ROBERT ZEMECKIS" ], [ "BACK TO THE FUTURE PART III", "directed_by", "ROBERT ZEMECKIS" ], [ "BACK TO THE FUTURE PART III", "has_genre", "ADVENTURE" ], [ "BACK TO THE FUTURE PART III", "has_tags", "ADVENTURE" ], [ "BACK TO THE FUTURE PART III", "has_tags", "CHRISTOPHER LLOYD" ], [ "BACK TO THE FUTURE PART III", "has_tags", "LEA THOMPSON" ], [ "BACK TO THE FUTURE PART III", "has_tags", "MICHAEL J. FOX" ], [ "BACK TO THE FUTURE PART III", "has_tags", "OWN" ], [ "BACK TO THE FUTURE PART III", "has_tags", "ROBERT ZEMECKIS" ], [ "BACK TO THE FUTURE PART III", "has_tags", "SCIENCE FICTION" ], [ "BACK TO THE FUTURE PART III", "has_tags", "TIME" ], [ "BACK TO THE FUTURE PART III", "has_tags", "TIME TRAVEL" ], [ "BACK TO THE FUTURE PART III", "release_year", "1990" ], [ "BACK TO THE FUTURE PART III", "starred_actors", "CHRISTOPHER LLOYD" ], [ "BACK TO THE FUTURE PART III", "starred_actors", "MICHAEL J. FOX" ], [ "BACK TO THE FUTURE PART III", "starred_actors", "THOMAS F. WILSON" ], [ "BACK TO THE FUTURE PART III", "written_by", "ROBERT ZEMECKIS" ], [ "BLUE IN THE FACE", "has_genre", "COMEDY" ], [ "BLUE IN THE FACE", "release_year", "1995" ], [ "BLUE IN THE FACE", "starred_actors", "MICHAEL J. FOX" ], [ "BRIGHT LIGHTS, BIG CITY", "has_genre", "DRAMA" ], [ "BRIGHT LIGHTS, BIG CITY", "starred_actors", "MICHAEL J. FOX" ], [ "CASUALTIES OF WAR", "has_genre", "DRAMA" ], [ "CASUALTIES OF WAR", "release_year", "1989" ], [ "CASUALTIES OF WAR", "starred_actors", "MICHAEL J. FOX" ], [ "DOC HOLLYWOOD", "has_genre", "COMEDY" ], [ "DOC HOLLYWOOD", "has_tags", "COMEDY" ], [ "DOC HOLLYWOOD", "has_tags", "MICHAEL J. FOX" ], [ "DOC HOLLYWOOD", "release_year", "1991" ], [ "DOC HOLLYWOOD", "starred_actors", "MICHAEL J. FOX" ], [ "FOR LOVE OR MONEY", "has_genre", "COMEDY" ], [ "FOR LOVE OR MONEY", "has_tags", "MICHAEL J. FOX" ], [ "FOR LOVE OR MONEY", "release_year", "1993" ], [ "FOR LOVE OR MONEY", "starred_actors", "MICHAEL J. FOX" ], [ "GREEDY", "has_genre", "COMEDY" ], [ "GREEDY", "has_tags", "MICHAEL J. FOX" ], [ "GREEDY", "starred_actors", "MICHAEL J. FOX" ], [ "LIFE WITH MIKEY", "has_genre", "COMEDY" ], [ "LIFE WITH MIKEY", "has_tags", "MICHAEL J. FOX" ], [ "LIFE WITH MIKEY", "release_year", "1993" ], [ "LIFE WITH MIKEY", "starred_actors", "MICHAEL J. FOX" ], [ "LIGHT OF DAY", "has_genre", "DRAMA" ], [ "LIGHT OF DAY", "starred_actors", "MICHAEL J. FOX" ], [ "MARS ATTACKS!", "has_genre", "COMEDY" ], [ "MARS ATTACKS!", "has_tags", "ANIMATION" ], [ "MARS ATTACKS!", "has_tags", "ANNETTE BENING" ], [ "MARS ATTACKS!", "has_tags", "COMEDY" ], [ "MARS ATTACKS!", "has_tags", "MICHAEL J. FOX" ], [ "MARS ATTACKS!", "release_year", "1996" ], [ "MARS ATTACKS!", "starred_actors", "ANNETTE BENING" ], [ "MIDNIGHT MADNESS", "has_genre", "COMEDY" ], [ "MIDNIGHT MADNESS", "has_tags", "MICHAEL J. FOX" ], [ "MIDNIGHT MADNESS", "starred_actors", "MICHAEL J. FOX" ], [ "PROBLEM CHILD", "has_genre", "COMEDY" ], [ "PROBLEM CHILD", "release_year", "1990" ], [ "PROBLEM CHILD", "starred_actors", "MICHAEL OLIVER" ], [ "STUART LITTLE", "has_genre", "ANIMATION" ], [ "STUART LITTLE", "has_genre", "COMEDY" ], [ "STUART LITTLE", "has_tags", "ANIMATION" ], [ "STUART LITTLE", "has_tags", "COMEDY" ], [ "STUART LITTLE", "has_tags", "MICHAEL J. FOX" ], [ "STUART LITTLE", "starred_actors", "MICHAEL J. FOX" ], [ "TEEN WOLF", "has_genre", "COMEDY" ], [ "TEEN WOLF", "has_tags", "COMEDY" ], [ "TEEN WOLF", "has_tags", "MICHAEL J. FOX" ], [ "TEEN WOLF", "starred_actors", "MICHAEL J. FOX" ], [ "THE AMERICAN PRESIDENT", "has_genre", "COMEDY" ], [ "THE AMERICAN PRESIDENT", "has_genre", "DRAMA" ], [ "THE AMERICAN PRESIDENT", "has_tags", "ANNETTE BENING" ], [ "THE AMERICAN PRESIDENT", "has_tags", "DRAMA" ], [ "THE AMERICAN PRESIDENT", "release_year", "1995" ], [ "THE AMERICAN PRESIDENT", "starred_actors", "ANNETTE BENING" ], [ "THE AMERICAN PRESIDENT", "starred_actors", "MICHAEL J. FOX" ], [ "THE FRIGHTENERS", "has_genre", "COMEDY" ], [ "THE FRIGHTENERS", "has_tags", "MICHAEL J. FOX" ], [ "THE FRIGHTENERS", "release_year", "1996" ], [ "THE FRIGHTENERS", "starred_actors", "MICHAEL J. FOX" ], [ "THE GOLDEN BOWL", "has_genre", "DRAMA" ], [ "THE HARD WAY", "has_genre", "COMEDY" ], [ "THE HARD WAY", "has_genre", "DRAMA" ], [ "THE HARD WAY", "has_tags", "MICHAEL J. FOX" ], [ "THE HARD WAY", "release_year", "1991" ], [ "THE HARD WAY", "starred_actors", "MICHAEL J. FOX" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10825, 1973 9377, 2014 9989, ALICE AND MARTIN 2975, BIRD PEOPLE 20757, CLOUDS OF SILS MARIA 39775, IN YOUR EYES 8248, JAPAN 36621, JEREMY 11017, JULIETTE BINOCHE 824, LATITUDES 37024, OUTRAGE 234, PEARL HARBOR 8379, ROMANCE 36977, THE GIRL WHO LEAPT THROUGH TIME 315, THE REWRITE src, edge_attr, dst 9989, has_genre, 8379 9989, starred_actors, 11017 2975, release_year, 9377 20757, release_year, 9377 20757, starred_actors, 11017 39775, has_genre, 8379 39775, release_year, 9377 36621, has_genre, 8379 36621, release_year, 10825 824, has_genre, 8379 824, release_year, 9377 37024, has_tags, 8248 37024, release_year, 10825 234, has_genre, 8379 234, has_tags, 8248 234, has_tags, 8379 36977, has_tags, 8248 36977, has_tags, 8379 315, has_genre, 8379 315, has_tags, 8379 315, release_year, 9377 Question: How are ALICE AND MARTIN, BIRD PEOPLE, and OUTRAGE related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ALICE AND MARTIN", "BIRD PEOPLE", "OUTRAGE" ], "valid_edges": [ [ "ALICE AND MARTIN", "has_genre", "ROMANCE" ], [ "ALICE AND MARTIN", "starred_actors", "JULIETTE BINOCHE" ], [ "BIRD PEOPLE", "release_year", "2014" ], [ "CLOUDS OF SILS MARIA", "release_year", "2014" ], [ "CLOUDS OF SILS MARIA", "starred_actors", "JULIETTE BINOCHE" ], [ "IN YOUR EYES", "has_genre", "ROMANCE" ], [ "IN YOUR EYES", "release_year", "2014" ], [ "JEREMY", "has_genre", "ROMANCE" ], [ "JEREMY", "release_year", "1973" ], [ "LATITUDES", "has_genre", "ROMANCE" ], [ "LATITUDES", "release_year", "2014" ], [ "OUTRAGE", "has_tags", "JAPAN" ], [ "OUTRAGE", "release_year", "1973" ], [ "PEARL HARBOR", "has_genre", "ROMANCE" ], [ "PEARL HARBOR", "has_tags", "JAPAN" ], [ "PEARL HARBOR", "has_tags", "ROMANCE" ], [ "THE GIRL WHO LEAPT THROUGH TIME", "has_tags", "JAPAN" ], [ "THE GIRL WHO LEAPT THROUGH TIME", "has_tags", "ROMANCE" ], [ "THE REWRITE", "has_genre", "ROMANCE" ], [ "THE REWRITE", "has_tags", "ROMANCE" ], [ "THE REWRITE", "release_year", "2014" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37967, 13 SINS 9377, 2014 37304, 21 JUMP STREET 26212, 3 DAYS TO KILL 6070, A BETTER WAY TO DIE 11686, A DARK TRUTH 29141, A MOST WANTED MAN 14987, A SECOND CHANCE 35101, ABDUCTION 39289, ACTION 35731, ACTION JACKSON 23806, ADDICTED 17258, AMERICAN HEIST 30709, AMERICAN SNIPER 20033, ANGEL 10248, ASSASSINATION 327, ASSASSINS 694, ASSAULT ON PRECINCT 13 23899, BAD COMPANY 36514, BRICK MANSIONS 6261, CELLULAR 20734, COBRA 28056, CONSPIRACY THEORY 9647, D-DAY 8961, DEATH PROOF 5148, DEATH RACE 23647, DERAILED 18348, DHOOM 6692, DISTRICT 9 38660, DIVERGENT 15961, DON 33511, DRACULA UNTOLD 32221, END OF DAYS 16653, ENEMIES CLOSER 8491, ESCAPE PLAN 28859, EXTREME OPS 25626, F/X 28271, F/X2 35493, FIRESTORM 21299, FIRST BLOOD 278, FORTRESS 26691, FREEZER 12703, GABRIEL 3724, GAMER 23299, GET CARTER 22832, GETAWAY 9642, GONE GIRL 13851, GOOD PEOPLE 37384, GUNDAY 22447, GUY BOLTON 9479, HANNA 12085, HAPPY NEW YEAR 19720, HAYWIRE 2752, HIDDEN AGENDA 25951, HIGHWAYMEN 29663, HOW TO TRAIN YOUR DRAGON 2 34230, I, FRANKENSTEIN 37328, ICEMAN 34211, IN ORDER OF DISAPPEARANCE 34430, IN THE BLOOD 23544, INCEPTION 33200, JESSABELLE 3365, JOHN WICK 32132, KILLER ELITE 26839, KILLERS 19523, LEFT BEHIND 35217, LOOPER 13743, LUCY 8068, MALEFICENT 18434, MAN ON A LEDGE 22373, MAN ON FIRE 36936, MAXIMUM CONVICTION 7626, NEED FOR SPEED 30350, NEXT 22868, NIGHTCRAWLER 29893, NO GOOD DEED 32201, NON-STOP 31027, NOT SAFE FOR WORK 17600, OFF LIMITS 4756, ONCE UPON A TIME IN SHANGHAI 12482, OPEN WINDOWS 32279, PARKER 21835, POINT BLANK 38688, POINT BREAK 10480, PREMIUM RUSH 16828, RACE WITH THE DEVIL 12428, RAGE 29252, REASONABLE DOUBT 18215, REDIRECTED 5554, RIDE ALONG 8516, ROBOCOP 29808, RONIN 2771, RUNNING ON KARMA 4804, S.W.A.T. 37097, SABOTAGE 30173, SALT 33939, SALTING THE BATTLEFIELD 10303, SEEKING JUSTICE 29005, SIN CITY 30321, SINNERS AND SAINTS 13, SNAKES ON A PLANE 31629, SO UNDERCOVER 27160, SOLO 2485, SPARKS 26269, STEREO 14619, STONEHEARST ASYLUM 30932, SWORDFISH 30003, TAKEN 22826, TAKEN 2 23782, TAKEN 3 27494, TAKERS 39976, TEENAGE MUTANT NINJA TURTLES 23821, THE BAG MAN 12208, THE BOURNE ULTIMATUM 30049, THE CAPTIVE 10912, THE EQUALIZER 2878, THE EVIL THAT MEN DO 24251, THE EXPENDABLES 3 19685, THE FINAL CUT 6524, THE GETAWAY 34975, THE GUEST 25954, THE HUNT FOR RED OCTOBER 4223, THE INTERVIEW 11904, THE KILLER ELITE 29213, THE LEGEND OF HERCULES 30751, THE LOFT 3760, THE MATRIX 11359, THE MAZE RUNNER 8839, THE MECHANIC 5250, THE MONKEY KING 15422, THE NEGOTIATOR 33328, THE NET 14632, THE NEXT MAN 31276, THE NUMBERS STATION 14064, THE OUTSIDER 22522, THE PEACEMAKER 30014, THE RAID 2 8660, THE RECKONING 20527, THE SCRIBBLER 28095, THE SIGNAL 22385, THE SUM OF ALL FEARS 25974, THE TRANSPORTER 23525, THE TWO FACES OF JANUARY 21593, THE VOICES 12441, THE WARRIORS 24811, THRILLER 14992, TRANSIT 22110, TRESPASS 37099, TRIANGLE 7138, TURBULENCE 10238, UNDERWORLD 5560, UNSTOPPABLE 12376, V FOR VENDETTA 5603, VEHICLE 19 26489, WELCOME TO THE PUNCH 6262, WHITE BIRD IN A BLIZZARD 32403, WHITE HOUSE DOWN 28356, WICKED BLOOD 36150, WILD GEESE II 31782, YOUNG ONES src, edge_attr, dst 37967, has_genre, 24811 37967, release_year, 9377 37304, has_genre, 39289 37304, has_tags, 9377 26212, has_genre, 39289 26212, has_genre, 24811 26212, release_year, 9377 6070, has_genre, 39289 6070, has_genre, 24811 11686, has_genre, 39289 11686, has_genre, 24811 29141, has_genre, 24811 29141, has_tags, 24811 29141, release_year, 9377 14987, has_genre, 24811 14987, release_year, 9377 35101, has_genre, 39289 35101, has_genre, 24811 35101, has_tags, 39289 35731, has_genre, 39289 35731, has_tags, 39289 35731, release_year, 9377 23806, has_genre, 24811 23806, release_year, 9377 17258, has_genre, 39289 17258, release_year, 9377 30709, has_genre, 39289 30709, release_year, 9377 20033, written_by, 22447 10248, has_genre, 39289 10248, has_genre, 24811 327, has_genre, 39289 327, has_genre, 24811 694, has_genre, 39289 694, has_genre, 24811 694, has_tags, 39289 23899, has_genre, 39289 23899, has_genre, 24811 23899, has_tags, 24811 36514, has_genre, 39289 36514, release_year, 9377 6261, has_genre, 24811 6261, has_tags, 39289 6261, has_tags, 24811 20734, has_genre, 39289 20734, has_tags, 39289 20734, has_tags, 24811 28056, has_genre, 39289 28056, has_tags, 24811 9647, has_genre, 39289 9647, has_genre, 24811 8961, has_genre, 39289 8961, has_genre, 24811 5148, has_genre, 39289 5148, has_genre, 24811 23647, has_genre, 39289 23647, has_genre, 24811 18348, has_genre, 39289 18348, has_genre, 24811 6692, has_genre, 39289 6692, has_genre, 24811 6692, has_tags, 39289 6692, has_tags, 24811 38660, has_tags, 39289 38660, release_year, 9377 15961, has_genre, 39289 15961, has_genre, 24811 33511, has_genre, 39289 33511, release_year, 9377 32221, has_genre, 39289 32221, has_tags, 24811 16653, has_genre, 39289 16653, has_genre, 24811 8491, has_genre, 39289 8491, has_genre, 24811 28859, has_genre, 39289 28859, has_genre, 24811 25626, has_genre, 39289 25626, has_genre, 24811 28271, has_genre, 39289 28271, has_genre, 24811 35493, has_genre, 39289 35493, has_genre, 24811 21299, has_genre, 39289 21299, has_genre, 24811 21299, has_tags, 39289 278, has_genre, 39289 278, has_genre, 24811 26691, has_genre, 39289 26691, has_genre, 24811 26691, release_year, 9377 12703, has_genre, 39289 12703, has_tags, 20033 3724, has_genre, 39289 3724, has_genre, 24811 3724, has_tags, 39289 23299, has_genre, 39289 23299, has_genre, 24811 22832, has_genre, 39289 22832, has_genre, 24811 9642, has_genre, 24811 9642, has_tags, 9377 9642, has_tags, 24811 9642, release_year, 9377 13851, has_genre, 24811 13851, release_year, 9377 37384, has_genre, 39289 37384, release_year, 9377 9479, has_genre, 39289 9479, has_genre, 24811 9479, has_tags, 39289 9479, has_tags, 24811 12085, has_genre, 39289 12085, release_year, 9377 19720, has_genre, 39289 19720, has_genre, 24811 19720, has_tags, 39289 2752, has_genre, 39289 2752, has_genre, 24811 25951, has_genre, 39289 25951, has_genre, 24811 29663, has_genre, 39289 29663, release_year, 9377 34230, has_genre, 39289 34230, release_year, 9377 37328, has_genre, 39289 37328, release_year, 9377 34211, has_genre, 39289 34211, release_year, 9377 34430, has_genre, 39289 34430, release_year, 9377 23544, has_genre, 39289 23544, has_tags, 39289 23544, has_tags, 24811 33200, has_genre, 24811 33200, release_year, 9377 3365, has_genre, 39289 3365, has_genre, 24811 3365, has_tags, 39289 32132, has_genre, 39289 32132, has_genre, 24811 32132, has_tags, 39289 26839, has_genre, 39289 26839, release_year, 9377 19523, has_genre, 39289 19523, has_genre, 24811 19523, release_year, 9377 35217, has_genre, 39289 35217, has_tags, 24811 13743, has_genre, 39289 13743, release_year, 9377 8068, has_genre, 39289 8068, release_year, 9377 18434, has_genre, 39289 18434, has_genre, 24811 22373, has_genre, 39289 22373, has_genre, 24811 22373, has_tags, 39289 36936, has_genre, 39289 36936, has_genre, 24811 7626, has_genre, 39289 7626, has_tags, 39289 7626, release_year, 9377 30350, has_genre, 39289 30350, has_genre, 24811 30350, has_tags, 39289 22868, has_genre, 24811 22868, has_tags, 24811 22868, release_year, 9377 29893, has_genre, 24811 29893, release_year, 9377 32201, has_genre, 39289 32201, release_year, 9377 31027, has_genre, 24811 31027, release_year, 9377 17600, has_genre, 39289 17600, has_genre, 24811 4756, has_genre, 39289 4756, release_year, 9377 12482, has_genre, 24811 12482, release_year, 9377 32279, has_genre, 39289 32279, has_genre, 24811 21835, has_genre, 39289 21835, has_genre, 24811 21835, has_tags, 39289 21835, has_tags, 24811 38688, has_genre, 39289 38688, has_genre, 24811 10480, has_genre, 39289 10480, has_genre, 24811 10480, has_tags, 39289 10480, has_tags, 24811 16828, has_genre, 39289 16828, has_genre, 24811 12428, has_genre, 39289 12428, has_genre, 24811 12428, release_year, 9377 29252, has_genre, 24811 29252, release_year, 9377 18215, has_genre, 39289 18215, release_year, 9377 5554, has_genre, 39289 5554, release_year, 9377 8516, has_genre, 39289 8516, has_tags, 39289 8516, release_year, 9377 29808, has_genre, 39289 29808, has_tags, 39289 29808, has_tags, 24811 2771, has_genre, 39289 2771, has_genre, 24811 4804, has_genre, 39289 4804, has_genre, 24811 4804, has_tags, 39289 37097, has_genre, 24811 37097, release_year, 9377 30173, has_genre, 39289 30173, has_tags, 39289 30173, has_tags, 24811 33939, has_genre, 39289 33939, release_year, 9377 10303, has_genre, 39289 10303, has_genre, 24811 10303, has_tags, 39289 29005, has_genre, 24811 29005, has_tags, 39289 30321, has_genre, 39289 30321, has_genre, 24811 13, has_genre, 39289 13, has_genre, 24811 31629, has_genre, 39289 27160, has_genre, 39289 27160, has_genre, 24811 2485, has_genre, 39289 2485, has_genre, 24811 26269, has_genre, 24811 26269, release_year, 9377 14619, has_genre, 24811 14619, release_year, 9377 30932, has_genre, 39289 30932, has_genre, 24811 30932, has_tags, 39289 30003, has_genre, 39289 30003, has_genre, 24811 30003, has_tags, 39289 30003, has_tags, 24811 22826, has_genre, 39289 22826, has_genre, 24811 23782, has_genre, 39289 23782, has_genre, 24811 23782, has_tags, 39289 23782, release_year, 9377 27494, has_genre, 39289 27494, has_genre, 24811 39976, has_genre, 39289 39976, has_tags, 39289 39976, release_year, 9377 23821, has_genre, 24811 23821, release_year, 9377 12208, has_genre, 39289 12208, has_genre, 24811 12208, has_tags, 39289 12208, has_tags, 24811 30049, has_genre, 24811 30049, release_year, 9377 10912, has_genre, 39289 10912, has_genre, 24811 10912, has_tags, 39289 10912, release_year, 9377 2878, has_genre, 39289 2878, has_genre, 24811 24251, has_genre, 39289 24251, release_year, 9377 19685, has_genre, 39289 19685, has_genre, 24811 6524, has_genre, 39289 6524, has_genre, 24811 34975, has_genre, 24811 34975, release_year, 9377 25954, has_genre, 39289 25954, has_genre, 24811 25954, has_tags, 39289 25954, has_tags, 24811 4223, has_genre, 39289 4223, has_genre, 24811 4223, release_year, 9377 11904, has_genre, 39289 11904, has_genre, 24811 29213, has_genre, 39289 29213, release_year, 9377 30751, has_genre, 24811 30751, release_year, 9377 3760, has_genre, 39289 3760, has_tags, 39289 3760, has_tags, 24811 11359, has_genre, 39289 11359, has_tags, 39289 11359, release_year, 9377 8839, has_genre, 39289 8839, has_genre, 24811 8839, has_tags, 39289 5250, has_genre, 39289 5250, release_year, 9377 15422, has_genre, 39289 15422, has_tags, 24811 33328, has_genre, 39289 33328, has_tags, 39289 33328, has_tags, 24811 14632, has_genre, 39289 14632, has_genre, 24811 31276, has_genre, 39289 31276, has_genre, 24811 14064, has_genre, 39289 14064, release_year, 9377 22522, has_genre, 39289 22522, has_genre, 24811 30014, has_genre, 39289 30014, has_tags, 39289 30014, release_year, 9377 8660, has_genre, 24811 8660, release_year, 9377 20527, has_genre, 24811 20527, release_year, 9377 28095, has_genre, 24811 28095, release_year, 9377 22385, has_genre, 39289 22385, has_genre, 24811 25974, has_genre, 39289 25974, has_genre, 24811 25974, has_tags, 39289 23525, has_genre, 24811 23525, release_year, 9377 21593, has_genre, 24811 21593, release_year, 9377 12441, has_genre, 39289 12441, has_genre, 24811 14992, has_genre, 39289 14992, has_genre, 24811 22110, has_genre, 39289 22110, has_genre, 24811 37099, has_genre, 39289 37099, has_genre, 24811 7138, has_genre, 39289 7138, has_genre, 24811 10238, has_genre, 39289 10238, has_genre, 24811 10238, has_tags, 39289 5560, has_genre, 39289 5560, has_genre, 24811 12376, has_genre, 39289 12376, has_genre, 24811 12376, has_tags, 39289 12376, has_tags, 24811 5603, has_genre, 39289 5603, has_genre, 24811 26489, has_genre, 39289 26489, has_genre, 24811 6262, has_genre, 24811 6262, release_year, 9377 32403, has_genre, 39289 32403, has_genre, 24811 32403, has_tags, 39289 32403, has_tags, 24811 28356, has_genre, 39289 28356, has_genre, 24811 28356, release_year, 9377 36150, has_genre, 39289 36150, has_genre, 24811 31782, has_genre, 39289 31782, release_year, 9377 Question: For what reason are A MOST WANTED MAN, GUY BOLTON, and SO UNDERCOVER associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "A MOST WANTED MAN", "GUY BOLTON", "SO UNDERCOVER" ], "valid_edges": [ [ "13 SINS", "has_genre", "THRILLER" ], [ "13 SINS", "release_year", "2014" ], [ "21 JUMP STREET", "has_genre", "ACTION" ], [ "21 JUMP STREET", "has_tags", "2014" ], [ "3 DAYS TO KILL", "has_genre", "ACTION" ], [ "3 DAYS TO KILL", "has_genre", "THRILLER" ], [ "3 DAYS TO KILL", "release_year", "2014" ], [ "A BETTER WAY TO DIE", "has_genre", "ACTION" ], [ "A BETTER WAY TO DIE", "has_genre", "THRILLER" ], [ "A DARK TRUTH", "has_genre", "ACTION" ], [ "A DARK TRUTH", "has_genre", "THRILLER" ], [ "A MOST WANTED MAN", "has_genre", "THRILLER" ], [ "A MOST WANTED MAN", "has_tags", "THRILLER" ], [ "A MOST WANTED MAN", "release_year", "2014" ], [ "A SECOND CHANCE", "has_genre", "THRILLER" ], [ "A SECOND CHANCE", "release_year", "2014" ], [ "ABDUCTION", "has_genre", "ACTION" ], [ "ABDUCTION", "has_genre", "THRILLER" ], [ "ABDUCTION", "has_tags", "ACTION" ], [ "ACTION JACKSON", "has_genre", "ACTION" ], [ "ACTION JACKSON", "has_tags", "ACTION" ], [ "ACTION JACKSON", "release_year", "2014" ], [ "ADDICTED", "has_genre", "THRILLER" ], [ "ADDICTED", "release_year", "2014" ], [ "AMERICAN HEIST", "has_genre", "ACTION" ], [ "AMERICAN HEIST", "release_year", "2014" ], [ "AMERICAN SNIPER", "has_genre", "ACTION" ], [ "AMERICAN SNIPER", "release_year", "2014" ], [ "ANGEL", "written_by", "GUY BOLTON" ], [ "ASSASSINATION", "has_genre", "ACTION" ], [ "ASSASSINATION", "has_genre", "THRILLER" ], [ "ASSASSINS", "has_genre", "ACTION" ], [ "ASSASSINS", "has_genre", "THRILLER" ], [ "ASSAULT ON PRECINCT 13", "has_genre", "ACTION" ], [ "ASSAULT ON PRECINCT 13", "has_genre", "THRILLER" ], [ "ASSAULT ON PRECINCT 13", "has_tags", "ACTION" ], [ "BAD COMPANY", "has_genre", "ACTION" ], [ "BAD COMPANY", "has_genre", "THRILLER" ], [ "BAD COMPANY", "has_tags", "THRILLER" ], [ "BRICK MANSIONS", "has_genre", "ACTION" ], [ "BRICK MANSIONS", "release_year", "2014" ], [ "CELLULAR", "has_genre", "THRILLER" ], [ "CELLULAR", "has_tags", "ACTION" ], [ "CELLULAR", "has_tags", "THRILLER" ], [ "COBRA", "has_genre", "ACTION" ], [ "COBRA", "has_tags", "ACTION" ], [ "COBRA", "has_tags", "THRILLER" ], [ "CONSPIRACY THEORY", "has_genre", "ACTION" ], [ "CONSPIRACY THEORY", "has_tags", "THRILLER" ], [ "D-DAY", "has_genre", "ACTION" ], [ "D-DAY", "has_genre", "THRILLER" ], [ "DEATH PROOF", "has_genre", "ACTION" ], [ "DEATH PROOF", "has_genre", "THRILLER" ], [ "DEATH RACE", "has_genre", "ACTION" ], [ "DEATH RACE", "has_genre", "THRILLER" ], [ "DERAILED", "has_genre", "ACTION" ], [ "DERAILED", "has_genre", "THRILLER" ], [ "DHOOM", "has_genre", "ACTION" ], [ "DHOOM", "has_genre", "THRILLER" ], [ "DISTRICT 9", "has_genre", "ACTION" ], [ "DISTRICT 9", "has_genre", "THRILLER" ], [ "DISTRICT 9", "has_tags", "ACTION" ], [ "DISTRICT 9", "has_tags", "THRILLER" ], [ "DIVERGENT", "has_tags", "ACTION" ], [ "DIVERGENT", "release_year", "2014" ], [ "DON", "has_genre", "ACTION" ], [ "DON", "has_genre", "THRILLER" ], [ "DRACULA UNTOLD", "has_genre", "ACTION" ], [ "DRACULA UNTOLD", "release_year", "2014" ], [ "END OF DAYS", "has_genre", "ACTION" ], [ "END OF DAYS", "has_tags", "THRILLER" ], [ "ENEMIES CLOSER", "has_genre", "ACTION" ], [ "ENEMIES CLOSER", "has_genre", "THRILLER" ], [ "ESCAPE PLAN", "has_genre", "ACTION" ], [ "ESCAPE PLAN", "has_genre", "THRILLER" ], [ "EXTREME OPS", "has_genre", "ACTION" ], [ "EXTREME OPS", "has_genre", "THRILLER" ], [ "F/X", "has_genre", "ACTION" ], [ "F/X", "has_genre", "THRILLER" ], [ "F/X2", "has_genre", "ACTION" ], [ "F/X2", "has_genre", "THRILLER" ], [ "FIRESTORM", "has_genre", "ACTION" ], [ "FIRESTORM", "has_genre", "THRILLER" ], [ "FIRST BLOOD", "has_genre", "ACTION" ], [ "FIRST BLOOD", "has_genre", "THRILLER" ], [ "FIRST BLOOD", "has_tags", "ACTION" ], [ "FORTRESS", "has_genre", "ACTION" ], [ "FORTRESS", "has_genre", "THRILLER" ], [ "FREEZER", "has_genre", "ACTION" ], [ "FREEZER", "has_genre", "THRILLER" ], [ "FREEZER", "release_year", "2014" ], [ "GABRIEL", "has_genre", "ACTION" ], [ "GABRIEL", "has_tags", "ANGEL" ], [ "GAMER", "has_genre", "ACTION" ], [ "GAMER", "has_genre", "THRILLER" ], [ "GAMER", "has_tags", "ACTION" ], [ "GET CARTER", "has_genre", "ACTION" ], [ "GET CARTER", "has_genre", "THRILLER" ], [ "GETAWAY", "has_genre", "ACTION" ], [ "GETAWAY", "has_genre", "THRILLER" ], [ "GONE GIRL", "has_genre", "THRILLER" ], [ "GONE GIRL", "has_tags", "2014" ], [ "GONE GIRL", "has_tags", "THRILLER" ], [ "GONE GIRL", "release_year", "2014" ], [ "GOOD PEOPLE", "has_genre", "THRILLER" ], [ "GOOD PEOPLE", "release_year", "2014" ], [ "GUNDAY", "has_genre", "ACTION" ], [ "GUNDAY", "release_year", "2014" ], [ "HANNA", "has_genre", "ACTION" ], [ "HANNA", "has_genre", "THRILLER" ], [ "HANNA", "has_tags", "ACTION" ], [ "HANNA", "has_tags", "THRILLER" ], [ "HAPPY NEW YEAR", "has_genre", "ACTION" ], [ "HAPPY NEW YEAR", "release_year", "2014" ], [ "HAYWIRE", "has_genre", "ACTION" ], [ "HAYWIRE", "has_genre", "THRILLER" ], [ "HAYWIRE", "has_tags", "ACTION" ], [ "HIDDEN AGENDA", "has_genre", "ACTION" ], [ "HIDDEN AGENDA", "has_genre", "THRILLER" ], [ "HIGHWAYMEN", "has_genre", "ACTION" ], [ "HIGHWAYMEN", "has_genre", "THRILLER" ], [ "HOW TO TRAIN YOUR DRAGON 2", "has_genre", "ACTION" ], [ "HOW TO TRAIN YOUR DRAGON 2", "release_year", "2014" ], [ "I, FRANKENSTEIN", "has_genre", "ACTION" ], [ "I, FRANKENSTEIN", "release_year", "2014" ], [ "ICEMAN", "has_genre", "ACTION" ], [ "ICEMAN", "release_year", "2014" ], [ "IN ORDER OF DISAPPEARANCE", "has_genre", "ACTION" ], [ "IN ORDER OF DISAPPEARANCE", "release_year", "2014" ], [ "IN THE BLOOD", "has_genre", "ACTION" ], [ "IN THE BLOOD", "release_year", "2014" ], [ "INCEPTION", "has_genre", "ACTION" ], [ "INCEPTION", "has_tags", "ACTION" ], [ "INCEPTION", "has_tags", "THRILLER" ], [ "JESSABELLE", "has_genre", "THRILLER" ], [ "JESSABELLE", "release_year", "2014" ], [ "JOHN WICK", "has_genre", "ACTION" ], [ "JOHN WICK", "has_genre", "THRILLER" ], [ "JOHN WICK", "has_tags", "ACTION" ], [ "KILLER ELITE", "has_genre", "ACTION" ], [ "KILLER ELITE", "has_genre", "THRILLER" ], [ "KILLER ELITE", "has_tags", "ACTION" ], [ "KILLERS", "has_genre", "ACTION" ], [ "KILLERS", "release_year", "2014" ], [ "LEFT BEHIND", "has_genre", "ACTION" ], [ "LEFT BEHIND", "has_genre", "THRILLER" ], [ "LEFT BEHIND", "release_year", "2014" ], [ "LOOPER", "has_genre", "ACTION" ], [ "LOOPER", "has_tags", "THRILLER" ], [ "LUCY", "has_genre", "ACTION" ], [ "LUCY", "release_year", "2014" ], [ "MALEFICENT", "has_genre", "ACTION" ], [ "MALEFICENT", "release_year", "2014" ], [ "MAN ON A LEDGE", "has_genre", "ACTION" ], [ "MAN ON A LEDGE", "has_genre", "THRILLER" ], [ "MAN ON FIRE", "has_genre", "ACTION" ], [ "MAN ON FIRE", "has_genre", "THRILLER" ], [ "MAN ON FIRE", "has_tags", "ACTION" ], [ "MAXIMUM CONVICTION", "has_genre", "ACTION" ], [ "MAXIMUM CONVICTION", "has_genre", "THRILLER" ], [ "NEED FOR SPEED", "has_genre", "ACTION" ], [ "NEED FOR SPEED", "has_tags", "ACTION" ], [ "NEED FOR SPEED", "release_year", "2014" ], [ "NEXT", "has_genre", "ACTION" ], [ "NEXT", "has_genre", "THRILLER" ], [ "NEXT", "has_tags", "ACTION" ], [ "NIGHTCRAWLER", "has_genre", "THRILLER" ], [ "NIGHTCRAWLER", "has_tags", "THRILLER" ], [ "NIGHTCRAWLER", "release_year", "2014" ], [ "NO GOOD DEED", "has_genre", "THRILLER" ], [ "NO GOOD DEED", "release_year", "2014" ], [ "NON-STOP", "has_genre", "ACTION" ], [ "NON-STOP", "release_year", "2014" ], [ "NOT SAFE FOR WORK", "has_genre", "THRILLER" ], [ "NOT SAFE FOR WORK", "release_year", "2014" ], [ "OFF LIMITS", "has_genre", "ACTION" ], [ "OFF LIMITS", "has_genre", "THRILLER" ], [ "ONCE UPON A TIME IN SHANGHAI", "has_genre", "ACTION" ], [ "ONCE UPON A TIME IN SHANGHAI", "release_year", "2014" ], [ "OPEN WINDOWS", "has_genre", "THRILLER" ], [ "OPEN WINDOWS", "release_year", "2014" ], [ "PARKER", "has_genre", "ACTION" ], [ "PARKER", "has_genre", "THRILLER" ], [ "POINT BLANK", "has_genre", "ACTION" ], [ "POINT BLANK", "has_genre", "THRILLER" ], [ "POINT BLANK", "has_tags", "ACTION" ], [ "POINT BLANK", "has_tags", "THRILLER" ], [ "POINT BREAK", "has_genre", "ACTION" ], [ "POINT BREAK", "has_genre", "THRILLER" ], [ "PREMIUM RUSH", "has_genre", "ACTION" ], [ "PREMIUM RUSH", "has_genre", "THRILLER" ], [ "PREMIUM RUSH", "has_tags", "ACTION" ], [ "PREMIUM RUSH", "has_tags", "THRILLER" ], [ "RACE WITH THE DEVIL", "has_genre", "ACTION" ], [ "RACE WITH THE DEVIL", "has_genre", "THRILLER" ], [ "RAGE", "has_genre", "ACTION" ], [ "RAGE", "has_genre", "THRILLER" ], [ "RAGE", "release_year", "2014" ], [ "REASONABLE DOUBT", "has_genre", "THRILLER" ], [ "REASONABLE DOUBT", "release_year", "2014" ], [ "REDIRECTED", "has_genre", "ACTION" ], [ "REDIRECTED", "release_year", "2014" ], [ "RIDE ALONG", "has_genre", "ACTION" ], [ "RIDE ALONG", "release_year", "2014" ], [ "ROBOCOP", "has_genre", "ACTION" ], [ "ROBOCOP", "has_tags", "ACTION" ], [ "ROBOCOP", "release_year", "2014" ], [ "RONIN", "has_genre", "ACTION" ], [ "RONIN", "has_tags", "ACTION" ], [ "RONIN", "has_tags", "THRILLER" ], [ "RUNNING ON KARMA", "has_genre", "ACTION" ], [ "RUNNING ON KARMA", "has_genre", "THRILLER" ], [ "S.W.A.T.", "has_genre", "ACTION" ], [ "S.W.A.T.", "has_genre", "THRILLER" ], [ "S.W.A.T.", "has_tags", "ACTION" ], [ "SABOTAGE", "has_genre", "THRILLER" ], [ "SABOTAGE", "release_year", "2014" ], [ "SALT", "has_genre", "ACTION" ], [ "SALT", "has_tags", "ACTION" ], [ "SALT", "has_tags", "THRILLER" ], [ "SALTING THE BATTLEFIELD", "has_genre", "ACTION" ], [ "SALTING THE BATTLEFIELD", "release_year", "2014" ], [ "SEEKING JUSTICE", "has_genre", "ACTION" ], [ "SEEKING JUSTICE", "has_genre", "THRILLER" ], [ "SEEKING JUSTICE", "has_tags", "ACTION" ], [ "SIN CITY", "has_genre", "THRILLER" ], [ "SIN CITY", "has_tags", "ACTION" ], [ "SINNERS AND SAINTS", "has_genre", "ACTION" ], [ "SINNERS AND SAINTS", "has_genre", "THRILLER" ], [ "SNAKES ON A PLANE", "has_genre", "ACTION" ], [ "SNAKES ON A PLANE", "has_genre", "THRILLER" ], [ "SO UNDERCOVER", "has_genre", "ACTION" ], [ "SOLO", "has_genre", "ACTION" ], [ "SOLO", "has_genre", "THRILLER" ], [ "SPARKS", "has_genre", "ACTION" ], [ "SPARKS", "has_genre", "THRILLER" ], [ "STEREO", "has_genre", "THRILLER" ], [ "STEREO", "release_year", "2014" ], [ "STONEHEARST ASYLUM", "has_genre", "THRILLER" ], [ "STONEHEARST ASYLUM", "release_year", "2014" ], [ "SWORDFISH", "has_genre", "ACTION" ], [ "SWORDFISH", "has_genre", "THRILLER" ], [ "SWORDFISH", "has_tags", "ACTION" ], [ "TAKEN", "has_genre", "ACTION" ], [ "TAKEN", "has_genre", "THRILLER" ], [ "TAKEN", "has_tags", "ACTION" ], [ "TAKEN", "has_tags", "THRILLER" ], [ "TAKEN 2", "has_genre", "ACTION" ], [ "TAKEN 2", "has_genre", "THRILLER" ], [ "TAKEN 3", "has_genre", "ACTION" ], [ "TAKEN 3", "has_genre", "THRILLER" ], [ "TAKEN 3", "has_tags", "ACTION" ], [ "TAKEN 3", "release_year", "2014" ], [ "TAKERS", "has_genre", "ACTION" ], [ "TAKERS", "has_genre", "THRILLER" ], [ "TEENAGE MUTANT NINJA TURTLES", "has_genre", "ACTION" ], [ "TEENAGE MUTANT NINJA TURTLES", "has_tags", "ACTION" ], [ "TEENAGE MUTANT NINJA TURTLES", "release_year", "2014" ], [ "THE BAG MAN", "has_genre", "THRILLER" ], [ "THE BAG MAN", "release_year", "2014" ], [ "THE BOURNE ULTIMATUM", "has_genre", "ACTION" ], [ "THE BOURNE ULTIMATUM", "has_genre", "THRILLER" ], [ "THE BOURNE ULTIMATUM", "has_tags", "ACTION" ], [ "THE BOURNE ULTIMATUM", "has_tags", "THRILLER" ], [ "THE CAPTIVE", "has_genre", "THRILLER" ], [ "THE CAPTIVE", "release_year", "2014" ], [ "THE EQUALIZER", "has_genre", "ACTION" ], [ "THE EQUALIZER", "has_genre", "THRILLER" ], [ "THE EQUALIZER", "has_tags", "ACTION" ], [ "THE EQUALIZER", "release_year", "2014" ], [ "THE EVIL THAT MEN DO", "has_genre", "ACTION" ], [ "THE EVIL THAT MEN DO", "has_genre", "THRILLER" ], [ "THE EXPENDABLES 3", "has_genre", "ACTION" ], [ "THE EXPENDABLES 3", "release_year", "2014" ], [ "THE FINAL CUT", "has_genre", "ACTION" ], [ "THE FINAL CUT", "has_genre", "THRILLER" ], [ "THE GETAWAY", "has_genre", "ACTION" ], [ "THE GETAWAY", "has_genre", "THRILLER" ], [ "THE GUEST", "has_genre", "THRILLER" ], [ "THE GUEST", "release_year", "2014" ], [ "THE HUNT FOR RED OCTOBER", "has_genre", "ACTION" ], [ "THE HUNT FOR RED OCTOBER", "has_genre", "THRILLER" ], [ "THE HUNT FOR RED OCTOBER", "has_tags", "ACTION" ], [ "THE HUNT FOR RED OCTOBER", "has_tags", "THRILLER" ], [ "THE INTERVIEW", "has_genre", "ACTION" ], [ "THE INTERVIEW", "has_genre", "THRILLER" ], [ "THE INTERVIEW", "release_year", "2014" ], [ "THE KILLER ELITE", "has_genre", "ACTION" ], [ "THE KILLER ELITE", "has_genre", "THRILLER" ], [ "THE LEGEND OF HERCULES", "has_genre", "ACTION" ], [ "THE LEGEND OF HERCULES", "release_year", "2014" ], [ "THE LOFT", "has_genre", "THRILLER" ], [ "THE LOFT", "release_year", "2014" ], [ "THE MATRIX", "has_genre", "ACTION" ], [ "THE MATRIX", "has_tags", "ACTION" ], [ "THE MATRIX", "has_tags", "THRILLER" ], [ "THE MAZE RUNNER", "has_genre", "ACTION" ], [ "THE MAZE RUNNER", "has_tags", "ACTION" ], [ "THE MAZE RUNNER", "release_year", "2014" ], [ "THE MECHANIC", "has_genre", "ACTION" ], [ "THE MECHANIC", "has_genre", "THRILLER" ], [ "THE MECHANIC", "has_tags", "ACTION" ], [ "THE MONKEY KING", "has_genre", "ACTION" ], [ "THE MONKEY KING", "release_year", "2014" ], [ "THE NEGOTIATOR", "has_genre", "ACTION" ], [ "THE NEGOTIATOR", "has_tags", "THRILLER" ], [ "THE NET", "has_genre", "ACTION" ], [ "THE NET", "has_tags", "ACTION" ], [ "THE NET", "has_tags", "THRILLER" ], [ "THE NEXT MAN", "has_genre", "ACTION" ], [ "THE NEXT MAN", "has_genre", "THRILLER" ], [ "THE NUMBERS STATION", "has_genre", "ACTION" ], [ "THE NUMBERS STATION", "has_genre", "THRILLER" ], [ "THE OUTSIDER", "has_genre", "ACTION" ], [ "THE OUTSIDER", "release_year", "2014" ], [ "THE PEACEMAKER", "has_genre", "ACTION" ], [ "THE PEACEMAKER", "has_genre", "THRILLER" ], [ "THE RAID 2", "has_genre", "ACTION" ], [ "THE RAID 2", "has_tags", "ACTION" ], [ "THE RAID 2", "release_year", "2014" ], [ "THE RECKONING", "has_genre", "THRILLER" ], [ "THE RECKONING", "release_year", "2014" ], [ "THE SCRIBBLER", "has_genre", "THRILLER" ], [ "THE SCRIBBLER", "release_year", "2014" ], [ "THE SIGNAL", "has_genre", "THRILLER" ], [ "THE SIGNAL", "release_year", "2014" ], [ "THE SUM OF ALL FEARS", "has_genre", "ACTION" ], [ "THE SUM OF ALL FEARS", "has_genre", "THRILLER" ], [ "THE TRANSPORTER", "has_genre", "ACTION" ], [ "THE TRANSPORTER", "has_genre", "THRILLER" ], [ "THE TRANSPORTER", "has_tags", "ACTION" ], [ "THE TWO FACES OF JANUARY", "has_genre", "THRILLER" ], [ "THE TWO FACES OF JANUARY", "release_year", "2014" ], [ "THE VOICES", "has_genre", "THRILLER" ], [ "THE VOICES", "release_year", "2014" ], [ "THE WARRIORS", "has_genre", "ACTION" ], [ "THE WARRIORS", "has_genre", "THRILLER" ], [ "TRANSIT", "has_genre", "ACTION" ], [ "TRANSIT", "has_genre", "THRILLER" ], [ "TRESPASS", "has_genre", "ACTION" ], [ "TRESPASS", "has_genre", "THRILLER" ], [ "TRIANGLE", "has_genre", "ACTION" ], [ "TRIANGLE", "has_genre", "THRILLER" ], [ "TURBULENCE", "has_genre", "ACTION" ], [ "TURBULENCE", "has_genre", "THRILLER" ], [ "UNDERWORLD", "has_genre", "ACTION" ], [ "UNDERWORLD", "has_genre", "THRILLER" ], [ "UNDERWORLD", "has_tags", "ACTION" ], [ "UNSTOPPABLE", "has_genre", "ACTION" ], [ "UNSTOPPABLE", "has_genre", "THRILLER" ], [ "V FOR VENDETTA", "has_genre", "ACTION" ], [ "V FOR VENDETTA", "has_genre", "THRILLER" ], [ "V FOR VENDETTA", "has_tags", "ACTION" ], [ "V FOR VENDETTA", "has_tags", "THRILLER" ], [ "VEHICLE 19", "has_genre", "ACTION" ], [ "VEHICLE 19", "has_genre", "THRILLER" ], [ "WELCOME TO THE PUNCH", "has_genre", "ACTION" ], [ "WELCOME TO THE PUNCH", "has_genre", "THRILLER" ], [ "WHITE BIRD IN A BLIZZARD", "has_genre", "THRILLER" ], [ "WHITE BIRD IN A BLIZZARD", "release_year", "2014" ], [ "WHITE HOUSE DOWN", "has_genre", "ACTION" ], [ "WHITE HOUSE DOWN", "has_genre", "THRILLER" ], [ "WHITE HOUSE DOWN", "has_tags", "ACTION" ], [ "WHITE HOUSE DOWN", "has_tags", "THRILLER" ], [ "WICKED BLOOD", "has_genre", "ACTION" ], [ "WICKED BLOOD", "has_genre", "THRILLER" ], [ "WICKED BLOOD", "release_year", "2014" ], [ "WILD GEESE II", "has_genre", "ACTION" ], [ "WILD GEESE II", "has_genre", "THRILLER" ], [ "YOUNG ONES", "has_genre", "ACTION" ], [ "YOUNG ONES", "release_year", "2014" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 135, 1926 8486, 1999 29818, 3 BAD MEN 22900, DUEL IN THE SUN 22149, LIONEL BARRYMORE 36671, MAIA CAMPBELL 8379, ROMANCE 35403, TEARS OF THE BLACK TIGER 26527, THE BELLS 28418, THE TEMPTRESS 28632, THE VIRGINIAN 10866, THE WINNING OF BARBARA WORTH 23874, TRIPPIN' 36026, WESTERN src, edge_attr, dst 29818, has_genre, 36026 29818, release_year, 135 22900, has_genre, 36026 22900, starred_actors, 22149 8379, release_year, 8486 35403, has_genre, 8379 35403, has_tags, 36026 26527, release_year, 135 26527, starred_actors, 22149 28418, release_year, 135 28418, starred_actors, 22149 28632, has_genre, 8379 28632, has_genre, 36026 10866, has_genre, 36026 10866, release_year, 135 23874, release_year, 8486 23874, starred_actors, 36671 Question: In what context are MAIA CAMPBELL, TEARS OF THE BLACK TIGER, and THE BELLS connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "MAIA CAMPBELL", "TEARS OF THE BLACK TIGER", "THE BELLS" ], "valid_edges": [ [ "3 BAD MEN", "has_genre", "WESTERN" ], [ "3 BAD MEN", "release_year", "1926" ], [ "DUEL IN THE SUN", "has_genre", "WESTERN" ], [ "DUEL IN THE SUN", "starred_actors", "LIONEL BARRYMORE" ], [ "ROMANCE", "release_year", "1999" ], [ "TEARS OF THE BLACK TIGER", "has_genre", "ROMANCE" ], [ "TEARS OF THE BLACK TIGER", "has_tags", "WESTERN" ], [ "THE BELLS", "release_year", "1926" ], [ "THE BELLS", "starred_actors", "LIONEL BARRYMORE" ], [ "THE TEMPTRESS", "release_year", "1926" ], [ "THE TEMPTRESS", "starred_actors", "LIONEL BARRYMORE" ], [ "THE VIRGINIAN", "has_genre", "ROMANCE" ], [ "THE VIRGINIAN", "has_genre", "WESTERN" ], [ "THE WINNING OF BARBARA WORTH", "has_genre", "WESTERN" ], [ "THE WINNING OF BARBARA WORTH", "release_year", "1926" ], [ "TRIPPIN'", "release_year", "1999" ], [ "TRIPPIN'", "starred_actors", "MAIA CAMPBELL" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 4608, CLASS 19379, CRUEL INTENTIONS 2 36212, DRAMA 33112, ROGER KUMBLE 8673, THE TURIN HORSE src, edge_attr, dst 4608, has_genre, 36212 19379, directed_by, 33112 19379, has_genre, 36212 19379, written_by, 33112 8673, has_genre, 36212 Question: For what reason are CLASS, ROGER KUMBLE, and THE TURIN HORSE associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CLASS", "ROGER KUMBLE", "THE TURIN HORSE" ], "valid_edges": [ [ "CLASS", "has_genre", "DRAMA" ], [ "CRUEL INTENTIONS 2", "directed_by", "ROGER KUMBLE" ], [ "CRUEL INTENTIONS 2", "has_genre", "DRAMA" ], [ "CRUEL INTENTIONS 2", "written_by", "ROGER KUMBLE" ], [ "THE TURIN HORSE", "has_genre", "DRAMA" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 22772, 1961 17315, 2007 8265, ALDO GIUFFRÈ 944, BRIDGE TO THE SUN 22600, JUDGMENT AT NUREMBERG 20807, NICHOLAS BRENDON 17275, THE FOUR DAYS OF NAPLES 39789, THE LAST TIME I SAW ARCHIE 27987, UNHOLY 22214, WAR src, edge_attr, dst 944, has_genre, 22214 944, release_year, 22772 22600, has_genre, 22214 22600, has_tags, 22214 22600, release_year, 22772 17275, has_genre, 22214 17275, starred_actors, 8265 39789, has_genre, 22214 39789, release_year, 22772 27987, release_year, 17315 27987, starred_actors, 20807 22214, release_year, 17315 Question: In what context are ALDO GIUFFRÈ, BRIDGE TO THE SUN, and NICHOLAS BRENDON connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ALDO GIUFFRÈ", "BRIDGE TO THE SUN", "NICHOLAS BRENDON" ], "valid_edges": [ [ "BRIDGE TO THE SUN", "has_genre", "WAR" ], [ "BRIDGE TO THE SUN", "release_year", "1961" ], [ "JUDGMENT AT NUREMBERG", "has_genre", "WAR" ], [ "JUDGMENT AT NUREMBERG", "has_tags", "WAR" ], [ "JUDGMENT AT NUREMBERG", "release_year", "1961" ], [ "THE FOUR DAYS OF NAPLES", "has_genre", "WAR" ], [ "THE FOUR DAYS OF NAPLES", "starred_actors", "ALDO GIUFFRÈ" ], [ "THE LAST TIME I SAW ARCHIE", "has_genre", "WAR" ], [ "THE LAST TIME I SAW ARCHIE", "release_year", "1961" ], [ "UNHOLY", "release_year", "2007" ], [ "UNHOLY", "starred_actors", "NICHOLAS BRENDON" ], [ "WAR", "release_year", "2007" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27810, 1968 7841, 1987 9589, BLUE 9585, CORRUPTION 36953, DORIS DAY 31444, KARL MALDEN 24089, NUTS 35865, ON THE WATERFRONT 10317, RON LINK 35453, WHERE WERE YOU WHEN THE LIGHTS WENT OUT? 3600, WITH SIX YOU GET EGGROLL 16941, ZOMBIE HIGH src, edge_attr, dst 9589, release_year, 27810 9589, starred_actors, 31444 9585, release_year, 27810 24089, release_year, 7841 24089, starred_actors, 31444 35865, has_tags, 9585 35865, has_tags, 31444 35865, starred_actors, 31444 35453, release_year, 27810 35453, starred_actors, 36953 3600, release_year, 27810 3600, starred_actors, 36953 16941, directed_by, 10317 16941, release_year, 7841 Question: For what reason are KARL MALDEN, RON LINK, and WHERE WERE YOU WHEN THE LIGHTS WENT OUT? associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "KARL MALDEN", "RON LINK", "WHERE WERE YOU WHEN THE LIGHTS WENT OUT?" ], "valid_edges": [ [ "BLUE", "release_year", "1968" ], [ "BLUE", "starred_actors", "KARL MALDEN" ], [ "CORRUPTION", "release_year", "1968" ], [ "NUTS", "release_year", "1987" ], [ "NUTS", "starred_actors", "KARL MALDEN" ], [ "ON THE WATERFRONT", "has_tags", "CORRUPTION" ], [ "ON THE WATERFRONT", "has_tags", "KARL MALDEN" ], [ "ON THE WATERFRONT", "starred_actors", "KARL MALDEN" ], [ "WHERE WERE YOU WHEN THE LIGHTS WENT OUT?", "release_year", "1968" ], [ "WHERE WERE YOU WHEN THE LIGHTS WENT OUT?", "starred_actors", "DORIS DAY" ], [ "WITH SIX YOU GET EGGROLL", "release_year", "1968" ], [ "WITH SIX YOU GET EGGROLL", "starred_actors", "DORIS DAY" ], [ "ZOMBIE HIGH", "directed_by", "RON LINK" ], [ "ZOMBIE HIGH", "release_year", "1987" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6238, A BRIEF HISTORY OF TIME 12841, DOCUMENTARY 13596, ERROL MORRIS 21005, FOR THE BIBLE TELLS ME SO 24544, GENE ROBINSON 9975, JEFFREY FRIEDMAN 37499, PARAGRAPH 175 21801, ROB EPSTEIN 24948, THE CELLULOID CLOSET 11160, THE THIN BLUE LINE 38742, THE UNKNOWN KNOWN src, edge_attr, dst 6238, directed_by, 13596 6238, has_genre, 12841 6238, has_tags, 13596 21005, has_genre, 12841 21005, has_tags, 12841 21005, starred_actors, 24544 37499, directed_by, 9975 37499, directed_by, 21801 37499, has_genre, 12841 24948, directed_by, 9975 24948, directed_by, 21801 24948, has_genre, 12841 24948, has_tags, 12841 24948, has_tags, 21801 24948, written_by, 9975 24948, written_by, 21801 11160, directed_by, 13596 11160, has_genre, 12841 11160, has_tags, 13596 11160, written_by, 13596 38742, directed_by, 13596 38742, has_genre, 12841 38742, starred_actors, 13596 38742, written_by, 13596 Question: For what reason are ERROL MORRIS, GENE ROBINSON, and JEFFREY FRIEDMAN associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ERROL MORRIS", "GENE ROBINSON", "JEFFREY FRIEDMAN" ], "valid_edges": [ [ "A BRIEF HISTORY OF TIME", "directed_by", "ERROL MORRIS" ], [ "A BRIEF HISTORY OF TIME", "has_genre", "DOCUMENTARY" ], [ "A BRIEF HISTORY OF TIME", "has_tags", "ERROL MORRIS" ], [ "FOR THE BIBLE TELLS ME SO", "has_genre", "DOCUMENTARY" ], [ "FOR THE BIBLE TELLS ME SO", "has_tags", "DOCUMENTARY" ], [ "FOR THE BIBLE TELLS ME SO", "starred_actors", "GENE ROBINSON" ], [ "PARAGRAPH 175", "directed_by", "JEFFREY FRIEDMAN" ], [ "PARAGRAPH 175", "directed_by", "ROB EPSTEIN" ], [ "PARAGRAPH 175", "has_genre", "DOCUMENTARY" ], [ "THE CELLULOID CLOSET", "directed_by", "JEFFREY FRIEDMAN" ], [ "THE CELLULOID CLOSET", "directed_by", "ROB EPSTEIN" ], [ "THE CELLULOID CLOSET", "has_genre", "DOCUMENTARY" ], [ "THE CELLULOID CLOSET", "has_tags", "DOCUMENTARY" ], [ "THE CELLULOID CLOSET", "has_tags", "ROB EPSTEIN" ], [ "THE CELLULOID CLOSET", "written_by", "JEFFREY FRIEDMAN" ], [ "THE CELLULOID CLOSET", "written_by", "ROB EPSTEIN" ], [ "THE THIN BLUE LINE", "directed_by", "ERROL MORRIS" ], [ "THE THIN BLUE LINE", "has_genre", "DOCUMENTARY" ], [ "THE THIN BLUE LINE", "has_tags", "ERROL MORRIS" ], [ "THE THIN BLUE LINE", "written_by", "ERROL MORRIS" ], [ "THE UNKNOWN KNOWN", "directed_by", "ERROL MORRIS" ], [ "THE UNKNOWN KNOWN", "has_genre", "DOCUMENTARY" ], [ "THE UNKNOWN KNOWN", "starred_actors", "ERROL MORRIS" ], [ "THE UNKNOWN KNOWN", "written_by", "ERROL MORRIS" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 14259, 1997 36580, BARRY GIFFORD 15936, DAVID LYNCH 28252, DISTANT DRUMS 278, FORTRESS 37809, LORYN LOCKLIN 398, LOST HIGHWAY 24811, THRILLER 36026, WESTERN 18038, WILD AT HEART src, edge_attr, dst 28252, has_genre, 36026 278, has_genre, 24811 278, starred_actors, 37809 398, directed_by, 15936 398, has_genre, 24811 398, has_tags, 15936 398, release_year, 14259 398, written_by, 36580 398, written_by, 15936 36026, release_year, 14259 18038, directed_by, 15936 18038, has_genre, 24811 18038, has_tags, 15936 18038, written_by, 36580 18038, written_by, 15936 Question: How are BARRY GIFFORD, DISTANT DRUMS, and LORYN LOCKLIN related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BARRY GIFFORD", "DISTANT DRUMS", "LORYN LOCKLIN" ], "valid_edges": [ [ "DISTANT DRUMS", "has_genre", "WESTERN" ], [ "FORTRESS", "has_genre", "THRILLER" ], [ "FORTRESS", "starred_actors", "LORYN LOCKLIN" ], [ "LOST HIGHWAY", "directed_by", "DAVID LYNCH" ], [ "LOST HIGHWAY", "has_genre", "THRILLER" ], [ "LOST HIGHWAY", "has_tags", "DAVID LYNCH" ], [ "LOST HIGHWAY", "release_year", "1997" ], [ "LOST HIGHWAY", "written_by", "BARRY GIFFORD" ], [ "LOST HIGHWAY", "written_by", "DAVID LYNCH" ], [ "WESTERN", "release_year", "1997" ], [ "WILD AT HEART", "directed_by", "DAVID LYNCH" ], [ "WILD AT HEART", "has_genre", "THRILLER" ], [ "WILD AT HEART", "has_tags", "DAVID LYNCH" ], [ "WILD AT HEART", "written_by", "BARRY GIFFORD" ], [ "WILD AT HEART", "written_by", "DAVID LYNCH" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 724, 1979 6405, APOCALYPSE NOW 32828, BADLANDS 11298, BOLIVIA 35953, BUTCH CASSIDY AND THE SUNDANCE KID 6267, MARTIN SHEEN 37497, NATIONAL FILM REGISTRY 17018, WILLIAM RICHERT 1934, WINTER KILLS src, edge_attr, dst 6405, has_tags, 6267 6405, has_tags, 37497 6405, release_year, 724 6405, starred_actors, 6267 32828, has_tags, 6267 32828, has_tags, 37497 32828, starred_actors, 6267 35953, has_tags, 11298 35953, has_tags, 37497 1934, directed_by, 17018 1934, release_year, 724 1934, written_by, 17018 Question: In what context are BOLIVIA, MARTIN SHEEN, and WILLIAM RICHERT connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BOLIVIA", "MARTIN SHEEN", "WILLIAM RICHERT" ], "valid_edges": [ [ "APOCALYPSE NOW", "has_tags", "MARTIN SHEEN" ], [ "APOCALYPSE NOW", "has_tags", "NATIONAL FILM REGISTRY" ], [ "APOCALYPSE NOW", "release_year", "1979" ], [ "APOCALYPSE NOW", "starred_actors", "MARTIN SHEEN" ], [ "BADLANDS", "has_tags", "MARTIN SHEEN" ], [ "BADLANDS", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BADLANDS", "starred_actors", "MARTIN SHEEN" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "BOLIVIA" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "NATIONAL FILM REGISTRY" ], [ "WINTER KILLS", "directed_by", "WILLIAM RICHERT" ], [ "WINTER KILLS", "release_year", "1979" ], [ "WINTER KILLS", "written_by", "WILLIAM RICHERT" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27810, 1968 17315, 2007 14403, BATTLE FOR TERRA 9790, BLAKE EDWARDS 5241, DARLING LILI 5038, FINIAN'S RAINBOW 29924, FRED ASTAIRE 16002, FRED SAIDY 18638, INSPECTOR CLOUSEAU 30818, JACK LEMMON 16406, JULIE ANDREWS 24593, MUSICAL 8397, MY SISTER EILEEN 35298, OPERATION MAD BALL 33297, OPERATION PETTICOAT 36805, RICHARD QUINE 18254, THE NOTORIOUS LANDLADY 929, THE PARTY 32562, VICTOR VICTORIA 22214, WAR src, edge_attr, dst 14403, release_year, 17315 5241, directed_by, 9790 5241, has_genre, 24593 5241, starred_actors, 16406 5241, written_by, 9790 5038, has_genre, 24593 5038, has_tags, 29924 5038, has_tags, 24593 5038, release_year, 27810 5038, starred_actors, 29924 5038, written_by, 16002 18638, release_year, 27810 18638, written_by, 9790 8397, directed_by, 36805 8397, has_genre, 24593 8397, starred_actors, 30818 8397, written_by, 9790 8397, written_by, 36805 35298, directed_by, 36805 35298, has_genre, 22214 35298, starred_actors, 30818 35298, written_by, 9790 33297, directed_by, 9790 33297, has_genre, 22214 33297, has_tags, 9790 18254, directed_by, 36805 18254, has_tags, 30818 18254, starred_actors, 29924 18254, starred_actors, 30818 18254, written_by, 9790 929, directed_by, 9790 929, has_tags, 9790 929, release_year, 27810 929, written_by, 9790 32562, directed_by, 9790 32562, has_genre, 24593 32562, has_tags, 9790 32562, has_tags, 16406 32562, starred_actors, 16406 32562, written_by, 9790 22214, release_year, 17315 Question: For what reason are BATTLE FOR TERRA, BLAKE EDWARDS, and FRED SAIDY associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BATTLE FOR TERRA", "BLAKE EDWARDS", "FRED SAIDY" ], "valid_edges": [ [ "BATTLE FOR TERRA", "release_year", "2007" ], [ "DARLING LILI", "directed_by", "BLAKE EDWARDS" ], [ "DARLING LILI", "has_genre", "MUSICAL" ], [ "DARLING LILI", "starred_actors", "JULIE ANDREWS" ], [ "DARLING LILI", "written_by", "BLAKE EDWARDS" ], [ "FINIAN'S RAINBOW", "has_genre", "MUSICAL" ], [ "FINIAN'S RAINBOW", "has_tags", "FRED ASTAIRE" ], [ "FINIAN'S RAINBOW", "has_tags", "MUSICAL" ], [ "FINIAN'S RAINBOW", "release_year", "1968" ], [ "FINIAN'S RAINBOW", "starred_actors", "FRED ASTAIRE" ], [ "FINIAN'S RAINBOW", "written_by", "FRED SAIDY" ], [ "INSPECTOR CLOUSEAU", "release_year", "1968" ], [ "INSPECTOR CLOUSEAU", "written_by", "BLAKE EDWARDS" ], [ "MY SISTER EILEEN", "directed_by", "RICHARD QUINE" ], [ "MY SISTER EILEEN", "has_genre", "MUSICAL" ], [ "MY SISTER EILEEN", "starred_actors", "JACK LEMMON" ], [ "MY SISTER EILEEN", "written_by", "BLAKE EDWARDS" ], [ "MY SISTER EILEEN", "written_by", "RICHARD QUINE" ], [ "OPERATION MAD BALL", "directed_by", "RICHARD QUINE" ], [ "OPERATION MAD BALL", "has_genre", "WAR" ], [ "OPERATION MAD BALL", "starred_actors", "JACK LEMMON" ], [ "OPERATION MAD BALL", "written_by", "BLAKE EDWARDS" ], [ "OPERATION PETTICOAT", "directed_by", "BLAKE EDWARDS" ], [ "OPERATION PETTICOAT", "has_genre", "WAR" ], [ "OPERATION PETTICOAT", "has_tags", "BLAKE EDWARDS" ], [ "THE NOTORIOUS LANDLADY", "directed_by", "RICHARD QUINE" ], [ "THE NOTORIOUS LANDLADY", "has_tags", "JACK LEMMON" ], [ "THE NOTORIOUS LANDLADY", "starred_actors", "FRED ASTAIRE" ], [ "THE NOTORIOUS LANDLADY", "starred_actors", "JACK LEMMON" ], [ "THE NOTORIOUS LANDLADY", "written_by", "BLAKE EDWARDS" ], [ "THE PARTY", "directed_by", "BLAKE EDWARDS" ], [ "THE PARTY", "has_tags", "BLAKE EDWARDS" ], [ "THE PARTY", "release_year", "1968" ], [ "THE PARTY", "written_by", "BLAKE EDWARDS" ], [ "VICTOR VICTORIA", "directed_by", "BLAKE EDWARDS" ], [ "VICTOR VICTORIA", "has_genre", "MUSICAL" ], [ "VICTOR VICTORIA", "has_tags", "BLAKE EDWARDS" ], [ "VICTOR VICTORIA", "has_tags", "JULIE ANDREWS" ], [ "VICTOR VICTORIA", "starred_actors", "JULIE ANDREWS" ], [ "VICTOR VICTORIA", "written_by", "BLAKE EDWARDS" ], [ "WAR", "release_year", "2007" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 25717, 1953 16580, BRINGING DOWN THE HOUSE 28076, DIANE KEATON 32694, DON TAYLOR 38250, FATHER OF THE BRIDE 29397, LÁSZLÓ KARDOS 16378, MAD MONEY 13199, QUEEN LATIFAH 7122, SMALL TOWN GIRL 21196, STALAG 17 24849, STEVE MARTIN src, edge_attr, dst 16580, starred_actors, 13199 16580, starred_actors, 24849 38250, has_tags, 24849 38250, starred_actors, 28076 38250, starred_actors, 32694 38250, starred_actors, 24849 16378, has_tags, 28076 16378, has_tags, 13199 16378, starred_actors, 28076 7122, directed_by, 29397 7122, release_year, 25717 21196, release_year, 25717 21196, starred_actors, 32694 Question: In what context are DON TAYLOR, LÁSZLÓ KARDOS, and QUEEN LATIFAH connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DON TAYLOR", "LÁSZLÓ KARDOS", "QUEEN LATIFAH" ], "valid_edges": [ [ "BRINGING DOWN THE HOUSE", "starred_actors", "QUEEN LATIFAH" ], [ "BRINGING DOWN THE HOUSE", "starred_actors", "STEVE MARTIN" ], [ "FATHER OF THE BRIDE", "has_tags", "STEVE MARTIN" ], [ "FATHER OF THE BRIDE", "starred_actors", "DIANE KEATON" ], [ "FATHER OF THE BRIDE", "starred_actors", "DON TAYLOR" ], [ "FATHER OF THE BRIDE", "starred_actors", "STEVE MARTIN" ], [ "MAD MONEY", "has_tags", "DIANE KEATON" ], [ "MAD MONEY", "has_tags", "QUEEN LATIFAH" ], [ "MAD MONEY", "starred_actors", "DIANE KEATON" ], [ "SMALL TOWN GIRL", "directed_by", "LÁSZLÓ KARDOS" ], [ "SMALL TOWN GIRL", "release_year", "1953" ], [ "STALAG 17", "release_year", "1953" ], [ "STALAG 17", "starred_actors", "DON TAYLOR" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 14259, 1997 24331, DAVID CHUNG 1580, JOHN WESLEY HARDIN 18456, THE BALLAD OF LITTLE JO 15059, THE LAWLESS BREED 4814, WARRIORS OF VIRTUE 36026, WESTERN src, edge_attr, dst 18456, has_genre, 36026 18456, starred_actors, 24331 15059, has_genre, 36026 15059, written_by, 1580 4814, release_year, 14259 36026, release_year, 14259 Question: How are DAVID CHUNG, JOHN WESLEY HARDIN, and WARRIORS OF VIRTUE related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DAVID CHUNG", "JOHN WESLEY HARDIN", "WARRIORS OF VIRTUE" ], "valid_edges": [ [ "THE BALLAD OF LITTLE JO", "has_genre", "WESTERN" ], [ "THE BALLAD OF LITTLE JO", "starred_actors", "DAVID CHUNG" ], [ "THE LAWLESS BREED", "has_genre", "WESTERN" ], [ "THE LAWLESS BREED", "written_by", "JOHN WESLEY HARDIN" ], [ "WARRIORS OF VIRTUE", "release_year", "1997" ], [ "WESTERN", "release_year", "1997" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17480, 1988 3471, A HANDFUL OF DUST 26728, ALIEN NATION 20999, ALONG CAME A SPIDER 25660, BULLETPROOF 31878, CLEAN AND SOBER 5743, DAMON WAYANS 18349, EARTH GIRLS ARE EASY 1038, JAMES CAAN 26861, MORGAN FREEMAN src, edge_attr, dst 3471, release_year, 17480 26728, release_year, 17480 26728, starred_actors, 1038 20999, has_tags, 26861 20999, starred_actors, 26861 25660, starred_actors, 5743 25660, starred_actors, 1038 31878, has_tags, 26861 31878, release_year, 17480 31878, starred_actors, 26861 18349, release_year, 17480 18349, starred_actors, 5743 Question: In what context are A HANDFUL OF DUST, ALONG CAME A SPIDER, and BULLETPROOF connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "A HANDFUL OF DUST", "ALONG CAME A SPIDER", "BULLETPROOF" ], "valid_edges": [ [ "A HANDFUL OF DUST", "release_year", "1988" ], [ "ALIEN NATION", "release_year", "1988" ], [ "ALIEN NATION", "starred_actors", "JAMES CAAN" ], [ "ALONG CAME A SPIDER", "has_tags", "MORGAN FREEMAN" ], [ "ALONG CAME A SPIDER", "starred_actors", "MORGAN FREEMAN" ], [ "BULLETPROOF", "starred_actors", "DAMON WAYANS" ], [ "BULLETPROOF", "starred_actors", "JAMES CAAN" ], [ "CLEAN AND SOBER", "has_tags", "MORGAN FREEMAN" ], [ "CLEAN AND SOBER", "release_year", "1988" ], [ "CLEAN AND SOBER", "starred_actors", "MORGAN FREEMAN" ], [ "EARTH GIRLS ARE EASY", "release_year", "1988" ], [ "EARTH GIRLS ARE EASY", "starred_actors", "DAMON WAYANS" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3863, 1962 9367, BETTE DAVIS 5189, CAPE FEAR 6158, EDGAR ALLAN POE 26688, ERNESTO GASTALDI 3400, GAMBLING CITY 29624, MADAME SIN 29026, PSYCHOLOGICAL THRILLER 16724, ROBERT ALDRICH 1890, SERGIO MARTINO 11790, SODOM AND GOMORRAH 26202, TALES OF TERROR 17058, THE HORRIBLE DR. HICHCOCK 28071, WHAT EVER HAPPENED TO BABY JANE? 3151, YOUR VICE IS A LOCKED ROOM AND ONLY I HAVE THE KEY src, edge_attr, dst 5189, has_tags, 29026 5189, release_year, 3863 3400, directed_by, 1890 3400, written_by, 26688 3400, written_by, 1890 29624, starred_actors, 9367 11790, directed_by, 16724 11790, release_year, 3863 26202, has_tags, 6158 26202, release_year, 3863 26202, written_by, 6158 17058, release_year, 3863 17058, written_by, 26688 28071, directed_by, 16724 28071, has_tags, 9367 28071, has_tags, 29026 28071, has_tags, 16724 28071, release_year, 3863 28071, starred_actors, 9367 3151, directed_by, 1890 3151, written_by, 6158 Question: In what context are 1962, MADAME SIN, and SERGIO MARTINO connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "1962", "MADAME SIN", "SERGIO MARTINO" ], "valid_edges": [ [ "CAPE FEAR", "has_tags", "PSYCHOLOGICAL THRILLER" ], [ "CAPE FEAR", "release_year", "1962" ], [ "GAMBLING CITY", "directed_by", "SERGIO MARTINO" ], [ "GAMBLING CITY", "written_by", "ERNESTO GASTALDI" ], [ "GAMBLING CITY", "written_by", "SERGIO MARTINO" ], [ "MADAME SIN", "starred_actors", "BETTE DAVIS" ], [ "SODOM AND GOMORRAH", "directed_by", "ROBERT ALDRICH" ], [ "SODOM AND GOMORRAH", "release_year", "1962" ], [ "TALES OF TERROR", "has_tags", "EDGAR ALLAN POE" ], [ "TALES OF TERROR", "release_year", "1962" ], [ "TALES OF TERROR", "written_by", "EDGAR ALLAN POE" ], [ "THE HORRIBLE DR. HICHCOCK", "release_year", "1962" ], [ "THE HORRIBLE DR. HICHCOCK", "written_by", "ERNESTO GASTALDI" ], [ "WHAT EVER HAPPENED TO BABY JANE?", "directed_by", "ROBERT ALDRICH" ], [ "WHAT EVER HAPPENED TO BABY JANE?", "has_tags", "BETTE DAVIS" ], [ "WHAT EVER HAPPENED TO BABY JANE?", "has_tags", "PSYCHOLOGICAL THRILLER" ], [ "WHAT EVER HAPPENED TO BABY JANE?", "has_tags", "ROBERT ALDRICH" ], [ "WHAT EVER HAPPENED TO BABY JANE?", "release_year", "1962" ], [ "WHAT EVER HAPPENED TO BABY JANE?", "starred_actors", "BETTE DAVIS" ], [ "YOUR VICE IS A LOCKED ROOM AND ONLY I HAVE THE KEY", "directed_by", "SERGIO MARTINO" ], [ "YOUR VICE IS A LOCKED ROOM AND ONLY I HAVE THE KEY", "written_by", "EDGAR ALLAN POE" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1430, 1949 39045, ALFRED HITCHCOCK 36458, ALLAN DWAN 6610, DESTINATION TOKYO 19427, JAMES BRIDIE 28476, MURDER 23006, SANDS OF IWO JIMA 5482, THE PARADINE CASE 164, UNDER CAPRICORN 22214, WAR src, edge_attr, dst 6610, has_genre, 22214 23006, directed_by, 36458 23006, has_genre, 22214 23006, has_tags, 36458 23006, release_year, 1430 5482, directed_by, 39045 5482, has_tags, 28476 5482, written_by, 19427 164, directed_by, 39045 164, release_year, 1430 164, written_by, 19427 22214, has_tags, 28476 Question: In what context are ALLAN DWAN, DESTINATION TOKYO, and JAMES BRIDIE connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ALLAN DWAN", "DESTINATION TOKYO", "JAMES BRIDIE" ], "valid_edges": [ [ "DESTINATION TOKYO", "has_genre", "WAR" ], [ "SANDS OF IWO JIMA", "directed_by", "ALLAN DWAN" ], [ "SANDS OF IWO JIMA", "has_genre", "WAR" ], [ "SANDS OF IWO JIMA", "has_tags", "ALLAN DWAN" ], [ "SANDS OF IWO JIMA", "release_year", "1949" ], [ "THE PARADINE CASE", "directed_by", "ALFRED HITCHCOCK" ], [ "THE PARADINE CASE", "has_tags", "MURDER" ], [ "THE PARADINE CASE", "written_by", "JAMES BRIDIE" ], [ "UNDER CAPRICORN", "directed_by", "ALFRED HITCHCOCK" ], [ "UNDER CAPRICORN", "release_year", "1949" ], [ "UNDER CAPRICORN", "written_by", "JAMES BRIDIE" ], [ "WAR", "has_tags", "MURDER" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 21278, A SUMMER'S TALE 16826, DANIÈLE GÉGAUFF 16016, DIAMOND GIRL 6012, FRENCH 16465, JONATHAN CAKE 3489, MELVIL POUPAUD 1103, PLEASURE PARTY 8379, ROMANCE src, edge_attr, dst 21278, has_genre, 8379 21278, in_language, 6012 21278, starred_actors, 3489 16016, has_genre, 8379 16016, starred_actors, 16465 1103, in_language, 6012 1103, starred_actors, 16826 Question: In what context are DANIÈLE GÉGAUFF, JONATHAN CAKE, and MELVIL POUPAUD connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DANIÈLE GÉGAUFF", "JONATHAN CAKE", "MELVIL POUPAUD" ], "valid_edges": [ [ "A SUMMER'S TALE", "has_genre", "ROMANCE" ], [ "A SUMMER'S TALE", "in_language", "FRENCH" ], [ "A SUMMER'S TALE", "starred_actors", "MELVIL POUPAUD" ], [ "DIAMOND GIRL", "has_genre", "ROMANCE" ], [ "DIAMOND GIRL", "starred_actors", "JONATHAN CAKE" ], [ "PLEASURE PARTY", "in_language", "FRENCH" ], [ "PLEASURE PARTY", "starred_actors", "DANIÈLE GÉGAUFF" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 8486, 1999 22694, ALAN PARKER 17481, ANGELA'S ASHES 32409, JOE BREEN 35341, ORFEU 35792, ROBERT CARLYLE 4345, THE COMMITMENTS 13675, THE FULL MONTY 32164, VINICIUS DE MORAES 13642, WORKING CLASS src, edge_attr, dst 17481, directed_by, 22694 17481, has_tags, 22694 17481, release_year, 8486 17481, starred_actors, 32409 17481, starred_actors, 35792 17481, written_by, 22694 35341, release_year, 8486 35341, written_by, 32164 4345, directed_by, 22694 4345, has_tags, 22694 4345, has_tags, 13642 13675, has_tags, 35792 13675, has_tags, 13642 13675, starred_actors, 35792 Question: How are JOE BREEN, VINICIUS DE MORAES, and WORKING CLASS related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JOE BREEN", "VINICIUS DE MORAES", "WORKING CLASS" ], "valid_edges": [ [ "ANGELA'S ASHES", "directed_by", "ALAN PARKER" ], [ "ANGELA'S ASHES", "has_tags", "ALAN PARKER" ], [ "ANGELA'S ASHES", "release_year", "1999" ], [ "ANGELA'S ASHES", "starred_actors", "JOE BREEN" ], [ "ANGELA'S ASHES", "starred_actors", "ROBERT CARLYLE" ], [ "ANGELA'S ASHES", "written_by", "ALAN PARKER" ], [ "ORFEU", "release_year", "1999" ], [ "ORFEU", "written_by", "VINICIUS DE MORAES" ], [ "THE COMMITMENTS", "directed_by", "ALAN PARKER" ], [ "THE COMMITMENTS", "has_tags", "ALAN PARKER" ], [ "THE COMMITMENTS", "has_tags", "WORKING CLASS" ], [ "THE FULL MONTY", "has_tags", "ROBERT CARLYLE" ], [ "THE FULL MONTY", "has_tags", "WORKING CLASS" ], [ "THE FULL MONTY", "starred_actors", "ROBERT CARLYLE" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10349, CHICAGO 36212, DRAMA 34569, FRANK URSON 35421, GO FISH 22945, HIGH FIDELITY 3972, IN OLD CHICAGO 20283, MEAN CREEK 8552, MEDIUM COOL 1409, MOE HOWARD 22845, MUSIC 1372, RETURN TO ME 15995, ROCKIN' IN THE ROCKIES 39016, STOLEN SUMMER 32295, THE DILEMMA src, edge_attr, dst 10349, directed_by, 34569 10349, has_genre, 36212 10349, has_tags, 10349 10349, has_tags, 22845 35421, has_genre, 36212 35421, has_tags, 10349 22945, has_genre, 36212 22945, has_tags, 10349 22945, has_tags, 36212 3972, has_genre, 36212 3972, has_tags, 10349 20283, has_genre, 36212 20283, has_tags, 36212 8552, has_genre, 36212 8552, has_tags, 10349 1372, has_genre, 36212 1372, has_tags, 10349 15995, has_genre, 22845 15995, starred_actors, 1409 39016, has_genre, 36212 39016, has_tags, 10349 32295, has_genre, 36212 32295, has_tags, 10349 Question: For what reason are FRANK URSON, MEAN CREEK, and MOE HOWARD associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "FRANK URSON", "MEAN CREEK", "MOE HOWARD" ], "valid_edges": [ [ "CHICAGO", "directed_by", "FRANK URSON" ], [ "CHICAGO", "has_genre", "DRAMA" ], [ "CHICAGO", "has_tags", "CHICAGO" ], [ "CHICAGO", "has_tags", "MUSIC" ], [ "GO FISH", "has_genre", "DRAMA" ], [ "GO FISH", "has_tags", "CHICAGO" ], [ "HIGH FIDELITY", "has_genre", "DRAMA" ], [ "HIGH FIDELITY", "has_tags", "CHICAGO" ], [ "HIGH FIDELITY", "has_tags", "DRAMA" ], [ "IN OLD CHICAGO", "has_genre", "DRAMA" ], [ "IN OLD CHICAGO", "has_tags", "CHICAGO" ], [ "MEAN CREEK", "has_genre", "DRAMA" ], [ "MEAN CREEK", "has_tags", "DRAMA" ], [ "MEDIUM COOL", "has_genre", "DRAMA" ], [ "MEDIUM COOL", "has_tags", "CHICAGO" ], [ "RETURN TO ME", "has_genre", "DRAMA" ], [ "RETURN TO ME", "has_tags", "CHICAGO" ], [ "ROCKIN' IN THE ROCKIES", "has_genre", "MUSIC" ], [ "ROCKIN' IN THE ROCKIES", "starred_actors", "MOE HOWARD" ], [ "STOLEN SUMMER", "has_genre", "DRAMA" ], [ "STOLEN SUMMER", "has_tags", "CHICAGO" ], [ "THE DILEMMA", "has_genre", "DRAMA" ], [ "THE DILEMMA", "has_tags", "CHICAGO" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27816, BANANAS 32479, BEWITCHED 30330, CLEAVANT DERRICKS 30463, COMEDY 38118, MOSCOW ON THE HUDSON 9271, OFF BEAT src, edge_attr, dst 27816, has_genre, 30463 27816, has_tags, 30463 32479, has_genre, 30463 32479, has_tags, 30463 38118, has_genre, 30463 38118, starred_actors, 30330 9271, has_genre, 30463 9271, starred_actors, 30330 Question: How are BANANAS, BEWITCHED, and CLEAVANT DERRICKS related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BANANAS", "BEWITCHED", "CLEAVANT DERRICKS" ], "valid_edges": [ [ "BANANAS", "has_genre", "COMEDY" ], [ "BANANAS", "has_tags", "COMEDY" ], [ "BEWITCHED", "has_genre", "COMEDY" ], [ "BEWITCHED", "has_tags", "COMEDY" ], [ "MOSCOW ON THE HUDSON", "has_genre", "COMEDY" ], [ "MOSCOW ON THE HUDSON", "starred_actors", "CLEAVANT DERRICKS" ], [ "OFF BEAT", "has_genre", "COMEDY" ], [ "OFF BEAT", "starred_actors", "CLEAVANT DERRICKS" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 2779, A PROPHET 4763, ADVENTURE 7373, DALE VAN EVERY 36212, DRAMA 6012, FRENCH 23711, JACQUES AUDIARD 39185, NORTH WEST FRONTIER 6593, ROBIN ESTRIDGE 30316, RUST AND BONE 3627, THE TALK OF THE TOWN 33295, TRADER HORN src, edge_attr, dst 2779, directed_by, 23711 2779, has_genre, 36212 2779, has_tags, 6012 2779, has_tags, 23711 2779, in_language, 6012 2779, written_by, 23711 39185, has_genre, 4763 39185, written_by, 6593 30316, directed_by, 23711 30316, has_genre, 36212 30316, has_tags, 23711 30316, in_language, 6012 30316, written_by, 23711 3627, has_genre, 36212 3627, written_by, 7373 33295, has_genre, 4763 33295, written_by, 7373 Question: How are DALE VAN EVERY, JACQUES AUDIARD, and ROBIN ESTRIDGE related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DALE VAN EVERY", "JACQUES AUDIARD", "ROBIN ESTRIDGE" ], "valid_edges": [ [ "A PROPHET", "directed_by", "JACQUES AUDIARD" ], [ "A PROPHET", "has_genre", "DRAMA" ], [ "A PROPHET", "has_tags", "FRENCH" ], [ "A PROPHET", "has_tags", "JACQUES AUDIARD" ], [ "A PROPHET", "in_language", "FRENCH" ], [ "A PROPHET", "written_by", "JACQUES AUDIARD" ], [ "NORTH WEST FRONTIER", "has_genre", "ADVENTURE" ], [ "NORTH WEST FRONTIER", "written_by", "ROBIN ESTRIDGE" ], [ "RUST AND BONE", "directed_by", "JACQUES AUDIARD" ], [ "RUST AND BONE", "has_genre", "DRAMA" ], [ "RUST AND BONE", "has_tags", "JACQUES AUDIARD" ], [ "RUST AND BONE", "in_language", "FRENCH" ], [ "RUST AND BONE", "written_by", "JACQUES AUDIARD" ], [ "THE TALK OF THE TOWN", "has_genre", "DRAMA" ], [ "THE TALK OF THE TOWN", "written_by", "DALE VAN EVERY" ], [ "TRADER HORN", "has_genre", "ADVENTURE" ], [ "TRADER HORN", "written_by", "DALE VAN EVERY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24818, 1992 4310, 24 HOUR PARTY PEOPLE 9005, 3 NINJAS 30146, A CHRISTMAS CAROL 4269, A HARD DAY'S NIGHT 31344, A LEAGUE OF THEIR OWN 29389, A MIGHTY WIND 8198, A PRAIRIE HOME COMPANION 8049, A PRIVATE FUNCTION 8837, AIRHEADS 26858, ARMY OF DARKNESS 14271, BEETHOVEN 9127, BIG GIRLS DON'T CRY... THEY GET EVEN 32193, BLAME IT ON THE BELLBOY 16023, BLUES BROTHERS 2000 19829, BOOMERANG 350, BOYS ON THE SIDE 8606, BRAIN DONORS 23319, BUFFY THE VAMPIRE SLAYER 30182, BURGLAR 33773, BÉBÉ'S KIDS 2450, CALIFORNIA SUITE 10877, CAPTAIN RON 29831, CB4 9284, CHANCES ARE 10349, CHICAGO 15721, CIAO, PROFESSORE! 12356, CLASS ACT 30463, COMEDY 10272, CONFESSIONS OF A TEENAGE DRAMA QUEEN 33111, COPPER MOUNTAIN 30836, COSI 11807, CRITTERS 4 30019, CROSSROADS 27380, DEATH BECOMES HER 18420, DOUBLE DYNAMITE 27674, EASY COME, EASY GO 10757, EDDIE 2380, EMILE ARDOLINO 9457, ENCINO MAN 31630, EVIL TOONS 3955, FINDING NORTH 5636, FOLKS! 5287, FROZEN 32553, FROZEN ASSETS 8788, FUN IN ACAPULCO 21640, GARDEN STATE 29593, GET CRAZY 19795, GET YOURSELF A COLLEGE GIRL 25033, GOING MY WAY 19871, GYPSY 20263, HAIR 9798, HAIRSPRAY 1292, HEDWIG AND THE ANGRY INCH 3829, HERO 14375, HIGH SCHOOL MUSICAL 17578, HOCUS POCUS 18546, HONEYMOON IN VEGAS 17037, HOUSE PARTY 25277, HUSBANDS AND WIVES 33279, IN BRUGES 4419, IN THE SOUP 36998, JAMES CRAIG 10109, JOSIE AND THE PUSSYCATS 16510, JOYFUL NOISE 2938, JUMPIN' JACK FLASH 5692, KATHY NAJIMY 1477, KEEPING MUM 6013, KILLING BONO 25510, KING OF BEGGARS 13704, KUFFS 18950, LADYBUGS 191, LEAVING NORMAL 8851, LITTLE SHOP OF HORRORS 24500, LITTLE SISTER 17663, MADE IN AMERICA 28518, MAGGIE SMITH 8268, MALEDETTO IL GIORNO CHE T'HO INCONTRATO 10560, MAN BITES DOG 24068, MAN TROUBLE 4561, MEMOIRS OF AN INVISIBLE MAN 34536, MISTRESS 39399, MO' MONEY 17135, MOM AND DAD SAVE THE WORLD 20003, MONSTERS, INC. 815, MR. BASEBALL 22845, MUSIC 2483, MUSIC AND LYRICS 21919, MY COUSIN VINNY 2581, MY NEW GUN 40064, MY OLD LADY 14797, O BROTHER, WHERE ART THOU? 5775, OCCULT 9638, ON OUR MERRY WAY 35308, ONE HUNDRED MEN AND A GIRL 14917, OUT ON A LIMB 16910, PARENTI SERPENTI 25678, PETER'S FRIENDS 6864, PITCH PERFECT 34602, PUNCH-DRUNK LOVE 25023, QUARTET 15214, RADIO DAYS 32180, RAT RACE 36575, RHINESTONE 30475, RIO 22107, ROCK 'N' ROLL HIGH SCHOOL 38381, ROCK STAR 901, SCHOOL OF ROCK 30519, SCOTT PILGRIM VS. THE WORLD 21512, SHERLOCK HOLMES 3358, SINGLES 8652, SISTER ACT 22068, SOUL MEN 13437, SOUND OF NOISE 4459, SPICE WORLD 17370, STAY TUNED 2033, STOP! OR MY MOM WILL SHOOT 22993, STRAIGHT TALK 1432, STRICTLY BALLROOM 37498, TENACIOUS D IN THE PICK OF DESTINY 39535, THAT THING YOU DO! 25270, THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT 23599, THE BEST EXOTIC MARIGOLD HOTEL 36928, THE BIKINI CARWASH COMPANY 26008, THE BLUES BROTHERS 13869, THE DISTINGUISHED GENTLEMAN 20929, THE FIGHTING TEMPTATIONS 27031, THE FIRST WIVES CLUB 13675, THE FULL MONTY 2656, THE GIRL CAN'T HELP IT 21831, THE GUN IN BETTY LOU'S HANDBAG 31283, THE HOUND OF THE BASKERVILLES 39978, THE HUMAN COMEDY 19226, THE MARC PEASE EXPERIENCE 24724, THE MIGHTY DUCKS 26128, THE MUPPET CHRISTMAS CAROL 11189, THE MUPPETS 24035, THE NORTHERNERS 10721, THE ROCKY HORROR PICTURE SHOW 8791, THE SECOND BEST EXOTIC MARIGOLD HOTEL 37600, THE SECRET POLICEMAN'S OTHER BALL 29027, THE TELEPHONE 31313, THE WEST POINT STORY 2281, TOYS 7279, TWIN DRAGONS 36262, UNFAITHFULLY YOURS 10376, USED PEOPLE 38839, WAYNE'S WORLD 12506, WENDY MAKKENA 20751, WHITE MEN CAN'T JUMP 37332, WHOOPI GOLDBERG src, edge_attr, dst 4310, has_genre, 30463 4310, has_tags, 22845 9005, has_genre, 30463 9005, release_year, 24818 30146, has_genre, 30463 30146, starred_actors, 37332 4269, has_genre, 30463 4269, has_genre, 22845 4269, has_tags, 30463 4269, has_tags, 22845 31344, has_genre, 30463 31344, release_year, 24818 29389, has_genre, 30463 29389, has_genre, 22845 8198, has_genre, 30463 8198, has_genre, 22845 8049, has_genre, 30463 8049, starred_actors, 28518 8837, has_genre, 30463 8837, has_genre, 22845 8837, has_tags, 30463 26858, has_genre, 30463 26858, has_tags, 30463 26858, release_year, 24818 14271, has_genre, 30463 14271, has_tags, 30463 14271, release_year, 24818 9127, has_genre, 30463 9127, release_year, 24818 32193, has_genre, 30463 32193, release_year, 24818 16023, has_genre, 30463 16023, has_tags, 22845 19829, has_genre, 30463 19829, release_year, 24818 350, has_genre, 30463 350, has_tags, 37332 350, starred_actors, 37332 8606, has_genre, 30463 8606, release_year, 24818 23319, has_genre, 30463 23319, has_tags, 30463 23319, release_year, 24818 30182, has_genre, 30463 30182, starred_actors, 37332 33773, has_genre, 30463 33773, release_year, 24818 2450, has_genre, 30463 2450, starred_actors, 28518 10877, has_genre, 30463 10877, has_tags, 30463 10877, release_year, 24818 29831, has_genre, 30463 29831, has_genre, 22845 9284, directed_by, 2380 9284, has_genre, 30463 10349, has_genre, 30463 10349, has_tags, 22845 15721, has_genre, 30463 15721, release_year, 24818 12356, has_genre, 30463 12356, release_year, 24818 10272, has_genre, 30463 10272, has_genre, 22845 10272, has_tags, 30463 33111, has_genre, 30463 33111, has_genre, 22845 30836, has_genre, 30463 30836, has_genre, 22845 11807, has_genre, 30463 11807, release_year, 24818 30019, has_genre, 30463 30019, has_genre, 22845 27380, has_genre, 30463 27380, release_year, 24818 18420, has_genre, 30463 18420, has_genre, 22845 27674, has_genre, 30463 27674, has_genre, 22845 10757, has_genre, 30463 10757, starred_actors, 37332 9457, has_genre, 30463 9457, release_year, 24818 31630, has_genre, 30463 31630, release_year, 24818 3955, has_genre, 30463 3955, starred_actors, 12506 5636, has_genre, 30463 5636, release_year, 24818 5287, has_genre, 30463 5287, has_tags, 22845 32553, has_genre, 30463 32553, release_year, 24818 8788, has_genre, 30463 8788, has_genre, 22845 21640, has_genre, 30463 21640, has_tags, 22845 29593, has_genre, 30463 29593, has_genre, 22845 19795, has_genre, 30463 19795, has_genre, 22845 25033, has_genre, 30463 25033, has_genre, 22845 19871, directed_by, 2380 19871, has_genre, 30463 20263, has_genre, 30463 20263, has_tags, 22845 9798, has_genre, 30463 9798, has_genre, 22845 9798, has_tags, 30463 1292, has_genre, 30463 1292, has_genre, 22845 1292, has_tags, 22845 3829, has_genre, 30463 3829, release_year, 24818 14375, has_genre, 30463 14375, has_tags, 22845 17578, has_genre, 30463 17578, starred_actors, 5692 18546, has_genre, 30463 18546, release_year, 24818 17037, has_genre, 30463 17037, has_genre, 22845 25277, has_genre, 30463 25277, release_year, 24818 33279, has_genre, 30463 33279, has_tags, 30463 33279, has_tags, 22845 4419, has_genre, 30463 4419, release_year, 24818 10109, has_genre, 30463 10109, has_genre, 22845 16510, has_genre, 30463 16510, has_genre, 22845 2938, has_genre, 30463 2938, has_tags, 37332 2938, starred_actors, 37332 1477, has_genre, 30463 1477, has_tags, 28518 1477, starred_actors, 28518 6013, has_genre, 30463 6013, has_genre, 22845 6013, has_tags, 22845 25510, has_genre, 30463 25510, release_year, 24818 13704, has_genre, 30463 13704, release_year, 24818 18950, has_genre, 30463 18950, release_year, 24818 191, has_genre, 30463 191, release_year, 24818 8851, has_genre, 30463 8851, has_tags, 22845 24500, has_genre, 30463 24500, release_year, 24818 17663, has_genre, 30463 17663, has_tags, 37332 17663, starred_actors, 37332 8268, has_genre, 30463 8268, release_year, 24818 10560, has_genre, 30463 10560, release_year, 24818 24068, has_genre, 30463 24068, release_year, 24818 4561, has_genre, 30463 4561, release_year, 24818 34536, has_genre, 30463 34536, release_year, 24818 39399, has_genre, 30463 39399, release_year, 24818 17135, has_genre, 30463 17135, release_year, 24818 20003, has_genre, 30463 20003, has_tags, 30463 20003, has_tags, 22845 815, has_genre, 30463 815, release_year, 24818 2483, has_genre, 30463 2483, has_genre, 22845 2483, has_tags, 30463 21919, has_genre, 30463 21919, has_tags, 30463 21919, release_year, 24818 2581, has_genre, 30463 2581, release_year, 24818 40064, has_genre, 30463 40064, starred_actors, 28518 14797, has_genre, 30463 14797, has_tags, 30463 14797, has_tags, 22845 9638, has_genre, 30463 9638, has_genre, 22845 35308, has_genre, 30463 35308, has_genre, 22845 14917, has_genre, 30463 14917, release_year, 24818 16910, has_genre, 30463 16910, release_year, 24818 25678, has_genre, 30463 25678, release_year, 24818 6864, has_genre, 30463 6864, has_genre, 22845 6864, has_tags, 22845 34602, has_genre, 30463 34602, has_tags, 30463 34602, has_tags, 22845 25023, has_genre, 30463 25023, has_tags, 30463 25023, starred_actors, 28518 15214, has_genre, 30463 15214, has_tags, 22845 32180, has_genre, 30463 32180, has_tags, 30463 32180, has_tags, 37332 36575, has_genre, 30463 36575, has_genre, 22845 30475, has_genre, 30463 30475, has_tags, 30463 30475, has_tags, 22845 22107, has_genre, 30463 22107, has_genre, 22845 38381, has_genre, 30463 38381, has_genre, 22845 901, has_genre, 30463 901, has_genre, 22845 901, has_tags, 22845 30519, has_genre, 30463 30519, has_tags, 30463 30519, has_tags, 22845 21512, has_tags, 30463 21512, has_tags, 5775 21512, has_tags, 21512 3358, has_genre, 30463 3358, release_year, 24818 8652, directed_by, 2380 8652, has_genre, 30463 8652, has_genre, 22845 8652, has_tags, 28518 8652, has_tags, 37332 8652, release_year, 24818 8652, starred_actors, 5692 8652, starred_actors, 28518 8652, starred_actors, 12506 8652, starred_actors, 37332 22068, has_genre, 30463 22068, has_genre, 22845 13437, has_genre, 30463 13437, has_genre, 22845 13437, has_tags, 22845 4459, has_genre, 30463 4459, has_genre, 22845 4459, has_tags, 22845 17370, has_genre, 30463 17370, release_year, 24818 2033, has_genre, 30463 2033, has_tags, 30463 2033, release_year, 24818 22993, has_genre, 30463 22993, release_year, 24818 1432, has_genre, 30463 1432, release_year, 24818 37498, has_genre, 30463 37498, has_genre, 22845 37498, has_tags, 30463 37498, has_tags, 22845 39535, has_genre, 30463 39535, has_genre, 22845 39535, has_tags, 22845 25270, has_genre, 30463 25270, has_genre, 22845 23599, has_genre, 30463 23599, has_tags, 28518 36928, has_genre, 30463 36928, release_year, 24818 26008, has_genre, 30463 26008, has_tags, 30463 26008, has_tags, 22845 13869, has_genre, 30463 13869, release_year, 24818 20929, has_genre, 30463 20929, has_genre, 22845 27031, has_genre, 30463 27031, starred_actors, 28518 13675, has_genre, 30463 13675, has_genre, 22845 2656, has_genre, 30463 2656, has_genre, 22845 21831, has_genre, 30463 21831, release_year, 24818 31283, has_genre, 30463 31283, has_tags, 21512 39978, has_genre, 30463 39978, starred_actors, 36998 19226, has_genre, 30463 19226, has_genre, 22845 24724, has_genre, 30463 24724, release_year, 24818 26128, has_genre, 30463 26128, release_year, 24818 11189, has_genre, 30463 11189, has_tags, 30463 11189, has_tags, 22845 24035, has_genre, 30463 24035, release_year, 24818 10721, has_genre, 30463 10721, has_tags, 22845 8791, has_genre, 30463 8791, starred_actors, 28518 37600, has_genre, 30463 37600, has_genre, 22845 29027, has_genre, 30463 29027, starred_actors, 37332 31313, has_genre, 30463 31313, has_genre, 22845 2281, has_genre, 30463 2281, has_tags, 22845 2281, release_year, 24818 7279, has_genre, 30463 7279, release_year, 24818 36262, has_genre, 30463 36262, has_genre, 22845 10376, has_genre, 30463 10376, release_year, 24818 38839, has_genre, 30463 38839, has_tags, 30463 38839, release_year, 24818 20751, has_genre, 30463 20751, has_tags, 30463 20751, release_year, 24818 Question: How are JAMES CRAIG, OCCULT, and SISTER ACT related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JAMES CRAIG", "OCCULT", "SISTER ACT" ], "valid_edges": [ [ "24 HOUR PARTY PEOPLE", "has_genre", "COMEDY" ], [ "24 HOUR PARTY PEOPLE", "has_tags", "MUSIC" ], [ "3 NINJAS", "has_genre", "COMEDY" ], [ "3 NINJAS", "release_year", "1992" ], [ "A CHRISTMAS CAROL", "has_genre", "COMEDY" ], [ "A CHRISTMAS CAROL", "starred_actors", "WHOOPI GOLDBERG" ], [ "A HARD DAY'S NIGHT", "has_genre", "COMEDY" ], [ "A HARD DAY'S NIGHT", "has_genre", "MUSIC" ], [ "A HARD DAY'S NIGHT", "has_tags", "COMEDY" ], [ "A HARD DAY'S NIGHT", "has_tags", "MUSIC" ], [ "A LEAGUE OF THEIR OWN", "has_genre", "COMEDY" ], [ "A LEAGUE OF THEIR OWN", "release_year", "1992" ], [ "A MIGHTY WIND", "has_genre", "COMEDY" ], [ "A MIGHTY WIND", "has_genre", "MUSIC" ], [ "A PRAIRIE HOME COMPANION", "has_genre", "COMEDY" ], [ "A PRAIRIE HOME COMPANION", "has_genre", "MUSIC" ], [ "A PRIVATE FUNCTION", "has_genre", "COMEDY" ], [ "A PRIVATE FUNCTION", "starred_actors", "MAGGIE SMITH" ], [ "AIRHEADS", "has_genre", "COMEDY" ], [ "AIRHEADS", "has_genre", "MUSIC" ], [ "AIRHEADS", "has_tags", "COMEDY" ], [ "ARMY OF DARKNESS", "has_genre", "COMEDY" ], [ "ARMY OF DARKNESS", "has_tags", "COMEDY" ], [ "ARMY OF DARKNESS", "release_year", "1992" ], [ "BEETHOVEN", "has_genre", "COMEDY" ], [ "BEETHOVEN", "has_tags", "COMEDY" ], [ "BEETHOVEN", "release_year", "1992" ], [ "BIG GIRLS DON'T CRY... THEY GET EVEN", "has_genre", "COMEDY" ], [ "BIG GIRLS DON'T CRY... THEY GET EVEN", "release_year", "1992" ], [ "BLAME IT ON THE BELLBOY", "has_genre", "COMEDY" ], [ "BLAME IT ON THE BELLBOY", "release_year", "1992" ], [ "BLUES BROTHERS 2000", "has_genre", "COMEDY" ], [ "BLUES BROTHERS 2000", "has_tags", "MUSIC" ], [ "BOOMERANG", "has_genre", "COMEDY" ], [ "BOOMERANG", "release_year", "1992" ], [ "BOYS ON THE SIDE", "has_genre", "COMEDY" ], [ "BOYS ON THE SIDE", "has_tags", "WHOOPI GOLDBERG" ], [ "BOYS ON THE SIDE", "starred_actors", "WHOOPI GOLDBERG" ], [ "BRAIN DONORS", "has_genre", "COMEDY" ], [ "BRAIN DONORS", "release_year", "1992" ], [ "BUFFY THE VAMPIRE SLAYER", "has_genre", "COMEDY" ], [ "BUFFY THE VAMPIRE SLAYER", "has_tags", "COMEDY" ], [ "BUFFY THE VAMPIRE SLAYER", "release_year", "1992" ], [ "BURGLAR", "has_genre", "COMEDY" ], [ "BURGLAR", "starred_actors", "WHOOPI GOLDBERG" ], [ "BÉBÉ'S KIDS", "has_genre", "COMEDY" ], [ "BÉBÉ'S KIDS", "release_year", "1992" ], [ "CALIFORNIA SUITE", "has_genre", "COMEDY" ], [ "CALIFORNIA SUITE", "starred_actors", "MAGGIE SMITH" ], [ "CAPTAIN RON", "has_genre", "COMEDY" ], [ "CAPTAIN RON", "has_tags", "COMEDY" ], [ "CAPTAIN RON", "release_year", "1992" ], [ "CB4", "has_genre", "COMEDY" ], [ "CB4", "has_genre", "MUSIC" ], [ "CHANCES ARE", "directed_by", "EMILE ARDOLINO" ], [ "CHANCES ARE", "has_genre", "COMEDY" ], [ "CHICAGO", "has_genre", "COMEDY" ], [ "CHICAGO", "has_tags", "MUSIC" ], [ "CIAO, PROFESSORE!", "has_genre", "COMEDY" ], [ "CIAO, PROFESSORE!", "release_year", "1992" ], [ "CLASS ACT", "has_genre", "COMEDY" ], [ "CLASS ACT", "release_year", "1992" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_genre", "COMEDY" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_genre", "MUSIC" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_tags", "COMEDY" ], [ "COPPER MOUNTAIN", "has_genre", "COMEDY" ], [ "COPPER MOUNTAIN", "has_genre", "MUSIC" ], [ "COSI", "has_genre", "COMEDY" ], [ "COSI", "has_genre", "MUSIC" ], [ "CRITTERS 4", "has_genre", "COMEDY" ], [ "CRITTERS 4", "release_year", "1992" ], [ "CROSSROADS", "has_genre", "COMEDY" ], [ "CROSSROADS", "has_genre", "MUSIC" ], [ "DEATH BECOMES HER", "has_genre", "COMEDY" ], [ "DEATH BECOMES HER", "release_year", "1992" ], [ "DOUBLE DYNAMITE", "has_genre", "COMEDY" ], [ "DOUBLE DYNAMITE", "has_genre", "MUSIC" ], [ "EASY COME, EASY GO", "has_genre", "COMEDY" ], [ "EASY COME, EASY GO", "has_genre", "MUSIC" ], [ "EDDIE", "has_genre", "COMEDY" ], [ "EDDIE", "starred_actors", "WHOOPI GOLDBERG" ], [ "ENCINO MAN", "has_genre", "COMEDY" ], [ "ENCINO MAN", "release_year", "1992" ], [ "EVIL TOONS", "has_genre", "COMEDY" ], [ "EVIL TOONS", "release_year", "1992" ], [ "FINDING NORTH", "has_genre", "COMEDY" ], [ "FINDING NORTH", "starred_actors", "WENDY MAKKENA" ], [ "FOLKS!", "has_genre", "COMEDY" ], [ "FOLKS!", "release_year", "1992" ], [ "FROZEN", "has_genre", "COMEDY" ], [ "FROZEN", "has_tags", "MUSIC" ], [ "FROZEN ASSETS", "has_genre", "COMEDY" ], [ "FROZEN ASSETS", "release_year", "1992" ], [ "FUN IN ACAPULCO", "has_genre", "COMEDY" ], [ "FUN IN ACAPULCO", "has_genre", "MUSIC" ], [ "GARDEN STATE", "has_genre", "COMEDY" ], [ "GARDEN STATE", "has_tags", "MUSIC" ], [ "GET CRAZY", "has_genre", "COMEDY" ], [ "GET CRAZY", "has_genre", "MUSIC" ], [ "GET YOURSELF A COLLEGE GIRL", "has_genre", "COMEDY" ], [ "GET YOURSELF A COLLEGE GIRL", "has_genre", "MUSIC" ], [ "GOING MY WAY", "has_genre", "COMEDY" ], [ "GOING MY WAY", "has_genre", "MUSIC" ], [ "GYPSY", "directed_by", "EMILE ARDOLINO" ], [ "GYPSY", "has_genre", "COMEDY" ], [ "HAIR", "has_genre", "COMEDY" ], [ "HAIR", "has_tags", "MUSIC" ], [ "HAIRSPRAY", "has_genre", "COMEDY" ], [ "HAIRSPRAY", "has_genre", "MUSIC" ], [ "HAIRSPRAY", "has_tags", "COMEDY" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "COMEDY" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "MUSIC" ], [ "HEDWIG AND THE ANGRY INCH", "has_tags", "MUSIC" ], [ "HERO", "has_genre", "COMEDY" ], [ "HERO", "release_year", "1992" ], [ "HIGH SCHOOL MUSICAL", "has_genre", "COMEDY" ], [ "HIGH SCHOOL MUSICAL", "has_tags", "MUSIC" ], [ "HOCUS POCUS", "has_genre", "COMEDY" ], [ "HOCUS POCUS", "starred_actors", "KATHY NAJIMY" ], [ "HONEYMOON IN VEGAS", "has_genre", "COMEDY" ], [ "HONEYMOON IN VEGAS", "release_year", "1992" ], [ "HOUSE PARTY", "has_genre", "COMEDY" ], [ "HOUSE PARTY", "has_genre", "MUSIC" ], [ "HUSBANDS AND WIVES", "has_genre", "COMEDY" ], [ "HUSBANDS AND WIVES", "release_year", "1992" ], [ "IN BRUGES", "has_genre", "COMEDY" ], [ "IN BRUGES", "has_tags", "COMEDY" ], [ "IN BRUGES", "has_tags", "MUSIC" ], [ "IN THE SOUP", "has_genre", "COMEDY" ], [ "IN THE SOUP", "release_year", "1992" ], [ "JOSIE AND THE PUSSYCATS", "has_genre", "COMEDY" ], [ "JOSIE AND THE PUSSYCATS", "has_genre", "MUSIC" ], [ "JOYFUL NOISE", "has_genre", "COMEDY" ], [ "JOYFUL NOISE", "has_genre", "MUSIC" ], [ "JUMPIN' JACK FLASH", "has_genre", "COMEDY" ], [ "JUMPIN' JACK FLASH", "has_tags", "WHOOPI GOLDBERG" ], [ "JUMPIN' JACK FLASH", "starred_actors", "WHOOPI GOLDBERG" ], [ "KEEPING MUM", "has_genre", "COMEDY" ], [ "KEEPING MUM", "has_tags", "MAGGIE SMITH" ], [ "KEEPING MUM", "starred_actors", "MAGGIE SMITH" ], [ "KILLING BONO", "has_genre", "COMEDY" ], [ "KILLING BONO", "has_genre", "MUSIC" ], [ "KILLING BONO", "has_tags", "MUSIC" ], [ "KING OF BEGGARS", "has_genre", "COMEDY" ], [ "KING OF BEGGARS", "release_year", "1992" ], [ "KUFFS", "has_genre", "COMEDY" ], [ "KUFFS", "release_year", "1992" ], [ "LADYBUGS", "has_genre", "COMEDY" ], [ "LADYBUGS", "release_year", "1992" ], [ "LEAVING NORMAL", "has_genre", "COMEDY" ], [ "LEAVING NORMAL", "release_year", "1992" ], [ "LITTLE SHOP OF HORRORS", "has_genre", "COMEDY" ], [ "LITTLE SHOP OF HORRORS", "has_tags", "MUSIC" ], [ "LITTLE SISTER", "has_genre", "COMEDY" ], [ "LITTLE SISTER", "release_year", "1992" ], [ "MADE IN AMERICA", "has_genre", "COMEDY" ], [ "MADE IN AMERICA", "has_tags", "WHOOPI GOLDBERG" ], [ "MADE IN AMERICA", "starred_actors", "WHOOPI GOLDBERG" ], [ "MALEDETTO IL GIORNO CHE T'HO INCONTRATO", "has_genre", "COMEDY" ], [ "MALEDETTO IL GIORNO CHE T'HO INCONTRATO", "release_year", "1992" ], [ "MAN BITES DOG", "has_genre", "COMEDY" ], [ "MAN BITES DOG", "release_year", "1992" ], [ "MAN TROUBLE", "has_genre", "COMEDY" ], [ "MAN TROUBLE", "release_year", "1992" ], [ "MEMOIRS OF AN INVISIBLE MAN", "has_genre", "COMEDY" ], [ "MEMOIRS OF AN INVISIBLE MAN", "release_year", "1992" ], [ "MISTRESS", "has_genre", "COMEDY" ], [ "MISTRESS", "release_year", "1992" ], [ "MO' MONEY", "has_genre", "COMEDY" ], [ "MO' MONEY", "release_year", "1992" ], [ "MOM AND DAD SAVE THE WORLD", "has_genre", "COMEDY" ], [ "MOM AND DAD SAVE THE WORLD", "release_year", "1992" ], [ "MONSTERS, INC.", "has_genre", "COMEDY" ], [ "MONSTERS, INC.", "has_tags", "COMEDY" ], [ "MONSTERS, INC.", "has_tags", "MUSIC" ], [ "MR. BASEBALL", "has_genre", "COMEDY" ], [ "MR. BASEBALL", "release_year", "1992" ], [ "MUSIC AND LYRICS", "has_genre", "COMEDY" ], [ "MUSIC AND LYRICS", "has_genre", "MUSIC" ], [ "MUSIC AND LYRICS", "has_tags", "COMEDY" ], [ "MY COUSIN VINNY", "has_genre", "COMEDY" ], [ "MY COUSIN VINNY", "has_tags", "COMEDY" ], [ "MY COUSIN VINNY", "release_year", "1992" ], [ "MY NEW GUN", "has_genre", "COMEDY" ], [ "MY NEW GUN", "release_year", "1992" ], [ "MY OLD LADY", "has_genre", "COMEDY" ], [ "MY OLD LADY", "starred_actors", "MAGGIE SMITH" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "COMEDY" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "COMEDY" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "MUSIC" ], [ "ON OUR MERRY WAY", "has_genre", "COMEDY" ], [ "ON OUR MERRY WAY", "has_genre", "MUSIC" ], [ "ONE HUNDRED MEN AND A GIRL", "has_genre", "COMEDY" ], [ "ONE HUNDRED MEN AND A GIRL", "has_genre", "MUSIC" ], [ "OUT ON A LIMB", "has_genre", "COMEDY" ], [ "OUT ON A LIMB", "release_year", "1992" ], [ "PARENTI SERPENTI", "has_genre", "COMEDY" ], [ "PARENTI SERPENTI", "release_year", "1992" ], [ "PETER'S FRIENDS", "has_genre", "COMEDY" ], [ "PETER'S FRIENDS", "release_year", "1992" ], [ "PITCH PERFECT", "has_genre", "COMEDY" ], [ "PITCH PERFECT", "has_genre", "MUSIC" ], [ "PITCH PERFECT", "has_tags", "MUSIC" ], [ "PUNCH-DRUNK LOVE", "has_genre", "COMEDY" ], [ "PUNCH-DRUNK LOVE", "has_tags", "COMEDY" ], [ "PUNCH-DRUNK LOVE", "has_tags", "MUSIC" ], [ "QUARTET", "has_genre", "COMEDY" ], [ "QUARTET", "has_tags", "COMEDY" ], [ "QUARTET", "starred_actors", "MAGGIE SMITH" ], [ "RADIO DAYS", "has_genre", "COMEDY" ], [ "RADIO DAYS", "has_tags", "MUSIC" ], [ "RAT RACE", "has_genre", "COMEDY" ], [ "RAT RACE", "has_tags", "COMEDY" ], [ "RAT RACE", "has_tags", "WHOOPI GOLDBERG" ], [ "RHINESTONE", "has_genre", "COMEDY" ], [ "RHINESTONE", "has_genre", "MUSIC" ], [ "RIO", "has_genre", "COMEDY" ], [ "RIO", "has_tags", "COMEDY" ], [ "RIO", "has_tags", "MUSIC" ], [ "ROCK 'N' ROLL HIGH SCHOOL", "has_genre", "COMEDY" ], [ "ROCK 'N' ROLL HIGH SCHOOL", "has_genre", "MUSIC" ], [ "ROCK STAR", "has_genre", "COMEDY" ], [ "ROCK STAR", "has_genre", "MUSIC" ], [ "SCHOOL OF ROCK", "has_genre", "COMEDY" ], [ "SCHOOL OF ROCK", "has_genre", "MUSIC" ], [ "SCHOOL OF ROCK", "has_tags", "MUSIC" ], [ "SCOTT PILGRIM VS. THE WORLD", "has_genre", "COMEDY" ], [ "SCOTT PILGRIM VS. THE WORLD", "has_tags", "COMEDY" ], [ "SCOTT PILGRIM VS. THE WORLD", "has_tags", "MUSIC" ], [ "SHERLOCK HOLMES", "has_tags", "COMEDY" ], [ "SHERLOCK HOLMES", "has_tags", "OCCULT" ], [ "SHERLOCK HOLMES", "has_tags", "SHERLOCK HOLMES" ], [ "SINGLES", "has_genre", "COMEDY" ], [ "SINGLES", "release_year", "1992" ], [ "SISTER ACT", "directed_by", "EMILE ARDOLINO" ], [ "SISTER ACT", "has_genre", "COMEDY" ], [ "SISTER ACT", "has_genre", "MUSIC" ], [ "SISTER ACT", "has_tags", "MAGGIE SMITH" ], [ "SISTER ACT", "has_tags", "WHOOPI GOLDBERG" ], [ "SISTER ACT", "release_year", "1992" ], [ "SISTER ACT", "starred_actors", "KATHY NAJIMY" ], [ "SISTER ACT", "starred_actors", "MAGGIE SMITH" ], [ "SISTER ACT", "starred_actors", "WENDY MAKKENA" ], [ "SISTER ACT", "starred_actors", "WHOOPI GOLDBERG" ], [ "SOUL MEN", "has_genre", "COMEDY" ], [ "SOUL MEN", "has_genre", "MUSIC" ], [ "SOUND OF NOISE", "has_genre", "COMEDY" ], [ "SOUND OF NOISE", "has_genre", "MUSIC" ], [ "SOUND OF NOISE", "has_tags", "MUSIC" ], [ "SPICE WORLD", "has_genre", "COMEDY" ], [ "SPICE WORLD", "has_genre", "MUSIC" ], [ "SPICE WORLD", "has_tags", "MUSIC" ], [ "STAY TUNED", "has_genre", "COMEDY" ], [ "STAY TUNED", "release_year", "1992" ], [ "STOP! OR MY MOM WILL SHOOT", "has_genre", "COMEDY" ], [ "STOP! OR MY MOM WILL SHOOT", "has_tags", "COMEDY" ], [ "STOP! OR MY MOM WILL SHOOT", "release_year", "1992" ], [ "STRAIGHT TALK", "has_genre", "COMEDY" ], [ "STRAIGHT TALK", "release_year", "1992" ], [ "STRICTLY BALLROOM", "has_genre", "COMEDY" ], [ "STRICTLY BALLROOM", "release_year", "1992" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "has_genre", "COMEDY" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "has_genre", "MUSIC" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "has_tags", "COMEDY" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "has_tags", "MUSIC" ], [ "THAT THING YOU DO!", "has_genre", "COMEDY" ], [ "THAT THING YOU DO!", "has_genre", "MUSIC" ], [ "THAT THING YOU DO!", "has_tags", "MUSIC" ], [ "THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT", "has_genre", "MUSIC" ], [ "THE BEST EXOTIC MARIGOLD HOTEL", "has_genre", "COMEDY" ], [ "THE BEST EXOTIC MARIGOLD HOTEL", "has_tags", "MAGGIE SMITH" ], [ "THE BIKINI CARWASH COMPANY", "has_genre", "COMEDY" ], [ "THE BIKINI CARWASH COMPANY", "release_year", "1992" ], [ "THE BLUES BROTHERS", "has_genre", "COMEDY" ], [ "THE BLUES BROTHERS", "has_tags", "COMEDY" ], [ "THE BLUES BROTHERS", "has_tags", "MUSIC" ], [ "THE DISTINGUISHED GENTLEMAN", "has_genre", "COMEDY" ], [ "THE DISTINGUISHED GENTLEMAN", "release_year", "1992" ], [ "THE FIGHTING TEMPTATIONS", "has_genre", "COMEDY" ], [ "THE FIGHTING TEMPTATIONS", "has_genre", "MUSIC" ], [ "THE FIRST WIVES CLUB", "has_genre", "COMEDY" ], [ "THE FIRST WIVES CLUB", "starred_actors", "MAGGIE SMITH" ], [ "THE FULL MONTY", "has_genre", "COMEDY" ], [ "THE FULL MONTY", "has_genre", "MUSIC" ], [ "THE GIRL CAN'T HELP IT", "has_genre", "COMEDY" ], [ "THE GIRL CAN'T HELP IT", "has_genre", "MUSIC" ], [ "THE GUN IN BETTY LOU'S HANDBAG", "has_genre", "COMEDY" ], [ "THE GUN IN BETTY LOU'S HANDBAG", "release_year", "1992" ], [ "THE HOUND OF THE BASKERVILLES", "has_genre", "COMEDY" ], [ "THE HOUND OF THE BASKERVILLES", "has_tags", "SHERLOCK HOLMES" ], [ "THE HUMAN COMEDY", "has_genre", "COMEDY" ], [ "THE HUMAN COMEDY", "starred_actors", "JAMES CRAIG" ], [ "THE MARC PEASE EXPERIENCE", "has_genre", "COMEDY" ], [ "THE MARC PEASE EXPERIENCE", "has_genre", "MUSIC" ], [ "THE MIGHTY DUCKS", "has_genre", "COMEDY" ], [ "THE MIGHTY DUCKS", "release_year", "1992" ], [ "THE MUPPET CHRISTMAS CAROL", "has_genre", "COMEDY" ], [ "THE MUPPET CHRISTMAS CAROL", "release_year", "1992" ], [ "THE MUPPETS", "has_genre", "COMEDY" ], [ "THE MUPPETS", "has_tags", "COMEDY" ], [ "THE MUPPETS", "has_tags", "MUSIC" ], [ "THE NORTHERNERS", "has_genre", "COMEDY" ], [ "THE NORTHERNERS", "release_year", "1992" ], [ "THE ROCKY HORROR PICTURE SHOW", "has_genre", "COMEDY" ], [ "THE ROCKY HORROR PICTURE SHOW", "has_tags", "MUSIC" ], [ "THE SECOND BEST EXOTIC MARIGOLD HOTEL", "has_genre", "COMEDY" ], [ "THE SECOND BEST EXOTIC MARIGOLD HOTEL", "starred_actors", "MAGGIE SMITH" ], [ "THE SECRET POLICEMAN'S OTHER BALL", "has_genre", "COMEDY" ], [ "THE SECRET POLICEMAN'S OTHER BALL", "has_genre", "MUSIC" ], [ "THE TELEPHONE", "has_genre", "COMEDY" ], [ "THE TELEPHONE", "starred_actors", "WHOOPI GOLDBERG" ], [ "THE WEST POINT STORY", "has_genre", "COMEDY" ], [ "THE WEST POINT STORY", "has_genre", "MUSIC" ], [ "TOYS", "has_genre", "COMEDY" ], [ "TOYS", "has_tags", "MUSIC" ], [ "TOYS", "release_year", "1992" ], [ "TWIN DRAGONS", "has_genre", "COMEDY" ], [ "TWIN DRAGONS", "release_year", "1992" ], [ "UNFAITHFULLY YOURS", "has_genre", "COMEDY" ], [ "UNFAITHFULLY YOURS", "has_genre", "MUSIC" ], [ "USED PEOPLE", "has_genre", "COMEDY" ], [ "USED PEOPLE", "release_year", "1992" ], [ "WAYNE'S WORLD", "has_genre", "COMEDY" ], [ "WAYNE'S WORLD", "has_tags", "COMEDY" ], [ "WAYNE'S WORLD", "release_year", "1992" ], [ "WHITE MEN CAN'T JUMP", "has_genre", "COMEDY" ], [ "WHITE MEN CAN'T JUMP", "has_tags", "COMEDY" ], [ "WHITE MEN CAN'T JUMP", "release_year", "1992" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 658, 2012 30665, 7 DAYS IN HAVANA 40144, CARANCHO 14724, CRIME 28900, JEREMY RENNER 8993, PABLO TRAPERO 16103, THE AVENGERS 7809, THE BIG HEAT 35366, THE BOURNE LEGACY 21183, WHITE ELEPHANT 32616, WILLIAM P. MCGIVERN src, edge_attr, dst 30665, directed_by, 8993 30665, release_year, 658 30665, written_by, 8993 40144, directed_by, 8993 40144, has_genre, 14724 40144, written_by, 8993 16103, has_tags, 28900 16103, release_year, 658 7809, has_genre, 14724 7809, written_by, 32616 35366, has_tags, 28900 35366, release_year, 658 35366, starred_actors, 28900 21183, directed_by, 8993 21183, release_year, 658 21183, written_by, 8993 Question: In what context are PABLO TRAPERO, THE BOURNE LEGACY, and WILLIAM P. MCGIVERN connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "PABLO TRAPERO", "THE BOURNE LEGACY", "WILLIAM P. MCGIVERN" ], "valid_edges": [ [ "7 DAYS IN HAVANA", "directed_by", "PABLO TRAPERO" ], [ "7 DAYS IN HAVANA", "release_year", "2012" ], [ "7 DAYS IN HAVANA", "written_by", "PABLO TRAPERO" ], [ "CARANCHO", "directed_by", "PABLO TRAPERO" ], [ "CARANCHO", "has_genre", "CRIME" ], [ "CARANCHO", "written_by", "PABLO TRAPERO" ], [ "THE AVENGERS", "has_tags", "JEREMY RENNER" ], [ "THE AVENGERS", "release_year", "2012" ], [ "THE BIG HEAT", "has_genre", "CRIME" ], [ "THE BIG HEAT", "written_by", "WILLIAM P. MCGIVERN" ], [ "THE BOURNE LEGACY", "has_tags", "JEREMY RENNER" ], [ "THE BOURNE LEGACY", "release_year", "2012" ], [ "THE BOURNE LEGACY", "starred_actors", "JEREMY RENNER" ], [ "WHITE ELEPHANT", "directed_by", "PABLO TRAPERO" ], [ "WHITE ELEPHANT", "release_year", "2012" ], [ "WHITE ELEPHANT", "written_by", "PABLO TRAPERO" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13408, 2001 17315, 2007 24524, AKS 20999, ALONG CAME A SPIDER 16071, ANAMORPH 12750, ANTITRUST 19554, AWAKE 26119, BLACK WATER 10473, BLACKWOODS 33881, BOARDING GATE 23863, CAPTIVITY 38311, CHAOS 30917, CHERRY CRUSH 7664, CLEANER 39282, DEAD SILENCE 8961, DEATH PROOF 11558, DESCENT 6015, DISTURBIA 13064, DOMESTIC DISTURBANCE 15291, DON'T SAY A WORD 27306, EARTH VS. THE SPIDER 12628, EASTERN PROMISES 30496, EMMETT'S MARK 3242, FERMAT'S ROOM 37985, FRAILTY 5287, FROZEN 9003, FUNNY GAMES 17938, HANNIBAL 2752, HIDDEN AGENDA 26493, I KNOW WHO KILLED ME 27489, INTACTO 27830, JOSHUA 378, JOY RIDE 22804, LUST, CAUTION 26860, MAD DETECTIVE 39315, MICHAEL CLAYTON 24632, MIMIC 2 5053, MULHOLLAND DRIVE 29903, NAKED FEAR 30350, NEXT 7805, NO COUNTRY FOR OLD MEN 30966, P2 32178, PERFECT STRANGER 38005, RENDITION 24844, SCOTT WOLF 6119, SLEUTH 24221, SPEAKING OF SEX 25120, SPIRAL 40061, STUCK 26125, SUNSHINE 30932, SWORDFISH 33436, THE BANK 5365, THE BODY 12208, THE BOURNE ULTIMATUM 10389, THE BRAVE ONE 25509, THE DEBT 4175, THE DETECTIVE 2599, THE EXPERIMENT 6242, THE FOURTH ANGEL 35772, THE GIRL BY THE LAKE 3847, THE GLASS HOUSE 22621, THE HITCHER 23333, THE HOLE 7134, THE INVASION 39043, THE LEARNING CURVE 36991, THE LIFE BEFORE HER EYES 5166, THE NUMBER 23 28095, THE SIGNAL 33478, THE TAILOR OF PANAMA 24811, THRILLER 22446, TIMBER FALLS 17169, TRAINING DAY 8974, TREED MURRAY 37099, TRIANGLE 23568, VANILLA SKY 25736, ZEBRA LOUNGE src, edge_attr, dst 24524, has_genre, 24811 24524, release_year, 13408 20999, has_tags, 24811 20999, release_year, 13408 16071, has_genre, 24811 16071, release_year, 17315 12750, has_genre, 24811 12750, release_year, 13408 19554, has_genre, 24811 19554, release_year, 17315 26119, has_tags, 24811 26119, release_year, 17315 10473, has_genre, 24811 10473, release_year, 13408 33881, has_genre, 24811 33881, release_year, 17315 23863, has_genre, 24811 23863, release_year, 17315 38311, has_genre, 24811 38311, release_year, 13408 30917, has_genre, 24811 30917, release_year, 17315 7664, has_genre, 24811 7664, release_year, 17315 39282, has_genre, 24811 39282, release_year, 17315 8961, has_genre, 24811 8961, release_year, 17315 11558, has_genre, 24811 11558, release_year, 17315 6015, has_genre, 24811 6015, has_tags, 24811 6015, release_year, 17315 13064, has_genre, 24811 13064, release_year, 13408 15291, has_genre, 24811 15291, has_tags, 24811 15291, release_year, 13408 27306, has_genre, 24811 27306, release_year, 13408 12628, has_genre, 24811 12628, release_year, 17315 30496, has_genre, 24811 30496, starred_actors, 24844 3242, has_genre, 24811 3242, release_year, 17315 37985, has_genre, 24811 37985, release_year, 13408 5287, has_genre, 24811 5287, release_year, 17315 9003, has_genre, 24811 9003, has_tags, 24811 9003, release_year, 17315 17938, has_genre, 24811 17938, release_year, 13408 2752, has_genre, 24811 2752, release_year, 13408 26493, has_genre, 24811 26493, release_year, 17315 27489, has_genre, 24811 27489, release_year, 13408 27830, has_genre, 24811 27830, has_tags, 24811 27830, release_year, 17315 378, has_genre, 24811 378, release_year, 13408 22804, has_genre, 24811 22804, release_year, 17315 26860, has_genre, 24811 26860, release_year, 17315 39315, has_tags, 24811 39315, release_year, 17315 24632, has_genre, 24811 24632, release_year, 13408 5053, has_genre, 24811 5053, has_tags, 24811 5053, release_year, 13408 29903, has_genre, 24811 29903, release_year, 17315 30350, has_genre, 24811 30350, release_year, 17315 7805, has_genre, 24811 7805, has_tags, 24811 7805, release_year, 17315 30966, has_genre, 24811 30966, release_year, 17315 32178, has_genre, 24811 32178, has_tags, 24811 32178, release_year, 17315 38005, has_genre, 24811 38005, release_year, 17315 6119, has_genre, 24811 6119, release_year, 17315 24221, release_year, 13408 25120, has_genre, 24811 25120, release_year, 17315 40061, has_genre, 24811 40061, release_year, 17315 26125, has_genre, 24811 26125, release_year, 17315 30932, has_genre, 24811 30932, release_year, 13408 33436, has_genre, 24811 33436, release_year, 13408 5365, has_genre, 24811 5365, release_year, 13408 12208, has_genre, 24811 12208, has_tags, 24811 12208, release_year, 17315 10389, has_genre, 24811 10389, release_year, 17315 25509, has_genre, 24811 25509, release_year, 17315 4175, has_genre, 24811 4175, release_year, 17315 2599, has_genre, 24811 2599, release_year, 13408 6242, has_genre, 24811 6242, release_year, 13408 35772, has_genre, 24811 35772, release_year, 17315 3847, has_genre, 24811 3847, release_year, 13408 22621, has_genre, 24811 22621, release_year, 17315 23333, has_genre, 24811 23333, release_year, 13408 7134, has_genre, 24811 7134, release_year, 17315 39043, has_genre, 24811 39043, release_year, 13408 36991, has_genre, 24811 36991, release_year, 17315 5166, has_genre, 24811 5166, release_year, 17315 28095, has_genre, 24811 28095, release_year, 17315 33478, has_genre, 24811 33478, release_year, 13408 22446, has_genre, 24811 22446, release_year, 17315 17169, has_genre, 24811 17169, release_year, 13408 8974, has_genre, 24811 8974, release_year, 13408 37099, has_genre, 24811 37099, release_year, 17315 23568, has_tags, 24811 23568, release_year, 13408 25736, has_genre, 24811 25736, release_year, 13408 Question: For what reason are BLACK WATER, SCOTT WOLF, and SPEAKING OF SEX associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BLACK WATER", "SCOTT WOLF", "SPEAKING OF SEX" ], "valid_edges": [ [ "AKS", "has_genre", "THRILLER" ], [ "AKS", "release_year", "2001" ], [ "ALONG CAME A SPIDER", "has_tags", "THRILLER" ], [ "ALONG CAME A SPIDER", "release_year", "2001" ], [ "ANAMORPH", "has_genre", "THRILLER" ], [ "ANAMORPH", "release_year", "2007" ], [ "ANTITRUST", "has_genre", "THRILLER" ], [ "ANTITRUST", "release_year", "2001" ], [ "AWAKE", "has_genre", "THRILLER" ], [ "AWAKE", "release_year", "2007" ], [ "BLACK WATER", "has_tags", "THRILLER" ], [ "BLACK WATER", "release_year", "2007" ], [ "BLACKWOODS", "has_genre", "THRILLER" ], [ "BLACKWOODS", "release_year", "2001" ], [ "BOARDING GATE", "has_genre", "THRILLER" ], [ "BOARDING GATE", "release_year", "2007" ], [ "CAPTIVITY", "has_genre", "THRILLER" ], [ "CAPTIVITY", "release_year", "2007" ], [ "CHAOS", "has_genre", "THRILLER" ], [ "CHAOS", "release_year", "2001" ], [ "CHERRY CRUSH", "has_genre", "THRILLER" ], [ "CHERRY CRUSH", "release_year", "2007" ], [ "CLEANER", "has_genre", "THRILLER" ], [ "CLEANER", "release_year", "2007" ], [ "DEAD SILENCE", "has_genre", "THRILLER" ], [ "DEAD SILENCE", "release_year", "2007" ], [ "DEATH PROOF", "has_genre", "THRILLER" ], [ "DEATH PROOF", "release_year", "2007" ], [ "DESCENT", "has_genre", "THRILLER" ], [ "DESCENT", "release_year", "2007" ], [ "DISTURBIA", "has_genre", "THRILLER" ], [ "DISTURBIA", "has_tags", "THRILLER" ], [ "DISTURBIA", "release_year", "2007" ], [ "DOMESTIC DISTURBANCE", "has_genre", "THRILLER" ], [ "DOMESTIC DISTURBANCE", "release_year", "2001" ], [ "DON'T SAY A WORD", "has_genre", "THRILLER" ], [ "DON'T SAY A WORD", "has_tags", "THRILLER" ], [ "DON'T SAY A WORD", "release_year", "2001" ], [ "EARTH VS. THE SPIDER", "has_genre", "THRILLER" ], [ "EARTH VS. THE SPIDER", "release_year", "2001" ], [ "EASTERN PROMISES", "has_genre", "THRILLER" ], [ "EASTERN PROMISES", "release_year", "2007" ], [ "EMMETT'S MARK", "has_genre", "THRILLER" ], [ "EMMETT'S MARK", "starred_actors", "SCOTT WOLF" ], [ "FERMAT'S ROOM", "has_genre", "THRILLER" ], [ "FERMAT'S ROOM", "release_year", "2007" ], [ "FRAILTY", "has_genre", "THRILLER" ], [ "FRAILTY", "release_year", "2001" ], [ "FROZEN", "has_genre", "THRILLER" ], [ "FROZEN", "release_year", "2007" ], [ "FUNNY GAMES", "has_genre", "THRILLER" ], [ "FUNNY GAMES", "has_tags", "THRILLER" ], [ "FUNNY GAMES", "release_year", "2007" ], [ "HANNIBAL", "has_genre", "THRILLER" ], [ "HANNIBAL", "release_year", "2001" ], [ "HIDDEN AGENDA", "has_genre", "THRILLER" ], [ "HIDDEN AGENDA", "release_year", "2001" ], [ "I KNOW WHO KILLED ME", "has_genre", "THRILLER" ], [ "I KNOW WHO KILLED ME", "release_year", "2007" ], [ "INTACTO", "has_genre", "THRILLER" ], [ "INTACTO", "release_year", "2001" ], [ "JOSHUA", "has_genre", "THRILLER" ], [ "JOSHUA", "has_tags", "THRILLER" ], [ "JOSHUA", "release_year", "2007" ], [ "JOY RIDE", "has_genre", "THRILLER" ], [ "JOY RIDE", "release_year", "2001" ], [ "LUST, CAUTION", "has_genre", "THRILLER" ], [ "LUST, CAUTION", "release_year", "2007" ], [ "MAD DETECTIVE", "has_genre", "THRILLER" ], [ "MAD DETECTIVE", "release_year", "2007" ], [ "MICHAEL CLAYTON", "has_tags", "THRILLER" ], [ "MICHAEL CLAYTON", "release_year", "2007" ], [ "MIMIC 2", "has_genre", "THRILLER" ], [ "MIMIC 2", "release_year", "2001" ], [ "MULHOLLAND DRIVE", "has_genre", "THRILLER" ], [ "MULHOLLAND DRIVE", "has_tags", "THRILLER" ], [ "MULHOLLAND DRIVE", "release_year", "2001" ], [ "NAKED FEAR", "has_genre", "THRILLER" ], [ "NAKED FEAR", "release_year", "2007" ], [ "NEXT", "has_genre", "THRILLER" ], [ "NEXT", "release_year", "2007" ], [ "NO COUNTRY FOR OLD MEN", "has_genre", "THRILLER" ], [ "NO COUNTRY FOR OLD MEN", "has_tags", "THRILLER" ], [ "NO COUNTRY FOR OLD MEN", "release_year", "2007" ], [ "P2", "has_genre", "THRILLER" ], [ "P2", "release_year", "2007" ], [ "PERFECT STRANGER", "has_genre", "THRILLER" ], [ "PERFECT STRANGER", "has_tags", "THRILLER" ], [ "PERFECT STRANGER", "release_year", "2007" ], [ "RENDITION", "has_genre", "THRILLER" ], [ "RENDITION", "release_year", "2007" ], [ "SLEUTH", "has_genre", "THRILLER" ], [ "SLEUTH", "release_year", "2007" ], [ "SPEAKING OF SEX", "release_year", "2001" ], [ "SPIRAL", "has_genre", "THRILLER" ], [ "SPIRAL", "release_year", "2007" ], [ "STUCK", "has_genre", "THRILLER" ], [ "STUCK", "release_year", "2007" ], [ "SUNSHINE", "has_genre", "THRILLER" ], [ "SUNSHINE", "release_year", "2007" ], [ "SWORDFISH", "has_genre", "THRILLER" ], [ "SWORDFISH", "release_year", "2001" ], [ "THE BANK", "has_genre", "THRILLER" ], [ "THE BANK", "release_year", "2001" ], [ "THE BODY", "has_genre", "THRILLER" ], [ "THE BODY", "release_year", "2001" ], [ "THE BOURNE ULTIMATUM", "has_genre", "THRILLER" ], [ "THE BOURNE ULTIMATUM", "has_tags", "THRILLER" ], [ "THE BOURNE ULTIMATUM", "release_year", "2007" ], [ "THE BRAVE ONE", "has_genre", "THRILLER" ], [ "THE BRAVE ONE", "release_year", "2007" ], [ "THE DEBT", "has_genre", "THRILLER" ], [ "THE DEBT", "release_year", "2007" ], [ "THE DETECTIVE", "has_genre", "THRILLER" ], [ "THE DETECTIVE", "release_year", "2007" ], [ "THE EXPERIMENT", "has_genre", "THRILLER" ], [ "THE EXPERIMENT", "release_year", "2001" ], [ "THE FOURTH ANGEL", "has_genre", "THRILLER" ], [ "THE FOURTH ANGEL", "release_year", "2001" ], [ "THE GIRL BY THE LAKE", "has_genre", "THRILLER" ], [ "THE GIRL BY THE LAKE", "release_year", "2007" ], [ "THE GLASS HOUSE", "has_genre", "THRILLER" ], [ "THE GLASS HOUSE", "release_year", "2001" ], [ "THE HITCHER", "has_genre", "THRILLER" ], [ "THE HITCHER", "release_year", "2007" ], [ "THE HOLE", "has_genre", "THRILLER" ], [ "THE HOLE", "release_year", "2001" ], [ "THE INVASION", "has_genre", "THRILLER" ], [ "THE INVASION", "release_year", "2007" ], [ "THE LEARNING CURVE", "has_genre", "THRILLER" ], [ "THE LEARNING CURVE", "release_year", "2001" ], [ "THE LIFE BEFORE HER EYES", "has_genre", "THRILLER" ], [ "THE LIFE BEFORE HER EYES", "release_year", "2007" ], [ "THE NUMBER 23", "has_genre", "THRILLER" ], [ "THE NUMBER 23", "release_year", "2007" ], [ "THE SIGNAL", "has_genre", "THRILLER" ], [ "THE SIGNAL", "release_year", "2007" ], [ "THE TAILOR OF PANAMA", "has_genre", "THRILLER" ], [ "THE TAILOR OF PANAMA", "release_year", "2001" ], [ "TIMBER FALLS", "has_genre", "THRILLER" ], [ "TIMBER FALLS", "release_year", "2007" ], [ "TRAINING DAY", "has_genre", "THRILLER" ], [ "TRAINING DAY", "release_year", "2001" ], [ "TREED MURRAY", "has_genre", "THRILLER" ], [ "TREED MURRAY", "release_year", "2001" ], [ "TRIANGLE", "has_genre", "THRILLER" ], [ "TRIANGLE", "release_year", "2007" ], [ "VANILLA SKY", "has_tags", "THRILLER" ], [ "VANILLA SKY", "release_year", "2001" ], [ "ZEBRA LOUNGE", "has_genre", "THRILLER" ], [ "ZEBRA LOUNGE", "release_year", "2001" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 8539, 1982 18504, 300 MILES TO HEAVEN 3849, A QUESTION OF SILENCE 3466, A SHORT FILM ABOUT LOVE 10184, ALL THAT I LOVE 8047, AN OFFICER AND A GENTLEMAN 20033, ANGEL 39876, ANNIE 16584, ARLENE SARNER 1156, AVALON 29743, BEST FRIENDS 26260, BLUE SKY 27, CAMERA BUFF 17892, CAMOUFLAGE 21730, DAY OF THE WACKO 2115, DEAD RINGERS 8663, DEEP END 35313, DESPERATE SEARCH 39164, DINER 36212, DRAMA 9693, FANNY AND ALEXANDER 5599, FIVE DAYS ONE SUMMER 15398, FLOATING SKYSCRAPERS 34973, FOUR NIGHTS WITH ANNA 9999, GANDHI 5359, HONKYTONK MAN 37734, IDENTIFICATION OF A WOMAN 25995, IF YOU COULD SEE WHAT I HEAR 15343, IN DARKNESS 29418, JEREMY IRONS 23999, JERRY LEICHTLING 2723, JERZY SKOLIMOWSKI 15322, LOLITA 36539, M. BUTTERFLY 35181, MARGIN CALL 23574, MISSING 12803, MONSIGNOR 19819, MOONLIGHTING 15644, OLIVER TWIST 25824, PARADISE 11477, PATRICIA MEDINA 20473, PEGGY SUE GOT MARRIED 38321, PENITENTIARY II 20075, POLISH 1280, QUERELLE 30622, SALTO 34329, SCHINDLER'S LIST 20221, SHOOT THE MOON 9274, SIX PACK 2950, SIX WEEKS 1857, SOME KIND OF HERO 35597, SOPHIE'S CHOICE 20689, STARSTRUCK 29038, STEALING BEAUTY 23708, SUICIDE ROOM 7985, SYMMETRY 12282, TATARAK 2819, TEMPEST 4666, TEX 14122, THAT CHAMPIONSHIP SEASON 36088, THAT NIGHT IN VARENNES 9426, THE ASHES 7224, THE BORDER 8920, THE DARK HOUSE 25509, THE DEBT 22234, THE ELEPHANT MAN 25206, THE FRENCH LIEUTENANT'S WOMAN 35661, THE MAN FROM SNOWY RIVER 38433, THE MERCHANT OF VENICE 27045, THE MISSION 15155, THE NIGHT OF THE SHOOTING STARS 29172, THE PLAGUE DOGS 20953, THE PREFAB PEOPLE 21368, THE PROMISED LAND 8251, THE SECRET OF NIMH 14833, THE SIMPLE-MINDED MURDERER 279, THE VERDICT 14988, THE WAY BACK 6079, THE WEDDING NIGHT 8555, THE WOMAN IN THE FIFTH 15504, THE WORDS 38787, THE WORLD ACCORDING TO GARP 11863, THE YEAR OF LIVING DANGEROUSLY 27750, VICE SQUAD 32286, WHITE DOG 28023, WHITE NIGHTS 6567, WITH FIRE AND SWORD src, edge_attr, dst 18504, has_genre, 36212 18504, in_language, 20075 3849, has_genre, 36212 3849, release_year, 8539 3466, has_genre, 36212 3466, in_language, 20075 10184, has_genre, 36212 10184, in_language, 20075 8047, has_genre, 36212 8047, release_year, 8539 20033, has_genre, 36212 20033, release_year, 8539 39876, has_genre, 36212 39876, release_year, 8539 1156, has_genre, 36212 1156, in_language, 20075 29743, has_genre, 36212 29743, release_year, 8539 26260, has_genre, 36212 26260, written_by, 16584 26260, written_by, 23999 27, has_genre, 36212 27, in_language, 20075 17892, has_genre, 36212 17892, in_language, 20075 21730, has_genre, 36212 21730, in_language, 20075 2115, has_genre, 36212 2115, starred_actors, 29418 8663, directed_by, 2723 8663, has_genre, 36212 8663, has_tags, 2723 8663, written_by, 2723 35313, has_genre, 36212 35313, starred_actors, 11477 39164, has_genre, 36212 39164, release_year, 8539 9693, has_genre, 36212 9693, release_year, 8539 5599, has_genre, 36212 5599, release_year, 8539 15398, has_genre, 36212 15398, in_language, 20075 34973, directed_by, 2723 34973, has_genre, 36212 34973, in_language, 20075 34973, written_by, 2723 9999, has_genre, 36212 9999, release_year, 8539 5359, has_genre, 36212 5359, release_year, 8539 37734, has_genre, 36212 37734, release_year, 8539 25995, has_genre, 36212 25995, release_year, 8539 15343, has_genre, 36212 15343, in_language, 20075 15322, has_genre, 36212 15322, has_tags, 36212 15322, starred_actors, 29418 36539, has_genre, 36212 36539, starred_actors, 29418 35181, has_genre, 36212 35181, has_tags, 29418 35181, starred_actors, 29418 23574, has_genre, 36212 23574, release_year, 8539 12803, has_genre, 36212 12803, release_year, 8539 19819, directed_by, 2723 19819, has_genre, 36212 19819, has_tags, 2723 19819, in_language, 20075 19819, release_year, 8539 19819, starred_actors, 29418 19819, written_by, 2723 15644, has_genre, 36212 15644, release_year, 8539 25824, has_genre, 36212 25824, release_year, 8539 20473, has_genre, 36212 20473, has_tags, 36212 20473, written_by, 16584 20473, written_by, 23999 38321, has_genre, 36212 38321, release_year, 8539 1280, has_genre, 36212 1280, release_year, 8539 30622, has_genre, 36212 30622, has_tags, 20075 30622, in_language, 20075 34329, has_genre, 36212 34329, has_tags, 36212 34329, in_language, 20075 20221, has_genre, 36212 20221, release_year, 8539 9274, has_genre, 36212 9274, release_year, 8539 2950, has_genre, 36212 2950, release_year, 8539 1857, has_genre, 36212 1857, release_year, 8539 35597, has_genre, 36212 35597, in_language, 20075 35597, release_year, 8539 20689, has_genre, 36212 20689, release_year, 8539 29038, has_genre, 36212 29038, has_tags, 29418 23708, has_genre, 36212 23708, in_language, 20075 7985, has_genre, 36212 7985, in_language, 20075 12282, has_genre, 36212 12282, in_language, 20075 2819, has_genre, 36212 2819, release_year, 8539 4666, has_genre, 36212 4666, release_year, 8539 14122, has_genre, 36212 14122, release_year, 8539 36088, has_genre, 36212 36088, release_year, 8539 9426, has_genre, 36212 9426, in_language, 20075 7224, has_genre, 36212 7224, release_year, 8539 8920, has_genre, 36212 8920, in_language, 20075 25509, has_genre, 36212 25509, in_language, 20075 22234, has_genre, 36212 22234, release_year, 8539 25206, has_genre, 36212 25206, has_tags, 29418 25206, starred_actors, 29418 35661, has_genre, 36212 35661, release_year, 8539 38433, has_genre, 36212 38433, starred_actors, 29418 27045, has_genre, 36212 27045, has_tags, 29418 27045, starred_actors, 29418 15155, has_genre, 36212 15155, release_year, 8539 29172, has_genre, 36212 29172, release_year, 8539 20953, has_genre, 36212 20953, release_year, 8539 21368, has_genre, 36212 21368, in_language, 20075 8251, has_genre, 36212 8251, release_year, 8539 14833, has_genre, 36212 14833, release_year, 8539 279, has_genre, 36212 279, release_year, 8539 14988, has_genre, 36212 14988, in_language, 20075 6079, has_genre, 36212 6079, in_language, 20075 8555, has_genre, 36212 8555, in_language, 20075 15504, has_genre, 36212 15504, has_tags, 29418 15504, starred_actors, 29418 38787, has_genre, 36212 38787, release_year, 8539 11863, has_genre, 36212 11863, release_year, 8539 27750, has_genre, 36212 27750, release_year, 8539 32286, has_genre, 36212 32286, release_year, 8539 28023, has_genre, 36212 28023, starred_actors, 2723 6567, has_genre, 36212 6567, in_language, 20075 Question: In what context are ARLENE SARNER, MOONLIGHTING, and PATRICIA MEDINA connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ARLENE SARNER", "MOONLIGHTING", "PATRICIA MEDINA" ], "valid_edges": [ [ "300 MILES TO HEAVEN", "has_genre", "DRAMA" ], [ "300 MILES TO HEAVEN", "in_language", "POLISH" ], [ "A QUESTION OF SILENCE", "has_genre", "DRAMA" ], [ "A QUESTION OF SILENCE", "release_year", "1982" ], [ "A SHORT FILM ABOUT LOVE", "has_genre", "DRAMA" ], [ "A SHORT FILM ABOUT LOVE", "in_language", "POLISH" ], [ "ALL THAT I LOVE", "has_genre", "DRAMA" ], [ "ALL THAT I LOVE", "in_language", "POLISH" ], [ "AN OFFICER AND A GENTLEMAN", "has_genre", "DRAMA" ], [ "AN OFFICER AND A GENTLEMAN", "release_year", "1982" ], [ "ANGEL", "has_genre", "DRAMA" ], [ "ANGEL", "release_year", "1982" ], [ "ANNIE", "has_genre", "DRAMA" ], [ "ANNIE", "release_year", "1982" ], [ "AVALON", "has_genre", "DRAMA" ], [ "AVALON", "in_language", "POLISH" ], [ "BEST FRIENDS", "has_genre", "DRAMA" ], [ "BEST FRIENDS", "release_year", "1982" ], [ "BLUE SKY", "has_genre", "DRAMA" ], [ "BLUE SKY", "written_by", "ARLENE SARNER" ], [ "BLUE SKY", "written_by", "JERRY LEICHTLING" ], [ "CAMERA BUFF", "has_genre", "DRAMA" ], [ "CAMERA BUFF", "in_language", "POLISH" ], [ "CAMOUFLAGE", "has_genre", "DRAMA" ], [ "CAMOUFLAGE", "in_language", "POLISH" ], [ "DAY OF THE WACKO", "has_genre", "DRAMA" ], [ "DAY OF THE WACKO", "in_language", "POLISH" ], [ "DEAD RINGERS", "has_genre", "DRAMA" ], [ "DEAD RINGERS", "starred_actors", "JEREMY IRONS" ], [ "DEEP END", "directed_by", "JERZY SKOLIMOWSKI" ], [ "DEEP END", "has_genre", "DRAMA" ], [ "DEEP END", "has_tags", "JERZY SKOLIMOWSKI" ], [ "DEEP END", "written_by", "JERZY SKOLIMOWSKI" ], [ "DESPERATE SEARCH", "has_genre", "DRAMA" ], [ "DESPERATE SEARCH", "starred_actors", "PATRICIA MEDINA" ], [ "DINER", "has_genre", "DRAMA" ], [ "DINER", "release_year", "1982" ], [ "FANNY AND ALEXANDER", "has_genre", "DRAMA" ], [ "FANNY AND ALEXANDER", "release_year", "1982" ], [ "FIVE DAYS ONE SUMMER", "has_genre", "DRAMA" ], [ "FIVE DAYS ONE SUMMER", "release_year", "1982" ], [ "FLOATING SKYSCRAPERS", "has_genre", "DRAMA" ], [ "FLOATING SKYSCRAPERS", "in_language", "POLISH" ], [ "FOUR NIGHTS WITH ANNA", "directed_by", "JERZY SKOLIMOWSKI" ], [ "FOUR NIGHTS WITH ANNA", "has_genre", "DRAMA" ], [ "FOUR NIGHTS WITH ANNA", "in_language", "POLISH" ], [ "FOUR NIGHTS WITH ANNA", "written_by", "JERZY SKOLIMOWSKI" ], [ "GANDHI", "has_genre", "DRAMA" ], [ "GANDHI", "release_year", "1982" ], [ "HONKYTONK MAN", "has_genre", "DRAMA" ], [ "HONKYTONK MAN", "release_year", "1982" ], [ "IDENTIFICATION OF A WOMAN", "has_genre", "DRAMA" ], [ "IDENTIFICATION OF A WOMAN", "release_year", "1982" ], [ "IF YOU COULD SEE WHAT I HEAR", "has_genre", "DRAMA" ], [ "IF YOU COULD SEE WHAT I HEAR", "release_year", "1982" ], [ "IN DARKNESS", "has_genre", "DRAMA" ], [ "IN DARKNESS", "in_language", "POLISH" ], [ "LOLITA", "has_genre", "DRAMA" ], [ "LOLITA", "has_tags", "DRAMA" ], [ "LOLITA", "starred_actors", "JEREMY IRONS" ], [ "M. BUTTERFLY", "has_genre", "DRAMA" ], [ "M. BUTTERFLY", "starred_actors", "JEREMY IRONS" ], [ "MARGIN CALL", "has_genre", "DRAMA" ], [ "MARGIN CALL", "has_tags", "JEREMY IRONS" ], [ "MARGIN CALL", "starred_actors", "JEREMY IRONS" ], [ "MISSING", "has_genre", "DRAMA" ], [ "MISSING", "release_year", "1982" ], [ "MONSIGNOR", "has_genre", "DRAMA" ], [ "MONSIGNOR", "release_year", "1982" ], [ "MOONLIGHTING", "directed_by", "JERZY SKOLIMOWSKI" ], [ "MOONLIGHTING", "has_genre", "DRAMA" ], [ "MOONLIGHTING", "has_tags", "JERZY SKOLIMOWSKI" ], [ "MOONLIGHTING", "in_language", "POLISH" ], [ "MOONLIGHTING", "release_year", "1982" ], [ "MOONLIGHTING", "starred_actors", "JEREMY IRONS" ], [ "MOONLIGHTING", "written_by", "JERZY SKOLIMOWSKI" ], [ "OLIVER TWIST", "has_genre", "DRAMA" ], [ "OLIVER TWIST", "release_year", "1982" ], [ "PARADISE", "has_genre", "DRAMA" ], [ "PARADISE", "release_year", "1982" ], [ "PEGGY SUE GOT MARRIED", "has_genre", "DRAMA" ], [ "PEGGY SUE GOT MARRIED", "has_tags", "DRAMA" ], [ "PEGGY SUE GOT MARRIED", "written_by", "ARLENE SARNER" ], [ "PEGGY SUE GOT MARRIED", "written_by", "JERRY LEICHTLING" ], [ "PENITENTIARY II", "has_genre", "DRAMA" ], [ "PENITENTIARY II", "release_year", "1982" ], [ "QUERELLE", "has_genre", "DRAMA" ], [ "QUERELLE", "release_year", "1982" ], [ "SALTO", "has_genre", "DRAMA" ], [ "SALTO", "has_tags", "POLISH" ], [ "SALTO", "in_language", "POLISH" ], [ "SCHINDLER'S LIST", "has_genre", "DRAMA" ], [ "SCHINDLER'S LIST", "has_tags", "DRAMA" ], [ "SCHINDLER'S LIST", "in_language", "POLISH" ], [ "SHOOT THE MOON", "has_genre", "DRAMA" ], [ "SHOOT THE MOON", "release_year", "1982" ], [ "SIX PACK", "has_genre", "DRAMA" ], [ "SIX PACK", "release_year", "1982" ], [ "SIX WEEKS", "has_genre", "DRAMA" ], [ "SIX WEEKS", "release_year", "1982" ], [ "SOME KIND OF HERO", "has_genre", "DRAMA" ], [ "SOME KIND OF HERO", "release_year", "1982" ], [ "SOPHIE'S CHOICE", "has_genre", "DRAMA" ], [ "SOPHIE'S CHOICE", "in_language", "POLISH" ], [ "SOPHIE'S CHOICE", "release_year", "1982" ], [ "STARSTRUCK", "has_genre", "DRAMA" ], [ "STARSTRUCK", "release_year", "1982" ], [ "STEALING BEAUTY", "has_genre", "DRAMA" ], [ "STEALING BEAUTY", "has_tags", "JEREMY IRONS" ], [ "SUICIDE ROOM", "has_genre", "DRAMA" ], [ "SUICIDE ROOM", "in_language", "POLISH" ], [ "SYMMETRY", "has_genre", "DRAMA" ], [ "SYMMETRY", "in_language", "POLISH" ], [ "TATARAK", "has_genre", "DRAMA" ], [ "TATARAK", "in_language", "POLISH" ], [ "TEMPEST", "has_genre", "DRAMA" ], [ "TEMPEST", "release_year", "1982" ], [ "TEX", "has_genre", "DRAMA" ], [ "TEX", "release_year", "1982" ], [ "THAT CHAMPIONSHIP SEASON", "has_genre", "DRAMA" ], [ "THAT CHAMPIONSHIP SEASON", "release_year", "1982" ], [ "THAT NIGHT IN VARENNES", "has_genre", "DRAMA" ], [ "THAT NIGHT IN VARENNES", "release_year", "1982" ], [ "THE ASHES", "has_genre", "DRAMA" ], [ "THE ASHES", "in_language", "POLISH" ], [ "THE BORDER", "has_genre", "DRAMA" ], [ "THE BORDER", "release_year", "1982" ], [ "THE DARK HOUSE", "has_genre", "DRAMA" ], [ "THE DARK HOUSE", "in_language", "POLISH" ], [ "THE DEBT", "has_genre", "DRAMA" ], [ "THE DEBT", "in_language", "POLISH" ], [ "THE ELEPHANT MAN", "has_genre", "DRAMA" ], [ "THE ELEPHANT MAN", "release_year", "1982" ], [ "THE FRENCH LIEUTENANT'S WOMAN", "has_genre", "DRAMA" ], [ "THE FRENCH LIEUTENANT'S WOMAN", "has_tags", "JEREMY IRONS" ], [ "THE FRENCH LIEUTENANT'S WOMAN", "starred_actors", "JEREMY IRONS" ], [ "THE MAN FROM SNOWY RIVER", "has_genre", "DRAMA" ], [ "THE MAN FROM SNOWY RIVER", "release_year", "1982" ], [ "THE MERCHANT OF VENICE", "has_genre", "DRAMA" ], [ "THE MERCHANT OF VENICE", "starred_actors", "JEREMY IRONS" ], [ "THE MISSION", "has_genre", "DRAMA" ], [ "THE MISSION", "has_tags", "JEREMY IRONS" ], [ "THE MISSION", "starred_actors", "JEREMY IRONS" ], [ "THE NIGHT OF THE SHOOTING STARS", "has_genre", "DRAMA" ], [ "THE NIGHT OF THE SHOOTING STARS", "release_year", "1982" ], [ "THE PLAGUE DOGS", "has_genre", "DRAMA" ], [ "THE PLAGUE DOGS", "release_year", "1982" ], [ "THE PREFAB PEOPLE", "has_genre", "DRAMA" ], [ "THE PREFAB PEOPLE", "release_year", "1982" ], [ "THE PROMISED LAND", "has_genre", "DRAMA" ], [ "THE PROMISED LAND", "in_language", "POLISH" ], [ "THE SECRET OF NIMH", "has_genre", "DRAMA" ], [ "THE SECRET OF NIMH", "release_year", "1982" ], [ "THE SIMPLE-MINDED MURDERER", "has_genre", "DRAMA" ], [ "THE SIMPLE-MINDED MURDERER", "release_year", "1982" ], [ "THE VERDICT", "has_genre", "DRAMA" ], [ "THE VERDICT", "release_year", "1982" ], [ "THE WAY BACK", "has_genre", "DRAMA" ], [ "THE WAY BACK", "in_language", "POLISH" ], [ "THE WEDDING NIGHT", "has_genre", "DRAMA" ], [ "THE WEDDING NIGHT", "in_language", "POLISH" ], [ "THE WOMAN IN THE FIFTH", "has_genre", "DRAMA" ], [ "THE WOMAN IN THE FIFTH", "in_language", "POLISH" ], [ "THE WORDS", "has_genre", "DRAMA" ], [ "THE WORDS", "has_tags", "JEREMY IRONS" ], [ "THE WORDS", "starred_actors", "JEREMY IRONS" ], [ "THE WORLD ACCORDING TO GARP", "has_genre", "DRAMA" ], [ "THE WORLD ACCORDING TO GARP", "release_year", "1982" ], [ "THE YEAR OF LIVING DANGEROUSLY", "has_genre", "DRAMA" ], [ "THE YEAR OF LIVING DANGEROUSLY", "release_year", "1982" ], [ "VICE SQUAD", "has_genre", "DRAMA" ], [ "VICE SQUAD", "release_year", "1982" ], [ "WHITE DOG", "has_genre", "DRAMA" ], [ "WHITE DOG", "release_year", "1982" ], [ "WHITE NIGHTS", "has_genre", "DRAMA" ], [ "WHITE NIGHTS", "starred_actors", "JERZY SKOLIMOWSKI" ], [ "WITH FIRE AND SWORD", "has_genre", "DRAMA" ], [ "WITH FIRE AND SWORD", "in_language", "POLISH" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26257, 1994 658, 2012 33217, 35 SHOTS OF RUM 30332, AMOUR 23257, AN UNFORGETTABLE SUMMER 25053, BASTARDS 4592, BEAU TRAVAIL 8230, BREAKING WIND 24707, CAMILLE REWINDS 21065, CHARLIE CHAN AT MONTE CARLO 31594, CHARLIE CHAN IN LONDON 4476, CHOCOLAT 22712, CLAIRE DENIS 7480, EDEN 32892, ENGLISH VINGLISH 28849, EUGENE FORDE 19570, FAREWELL, MY QUEEN 409, FARINELLI 6012, FRENCH 5647, HANNAH ARENDT 34345, HAPPINESS NEVER COMES ALONE 4762, I CAN'T SLEEP 38589, I DO 32290, IN THE HOUSE 18091, L'ENFER 14601, LES MISÉRABLES 39727, LIFE OF PI 17372, LOL 29549, MINA TANNENBAUM 7974, MY FATHER THE HERO 24915, MY WAY 21677, ON THE ROAD 38602, OUR CHILDREN 11056, PAULETTE 10493, POPULAIRE 25851, RED LIGHTS 33501, RENOIR 30316, RUST AND BONE 31774, SEE HOW THEY FALL 25060, SEXUAL CHRONICLES OF A FRENCH FAMILY 37345, SIMON KILLER 33759, SOMETHING IN THE AIR 3885, THE ARTIST AND THE MODEL 16929, THE GIRL 24652, THE MAN WHO LAUGHS 28735, THE OTHER SON 17457, THE SUICIDE SHOP 266, THREE WORLDS 27598, TROUBLE EVERY DAY 12860, TRUE LIES 20399, WARNER OLAND 38905, WHAT'S IN A NAME? 23392, WHITE MATERIAL 23141, WILD REEDS 33318, YOU AIN'T SEEN NOTHIN' YET 40040, ZARAFA src, edge_attr, dst 33217, directed_by, 22712 33217, has_tags, 22712 33217, in_language, 6012 33217, written_by, 22712 30332, has_tags, 6012 30332, in_language, 6012 30332, release_year, 658 23257, in_language, 6012 23257, release_year, 26257 25053, directed_by, 22712 25053, in_language, 6012 25053, written_by, 22712 4592, directed_by, 22712 4592, in_language, 6012 4592, written_by, 22712 8230, release_year, 658 24707, in_language, 6012 24707, release_year, 658 21065, directed_by, 28849 21065, has_tags, 28849 21065, in_language, 6012 21065, starred_actors, 20399 31594, directed_by, 28849 31594, has_tags, 28849 31594, starred_actors, 20399 4476, directed_by, 22712 4476, has_tags, 22712 4476, has_tags, 6012 4476, in_language, 6012 4476, written_by, 22712 7480, in_language, 6012 7480, release_year, 658 32892, in_language, 6012 32892, release_year, 658 19570, in_language, 6012 19570, release_year, 658 409, in_language, 6012 409, release_year, 26257 5647, in_language, 6012 5647, release_year, 658 34345, in_language, 6012 34345, release_year, 658 4762, directed_by, 22712 4762, in_language, 6012 4762, release_year, 26257 4762, written_by, 22712 38589, has_tags, 6012 38589, in_language, 6012 38589, release_year, 658 32290, in_language, 6012 32290, release_year, 658 18091, in_language, 6012 18091, release_year, 26257 14601, in_language, 6012 14601, release_year, 658 39727, in_language, 6012 39727, release_year, 658 17372, in_language, 6012 17372, release_year, 658 29549, in_language, 6012 29549, release_year, 26257 7974, in_language, 6012 7974, release_year, 26257 24915, in_language, 6012 24915, release_year, 658 21677, in_language, 6012 21677, release_year, 658 38602, in_language, 6012 38602, release_year, 658 11056, in_language, 6012 11056, release_year, 658 10493, in_language, 6012 10493, release_year, 658 25851, has_tags, 6012 25851, in_language, 6012 25851, release_year, 658 33501, in_language, 6012 33501, release_year, 658 30316, in_language, 6012 30316, release_year, 658 31774, in_language, 6012 31774, release_year, 26257 25060, in_language, 6012 25060, release_year, 658 37345, in_language, 6012 37345, release_year, 658 33759, in_language, 6012 33759, release_year, 658 3885, in_language, 6012 3885, release_year, 658 16929, in_language, 6012 16929, release_year, 658 24652, in_language, 6012 24652, release_year, 658 28735, in_language, 6012 28735, release_year, 658 17457, in_language, 6012 17457, release_year, 658 266, in_language, 6012 266, release_year, 658 27598, directed_by, 22712 27598, in_language, 6012 27598, written_by, 22712 12860, in_language, 6012 12860, release_year, 26257 38905, has_tags, 6012 38905, in_language, 6012 38905, release_year, 658 23392, directed_by, 22712 23392, has_tags, 22712 23392, in_language, 6012 23392, written_by, 22712 23141, in_language, 6012 23141, release_year, 26257 33318, in_language, 6012 33318, release_year, 658 40040, in_language, 6012 40040, release_year, 658 Question: For what reason are BREAKING WIND, EUGENE FORDE, and I CAN'T SLEEP associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BREAKING WIND", "EUGENE FORDE", "I CAN'T SLEEP" ], "valid_edges": [ [ "35 SHOTS OF RUM", "directed_by", "CLAIRE DENIS" ], [ "35 SHOTS OF RUM", "has_tags", "CLAIRE DENIS" ], [ "35 SHOTS OF RUM", "in_language", "FRENCH" ], [ "35 SHOTS OF RUM", "written_by", "CLAIRE DENIS" ], [ "AMOUR", "has_tags", "FRENCH" ], [ "AMOUR", "in_language", "FRENCH" ], [ "AMOUR", "release_year", "2012" ], [ "AN UNFORGETTABLE SUMMER", "in_language", "FRENCH" ], [ "AN UNFORGETTABLE SUMMER", "release_year", "1994" ], [ "BASTARDS", "directed_by", "CLAIRE DENIS" ], [ "BASTARDS", "in_language", "FRENCH" ], [ "BASTARDS", "written_by", "CLAIRE DENIS" ], [ "BEAU TRAVAIL", "directed_by", "CLAIRE DENIS" ], [ "BEAU TRAVAIL", "in_language", "FRENCH" ], [ "BEAU TRAVAIL", "written_by", "CLAIRE DENIS" ], [ "BREAKING WIND", "release_year", "2012" ], [ "CAMILLE REWINDS", "in_language", "FRENCH" ], [ "CAMILLE REWINDS", "release_year", "2012" ], [ "CHARLIE CHAN AT MONTE CARLO", "directed_by", "EUGENE FORDE" ], [ "CHARLIE CHAN AT MONTE CARLO", "has_tags", "EUGENE FORDE" ], [ "CHARLIE CHAN AT MONTE CARLO", "in_language", "FRENCH" ], [ "CHARLIE CHAN AT MONTE CARLO", "starred_actors", "WARNER OLAND" ], [ "CHARLIE CHAN IN LONDON", "directed_by", "EUGENE FORDE" ], [ "CHARLIE CHAN IN LONDON", "has_tags", "EUGENE FORDE" ], [ "CHARLIE CHAN IN LONDON", "starred_actors", "WARNER OLAND" ], [ "CHOCOLAT", "directed_by", "CLAIRE DENIS" ], [ "CHOCOLAT", "has_tags", "CLAIRE DENIS" ], [ "CHOCOLAT", "has_tags", "FRENCH" ], [ "CHOCOLAT", "in_language", "FRENCH" ], [ "CHOCOLAT", "written_by", "CLAIRE DENIS" ], [ "EDEN", "in_language", "FRENCH" ], [ "EDEN", "release_year", "2012" ], [ "ENGLISH VINGLISH", "in_language", "FRENCH" ], [ "ENGLISH VINGLISH", "release_year", "2012" ], [ "FAREWELL, MY QUEEN", "in_language", "FRENCH" ], [ "FAREWELL, MY QUEEN", "release_year", "2012" ], [ "FARINELLI", "in_language", "FRENCH" ], [ "FARINELLI", "release_year", "1994" ], [ "HANNAH ARENDT", "in_language", "FRENCH" ], [ "HANNAH ARENDT", "release_year", "2012" ], [ "HAPPINESS NEVER COMES ALONE", "in_language", "FRENCH" ], [ "HAPPINESS NEVER COMES ALONE", "release_year", "2012" ], [ "I CAN'T SLEEP", "directed_by", "CLAIRE DENIS" ], [ "I CAN'T SLEEP", "in_language", "FRENCH" ], [ "I CAN'T SLEEP", "release_year", "1994" ], [ "I CAN'T SLEEP", "written_by", "CLAIRE DENIS" ], [ "I DO", "has_tags", "FRENCH" ], [ "I DO", "in_language", "FRENCH" ], [ "I DO", "release_year", "2012" ], [ "IN THE HOUSE", "in_language", "FRENCH" ], [ "IN THE HOUSE", "release_year", "2012" ], [ "L'ENFER", "in_language", "FRENCH" ], [ "L'ENFER", "release_year", "1994" ], [ "LES MISÉRABLES", "in_language", "FRENCH" ], [ "LES MISÉRABLES", "release_year", "2012" ], [ "LIFE OF PI", "in_language", "FRENCH" ], [ "LIFE OF PI", "release_year", "2012" ], [ "LOL", "in_language", "FRENCH" ], [ "LOL", "release_year", "2012" ], [ "MINA TANNENBAUM", "in_language", "FRENCH" ], [ "MINA TANNENBAUM", "release_year", "1994" ], [ "MY FATHER THE HERO", "in_language", "FRENCH" ], [ "MY FATHER THE HERO", "release_year", "1994" ], [ "MY WAY", "in_language", "FRENCH" ], [ "MY WAY", "release_year", "2012" ], [ "ON THE ROAD", "in_language", "FRENCH" ], [ "ON THE ROAD", "release_year", "2012" ], [ "OUR CHILDREN", "in_language", "FRENCH" ], [ "OUR CHILDREN", "release_year", "2012" ], [ "PAULETTE", "in_language", "FRENCH" ], [ "PAULETTE", "release_year", "2012" ], [ "POPULAIRE", "in_language", "FRENCH" ], [ "POPULAIRE", "release_year", "2012" ], [ "RED LIGHTS", "has_tags", "FRENCH" ], [ "RED LIGHTS", "in_language", "FRENCH" ], [ "RED LIGHTS", "release_year", "2012" ], [ "RENOIR", "in_language", "FRENCH" ], [ "RENOIR", "release_year", "2012" ], [ "RUST AND BONE", "in_language", "FRENCH" ], [ "RUST AND BONE", "release_year", "2012" ], [ "SEE HOW THEY FALL", "in_language", "FRENCH" ], [ "SEE HOW THEY FALL", "release_year", "1994" ], [ "SEXUAL CHRONICLES OF A FRENCH FAMILY", "in_language", "FRENCH" ], [ "SEXUAL CHRONICLES OF A FRENCH FAMILY", "release_year", "2012" ], [ "SIMON KILLER", "in_language", "FRENCH" ], [ "SIMON KILLER", "release_year", "2012" ], [ "SOMETHING IN THE AIR", "in_language", "FRENCH" ], [ "SOMETHING IN THE AIR", "release_year", "2012" ], [ "THE ARTIST AND THE MODEL", "in_language", "FRENCH" ], [ "THE ARTIST AND THE MODEL", "release_year", "2012" ], [ "THE GIRL", "in_language", "FRENCH" ], [ "THE GIRL", "release_year", "2012" ], [ "THE MAN WHO LAUGHS", "in_language", "FRENCH" ], [ "THE MAN WHO LAUGHS", "release_year", "2012" ], [ "THE OTHER SON", "in_language", "FRENCH" ], [ "THE OTHER SON", "release_year", "2012" ], [ "THE SUICIDE SHOP", "in_language", "FRENCH" ], [ "THE SUICIDE SHOP", "release_year", "2012" ], [ "THREE WORLDS", "in_language", "FRENCH" ], [ "THREE WORLDS", "release_year", "2012" ], [ "TROUBLE EVERY DAY", "directed_by", "CLAIRE DENIS" ], [ "TROUBLE EVERY DAY", "in_language", "FRENCH" ], [ "TROUBLE EVERY DAY", "written_by", "CLAIRE DENIS" ], [ "TRUE LIES", "in_language", "FRENCH" ], [ "TRUE LIES", "release_year", "1994" ], [ "WHAT'S IN A NAME?", "has_tags", "FRENCH" ], [ "WHAT'S IN A NAME?", "in_language", "FRENCH" ], [ "WHAT'S IN A NAME?", "release_year", "2012" ], [ "WHITE MATERIAL", "directed_by", "CLAIRE DENIS" ], [ "WHITE MATERIAL", "has_tags", "CLAIRE DENIS" ], [ "WHITE MATERIAL", "in_language", "FRENCH" ], [ "WHITE MATERIAL", "written_by", "CLAIRE DENIS" ], [ "WILD REEDS", "in_language", "FRENCH" ], [ "WILD REEDS", "release_year", "1994" ], [ "YOU AIN'T SEEN NOTHIN' YET", "in_language", "FRENCH" ], [ "YOU AIN'T SEEN NOTHIN' YET", "release_year", "2012" ], [ "ZARAFA", "in_language", "FRENCH" ], [ "ZARAFA", "release_year", "2012" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36522, 1934 24749, A STUDY IN SCARLET 26614, ANNA MAY WONG 9764, BABE RUTH 10045, BD-R 29180, CHU CHIN CHOW 17924, REGINALD DENNY 23170, THE LOST PATROL 34208, THE PRIDE OF THE YANKEES src, edge_attr, dst 24749, has_tags, 10045 24749, starred_actors, 26614 29180, release_year, 36522 29180, starred_actors, 26614 23170, release_year, 36522 23170, starred_actors, 17924 34208, has_tags, 10045 34208, starred_actors, 9764 Question: For what reason are ANNA MAY WONG, BABE RUTH, and REGINALD DENNY associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ANNA MAY WONG", "BABE RUTH", "REGINALD DENNY" ], "valid_edges": [ [ "A STUDY IN SCARLET", "has_tags", "BD-R" ], [ "A STUDY IN SCARLET", "starred_actors", "ANNA MAY WONG" ], [ "CHU CHIN CHOW", "release_year", "1934" ], [ "CHU CHIN CHOW", "starred_actors", "ANNA MAY WONG" ], [ "THE LOST PATROL", "release_year", "1934" ], [ "THE LOST PATROL", "starred_actors", "REGINALD DENNY" ], [ "THE PRIDE OF THE YANKEES", "has_tags", "BD-R" ], [ "THE PRIDE OF THE YANKEES", "starred_actors", "BABE RUTH" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10193, ALLEN C. MILLER 10045, BD-R 22072, BEN JOHNSON 16823, BITE THE BULLET 11476, DEE WALLACE 34935, DILLINGER 23807, DOCTOR X 23540, E.T. THE EXTRA-TERRESTRIAL 26730, STEVEN SPIELBERG 18706, THE LAST PICTURE SHOW 28697, THE SUGARLAND EXPRESS 16504, THE TOWN THAT DREADED SUNDOWN src, edge_attr, dst 16823, has_tags, 10045 16823, starred_actors, 22072 34935, has_tags, 10045 34935, starred_actors, 22072 23807, has_tags, 10045 23807, written_by, 10193 23540, directed_by, 26730 23540, has_tags, 26730 23540, starred_actors, 11476 18706, has_tags, 10045 18706, starred_actors, 22072 28697, directed_by, 26730 28697, starred_actors, 22072 28697, written_by, 26730 16504, has_tags, 10045 16504, starred_actors, 22072 Question: For what reason are ALLEN C. MILLER, BEN JOHNSON, and DEE WALLACE associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ALLEN C. MILLER", "BEN JOHNSON", "DEE WALLACE" ], "valid_edges": [ [ "BITE THE BULLET", "has_tags", "BD-R" ], [ "BITE THE BULLET", "starred_actors", "BEN JOHNSON" ], [ "DILLINGER", "has_tags", "BD-R" ], [ "DILLINGER", "starred_actors", "BEN JOHNSON" ], [ "DOCTOR X", "has_tags", "BD-R" ], [ "DOCTOR X", "written_by", "ALLEN C. MILLER" ], [ "E.T. THE EXTRA-TERRESTRIAL", "directed_by", "STEVEN SPIELBERG" ], [ "E.T. THE EXTRA-TERRESTRIAL", "has_tags", "STEVEN SPIELBERG" ], [ "E.T. THE EXTRA-TERRESTRIAL", "starred_actors", "DEE WALLACE" ], [ "THE LAST PICTURE SHOW", "has_tags", "BD-R" ], [ "THE LAST PICTURE SHOW", "starred_actors", "BEN JOHNSON" ], [ "THE SUGARLAND EXPRESS", "directed_by", "STEVEN SPIELBERG" ], [ "THE SUGARLAND EXPRESS", "starred_actors", "BEN JOHNSON" ], [ "THE SUGARLAND EXPRESS", "written_by", "STEVEN SPIELBERG" ], [ "THE TOWN THAT DREADED SUNDOWN", "has_tags", "BD-R" ], [ "THE TOWN THAT DREADED SUNDOWN", "starred_actors", "BEN JOHNSON" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 658, 2012 22041, A BULLET FOR THE GENERAL 28463, AFTER THE FOX 30332, AMOUR 20546, ANZIO 3449, APARTMENT 1303 3D 30204, BAFFLED! 33711, CAESAR MUST DIE 5840, CERTIFIED COPY 13888, CITY OF THE LIVING DEAD 15275, CONVERSATION PIECE 11096, DANNY GLOVER 16041, DJANGO UNCHAINED 34275, DR. GOLDFOOT AND THE GIRL BOMBS 37267, DREAMGIRLS 31783, ENGLISH 32892, ENGLISH VINGLISH 7740, FOREIGN LETTERS 8046, GOSFORD PARK 23081, HEAVEN 35319, HOPE SPRINGS 28169, IN THE CUT 25854, INTERVISTA 16200, ITALIAN 38160, JOURNEY TO ITALY 14601, LES MISÉRABLES 27996, LOCKOUT 34611, ME AND YOU 8368, MUSHROOMING 15145, MYSTERY 769, MYSTERY TRAIN 5744, OFFENDER 21677, ON THE ROAD 8509, PASSION 738, PLOT OF FEAR 38043, PUSHER 35746, REALITY 32487, SAPPHIRE 430, SHANGHAI 29238, SHOESHINE 6119, SLEUTH 8436, SPIRITS OF THE DEAD 29427, STARCRASH 40067, STOLEN 22826, TAKEN 2 30456, TEDDY BEAR 31479, TEOREMA 9091, THE ADVENTURES OF PICASSO 15568, THE CANTERBURY TALES 38918, THE FAMILY 38614, THE IMPOSSIBLE 4091, THE LADY VANISHES 28107, THE LAST KISS 12269, THE MOTEL LIFE 37910, THE MOUNTAIN OF THE CANNIBAL GOD 18162, THE RAVEN 18274, THE ROSE TATTOO 25030, THE UNKNOWN WOMAN 14962, THE WATCHER IN THE WOODS 3437, THE WOMAN IN BLACK 15504, THE WORDS 6598, TO ROME WITH LOVE 33119, TOM EYEN 26367, WAR AND PEACE 28211, WHAT HAVE YOU DONE TO SOLANGE? src, edge_attr, dst 658, has_tags, 11096 22041, in_language, 31783 22041, in_language, 16200 28463, in_language, 31783 28463, in_language, 16200 30332, in_language, 31783 30332, release_year, 658 20546, in_language, 31783 20546, in_language, 16200 3449, in_language, 31783 3449, release_year, 658 30204, has_genre, 15145 30204, in_language, 31783 33711, in_language, 16200 33711, release_year, 658 5840, in_language, 31783 5840, in_language, 16200 13888, has_tags, 16200 13888, in_language, 31783 13888, in_language, 16200 15275, in_language, 31783 15275, in_language, 16200 16041, in_language, 31783 16041, release_year, 658 34275, in_language, 31783 34275, in_language, 16200 37267, starred_actors, 11096 37267, written_by, 33119 32892, in_language, 31783 32892, release_year, 658 7740, in_language, 31783 7740, release_year, 658 8046, has_genre, 15145 8046, in_language, 31783 23081, in_language, 31783 23081, in_language, 16200 35319, in_language, 31783 35319, release_year, 658 28169, has_genre, 15145 28169, in_language, 31783 25854, in_language, 31783 25854, in_language, 16200 38160, in_language, 31783 38160, in_language, 16200 14601, in_language, 31783 14601, release_year, 658 27996, in_language, 31783 27996, release_year, 658 34611, in_language, 16200 34611, release_year, 658 8368, release_year, 658 769, in_language, 31783 769, in_language, 16200 5744, in_language, 31783 5744, release_year, 658 21677, in_language, 31783 21677, release_year, 658 8509, in_language, 31783 8509, release_year, 658 738, has_genre, 15145 738, in_language, 16200 38043, in_language, 31783 38043, release_year, 658 35746, in_language, 16200 35746, release_year, 658 32487, has_genre, 15145 32487, in_language, 31783 430, has_genre, 15145 430, release_year, 658 29238, in_language, 31783 29238, in_language, 16200 6119, has_genre, 15145 6119, has_tags, 15145 6119, in_language, 16200 8436, has_genre, 15145 8436, in_language, 31783 8436, in_language, 16200 29427, in_language, 31783 29427, in_language, 16200 40067, has_genre, 15145 40067, release_year, 658 22826, in_language, 31783 22826, release_year, 658 30456, in_language, 31783 30456, release_year, 658 31479, has_genre, 15145 31479, in_language, 16200 9091, in_language, 31783 9091, in_language, 16200 15568, in_language, 31783 15568, in_language, 16200 38918, in_language, 31783 38918, in_language, 16200 38614, in_language, 31783 38614, release_year, 658 4091, has_genre, 15145 4091, in_language, 31783 28107, in_language, 31783 28107, in_language, 16200 12269, has_genre, 15145 12269, release_year, 658 37910, in_language, 31783 37910, in_language, 16200 18162, has_genre, 15145 18162, release_year, 658 18274, in_language, 31783 18274, in_language, 16200 25030, has_genre, 15145 25030, in_language, 16200 14962, has_genre, 15145 14962, in_language, 31783 3437, in_language, 31783 3437, release_year, 658 15504, has_genre, 15145 15504, release_year, 658 6598, in_language, 16200 6598, release_year, 658 26367, in_language, 31783 26367, in_language, 16200 28211, has_genre, 15145 28211, in_language, 16200 Question: How are MUSHROOMING, SPIRITS OF THE DEAD, and TOM EYEN related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "MUSHROOMING", "SPIRITS OF THE DEAD", "TOM EYEN" ], "valid_edges": [ [ "2012", "has_tags", "DANNY GLOVER" ], [ "A BULLET FOR THE GENERAL", "in_language", "ENGLISH" ], [ "A BULLET FOR THE GENERAL", "in_language", "ITALIAN" ], [ "AFTER THE FOX", "in_language", "ENGLISH" ], [ "AFTER THE FOX", "in_language", "ITALIAN" ], [ "AMOUR", "in_language", "ENGLISH" ], [ "AMOUR", "release_year", "2012" ], [ "ANZIO", "in_language", "ENGLISH" ], [ "ANZIO", "in_language", "ITALIAN" ], [ "APARTMENT 1303 3D", "in_language", "ENGLISH" ], [ "APARTMENT 1303 3D", "release_year", "2012" ], [ "BAFFLED!", "has_genre", "MYSTERY" ], [ "BAFFLED!", "in_language", "ENGLISH" ], [ "CAESAR MUST DIE", "in_language", "ITALIAN" ], [ "CAESAR MUST DIE", "release_year", "2012" ], [ "CERTIFIED COPY", "in_language", "ENGLISH" ], [ "CERTIFIED COPY", "in_language", "ITALIAN" ], [ "CITY OF THE LIVING DEAD", "has_tags", "ITALIAN" ], [ "CITY OF THE LIVING DEAD", "in_language", "ENGLISH" ], [ "CITY OF THE LIVING DEAD", "in_language", "ITALIAN" ], [ "CONVERSATION PIECE", "in_language", "ENGLISH" ], [ "CONVERSATION PIECE", "in_language", "ITALIAN" ], [ "DJANGO UNCHAINED", "in_language", "ENGLISH" ], [ "DJANGO UNCHAINED", "release_year", "2012" ], [ "DR. GOLDFOOT AND THE GIRL BOMBS", "in_language", "ENGLISH" ], [ "DR. GOLDFOOT AND THE GIRL BOMBS", "in_language", "ITALIAN" ], [ "DREAMGIRLS", "starred_actors", "DANNY GLOVER" ], [ "DREAMGIRLS", "written_by", "TOM EYEN" ], [ "ENGLISH VINGLISH", "in_language", "ENGLISH" ], [ "ENGLISH VINGLISH", "release_year", "2012" ], [ "FOREIGN LETTERS", "in_language", "ENGLISH" ], [ "FOREIGN LETTERS", "release_year", "2012" ], [ "GOSFORD PARK", "has_genre", "MYSTERY" ], [ "GOSFORD PARK", "in_language", "ENGLISH" ], [ "HEAVEN", "in_language", "ENGLISH" ], [ "HEAVEN", "in_language", "ITALIAN" ], [ "HOPE SPRINGS", "in_language", "ENGLISH" ], [ "HOPE SPRINGS", "release_year", "2012" ], [ "IN THE CUT", "has_genre", "MYSTERY" ], [ "IN THE CUT", "in_language", "ENGLISH" ], [ "INTERVISTA", "in_language", "ENGLISH" ], [ "INTERVISTA", "in_language", "ITALIAN" ], [ "JOURNEY TO ITALY", "in_language", "ENGLISH" ], [ "JOURNEY TO ITALY", "in_language", "ITALIAN" ], [ "LES MISÉRABLES", "in_language", "ENGLISH" ], [ "LES MISÉRABLES", "release_year", "2012" ], [ "LOCKOUT", "in_language", "ENGLISH" ], [ "LOCKOUT", "release_year", "2012" ], [ "ME AND YOU", "in_language", "ITALIAN" ], [ "ME AND YOU", "release_year", "2012" ], [ "MUSHROOMING", "release_year", "2012" ], [ "MYSTERY TRAIN", "in_language", "ENGLISH" ], [ "MYSTERY TRAIN", "in_language", "ITALIAN" ], [ "OFFENDER", "in_language", "ENGLISH" ], [ "OFFENDER", "release_year", "2012" ], [ "ON THE ROAD", "in_language", "ENGLISH" ], [ "ON THE ROAD", "release_year", "2012" ], [ "PASSION", "in_language", "ENGLISH" ], [ "PASSION", "release_year", "2012" ], [ "PLOT OF FEAR", "has_genre", "MYSTERY" ], [ "PLOT OF FEAR", "in_language", "ITALIAN" ], [ "PUSHER", "in_language", "ENGLISH" ], [ "PUSHER", "release_year", "2012" ], [ "REALITY", "in_language", "ITALIAN" ], [ "REALITY", "release_year", "2012" ], [ "SAPPHIRE", "has_genre", "MYSTERY" ], [ "SAPPHIRE", "in_language", "ENGLISH" ], [ "SHANGHAI", "has_genre", "MYSTERY" ], [ "SHANGHAI", "release_year", "2012" ], [ "SHOESHINE", "in_language", "ENGLISH" ], [ "SHOESHINE", "in_language", "ITALIAN" ], [ "SLEUTH", "has_genre", "MYSTERY" ], [ "SLEUTH", "has_tags", "MYSTERY" ], [ "SLEUTH", "in_language", "ITALIAN" ], [ "SPIRITS OF THE DEAD", "has_genre", "MYSTERY" ], [ "SPIRITS OF THE DEAD", "in_language", "ENGLISH" ], [ "SPIRITS OF THE DEAD", "in_language", "ITALIAN" ], [ "STARCRASH", "in_language", "ENGLISH" ], [ "STARCRASH", "in_language", "ITALIAN" ], [ "STOLEN", "has_genre", "MYSTERY" ], [ "STOLEN", "release_year", "2012" ], [ "TAKEN 2", "in_language", "ENGLISH" ], [ "TAKEN 2", "release_year", "2012" ], [ "TEDDY BEAR", "in_language", "ENGLISH" ], [ "TEDDY BEAR", "release_year", "2012" ], [ "TEOREMA", "has_genre", "MYSTERY" ], [ "TEOREMA", "in_language", "ITALIAN" ], [ "THE ADVENTURES OF PICASSO", "in_language", "ENGLISH" ], [ "THE ADVENTURES OF PICASSO", "in_language", "ITALIAN" ], [ "THE CANTERBURY TALES", "in_language", "ENGLISH" ], [ "THE CANTERBURY TALES", "in_language", "ITALIAN" ], [ "THE FAMILY", "in_language", "ENGLISH" ], [ "THE FAMILY", "in_language", "ITALIAN" ], [ "THE IMPOSSIBLE", "in_language", "ENGLISH" ], [ "THE IMPOSSIBLE", "release_year", "2012" ], [ "THE LADY VANISHES", "has_genre", "MYSTERY" ], [ "THE LADY VANISHES", "in_language", "ENGLISH" ], [ "THE LAST KISS", "in_language", "ENGLISH" ], [ "THE LAST KISS", "in_language", "ITALIAN" ], [ "THE MOTEL LIFE", "has_genre", "MYSTERY" ], [ "THE MOTEL LIFE", "release_year", "2012" ], [ "THE MOUNTAIN OF THE CANNIBAL GOD", "in_language", "ENGLISH" ], [ "THE MOUNTAIN OF THE CANNIBAL GOD", "in_language", "ITALIAN" ], [ "THE RAVEN", "has_genre", "MYSTERY" ], [ "THE RAVEN", "release_year", "2012" ], [ "THE ROSE TATTOO", "in_language", "ENGLISH" ], [ "THE ROSE TATTOO", "in_language", "ITALIAN" ], [ "THE UNKNOWN WOMAN", "has_genre", "MYSTERY" ], [ "THE UNKNOWN WOMAN", "in_language", "ITALIAN" ], [ "THE WATCHER IN THE WOODS", "has_genre", "MYSTERY" ], [ "THE WATCHER IN THE WOODS", "in_language", "ENGLISH" ], [ "THE WOMAN IN BLACK", "in_language", "ENGLISH" ], [ "THE WOMAN IN BLACK", "release_year", "2012" ], [ "THE WORDS", "has_genre", "MYSTERY" ], [ "THE WORDS", "release_year", "2012" ], [ "TO ROME WITH LOVE", "in_language", "ITALIAN" ], [ "TO ROME WITH LOVE", "release_year", "2012" ], [ "WAR AND PEACE", "in_language", "ENGLISH" ], [ "WAR AND PEACE", "in_language", "ITALIAN" ], [ "WHAT HAVE YOU DONE TO SOLANGE?", "has_genre", "MYSTERY" ], [ "WHAT HAVE YOU DONE TO SOLANGE?", "in_language", "ITALIAN" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6776, 2000 25611, 4 FOR TEXAS 8221, A MAN ESCAPED 37987, A ROOM WITH A VIEW 21271, ALL THE PRETTY HORSES 10045, BD-R 6942, BEDAZZLED 39085, BILLY ELLIOT 16823, BITE THE BULLET 5809, BUCK AND THE PREACHER 35953, BUTCH CASSIDY AND THE SUNDANCE KID 7432, CHEYENNE AUTUMN 26781, CIMARRON 26931, COOL HAND LUKE 21286, DAVID COPPERFIELD 16041, DJANGO UNCHAINED 31564, ENGLAND 34004, FAIL SAFE 23299, GET CARTER 565, GREENFINGERS 20941, HAMLET 35856, HEARTS OF THE WEST 11980, HEAVEN'S GATE 39972, HOLLOW MAN 5870, HORROR 5779, JEFFREY BOAM 33417, JOHNNY GUITAR 27312, MAIL ORDER BRIDE 37887, MAN OF THE WEST 27954, MIDNIGHT EXPRESS 9564, MONTE WALSH 38294, MRS. MINIVER 15797, MY DARLING CLEMENTINE 7730, NEVADA SMITH 14797, O BROTHER, WHERE ART THOU? 27893, POSSESSED 30919, PRISON 4848, RIDE THE HIGH COUNTRY 36102, RIO BRAVO 18821, RUN OF THE ARROW 27807, SHAFT 15270, SHOOT-OUT AT MEDICINE BEND 3226, STAGECOACH 420, SUPPORT YOUR LOCAL SHERIFF! 35403, TEARS OF THE BLACK TIGER 7763, THE CHEYENNE SOCIAL CLUB 25685, THE CLAIM 26351, THE DEAD ZONE 21845, THE DEADLY COMPANIONS 21435, THE GOOD, THE BAD AND THE UGLY 15600, THE HALLELUJAH TRAIL 26955, THE HOLIDAY 31283, THE HOUND OF THE BASKERVILLES 9210, THE LION IN WINTER 28552, THE MAGNIFICENT SEVEN 36235, THE MAN WHO SHOT LIBERTY VALANCE 39232, THE NAKED SPUR 11902, THE OUTLAW JOSEY WALES 4624, THE OX-BOW INCIDENT 19768, THE PROFESSIONALS 27611, THE SEARCHERS 18433, THE WILD BUNCH 36026, WESTERN src, edge_attr, dst 25611, has_genre, 36026 25611, has_tags, 10045 8221, has_tags, 10045 8221, has_tags, 30919 37987, has_tags, 10045 37987, has_tags, 31564 21271, has_genre, 36026 21271, release_year, 6776 6942, has_tags, 10045 6942, release_year, 6776 39085, has_tags, 31564 39085, release_year, 6776 16823, has_genre, 36026 16823, has_tags, 10045 5809, has_genre, 36026 5809, has_tags, 10045 35953, has_genre, 36026 35953, has_tags, 10045 35953, has_tags, 36026 7432, has_genre, 36026 7432, has_tags, 10045 26781, has_genre, 36026 26781, has_tags, 10045 26931, has_tags, 10045 26931, has_tags, 30919 21286, has_tags, 10045 21286, release_year, 6776 16041, has_genre, 36026 16041, has_tags, 10045 16041, has_tags, 36026 34004, has_tags, 10045 34004, release_year, 6776 23299, has_tags, 10045 23299, release_year, 6776 565, has_tags, 31564 565, has_tags, 30919 565, release_year, 6776 20941, has_tags, 10045 20941, release_year, 6776 35856, has_genre, 36026 35856, has_tags, 10045 11980, has_tags, 10045 11980, has_tags, 36026 39972, has_tags, 10045 39972, release_year, 6776 33417, has_genre, 36026 33417, has_tags, 10045 33417, has_tags, 36026 27312, has_genre, 36026 27312, has_tags, 10045 37887, has_genre, 36026 37887, has_tags, 10045 37887, has_tags, 36026 27954, has_tags, 10045 27954, has_tags, 30919 9564, has_genre, 36026 9564, has_tags, 10045 38294, has_tags, 10045 38294, has_tags, 31564 15797, has_genre, 36026 15797, has_tags, 10045 7730, has_genre, 36026 7730, has_tags, 10045 14797, has_tags, 10045 14797, release_year, 6776 27893, has_tags, 10045 27893, release_year, 6776 30919, has_genre, 5870 30919, has_tags, 30919 4848, has_genre, 36026 4848, has_tags, 10045 36102, has_genre, 36026 36102, has_tags, 10045 36102, has_tags, 36026 18821, has_genre, 36026 18821, has_tags, 10045 27807, has_tags, 10045 27807, release_year, 6776 15270, has_genre, 36026 15270, has_tags, 10045 3226, has_genre, 36026 3226, has_tags, 10045 3226, has_tags, 36026 420, has_genre, 36026 420, has_tags, 10045 420, has_tags, 36026 35403, has_tags, 36026 35403, release_year, 6776 7763, has_genre, 36026 7763, has_tags, 10045 25685, has_genre, 36026 25685, release_year, 6776 26351, has_genre, 5870 26351, written_by, 5779 21845, has_genre, 36026 21845, has_tags, 10045 21435, has_genre, 36026 21435, has_tags, 10045 21435, has_tags, 36026 15600, has_genre, 36026 15600, has_tags, 10045 15600, has_tags, 36026 26955, has_tags, 10045 26955, has_tags, 31564 31283, has_tags, 10045 31283, release_year, 6776 9210, has_tags, 10045 9210, has_tags, 31564 28552, has_genre, 36026 28552, has_tags, 10045 28552, has_tags, 36026 36235, has_genre, 36026 36235, has_tags, 10045 36235, has_tags, 36026 39232, has_genre, 36026 39232, has_tags, 10045 11902, has_genre, 36026 11902, has_tags, 10045 11902, has_tags, 36026 4624, has_genre, 36026 4624, has_tags, 10045 4624, has_tags, 36026 19768, has_genre, 36026 19768, has_tags, 10045 27611, has_genre, 36026 27611, has_tags, 10045 27611, has_tags, 36026 18433, has_genre, 36026 18433, has_tags, 10045 18433, has_tags, 36026 Question: In what context are GREENFINGERS, JEFFREY BOAM, and RIO BRAVO connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "GREENFINGERS", "JEFFREY BOAM", "RIO BRAVO" ], "valid_edges": [ [ "4 FOR TEXAS", "has_genre", "WESTERN" ], [ "4 FOR TEXAS", "has_tags", "BD-R" ], [ "A MAN ESCAPED", "has_tags", "BD-R" ], [ "A MAN ESCAPED", "has_tags", "PRISON" ], [ "A ROOM WITH A VIEW", "has_tags", "BD-R" ], [ "A ROOM WITH A VIEW", "has_tags", "ENGLAND" ], [ "ALL THE PRETTY HORSES", "has_genre", "WESTERN" ], [ "ALL THE PRETTY HORSES", "release_year", "2000" ], [ "BEDAZZLED", "has_tags", "BD-R" ], [ "BEDAZZLED", "release_year", "2000" ], [ "BILLY ELLIOT", "has_tags", "ENGLAND" ], [ "BILLY ELLIOT", "release_year", "2000" ], [ "BITE THE BULLET", "has_genre", "WESTERN" ], [ "BITE THE BULLET", "has_tags", "BD-R" ], [ "BUCK AND THE PREACHER", "has_genre", "WESTERN" ], [ "BUCK AND THE PREACHER", "has_tags", "BD-R" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_genre", "WESTERN" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "BD-R" ], [ "BUTCH CASSIDY AND THE SUNDANCE KID", "has_tags", "WESTERN" ], [ "CHEYENNE AUTUMN", "has_genre", "WESTERN" ], [ "CHEYENNE AUTUMN", "has_tags", "BD-R" ], [ "CIMARRON", "has_genre", "WESTERN" ], [ "CIMARRON", "has_tags", "BD-R" ], [ "COOL HAND LUKE", "has_tags", "BD-R" ], [ "COOL HAND LUKE", "has_tags", "PRISON" ], [ "DAVID COPPERFIELD", "has_tags", "BD-R" ], [ "DAVID COPPERFIELD", "release_year", "2000" ], [ "DJANGO UNCHAINED", "has_genre", "WESTERN" ], [ "DJANGO UNCHAINED", "has_tags", "BD-R" ], [ "DJANGO UNCHAINED", "has_tags", "WESTERN" ], [ "FAIL SAFE", "has_tags", "BD-R" ], [ "FAIL SAFE", "release_year", "2000" ], [ "GET CARTER", "has_tags", "BD-R" ], [ "GET CARTER", "release_year", "2000" ], [ "GREENFINGERS", "has_tags", "ENGLAND" ], [ "GREENFINGERS", "has_tags", "PRISON" ], [ "GREENFINGERS", "release_year", "2000" ], [ "HAMLET", "has_tags", "BD-R" ], [ "HAMLET", "release_year", "2000" ], [ "HEARTS OF THE WEST", "has_genre", "WESTERN" ], [ "HEARTS OF THE WEST", "has_tags", "BD-R" ], [ "HEAVEN'S GATE", "has_tags", "BD-R" ], [ "HEAVEN'S GATE", "has_tags", "WESTERN" ], [ "HOLLOW MAN", "has_tags", "BD-R" ], [ "HOLLOW MAN", "release_year", "2000" ], [ "JOHNNY GUITAR", "has_genre", "WESTERN" ], [ "JOHNNY GUITAR", "has_tags", "BD-R" ], [ "JOHNNY GUITAR", "has_tags", "WESTERN" ], [ "MAIL ORDER BRIDE", "has_genre", "WESTERN" ], [ "MAIL ORDER BRIDE", "has_tags", "BD-R" ], [ "MAN OF THE WEST", "has_genre", "WESTERN" ], [ "MAN OF THE WEST", "has_tags", "BD-R" ], [ "MAN OF THE WEST", "has_tags", "WESTERN" ], [ "MIDNIGHT EXPRESS", "has_tags", "BD-R" ], [ "MIDNIGHT EXPRESS", "has_tags", "PRISON" ], [ "MONTE WALSH", "has_genre", "WESTERN" ], [ "MONTE WALSH", "has_tags", "BD-R" ], [ "MRS. MINIVER", "has_tags", "BD-R" ], [ "MRS. MINIVER", "has_tags", "ENGLAND" ], [ "MY DARLING CLEMENTINE", "has_genre", "WESTERN" ], [ "MY DARLING CLEMENTINE", "has_tags", "BD-R" ], [ "NEVADA SMITH", "has_genre", "WESTERN" ], [ "NEVADA SMITH", "has_tags", "BD-R" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "BD-R" ], [ "O BROTHER, WHERE ART THOU?", "release_year", "2000" ], [ "POSSESSED", "has_tags", "BD-R" ], [ "POSSESSED", "release_year", "2000" ], [ "PRISON", "has_genre", "HORROR" ], [ "PRISON", "has_tags", "PRISON" ], [ "RIDE THE HIGH COUNTRY", "has_genre", "WESTERN" ], [ "RIDE THE HIGH COUNTRY", "has_tags", "BD-R" ], [ "RIO BRAVO", "has_genre", "WESTERN" ], [ "RIO BRAVO", "has_tags", "BD-R" ], [ "RIO BRAVO", "has_tags", "WESTERN" ], [ "RUN OF THE ARROW", "has_genre", "WESTERN" ], [ "RUN OF THE ARROW", "has_tags", "BD-R" ], [ "SHAFT", "has_tags", "BD-R" ], [ "SHAFT", "release_year", "2000" ], [ "SHOOT-OUT AT MEDICINE BEND", "has_genre", "WESTERN" ], [ "SHOOT-OUT AT MEDICINE BEND", "has_tags", "BD-R" ], [ "STAGECOACH", "has_genre", "WESTERN" ], [ "STAGECOACH", "has_tags", "BD-R" ], [ "STAGECOACH", "has_tags", "WESTERN" ], [ "SUPPORT YOUR LOCAL SHERIFF!", "has_genre", "WESTERN" ], [ "SUPPORT YOUR LOCAL SHERIFF!", "has_tags", "BD-R" ], [ "SUPPORT YOUR LOCAL SHERIFF!", "has_tags", "WESTERN" ], [ "TEARS OF THE BLACK TIGER", "has_tags", "WESTERN" ], [ "TEARS OF THE BLACK TIGER", "release_year", "2000" ], [ "THE CHEYENNE SOCIAL CLUB", "has_genre", "WESTERN" ], [ "THE CHEYENNE SOCIAL CLUB", "has_tags", "BD-R" ], [ "THE CLAIM", "has_genre", "WESTERN" ], [ "THE CLAIM", "release_year", "2000" ], [ "THE DEAD ZONE", "has_genre", "HORROR" ], [ "THE DEAD ZONE", "written_by", "JEFFREY BOAM" ], [ "THE DEADLY COMPANIONS", "has_genre", "WESTERN" ], [ "THE DEADLY COMPANIONS", "has_tags", "BD-R" ], [ "THE GOOD, THE BAD AND THE UGLY", "has_genre", "WESTERN" ], [ "THE GOOD, THE BAD AND THE UGLY", "has_tags", "BD-R" ], [ "THE GOOD, THE BAD AND THE UGLY", "has_tags", "WESTERN" ], [ "THE HALLELUJAH TRAIL", "has_genre", "WESTERN" ], [ "THE HALLELUJAH TRAIL", "has_tags", "BD-R" ], [ "THE HALLELUJAH TRAIL", "has_tags", "WESTERN" ], [ "THE HOLIDAY", "has_tags", "BD-R" ], [ "THE HOLIDAY", "has_tags", "ENGLAND" ], [ "THE HOUND OF THE BASKERVILLES", "has_tags", "BD-R" ], [ "THE HOUND OF THE BASKERVILLES", "release_year", "2000" ], [ "THE LION IN WINTER", "has_tags", "BD-R" ], [ "THE LION IN WINTER", "has_tags", "ENGLAND" ], [ "THE MAGNIFICENT SEVEN", "has_genre", "WESTERN" ], [ "THE MAGNIFICENT SEVEN", "has_tags", "BD-R" ], [ "THE MAGNIFICENT SEVEN", "has_tags", "WESTERN" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_genre", "WESTERN" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "BD-R" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "WESTERN" ], [ "THE NAKED SPUR", "has_genre", "WESTERN" ], [ "THE NAKED SPUR", "has_tags", "BD-R" ], [ "THE OUTLAW JOSEY WALES", "has_genre", "WESTERN" ], [ "THE OUTLAW JOSEY WALES", "has_tags", "BD-R" ], [ "THE OUTLAW JOSEY WALES", "has_tags", "WESTERN" ], [ "THE OX-BOW INCIDENT", "has_genre", "WESTERN" ], [ "THE OX-BOW INCIDENT", "has_tags", "BD-R" ], [ "THE OX-BOW INCIDENT", "has_tags", "WESTERN" ], [ "THE PROFESSIONALS", "has_genre", "WESTERN" ], [ "THE PROFESSIONALS", "has_tags", "BD-R" ], [ "THE SEARCHERS", "has_genre", "WESTERN" ], [ "THE SEARCHERS", "has_tags", "BD-R" ], [ "THE SEARCHERS", "has_tags", "WESTERN" ], [ "THE WILD BUNCH", "has_genre", "WESTERN" ], [ "THE WILD BUNCH", "has_tags", "BD-R" ], [ "THE WILD BUNCH", "has_tags", "WESTERN" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10045, BD-R 8156, BYE BYE BRAVERMAN 30463, COMEDY 7393, CRIME AND PUNISHMENT 3463, DARE 5324, DAVID BRIND 36212, DRAMA 35646, MENAHEM GOLAN 28063, OVER THE BROOKLYN BRIDGE 18490, OVER THE TOP 36130, WALLACE MARKFIELD src, edge_attr, dst 8156, has_genre, 30463 8156, has_tags, 10045 8156, written_by, 36130 7393, directed_by, 35646 7393, has_tags, 10045 7393, written_by, 35646 3463, has_genre, 36212 3463, written_by, 5324 28063, directed_by, 35646 28063, has_genre, 30463 28063, has_tags, 35646 18490, directed_by, 35646 18490, has_genre, 36212 18490, has_tags, 35646 Question: In what context are DAVID BRIND, MENAHEM GOLAN, and WALLACE MARKFIELD connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DAVID BRIND", "MENAHEM GOLAN", "WALLACE MARKFIELD" ], "valid_edges": [ [ "BYE BYE BRAVERMAN", "has_genre", "COMEDY" ], [ "BYE BYE BRAVERMAN", "has_tags", "BD-R" ], [ "BYE BYE BRAVERMAN", "written_by", "WALLACE MARKFIELD" ], [ "CRIME AND PUNISHMENT", "directed_by", "MENAHEM GOLAN" ], [ "CRIME AND PUNISHMENT", "has_tags", "BD-R" ], [ "CRIME AND PUNISHMENT", "written_by", "MENAHEM GOLAN" ], [ "DARE", "has_genre", "DRAMA" ], [ "DARE", "written_by", "DAVID BRIND" ], [ "OVER THE BROOKLYN BRIDGE", "directed_by", "MENAHEM GOLAN" ], [ "OVER THE BROOKLYN BRIDGE", "has_genre", "COMEDY" ], [ "OVER THE BROOKLYN BRIDGE", "has_tags", "MENAHEM GOLAN" ], [ "OVER THE TOP", "directed_by", "MENAHEM GOLAN" ], [ "OVER THE TOP", "has_genre", "DRAMA" ], [ "OVER THE TOP", "has_tags", "MENAHEM GOLAN" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29036, A MIDSUMMER NIGHT'S DREAM 10045, BD-R 17939, BURT REYNOLDS 1040, CAPTAIN BLOOD 12331, DAMES 28094, DELIVERANCE 6044, DICK POWELL 36196, DR. EHRLICH'S MAGIC BULLET 4057, FOOTLIGHT PARADE 24124, GAMBIT 20693, GONE WITH THE WIND 17323, KEVIN KLINE 26649, KISMET 36261, LAST VEGAS 18367, MICHAEL HOFFMAN 6972, OLIVIA DE HAVILLAND 4261, SALLY FIELD 94, SATAN MET A LADY 14350, SMOKEY AND THE BANDIT 17988, THE BAD AND THE BEAUTIFUL 7639, THE CHARGE OF THE LIGHT BRIGADE 16732, THE END 20658, THE LIFE OF EMILE ZOLA 33513, THE MAN WHO LOVED WOMEN 12160, THE PRIVATE LIVES OF ELIZABETH AND ESSEX 4784, THE SNAKE PIT 10474, WILLIAM DIETERLE src, edge_attr, dst 29036, directed_by, 18367 29036, directed_by, 10474 29036, has_tags, 10045 29036, has_tags, 6972 29036, has_tags, 10474 29036, starred_actors, 6044 29036, starred_actors, 17323 29036, written_by, 18367 1040, has_tags, 10045 1040, has_tags, 6972 1040, starred_actors, 6972 12331, has_tags, 10045 12331, starred_actors, 6044 28094, has_tags, 10045 28094, has_tags, 17939 28094, starred_actors, 17939 36196, directed_by, 10474 36196, has_tags, 10045 36196, has_tags, 10474 4057, has_tags, 10045 4057, starred_actors, 6044 24124, directed_by, 18367 24124, has_tags, 10045 20693, has_tags, 10045 20693, has_tags, 6972 26649, directed_by, 10474 26649, has_tags, 10045 36261, starred_actors, 17323 94, directed_by, 10474 94, has_tags, 10045 14350, has_tags, 10045 14350, starred_actors, 17939 14350, starred_actors, 4261 17988, has_tags, 10045 17988, starred_actors, 6044 7639, has_tags, 10045 7639, starred_actors, 6972 16732, directed_by, 17939 16732, has_tags, 10045 16732, starred_actors, 17939 16732, starred_actors, 4261 20658, directed_by, 10474 20658, has_tags, 10045 20658, has_tags, 10474 33513, has_tags, 10045 33513, starred_actors, 17939 12160, has_tags, 10045 12160, starred_actors, 6972 4784, has_tags, 10045 4784, has_tags, 6972 4784, starred_actors, 6972 Question: For what reason are BD-R, BURT REYNOLDS, and LAST VEGAS associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BD-R", "BURT REYNOLDS", "LAST VEGAS" ], "valid_edges": [ [ "A MIDSUMMER NIGHT'S DREAM", "directed_by", "MICHAEL HOFFMAN" ], [ "A MIDSUMMER NIGHT'S DREAM", "directed_by", "WILLIAM DIETERLE" ], [ "A MIDSUMMER NIGHT'S DREAM", "has_tags", "BD-R" ], [ "A MIDSUMMER NIGHT'S DREAM", "has_tags", "OLIVIA DE HAVILLAND" ], [ "A MIDSUMMER NIGHT'S DREAM", "has_tags", "WILLIAM DIETERLE" ], [ "A MIDSUMMER NIGHT'S DREAM", "starred_actors", "DICK POWELL" ], [ "A MIDSUMMER NIGHT'S DREAM", "starred_actors", "KEVIN KLINE" ], [ "A MIDSUMMER NIGHT'S DREAM", "written_by", "MICHAEL HOFFMAN" ], [ "CAPTAIN BLOOD", "has_tags", "BD-R" ], [ "CAPTAIN BLOOD", "has_tags", "OLIVIA DE HAVILLAND" ], [ "CAPTAIN BLOOD", "starred_actors", "OLIVIA DE HAVILLAND" ], [ "DAMES", "has_tags", "BD-R" ], [ "DAMES", "starred_actors", "DICK POWELL" ], [ "DELIVERANCE", "has_tags", "BD-R" ], [ "DELIVERANCE", "has_tags", "BURT REYNOLDS" ], [ "DELIVERANCE", "starred_actors", "BURT REYNOLDS" ], [ "DR. EHRLICH'S MAGIC BULLET", "directed_by", "WILLIAM DIETERLE" ], [ "DR. EHRLICH'S MAGIC BULLET", "has_tags", "BD-R" ], [ "DR. EHRLICH'S MAGIC BULLET", "has_tags", "WILLIAM DIETERLE" ], [ "FOOTLIGHT PARADE", "has_tags", "BD-R" ], [ "FOOTLIGHT PARADE", "starred_actors", "DICK POWELL" ], [ "GAMBIT", "directed_by", "MICHAEL HOFFMAN" ], [ "GAMBIT", "has_tags", "BD-R" ], [ "GONE WITH THE WIND", "has_tags", "BD-R" ], [ "GONE WITH THE WIND", "has_tags", "OLIVIA DE HAVILLAND" ], [ "KISMET", "directed_by", "WILLIAM DIETERLE" ], [ "KISMET", "has_tags", "BD-R" ], [ "LAST VEGAS", "starred_actors", "KEVIN KLINE" ], [ "SATAN MET A LADY", "directed_by", "WILLIAM DIETERLE" ], [ "SATAN MET A LADY", "has_tags", "BD-R" ], [ "SMOKEY AND THE BANDIT", "has_tags", "BD-R" ], [ "SMOKEY AND THE BANDIT", "starred_actors", "BURT REYNOLDS" ], [ "SMOKEY AND THE BANDIT", "starred_actors", "SALLY FIELD" ], [ "THE BAD AND THE BEAUTIFUL", "has_tags", "BD-R" ], [ "THE BAD AND THE BEAUTIFUL", "starred_actors", "DICK POWELL" ], [ "THE CHARGE OF THE LIGHT BRIGADE", "has_tags", "BD-R" ], [ "THE CHARGE OF THE LIGHT BRIGADE", "starred_actors", "OLIVIA DE HAVILLAND" ], [ "THE END", "directed_by", "BURT REYNOLDS" ], [ "THE END", "has_tags", "BD-R" ], [ "THE END", "starred_actors", "BURT REYNOLDS" ], [ "THE END", "starred_actors", "SALLY FIELD" ], [ "THE LIFE OF EMILE ZOLA", "directed_by", "WILLIAM DIETERLE" ], [ "THE LIFE OF EMILE ZOLA", "has_tags", "BD-R" ], [ "THE LIFE OF EMILE ZOLA", "has_tags", "WILLIAM DIETERLE" ], [ "THE MAN WHO LOVED WOMEN", "has_tags", "BD-R" ], [ "THE MAN WHO LOVED WOMEN", "starred_actors", "BURT REYNOLDS" ], [ "THE PRIVATE LIVES OF ELIZABETH AND ESSEX", "has_tags", "BD-R" ], [ "THE PRIVATE LIVES OF ELIZABETH AND ESSEX", "starred_actors", "OLIVIA DE HAVILLAND" ], [ "THE SNAKE PIT", "has_tags", "BD-R" ], [ "THE SNAKE PIT", "has_tags", "OLIVIA DE HAVILLAND" ], [ "THE SNAKE PIT", "starred_actors", "OLIVIA DE HAVILLAND" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 30172, 1964 8486, 1999 658, 2012 15145, MYSTERY 38226, RESOLUTION 430, SHANGHAI 34833, SIMON WEST 40067, STOLEN 4157, THE BEST MAN 24173, THE EXPENDABLES 2 598, THE GENERAL'S DAUGHTER 33864, THE MOON-SPINNERS 12269, THE MOTEL LIFE 18162, THE RAVEN 15504, THE WORDS src, edge_attr, dst 38226, release_year, 658 430, has_genre, 15145 430, release_year, 658 40067, has_genre, 15145 40067, release_year, 658 4157, release_year, 30172 4157, release_year, 8486 24173, directed_by, 34833 24173, has_tags, 34833 24173, release_year, 658 598, directed_by, 34833 598, has_genre, 15145 598, has_tags, 34833 598, release_year, 8486 33864, release_year, 30172 12269, has_genre, 15145 12269, release_year, 658 18162, has_genre, 15145 18162, release_year, 658 15504, has_genre, 15145 15504, release_year, 658 Question: In what context are RESOLUTION, THE GENERAL'S DAUGHTER, and THE MOON-SPINNERS connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "RESOLUTION", "THE GENERAL'S DAUGHTER", "THE MOON-SPINNERS" ], "valid_edges": [ [ "RESOLUTION", "release_year", "2012" ], [ "SHANGHAI", "has_genre", "MYSTERY" ], [ "SHANGHAI", "release_year", "2012" ], [ "STOLEN", "has_genre", "MYSTERY" ], [ "STOLEN", "release_year", "2012" ], [ "THE BEST MAN", "release_year", "1964" ], [ "THE BEST MAN", "release_year", "1999" ], [ "THE EXPENDABLES 2", "directed_by", "SIMON WEST" ], [ "THE EXPENDABLES 2", "has_tags", "SIMON WEST" ], [ "THE EXPENDABLES 2", "release_year", "2012" ], [ "THE GENERAL'S DAUGHTER", "directed_by", "SIMON WEST" ], [ "THE GENERAL'S DAUGHTER", "has_genre", "MYSTERY" ], [ "THE GENERAL'S DAUGHTER", "has_tags", "SIMON WEST" ], [ "THE GENERAL'S DAUGHTER", "release_year", "1999" ], [ "THE MOON-SPINNERS", "release_year", "1964" ], [ "THE MOTEL LIFE", "has_genre", "MYSTERY" ], [ "THE MOTEL LIFE", "release_year", "2012" ], [ "THE RAVEN", "has_genre", "MYSTERY" ], [ "THE RAVEN", "release_year", "2012" ], [ "THE WORDS", "has_genre", "MYSTERY" ], [ "THE WORDS", "release_year", "2012" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 18366, 1960 6925, 1966 16160, COME DRINK WITH ME 24508, DAVID SWIFT 12903, DISNEY 24638, ENCHANTED 35596, HAYLEY MILLS 21518, HONEY, I SHRUNK THE KIDS 21580, KIDS 1989, KING HU 4303, NEW YORK CITY 21773, POLLYANNA 18762, SEQUEL 34600, SPIDER-MAN 38117, SPIDER-MAN 2 2980, SUPERHERO 8061, SWISS FAMILY ROBINSON 14774, THAT DARN CAT! 24357, THE PARENT TRAP 26382, YOU'RE A BIG BOY NOW src, edge_attr, dst 16160, directed_by, 1989 16160, release_year, 6925 16160, written_by, 1989 24638, has_tags, 12903 24638, has_tags, 4303 21518, has_tags, 12903 21518, has_tags, 21580 21580, has_tags, 4303 21773, directed_by, 24508 21773, has_tags, 24508 21773, has_tags, 12903 21773, has_tags, 35596 21773, release_year, 18366 21773, starred_actors, 35596 21773, written_by, 24508 34600, has_tags, 4303 34600, has_tags, 18762 34600, has_tags, 2980 38117, has_tags, 4303 38117, has_tags, 18762 38117, has_tags, 2980 8061, has_tags, 12903 8061, release_year, 18366 14774, has_tags, 12903 14774, has_tags, 35596 14774, starred_actors, 35596 24357, directed_by, 24508 24357, has_tags, 24508 24357, has_tags, 12903 24357, has_tags, 35596 24357, starred_actors, 35596 24357, written_by, 24508 26382, has_tags, 4303 26382, release_year, 6925 Question: In what context are KING HU, NEW YORK CITY, and POLLYANNA connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "KING HU", "NEW YORK CITY", "POLLYANNA" ], "valid_edges": [ [ "COME DRINK WITH ME", "directed_by", "KING HU" ], [ "COME DRINK WITH ME", "release_year", "1966" ], [ "COME DRINK WITH ME", "written_by", "KING HU" ], [ "ENCHANTED", "has_tags", "DISNEY" ], [ "ENCHANTED", "has_tags", "NEW YORK CITY" ], [ "HONEY, I SHRUNK THE KIDS", "has_tags", "DISNEY" ], [ "HONEY, I SHRUNK THE KIDS", "has_tags", "KIDS" ], [ "KIDS", "has_tags", "NEW YORK CITY" ], [ "POLLYANNA", "directed_by", "DAVID SWIFT" ], [ "POLLYANNA", "has_tags", "DAVID SWIFT" ], [ "POLLYANNA", "has_tags", "DISNEY" ], [ "POLLYANNA", "has_tags", "HAYLEY MILLS" ], [ "POLLYANNA", "release_year", "1960" ], [ "POLLYANNA", "starred_actors", "HAYLEY MILLS" ], [ "POLLYANNA", "written_by", "DAVID SWIFT" ], [ "SPIDER-MAN", "has_tags", "NEW YORK CITY" ], [ "SPIDER-MAN", "has_tags", "SEQUEL" ], [ "SPIDER-MAN", "has_tags", "SUPERHERO" ], [ "SPIDER-MAN 2", "has_tags", "NEW YORK CITY" ], [ "SPIDER-MAN 2", "has_tags", "SEQUEL" ], [ "SPIDER-MAN 2", "has_tags", "SUPERHERO" ], [ "SWISS FAMILY ROBINSON", "has_tags", "DISNEY" ], [ "SWISS FAMILY ROBINSON", "release_year", "1960" ], [ "THAT DARN CAT!", "has_tags", "DISNEY" ], [ "THAT DARN CAT!", "has_tags", "HAYLEY MILLS" ], [ "THAT DARN CAT!", "starred_actors", "HAYLEY MILLS" ], [ "THE PARENT TRAP", "directed_by", "DAVID SWIFT" ], [ "THE PARENT TRAP", "has_tags", "DAVID SWIFT" ], [ "THE PARENT TRAP", "has_tags", "DISNEY" ], [ "THE PARENT TRAP", "has_tags", "HAYLEY MILLS" ], [ "THE PARENT TRAP", "starred_actors", "HAYLEY MILLS" ], [ "THE PARENT TRAP", "written_by", "DAVID SWIFT" ], [ "YOU'RE A BIG BOY NOW", "has_tags", "NEW YORK CITY" ], [ "YOU'RE A BIG BOY NOW", "release_year", "1966" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26310, 1947 36163, 1967 6721, 1972 19131, BONNIE AND CLYDE 11767, HUNGRY HILL 19536, TERENCE YOUNG 39072, THE MAN WHO QUIT SMOKING 25837, THE PERILS OF PAULINE 19255, THE VALACHI PAPERS 499, WAIT UNTIL DARK src, edge_attr, dst 19131, release_year, 36163 11767, release_year, 26310 11767, written_by, 19536 39072, release_year, 6721 25837, release_year, 26310 25837, release_year, 36163 19255, directed_by, 19536 19255, release_year, 6721 499, directed_by, 19536 499, has_tags, 19536 499, release_year, 36163 Question: In what context are BONNIE AND CLYDE, HUNGRY HILL, and THE MAN WHO QUIT SMOKING connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BONNIE AND CLYDE", "HUNGRY HILL", "THE MAN WHO QUIT SMOKING" ], "valid_edges": [ [ "BONNIE AND CLYDE", "release_year", "1967" ], [ "HUNGRY HILL", "release_year", "1947" ], [ "HUNGRY HILL", "written_by", "TERENCE YOUNG" ], [ "THE MAN WHO QUIT SMOKING", "release_year", "1972" ], [ "THE PERILS OF PAULINE", "release_year", "1947" ], [ "THE PERILS OF PAULINE", "release_year", "1967" ], [ "THE VALACHI PAPERS", "directed_by", "TERENCE YOUNG" ], [ "THE VALACHI PAPERS", "release_year", "1972" ], [ "WAIT UNTIL DARK", "directed_by", "TERENCE YOUNG" ], [ "WAIT UNTIL DARK", "has_tags", "TERENCE YOUNG" ], [ "WAIT UNTIL DARK", "release_year", "1967" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6253, 1936 18132, 1938 11112, 1939 11, 1940 21931, 1941 26423, 1950 6216, 1952 25717, 1953 1567, 1954 14004, 1955 33637, 1959 3863, 1962 4981, 1965 27810, 1968 39813, 1971 4763, ADVENTURE 39045, ALFRED HITCHCOCK 9677, ANATOMY OF A MURDER 13999, ANDREW V. MCLAGLEN 5661, ANTHONY MANN 35990, ARTHUR KENNEDY 4816, BANDOLERO! 10045, BD-R 3204, BEND OF THE RIVER 3706, BEULAH BONDI 36479, BORN TO DANCE 16749, BROKEN ARROW 29246, CARBINE WILLIAMS 35148, CLARENCE BROWN 14728, CLASSIC 19585, COME LIVE WITH ME 30463, COMEDY 21423, DEAR BRIGITTE 7159, DESTRY RIDES AGAIN 36212, DRAMA 10509, FAMILY 8406, FIRECREEK 13009, FOOLS' PARADE 23668, FRANK CAPRA 27953, GEORGE KENNEDY 18850, GEORGE STEVENS 11565, GOOD 34149, HENRY FONDA 38940, HENRY KOSTER 27350, HITCHCOCK 1331, IT'S A WONDERFUL LIFE 26280, IT'S A WONDERFUL WORLD 7736, JAMES STEWART 2818, JEAN ARTHUR 13255, JOHN FORD 12435, JOHN WAYNE 26627, MADE FOR EACH OTHER 27297, MAGIC TOWN 31669, MARGARET SULLAVAN 36999, MAUREEN O'HARA 20920, MR. HOBBS TAKES A VACATION 26086, MR. SMITH GOES TO WASHINGTON 28476, MURDER 24593, MUSICAL 37497, NATIONAL FILM REGISTRY 35223, NIGHT PASSAGE 23166, NO TIME FOR COMEDY 15311, OF HUMAN HEARTS 9638, ON OUR MERRY WAY 14982, PAULETTE GODDARD 23008, PETER FERDINANDO 19648, POT O' GOLD 37135, REAR WINDOW 7098, SHENANDOAH 38066, SHIRLEY JONES 26381, STRATEGIC AIR COMMAND 11290, TAKE HER, SHE'S MINE 7763, THE CHEYENNE SOCIAL CLUB 27995, THE FAR COUNTRY 32820, THE FBI STORY 757, THE FLIGHT OF THE PHOENIX 26752, THE GLENN MILLER STORY 17394, THE MAN FROM LARAMIE 36235, THE MAN WHO SHOT LIBERTY VALANCE 1533, THE MORTAL STORM 39232, THE NAKED SPUR 28172, THE PHILADELPHIA STORY 2555, THE RARE BREED 31357, THE SHOOTIST 30253, THE SHOP AROUND THE CORNER 32860, THE SHOPWORN ANGEL 24811, THRILLER 32490, THUNDER BAY 4149, TONY 37207, TWO RODE TOGETHER 7957, VERTIGO 13631, VIVACIOUS LADY 22214, WAR 36026, WESTERN 14809, WIFE VS. SECRETARY 26441, WINCHESTER '73 8184, YOU CAN'T TAKE IT WITH YOU 23675, ZERO FOR CONDUCT src, edge_attr, dst 9677, has_genre, 36212 9677, has_tags, 10045 9677, has_tags, 7736 9677, has_tags, 28476 9677, release_year, 33637 9677, starred_actors, 7736 4816, directed_by, 13999 4816, has_tags, 10045 4816, release_year, 27810 4816, starred_actors, 27953 4816, starred_actors, 7736 3204, directed_by, 5661 3204, has_genre, 36026 3204, has_tags, 5661 3204, has_tags, 7736 3204, release_year, 6216 3204, starred_actors, 35990 3204, starred_actors, 7736 36479, has_genre, 30463 36479, has_genre, 24593 36479, has_imdb_rating, 11565 36479, release_year, 6253 36479, starred_actors, 7736 16749, has_genre, 36212 16749, has_genre, 36026 16749, release_year, 26423 16749, starred_actors, 7736 29246, has_genre, 36212 29246, release_year, 6216 29246, starred_actors, 7736 19585, directed_by, 35148 19585, has_genre, 30463 19585, has_tags, 35148 19585, release_year, 21931 19585, starred_actors, 7736 21423, directed_by, 38940 21423, has_genre, 30463 21423, has_genre, 10509 21423, has_tags, 30463 21423, release_year, 4981 21423, starred_actors, 7736 7159, has_genre, 36026 7159, has_tags, 7736 7159, has_tags, 37497 7159, release_year, 11112 7159, starred_actors, 7736 8406, has_genre, 36026 8406, release_year, 27810 8406, starred_actors, 34149 8406, starred_actors, 7736 13009, has_genre, 36212 13009, release_year, 39813 13009, starred_actors, 27953 13009, starred_actors, 7736 1331, directed_by, 23668 1331, has_genre, 36212 1331, has_genre, 10509 1331, has_tags, 14728 1331, has_tags, 36212 1331, has_tags, 10509 1331, has_tags, 23668 1331, has_tags, 7736 1331, starred_actors, 7736 1331, written_by, 23668 26280, has_genre, 30463 26280, release_year, 11112 26280, starred_actors, 7736 26627, has_genre, 36212 26627, release_year, 11112 26627, release_year, 39813 26627, starred_actors, 7736 27297, has_genre, 30463 27297, starred_actors, 7736 20920, directed_by, 38940 20920, has_genre, 30463 20920, has_tags, 38940 20920, release_year, 3863 20920, starred_actors, 7736 20920, starred_actors, 36999 26086, directed_by, 23668 26086, has_genre, 36212 26086, has_tags, 10045 26086, has_tags, 36212 26086, has_tags, 23668 26086, has_tags, 7736 26086, has_tags, 2818 26086, has_tags, 37497 26086, release_year, 11112 26086, starred_actors, 7736 26086, starred_actors, 2818 35223, has_genre, 36026 35223, starred_actors, 7736 23166, has_genre, 30463 23166, has_genre, 36212 23166, release_year, 11 23166, starred_actors, 7736 15311, directed_by, 35148 15311, has_genre, 36212 15311, release_year, 18132 15311, starred_actors, 3706 15311, starred_actors, 7736 9638, directed_by, 18850 9638, has_genre, 30463 9638, starred_actors, 34149 9638, starred_actors, 7736 9638, starred_actors, 14982 19648, has_genre, 30463 19648, has_genre, 24593 19648, has_tags, 7736 19648, release_year, 21931 19648, starred_actors, 7736 19648, starred_actors, 14982 37135, directed_by, 39045 37135, has_genre, 24811 37135, has_tags, 39045 37135, has_tags, 14728 37135, has_tags, 27350 37135, has_tags, 7736 37135, has_tags, 28476 37135, has_tags, 37497 37135, has_tags, 24811 37135, release_year, 1567 37135, starred_actors, 7736 7098, directed_by, 13999 7098, has_genre, 22214 7098, has_tags, 13999 7098, has_tags, 7736 7098, release_year, 4981 7098, starred_actors, 7736 26381, directed_by, 5661 26381, has_genre, 22214 26381, release_year, 14004 26381, starred_actors, 7736 11290, directed_by, 38940 11290, has_genre, 30463 11290, starred_actors, 7736 7763, has_genre, 30463 7763, has_genre, 36026 7763, has_tags, 10045 7763, starred_actors, 34149 7763, starred_actors, 7736 7763, starred_actors, 38066 27995, directed_by, 5661 27995, has_genre, 4763 27995, has_tags, 5661 27995, release_year, 1567 27995, starred_actors, 7736 32820, has_genre, 36212 32820, release_year, 33637 32820, starred_actors, 7736 757, has_genre, 36212 757, has_tags, 7736 757, release_year, 4981 757, starred_actors, 7736 26752, directed_by, 5661 26752, has_tags, 5661 26752, has_tags, 7736 26752, release_year, 1567 26752, starred_actors, 7736 17394, directed_by, 5661 17394, has_genre, 36026 17394, has_tags, 5661 17394, release_year, 14004 17394, starred_actors, 35990 17394, starred_actors, 7736 36235, directed_by, 13255 36235, has_genre, 36026 36235, has_tags, 10045 36235, has_tags, 7736 36235, has_tags, 13255 36235, has_tags, 12435 36235, has_tags, 37497 36235, has_tags, 36026 36235, release_year, 3863 36235, starred_actors, 7736 36235, starred_actors, 12435 1533, has_genre, 36212 1533, release_year, 11 1533, starred_actors, 7736 1533, starred_actors, 31669 39232, directed_by, 5661 39232, has_genre, 36026 39232, has_tags, 5661 39232, has_tags, 10045 39232, has_tags, 7736 39232, release_year, 25717 39232, starred_actors, 7736 28172, has_genre, 30463 28172, has_tags, 10045 28172, has_tags, 7736 28172, has_tags, 37497 28172, release_year, 11 28172, starred_actors, 7736 2555, directed_by, 13999 2555, has_genre, 36026 2555, starred_actors, 7736 2555, starred_actors, 36999 31357, has_genre, 36026 31357, has_tags, 12435 31357, starred_actors, 7736 31357, starred_actors, 12435 30253, has_genre, 30463 30253, has_tags, 10045 30253, has_tags, 7736 30253, has_tags, 37497 30253, release_year, 11 30253, starred_actors, 7736 30253, starred_actors, 31669 32860, has_genre, 36212 32860, has_genre, 22214 32860, release_year, 18132 32860, starred_actors, 7736 32860, starred_actors, 31669 32490, directed_by, 5661 32490, has_genre, 4763 32490, release_year, 25717 32490, starred_actors, 7736 4149, has_genre, 36212 4149, starred_actors, 23008 37207, directed_by, 13255 37207, has_genre, 36026 37207, starred_actors, 7736 37207, starred_actors, 38066 7957, directed_by, 39045 7957, has_genre, 24811 7957, has_tags, 39045 7957, has_tags, 14728 7957, has_tags, 27350 7957, has_tags, 7736 7957, starred_actors, 7736 13631, directed_by, 18850 13631, has_genre, 30463 13631, has_tags, 18850 13631, release_year, 18132 13631, starred_actors, 3706 13631, starred_actors, 7736 14809, directed_by, 35148 14809, has_genre, 30463 14809, has_tags, 35148 14809, has_tags, 7736 14809, release_year, 6253 26441, directed_by, 5661 26441, has_genre, 36026 26441, has_tags, 5661 26441, release_year, 26423 26441, starred_actors, 7736 8184, directed_by, 23668 8184, has_genre, 30463 8184, has_imdb_rating, 11565 8184, has_tags, 23668 8184, has_tags, 7736 8184, release_year, 18132 8184, starred_actors, 7736 8184, starred_actors, 2818 23675, has_tags, 10045 Question: For what reason are JAMES STEWART, PETER FERDINANDO, and ZERO FOR CONDUCT associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JAMES STEWART", "PETER FERDINANDO", "ZERO FOR CONDUCT" ], "valid_edges": [ [ "ANATOMY OF A MURDER", "has_genre", "DRAMA" ], [ "ANATOMY OF A MURDER", "has_tags", "BD-R" ], [ "ANATOMY OF A MURDER", "has_tags", "JAMES STEWART" ], [ "ANATOMY OF A MURDER", "has_tags", "MURDER" ], [ "ANATOMY OF A MURDER", "release_year", "1959" ], [ "ANATOMY OF A MURDER", "starred_actors", "JAMES STEWART" ], [ "BANDOLERO!", "directed_by", "ANDREW V. MCLAGLEN" ], [ "BANDOLERO!", "has_tags", "BD-R" ], [ "BANDOLERO!", "release_year", "1968" ], [ "BANDOLERO!", "starred_actors", "GEORGE KENNEDY" ], [ "BANDOLERO!", "starred_actors", "JAMES STEWART" ], [ "BEND OF THE RIVER", "directed_by", "ANTHONY MANN" ], [ "BEND OF THE RIVER", "has_genre", "WESTERN" ], [ "BEND OF THE RIVER", "has_tags", "ANTHONY MANN" ], [ "BEND OF THE RIVER", "has_tags", "JAMES STEWART" ], [ "BEND OF THE RIVER", "release_year", "1952" ], [ "BEND OF THE RIVER", "starred_actors", "ARTHUR KENNEDY" ], [ "BEND OF THE RIVER", "starred_actors", "JAMES STEWART" ], [ "BORN TO DANCE", "has_genre", "COMEDY" ], [ "BORN TO DANCE", "has_genre", "MUSICAL" ], [ "BORN TO DANCE", "has_imdb_rating", "GOOD" ], [ "BORN TO DANCE", "release_year", "1936" ], [ "BORN TO DANCE", "starred_actors", "JAMES STEWART" ], [ "BROKEN ARROW", "has_genre", "DRAMA" ], [ "BROKEN ARROW", "has_genre", "WESTERN" ], [ "BROKEN ARROW", "release_year", "1950" ], [ "BROKEN ARROW", "starred_actors", "JAMES STEWART" ], [ "CARBINE WILLIAMS", "has_genre", "DRAMA" ], [ "CARBINE WILLIAMS", "release_year", "1952" ], [ "CARBINE WILLIAMS", "starred_actors", "JAMES STEWART" ], [ "COME LIVE WITH ME", "directed_by", "CLARENCE BROWN" ], [ "COME LIVE WITH ME", "has_genre", "COMEDY" ], [ "COME LIVE WITH ME", "has_tags", "CLARENCE BROWN" ], [ "COME LIVE WITH ME", "release_year", "1941" ], [ "COME LIVE WITH ME", "starred_actors", "JAMES STEWART" ], [ "DEAR BRIGITTE", "directed_by", "HENRY KOSTER" ], [ "DEAR BRIGITTE", "has_genre", "COMEDY" ], [ "DEAR BRIGITTE", "has_genre", "FAMILY" ], [ "DEAR BRIGITTE", "has_tags", "COMEDY" ], [ "DEAR BRIGITTE", "release_year", "1965" ], [ "DEAR BRIGITTE", "starred_actors", "JAMES STEWART" ], [ "DESTRY RIDES AGAIN", "has_genre", "WESTERN" ], [ "DESTRY RIDES AGAIN", "has_tags", "JAMES STEWART" ], [ "DESTRY RIDES AGAIN", "has_tags", "NATIONAL FILM REGISTRY" ], [ "DESTRY RIDES AGAIN", "release_year", "1939" ], [ "DESTRY RIDES AGAIN", "starred_actors", "JAMES STEWART" ], [ "FIRECREEK", "has_genre", "WESTERN" ], [ "FIRECREEK", "release_year", "1968" ], [ "FIRECREEK", "starred_actors", "HENRY FONDA" ], [ "FIRECREEK", "starred_actors", "JAMES STEWART" ], [ "FOOLS' PARADE", "has_genre", "DRAMA" ], [ "FOOLS' PARADE", "release_year", "1971" ], [ "FOOLS' PARADE", "starred_actors", "GEORGE KENNEDY" ], [ "FOOLS' PARADE", "starred_actors", "JAMES STEWART" ], [ "IT'S A WONDERFUL LIFE", "directed_by", "FRANK CAPRA" ], [ "IT'S A WONDERFUL LIFE", "has_genre", "DRAMA" ], [ "IT'S A WONDERFUL LIFE", "has_genre", "FAMILY" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "CLASSIC" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "DRAMA" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "FAMILY" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "FRANK CAPRA" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "JAMES STEWART" ], [ "IT'S A WONDERFUL LIFE", "starred_actors", "JAMES STEWART" ], [ "IT'S A WONDERFUL LIFE", "written_by", "FRANK CAPRA" ], [ "IT'S A WONDERFUL WORLD", "has_genre", "COMEDY" ], [ "IT'S A WONDERFUL WORLD", "release_year", "1939" ], [ "IT'S A WONDERFUL WORLD", "starred_actors", "JAMES STEWART" ], [ "MADE FOR EACH OTHER", "has_genre", "DRAMA" ], [ "MADE FOR EACH OTHER", "release_year", "1939" ], [ "MADE FOR EACH OTHER", "release_year", "1971" ], [ "MADE FOR EACH OTHER", "starred_actors", "JAMES STEWART" ], [ "MAGIC TOWN", "has_genre", "COMEDY" ], [ "MAGIC TOWN", "starred_actors", "JAMES STEWART" ], [ "MR. HOBBS TAKES A VACATION", "directed_by", "HENRY KOSTER" ], [ "MR. HOBBS TAKES A VACATION", "has_genre", "COMEDY" ], [ "MR. HOBBS TAKES A VACATION", "has_tags", "HENRY KOSTER" ], [ "MR. HOBBS TAKES A VACATION", "release_year", "1962" ], [ "MR. HOBBS TAKES A VACATION", "starred_actors", "JAMES STEWART" ], [ "MR. HOBBS TAKES A VACATION", "starred_actors", "MAUREEN O'HARA" ], [ "MR. SMITH GOES TO WASHINGTON", "directed_by", "FRANK CAPRA" ], [ "MR. SMITH GOES TO WASHINGTON", "has_genre", "DRAMA" ], [ "MR. SMITH GOES TO WASHINGTON", "has_tags", "BD-R" ], [ "MR. SMITH GOES TO WASHINGTON", "has_tags", "DRAMA" ], [ "MR. SMITH GOES TO WASHINGTON", "has_tags", "FRANK CAPRA" ], [ "MR. SMITH GOES TO WASHINGTON", "has_tags", "JAMES STEWART" ], [ "MR. SMITH GOES TO WASHINGTON", "has_tags", "JEAN ARTHUR" ], [ "MR. SMITH GOES TO WASHINGTON", "has_tags", "NATIONAL FILM REGISTRY" ], [ "MR. SMITH GOES TO WASHINGTON", "release_year", "1939" ], [ "MR. SMITH GOES TO WASHINGTON", "starred_actors", "JAMES STEWART" ], [ "MR. SMITH GOES TO WASHINGTON", "starred_actors", "JEAN ARTHUR" ], [ "NIGHT PASSAGE", "has_genre", "WESTERN" ], [ "NIGHT PASSAGE", "starred_actors", "JAMES STEWART" ], [ "NO TIME FOR COMEDY", "has_genre", "COMEDY" ], [ "NO TIME FOR COMEDY", "has_genre", "DRAMA" ], [ "NO TIME FOR COMEDY", "release_year", "1940" ], [ "NO TIME FOR COMEDY", "starred_actors", "JAMES STEWART" ], [ "OF HUMAN HEARTS", "directed_by", "CLARENCE BROWN" ], [ "OF HUMAN HEARTS", "has_genre", "DRAMA" ], [ "OF HUMAN HEARTS", "release_year", "1938" ], [ "OF HUMAN HEARTS", "starred_actors", "BEULAH BONDI" ], [ "OF HUMAN HEARTS", "starred_actors", "JAMES STEWART" ], [ "ON OUR MERRY WAY", "directed_by", "GEORGE STEVENS" ], [ "ON OUR MERRY WAY", "has_genre", "COMEDY" ], [ "ON OUR MERRY WAY", "starred_actors", "HENRY FONDA" ], [ "ON OUR MERRY WAY", "starred_actors", "JAMES STEWART" ], [ "ON OUR MERRY WAY", "starred_actors", "PAULETTE GODDARD" ], [ "POT O' GOLD", "has_genre", "COMEDY" ], [ "POT O' GOLD", "has_genre", "MUSICAL" ], [ "POT O' GOLD", "has_tags", "JAMES STEWART" ], [ "POT O' GOLD", "release_year", "1941" ], [ "POT O' GOLD", "starred_actors", "JAMES STEWART" ], [ "POT O' GOLD", "starred_actors", "PAULETTE GODDARD" ], [ "REAR WINDOW", "directed_by", "ALFRED HITCHCOCK" ], [ "REAR WINDOW", "has_genre", "THRILLER" ], [ "REAR WINDOW", "has_tags", "ALFRED HITCHCOCK" ], [ "REAR WINDOW", "has_tags", "CLASSIC" ], [ "REAR WINDOW", "has_tags", "HITCHCOCK" ], [ "REAR WINDOW", "has_tags", "JAMES STEWART" ], [ "REAR WINDOW", "has_tags", "MURDER" ], [ "REAR WINDOW", "has_tags", "NATIONAL FILM REGISTRY" ], [ "REAR WINDOW", "has_tags", "THRILLER" ], [ "REAR WINDOW", "release_year", "1954" ], [ "REAR WINDOW", "starred_actors", "JAMES STEWART" ], [ "SHENANDOAH", "directed_by", "ANDREW V. MCLAGLEN" ], [ "SHENANDOAH", "has_genre", "WAR" ], [ "SHENANDOAH", "has_tags", "ANDREW V. MCLAGLEN" ], [ "SHENANDOAH", "has_tags", "JAMES STEWART" ], [ "SHENANDOAH", "release_year", "1965" ], [ "SHENANDOAH", "starred_actors", "JAMES STEWART" ], [ "STRATEGIC AIR COMMAND", "directed_by", "ANTHONY MANN" ], [ "STRATEGIC AIR COMMAND", "has_genre", "WAR" ], [ "STRATEGIC AIR COMMAND", "release_year", "1955" ], [ "STRATEGIC AIR COMMAND", "starred_actors", "JAMES STEWART" ], [ "TAKE HER, SHE'S MINE", "directed_by", "HENRY KOSTER" ], [ "TAKE HER, SHE'S MINE", "has_genre", "COMEDY" ], [ "TAKE HER, SHE'S MINE", "starred_actors", "JAMES STEWART" ], [ "THE CHEYENNE SOCIAL CLUB", "has_genre", "COMEDY" ], [ "THE CHEYENNE SOCIAL CLUB", "has_genre", "WESTERN" ], [ "THE CHEYENNE SOCIAL CLUB", "has_tags", "BD-R" ], [ "THE CHEYENNE SOCIAL CLUB", "starred_actors", "HENRY FONDA" ], [ "THE CHEYENNE SOCIAL CLUB", "starred_actors", "JAMES STEWART" ], [ "THE CHEYENNE SOCIAL CLUB", "starred_actors", "SHIRLEY JONES" ], [ "THE FAR COUNTRY", "directed_by", "ANTHONY MANN" ], [ "THE FAR COUNTRY", "has_genre", "ADVENTURE" ], [ "THE FAR COUNTRY", "has_tags", "ANTHONY MANN" ], [ "THE FAR COUNTRY", "release_year", "1954" ], [ "THE FAR COUNTRY", "starred_actors", "JAMES STEWART" ], [ "THE FBI STORY", "has_genre", "DRAMA" ], [ "THE FBI STORY", "release_year", "1959" ], [ "THE FBI STORY", "starred_actors", "JAMES STEWART" ], [ "THE FLIGHT OF THE PHOENIX", "has_genre", "DRAMA" ], [ "THE FLIGHT OF THE PHOENIX", "has_tags", "JAMES STEWART" ], [ "THE FLIGHT OF THE PHOENIX", "release_year", "1965" ], [ "THE FLIGHT OF THE PHOENIX", "starred_actors", "JAMES STEWART" ], [ "THE GLENN MILLER STORY", "directed_by", "ANTHONY MANN" ], [ "THE GLENN MILLER STORY", "has_tags", "ANTHONY MANN" ], [ "THE GLENN MILLER STORY", "has_tags", "JAMES STEWART" ], [ "THE GLENN MILLER STORY", "release_year", "1954" ], [ "THE GLENN MILLER STORY", "starred_actors", "JAMES STEWART" ], [ "THE MAN FROM LARAMIE", "directed_by", "ANTHONY MANN" ], [ "THE MAN FROM LARAMIE", "has_genre", "WESTERN" ], [ "THE MAN FROM LARAMIE", "has_tags", "ANTHONY MANN" ], [ "THE MAN FROM LARAMIE", "release_year", "1955" ], [ "THE MAN FROM LARAMIE", "starred_actors", "ARTHUR KENNEDY" ], [ "THE MAN FROM LARAMIE", "starred_actors", "JAMES STEWART" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "directed_by", "JOHN FORD" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_genre", "WESTERN" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "BD-R" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "JAMES STEWART" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "JOHN FORD" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "JOHN WAYNE" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "WESTERN" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "release_year", "1962" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "starred_actors", "JAMES STEWART" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "starred_actors", "JOHN WAYNE" ], [ "THE MORTAL STORM", "has_genre", "DRAMA" ], [ "THE MORTAL STORM", "release_year", "1940" ], [ "THE MORTAL STORM", "starred_actors", "JAMES STEWART" ], [ "THE MORTAL STORM", "starred_actors", "MARGARET SULLAVAN" ], [ "THE NAKED SPUR", "directed_by", "ANTHONY MANN" ], [ "THE NAKED SPUR", "has_genre", "WESTERN" ], [ "THE NAKED SPUR", "has_tags", "ANTHONY MANN" ], [ "THE NAKED SPUR", "has_tags", "BD-R" ], [ "THE NAKED SPUR", "has_tags", "JAMES STEWART" ], [ "THE NAKED SPUR", "release_year", "1953" ], [ "THE NAKED SPUR", "starred_actors", "JAMES STEWART" ], [ "THE PHILADELPHIA STORY", "has_genre", "COMEDY" ], [ "THE PHILADELPHIA STORY", "has_tags", "BD-R" ], [ "THE PHILADELPHIA STORY", "has_tags", "JAMES STEWART" ], [ "THE PHILADELPHIA STORY", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE PHILADELPHIA STORY", "release_year", "1940" ], [ "THE PHILADELPHIA STORY", "starred_actors", "JAMES STEWART" ], [ "THE RARE BREED", "directed_by", "ANDREW V. MCLAGLEN" ], [ "THE RARE BREED", "has_genre", "WESTERN" ], [ "THE RARE BREED", "starred_actors", "JAMES STEWART" ], [ "THE RARE BREED", "starred_actors", "MAUREEN O'HARA" ], [ "THE SHOOTIST", "has_genre", "WESTERN" ], [ "THE SHOOTIST", "has_tags", "JOHN WAYNE" ], [ "THE SHOOTIST", "starred_actors", "JAMES STEWART" ], [ "THE SHOOTIST", "starred_actors", "JOHN WAYNE" ], [ "THE SHOP AROUND THE CORNER", "has_genre", "COMEDY" ], [ "THE SHOP AROUND THE CORNER", "has_tags", "BD-R" ], [ "THE SHOP AROUND THE CORNER", "has_tags", "JAMES STEWART" ], [ "THE SHOP AROUND THE CORNER", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE SHOP AROUND THE CORNER", "release_year", "1940" ], [ "THE SHOP AROUND THE CORNER", "starred_actors", "JAMES STEWART" ], [ "THE SHOP AROUND THE CORNER", "starred_actors", "MARGARET SULLAVAN" ], [ "THE SHOPWORN ANGEL", "has_genre", "DRAMA" ], [ "THE SHOPWORN ANGEL", "has_genre", "WAR" ], [ "THE SHOPWORN ANGEL", "release_year", "1938" ], [ "THE SHOPWORN ANGEL", "starred_actors", "JAMES STEWART" ], [ "THE SHOPWORN ANGEL", "starred_actors", "MARGARET SULLAVAN" ], [ "THUNDER BAY", "directed_by", "ANTHONY MANN" ], [ "THUNDER BAY", "has_genre", "ADVENTURE" ], [ "THUNDER BAY", "release_year", "1953" ], [ "THUNDER BAY", "starred_actors", "JAMES STEWART" ], [ "TONY", "has_genre", "DRAMA" ], [ "TONY", "starred_actors", "PETER FERDINANDO" ], [ "TWO RODE TOGETHER", "directed_by", "JOHN FORD" ], [ "TWO RODE TOGETHER", "has_genre", "WESTERN" ], [ "TWO RODE TOGETHER", "starred_actors", "JAMES STEWART" ], [ "TWO RODE TOGETHER", "starred_actors", "SHIRLEY JONES" ], [ "VERTIGO", "directed_by", "ALFRED HITCHCOCK" ], [ "VERTIGO", "has_genre", "THRILLER" ], [ "VERTIGO", "has_tags", "ALFRED HITCHCOCK" ], [ "VERTIGO", "has_tags", "CLASSIC" ], [ "VERTIGO", "has_tags", "HITCHCOCK" ], [ "VERTIGO", "has_tags", "JAMES STEWART" ], [ "VERTIGO", "starred_actors", "JAMES STEWART" ], [ "VIVACIOUS LADY", "directed_by", "GEORGE STEVENS" ], [ "VIVACIOUS LADY", "has_genre", "COMEDY" ], [ "VIVACIOUS LADY", "has_tags", "GEORGE STEVENS" ], [ "VIVACIOUS LADY", "release_year", "1938" ], [ "VIVACIOUS LADY", "starred_actors", "BEULAH BONDI" ], [ "VIVACIOUS LADY", "starred_actors", "JAMES STEWART" ], [ "WIFE VS. SECRETARY", "directed_by", "CLARENCE BROWN" ], [ "WIFE VS. SECRETARY", "has_genre", "COMEDY" ], [ "WIFE VS. SECRETARY", "has_tags", "CLARENCE BROWN" ], [ "WIFE VS. SECRETARY", "has_tags", "JAMES STEWART" ], [ "WIFE VS. SECRETARY", "release_year", "1936" ], [ "WINCHESTER '73", "directed_by", "ANTHONY MANN" ], [ "WINCHESTER '73", "has_genre", "WESTERN" ], [ "WINCHESTER '73", "has_tags", "ANTHONY MANN" ], [ "WINCHESTER '73", "release_year", "1950" ], [ "WINCHESTER '73", "starred_actors", "JAMES STEWART" ], [ "YOU CAN'T TAKE IT WITH YOU", "directed_by", "FRANK CAPRA" ], [ "YOU CAN'T TAKE IT WITH YOU", "has_genre", "COMEDY" ], [ "YOU CAN'T TAKE IT WITH YOU", "has_imdb_rating", "GOOD" ], [ "YOU CAN'T TAKE IT WITH YOU", "has_tags", "FRANK CAPRA" ], [ "YOU CAN'T TAKE IT WITH YOU", "has_tags", "JAMES STEWART" ], [ "YOU CAN'T TAKE IT WITH YOU", "release_year", "1938" ], [ "YOU CAN'T TAKE IT WITH YOU", "starred_actors", "JAMES STEWART" ], [ "YOU CAN'T TAKE IT WITH YOU", "starred_actors", "JEAN ARTHUR" ], [ "ZERO FOR CONDUCT", "has_tags", "BD-R" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 7977, 1969 27938, BRIGITTE BARDOT 27948, BRUCE DAVISON 28933, LAST SUMMER 12165, SHALAKO 8153, THE HANOI HILTON 18187, ULZANA'S RAID 22214, WAR 36026, WESTERN src, edge_attr, dst 7977, has_genre, 22214 28933, release_year, 7977 28933, starred_actors, 27948 12165, has_genre, 36026 12165, starred_actors, 27938 8153, has_genre, 22214 18187, has_genre, 36026 18187, starred_actors, 27948 Question: How are BRIGITTE BARDOT, BRUCE DAVISON, and THE HANOI HILTON related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BRIGITTE BARDOT", "BRUCE DAVISON", "THE HANOI HILTON" ], "valid_edges": [ [ "1969", "has_genre", "WAR" ], [ "LAST SUMMER", "release_year", "1969" ], [ "LAST SUMMER", "starred_actors", "BRUCE DAVISON" ], [ "SHALAKO", "has_genre", "WESTERN" ], [ "SHALAKO", "starred_actors", "BRIGITTE BARDOT" ], [ "THE HANOI HILTON", "has_genre", "WAR" ], [ "ULZANA'S RAID", "has_genre", "WESTERN" ], [ "ULZANA'S RAID", "starred_actors", "BRUCE DAVISON" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35935, 2002 35845, 2006 30496, EMMETT'S MARK 36222, FEARLESS 35711, HARRY DEAN STANTON 19637, INLAND EMPIRE 31899, KEITH SNYDER 26470, NATIONALISM 7083, SONNY src, edge_attr, dst 30496, directed_by, 31899 30496, release_year, 35935 30496, written_by, 31899 36222, has_tags, 26470 36222, release_year, 35845 19637, has_tags, 35711 19637, release_year, 35845 7083, release_year, 35935 7083, starred_actors, 35711 Question: How are HARRY DEAN STANTON, KEITH SNYDER, and NATIONALISM related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "HARRY DEAN STANTON", "KEITH SNYDER", "NATIONALISM" ], "valid_edges": [ [ "EMMETT'S MARK", "directed_by", "KEITH SNYDER" ], [ "EMMETT'S MARK", "release_year", "2002" ], [ "EMMETT'S MARK", "written_by", "KEITH SNYDER" ], [ "FEARLESS", "has_tags", "NATIONALISM" ], [ "FEARLESS", "release_year", "2006" ], [ "INLAND EMPIRE", "has_tags", "HARRY DEAN STANTON" ], [ "INLAND EMPIRE", "release_year", "2006" ], [ "SONNY", "release_year", "2002" ], [ "SONNY", "starred_actors", "HARRY DEAN STANTON" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1097, 2003 20497, BEN AFFLECK 26583, BOUNCE 31208, DAREDEVIL 13799, DIABOLIQUE 37448, DON ROOS 35535, GIGLI 533, GRETA SCACCHI 25010, JENNIFER LOPEZ 21861, JERSEY GIRL 60, PAYCHECK 2196, SHATTERED 24811, THRILLER src, edge_attr, dst 26583, directed_by, 37448 26583, starred_actors, 20497 26583, written_by, 37448 31208, has_tags, 20497 31208, release_year, 1097 31208, starred_actors, 20497 13799, has_genre, 24811 13799, written_by, 37448 35535, has_tags, 20497 35535, has_tags, 25010 35535, release_year, 1097 35535, starred_actors, 20497 21861, has_tags, 20497 21861, has_tags, 25010 60, has_tags, 20497 60, release_year, 1097 60, starred_actors, 20497 2196, has_genre, 24811 2196, starred_actors, 533 Question: How are DON ROOS, GIGLI, and GRETA SCACCHI related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DON ROOS", "GIGLI", "GRETA SCACCHI" ], "valid_edges": [ [ "BOUNCE", "directed_by", "DON ROOS" ], [ "BOUNCE", "starred_actors", "BEN AFFLECK" ], [ "BOUNCE", "written_by", "DON ROOS" ], [ "DAREDEVIL", "has_tags", "BEN AFFLECK" ], [ "DAREDEVIL", "release_year", "2003" ], [ "DAREDEVIL", "starred_actors", "BEN AFFLECK" ], [ "DIABOLIQUE", "has_genre", "THRILLER" ], [ "DIABOLIQUE", "written_by", "DON ROOS" ], [ "GIGLI", "has_tags", "BEN AFFLECK" ], [ "GIGLI", "has_tags", "JENNIFER LOPEZ" ], [ "GIGLI", "release_year", "2003" ], [ "GIGLI", "starred_actors", "BEN AFFLECK" ], [ "JERSEY GIRL", "has_tags", "BEN AFFLECK" ], [ "JERSEY GIRL", "has_tags", "JENNIFER LOPEZ" ], [ "PAYCHECK", "has_tags", "BEN AFFLECK" ], [ "PAYCHECK", "release_year", "2003" ], [ "PAYCHECK", "starred_actors", "BEN AFFLECK" ], [ "SHATTERED", "has_genre", "THRILLER" ], [ "SHATTERED", "starred_actors", "GRETA SCACCHI" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17687, AMERICA'S SWEETHEARTS 24598, CHRISTMAS WITH THE KRANKS 30463, COMEDY 23734, COUPE DE VILLE 36212, DRAMA 13308, FREEDOMLAND 28038, HAPPY GO LOVELY 22891, JOE ROTH 21683, PARIS TROUT 9956, PETER DEXTER src, edge_attr, dst 17687, directed_by, 22891 17687, has_genre, 30463 24598, directed_by, 22891 24598, has_genre, 30463 23734, directed_by, 22891 23734, has_genre, 30463 23734, has_genre, 36212 13308, directed_by, 22891 13308, has_genre, 36212 28038, has_genre, 30463 21683, has_genre, 36212 21683, written_by, 9956 Question: How are HAPPY GO LOVELY, JOE ROTH, and PETER DEXTER related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "HAPPY GO LOVELY", "JOE ROTH", "PETER DEXTER" ], "valid_edges": [ [ "AMERICA'S SWEETHEARTS", "directed_by", "JOE ROTH" ], [ "AMERICA'S SWEETHEARTS", "has_genre", "COMEDY" ], [ "CHRISTMAS WITH THE KRANKS", "directed_by", "JOE ROTH" ], [ "CHRISTMAS WITH THE KRANKS", "has_genre", "COMEDY" ], [ "COUPE DE VILLE", "directed_by", "JOE ROTH" ], [ "COUPE DE VILLE", "has_genre", "COMEDY" ], [ "COUPE DE VILLE", "has_genre", "DRAMA" ], [ "FREEDOMLAND", "directed_by", "JOE ROTH" ], [ "FREEDOMLAND", "has_genre", "DRAMA" ], [ "HAPPY GO LOVELY", "has_genre", "COMEDY" ], [ "PARIS TROUT", "has_genre", "DRAMA" ], [ "PARIS TROUT", "written_by", "PETER DEXTER" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 7841, 1987 8486, 1999 6252, A CHINESE GHOST STORY 31344, A LEAGUE OF THEIR OWN 36420, A TAXING WOMAN 27451, ADDICTED TO LOVE 16054, ADVENTURES IN BABYSITTING 18051, AFTER HOURS 3473, AMAZON WOMEN ON THE MOON 1546, AN AMERICAN WEREWOLF IN LONDON 17761, BABY BOOM 37155, BACHELOR PARTY VEGAS 2069, BACK TO THE BEACH 34587, BAD TASTE 24579, BEVERLY HILLS COP II 7462, BEYOND THERAPY 18646, BIG SHOTS 7101, BLIND DATE 8781, BORN IN EAST L.A. 15416, BOYFRIENDS AND GIRLFRIENDS 32043, BROADCAST NEWS 30182, BURGLAR 29437, CAN'T BUY ME LOVE 10710, CLAIRE BLOOM 30463, COMEDY 19984, CREEPSHOW 2 5277, CRITICAL CONDITION 17866, CROSS MY HEART 12629, DATE WITH AN ANGEL 2382, DESPERATELY SEEKING SUSAN 37748, DONALD FAISON 31407, DRAGNET 32705, ERNEST GOES TO CAMP 16661, EVIL DEAD II 21763, GOOD MORNING, VIETNAM 11469, GRIFFIN DUNNE 32384, HAMLET GOES BUSINESS 12085, HAPPY NEW YEAR 28307, HARRY AND THE HENDERSONS 24557, HEAD OFFICE 36859, HELLO AGAIN 37602, HOLLYWOOD SHUFFLE 24940, HOPE AND GLORY 31686, HOT PURSUIT 23849, HOUSEKEEPING 9007, HUNK 16321, INNERSPACE 1166, ISHTAR 21514, JAMES FOLEY 25024, KEN FINKLEMAN 20866, LEIF 30420, LEONARD PART 6 39520, LETHAL WEAPON 28811, LIKE FATHER LIKE SON 1130, LISA PICARD IS FAMOUS 11952, MADONNA 7423, MAID TO ORDER 22842, MAKING MR. RIGHT 32481, MANNEQUIN 33763, MOONSTRUCK 16298, MORGAN STEWART'S COMING HOME 7353, MOVIE 43 36631, MUNCHIES 20549, NADINE 19632, NEXT DAY AIR 36424, OUTRAGEOUS FORTUNE 253, OVERBOARD 16172, PRACTICAL MAGIC 12939, PROJECT X 15214, RADIO DAYS 21462, RAISING ARIZONA 2855, REAL MEN 20748, RECKLESS 10717, RENT-A-COP 9184, RETURN TO HORROR HIGH 39429, ROXANNE 11041, SILENT NIGHT, DEADLY NIGHT PART 2 16951, STAKEOUT 3563, SUMMER SCHOOL 4755, SURF NAZIS MUST DIE 26790, SWEPT AWAY 32018, TEEN WOLF TOO 10020, THE ACCIDENTAL HUSBAND 27730, THE ALLNIGHTER 10194, THE BRAVE LITTLE TOASTER 38918, THE FAMILY 11787, THE HAUNTING 33993, THE MONSTER SQUAD 20674, THE NEXT BEST THING 17411, THE PICK-UP ARTIST 29641, THE PRINCESS BRIDE 27344, THE SQUEEZE 14621, THE WITCHES OF EASTWICK 32233, THREE O'CLOCK HIGH 26294, THROW MOMMA FROM THE TRAIN 22559, TIN MEN 36468, TOUGH GUYS DON'T DANCE 23874, TRIPPIN' 35371, UPTOWN GIRLS 6124, WALK LIKE A MAN 16913, WHO'S THAT GIRL 6981, WISH YOU WERE HERE src, edge_attr, dst 6252, has_genre, 30463 6252, release_year, 7841 31344, has_genre, 30463 31344, has_tags, 11952 31344, starred_actors, 11952 36420, has_genre, 30463 36420, release_year, 7841 27451, directed_by, 11469 27451, has_genre, 30463 27451, has_tags, 30463 16054, has_genre, 30463 16054, release_year, 7841 18051, has_genre, 30463 18051, starred_actors, 11469 3473, has_genre, 30463 3473, release_year, 7841 1546, has_genre, 30463 1546, has_tags, 11469 1546, starred_actors, 11469 17761, has_genre, 30463 17761, release_year, 7841 37155, has_genre, 30463 37155, starred_actors, 37748 2069, has_genre, 30463 2069, release_year, 7841 34587, has_genre, 30463 34587, release_year, 7841 24579, has_genre, 30463 24579, release_year, 7841 7462, has_genre, 30463 7462, release_year, 7841 18646, has_genre, 30463 18646, release_year, 7841 7101, has_genre, 30463 7101, release_year, 7841 8781, has_genre, 30463 8781, release_year, 7841 15416, has_genre, 30463 15416, release_year, 7841 32043, has_genre, 30463 32043, release_year, 7841 30182, has_genre, 30463 30182, release_year, 7841 29437, has_genre, 30463 29437, release_year, 7841 19984, has_genre, 30463 19984, release_year, 7841 5277, has_genre, 30463 5277, release_year, 7841 17866, has_genre, 30463 17866, release_year, 7841 12629, has_genre, 30463 12629, release_year, 7841 2382, has_genre, 30463 2382, has_tags, 11952 2382, starred_actors, 11952 31407, has_genre, 30463 31407, release_year, 7841 32705, has_genre, 30463 32705, release_year, 7841 16661, has_genre, 30463 16661, release_year, 7841 21763, has_genre, 30463 21763, release_year, 7841 32384, has_genre, 30463 32384, has_tags, 30463 32384, release_year, 7841 12085, has_genre, 30463 12085, release_year, 7841 28307, has_genre, 30463 28307, has_tags, 30463 28307, release_year, 7841 24557, directed_by, 25024 24557, has_genre, 30463 24557, written_by, 25024 36859, has_genre, 30463 36859, release_year, 7841 37602, has_genre, 30463 37602, release_year, 7841 24940, has_genre, 30463 24940, release_year, 7841 31686, has_genre, 30463 31686, release_year, 7841 23849, has_genre, 30463 23849, release_year, 7841 9007, has_genre, 30463 9007, release_year, 7841 16321, has_genre, 30463 16321, release_year, 7841 1166, has_genre, 30463 1166, release_year, 7841 20866, has_genre, 30463 20866, release_year, 7841 30420, has_genre, 30463 30420, release_year, 7841 39520, has_tags, 30463 39520, release_year, 7841 28811, has_genre, 30463 28811, release_year, 7841 1130, directed_by, 11469 1130, has_genre, 30463 1130, starred_actors, 11469 7423, has_genre, 30463 7423, release_year, 7841 22842, has_genre, 30463 22842, release_year, 7841 32481, has_genre, 30463 32481, release_year, 7841 33763, has_genre, 30463 33763, release_year, 7841 16298, has_genre, 30463 16298, release_year, 7841 7353, directed_by, 11469 7353, has_genre, 30463 36631, has_genre, 30463 36631, release_year, 7841 20549, has_genre, 30463 20549, release_year, 7841 19632, has_genre, 30463 19632, starred_actors, 37748 36424, has_genre, 30463 36424, release_year, 7841 253, has_genre, 30463 253, release_year, 7841 16172, directed_by, 11469 16172, has_genre, 30463 12939, has_genre, 30463 12939, release_year, 7841 15214, has_genre, 30463 15214, release_year, 7841 21462, has_genre, 30463 21462, has_tags, 30463 21462, release_year, 7841 2855, has_genre, 30463 2855, has_tags, 30463 2855, release_year, 7841 20748, directed_by, 21514 20748, has_genre, 30463 10717, has_genre, 30463 10717, release_year, 7841 9184, has_genre, 30463 9184, release_year, 7841 39429, has_genre, 30463 39429, release_year, 7841 11041, has_genre, 30463 11041, release_year, 7841 16951, has_genre, 30463 16951, release_year, 7841 3563, has_genre, 30463 3563, has_tags, 30463 3563, release_year, 7841 4755, has_genre, 30463 4755, release_year, 7841 26790, has_genre, 30463 26790, has_tags, 11952 26790, starred_actors, 11952 32018, has_genre, 30463 32018, release_year, 7841 10020, directed_by, 11469 10020, has_genre, 30463 27730, has_genre, 30463 27730, release_year, 7841 10194, has_genre, 30463 10194, release_year, 7841 38918, has_genre, 30463 38918, release_year, 7841 11787, release_year, 8486 11787, starred_actors, 10710 33993, has_genre, 30463 33993, release_year, 7841 20674, has_genre, 30463 20674, has_tags, 11952 20674, starred_actors, 11952 17411, has_genre, 30463 17411, release_year, 7841 29641, has_genre, 30463 29641, has_tags, 30463 29641, release_year, 7841 27344, has_genre, 30463 27344, release_year, 7841 14621, has_genre, 30463 14621, release_year, 7841 32233, has_genre, 30463 32233, release_year, 7841 26294, has_genre, 30463 26294, has_tags, 30463 26294, release_year, 7841 22559, has_genre, 30463 22559, release_year, 7841 36468, has_genre, 30463 36468, release_year, 7841 23874, has_genre, 30463 23874, release_year, 8486 23874, starred_actors, 37748 35371, has_genre, 30463 35371, starred_actors, 37748 6124, has_genre, 30463 6124, release_year, 7841 16913, directed_by, 21514 16913, has_genre, 30463 16913, has_tags, 21514 16913, has_tags, 11952 16913, release_year, 7841 16913, starred_actors, 11469 16913, starred_actors, 11952 16913, written_by, 25024 6981, has_genre, 30463 6981, release_year, 7841 Question: For what reason are CLAIRE BLOOM, DONALD FAISON, and WHO'S THAT GIRL associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CLAIRE BLOOM", "DONALD FAISON", "WHO'S THAT GIRL" ], "valid_edges": [ [ "A CHINESE GHOST STORY", "has_genre", "COMEDY" ], [ "A CHINESE GHOST STORY", "release_year", "1987" ], [ "A LEAGUE OF THEIR OWN", "has_genre", "COMEDY" ], [ "A LEAGUE OF THEIR OWN", "has_tags", "MADONNA" ], [ "A LEAGUE OF THEIR OWN", "starred_actors", "MADONNA" ], [ "A TAXING WOMAN", "has_genre", "COMEDY" ], [ "A TAXING WOMAN", "release_year", "1987" ], [ "ADDICTED TO LOVE", "directed_by", "GRIFFIN DUNNE" ], [ "ADDICTED TO LOVE", "has_genre", "COMEDY" ], [ "ADDICTED TO LOVE", "has_tags", "COMEDY" ], [ "ADVENTURES IN BABYSITTING", "has_genre", "COMEDY" ], [ "ADVENTURES IN BABYSITTING", "release_year", "1987" ], [ "AFTER HOURS", "has_genre", "COMEDY" ], [ "AFTER HOURS", "starred_actors", "GRIFFIN DUNNE" ], [ "AMAZON WOMEN ON THE MOON", "has_genre", "COMEDY" ], [ "AMAZON WOMEN ON THE MOON", "release_year", "1987" ], [ "AN AMERICAN WEREWOLF IN LONDON", "has_genre", "COMEDY" ], [ "AN AMERICAN WEREWOLF IN LONDON", "has_tags", "GRIFFIN DUNNE" ], [ "AN AMERICAN WEREWOLF IN LONDON", "starred_actors", "GRIFFIN DUNNE" ], [ "BABY BOOM", "has_genre", "COMEDY" ], [ "BABY BOOM", "release_year", "1987" ], [ "BACHELOR PARTY VEGAS", "has_genre", "COMEDY" ], [ "BACHELOR PARTY VEGAS", "starred_actors", "DONALD FAISON" ], [ "BACK TO THE BEACH", "has_genre", "COMEDY" ], [ "BACK TO THE BEACH", "release_year", "1987" ], [ "BAD TASTE", "has_genre", "COMEDY" ], [ "BAD TASTE", "release_year", "1987" ], [ "BEVERLY HILLS COP II", "has_genre", "COMEDY" ], [ "BEVERLY HILLS COP II", "release_year", "1987" ], [ "BEYOND THERAPY", "has_genre", "COMEDY" ], [ "BEYOND THERAPY", "release_year", "1987" ], [ "BIG SHOTS", "has_genre", "COMEDY" ], [ "BIG SHOTS", "release_year", "1987" ], [ "BLIND DATE", "has_genre", "COMEDY" ], [ "BLIND DATE", "release_year", "1987" ], [ "BORN IN EAST L.A.", "has_genre", "COMEDY" ], [ "BORN IN EAST L.A.", "release_year", "1987" ], [ "BOYFRIENDS AND GIRLFRIENDS", "has_genre", "COMEDY" ], [ "BOYFRIENDS AND GIRLFRIENDS", "release_year", "1987" ], [ "BROADCAST NEWS", "has_genre", "COMEDY" ], [ "BROADCAST NEWS", "release_year", "1987" ], [ "BURGLAR", "has_genre", "COMEDY" ], [ "BURGLAR", "release_year", "1987" ], [ "CAN'T BUY ME LOVE", "has_genre", "COMEDY" ], [ "CAN'T BUY ME LOVE", "release_year", "1987" ], [ "CREEPSHOW 2", "has_genre", "COMEDY" ], [ "CREEPSHOW 2", "release_year", "1987" ], [ "CRITICAL CONDITION", "has_genre", "COMEDY" ], [ "CRITICAL CONDITION", "release_year", "1987" ], [ "CROSS MY HEART", "has_genre", "COMEDY" ], [ "CROSS MY HEART", "release_year", "1987" ], [ "DATE WITH AN ANGEL", "has_genre", "COMEDY" ], [ "DATE WITH AN ANGEL", "release_year", "1987" ], [ "DESPERATELY SEEKING SUSAN", "has_genre", "COMEDY" ], [ "DESPERATELY SEEKING SUSAN", "has_tags", "MADONNA" ], [ "DESPERATELY SEEKING SUSAN", "starred_actors", "MADONNA" ], [ "DRAGNET", "has_genre", "COMEDY" ], [ "DRAGNET", "release_year", "1987" ], [ "ERNEST GOES TO CAMP", "has_genre", "COMEDY" ], [ "ERNEST GOES TO CAMP", "release_year", "1987" ], [ "EVIL DEAD II", "has_genre", "COMEDY" ], [ "EVIL DEAD II", "release_year", "1987" ], [ "GOOD MORNING, VIETNAM", "has_genre", "COMEDY" ], [ "GOOD MORNING, VIETNAM", "release_year", "1987" ], [ "HAMLET GOES BUSINESS", "has_genre", "COMEDY" ], [ "HAMLET GOES BUSINESS", "has_tags", "COMEDY" ], [ "HAMLET GOES BUSINESS", "release_year", "1987" ], [ "HAPPY NEW YEAR", "has_genre", "COMEDY" ], [ "HAPPY NEW YEAR", "release_year", "1987" ], [ "HARRY AND THE HENDERSONS", "has_genre", "COMEDY" ], [ "HARRY AND THE HENDERSONS", "has_tags", "COMEDY" ], [ "HARRY AND THE HENDERSONS", "release_year", "1987" ], [ "HEAD OFFICE", "directed_by", "KEN FINKLEMAN" ], [ "HEAD OFFICE", "has_genre", "COMEDY" ], [ "HEAD OFFICE", "written_by", "KEN FINKLEMAN" ], [ "HELLO AGAIN", "has_genre", "COMEDY" ], [ "HELLO AGAIN", "release_year", "1987" ], [ "HOLLYWOOD SHUFFLE", "has_genre", "COMEDY" ], [ "HOLLYWOOD SHUFFLE", "release_year", "1987" ], [ "HOPE AND GLORY", "has_genre", "COMEDY" ], [ "HOPE AND GLORY", "release_year", "1987" ], [ "HOT PURSUIT", "has_genre", "COMEDY" ], [ "HOT PURSUIT", "release_year", "1987" ], [ "HOUSEKEEPING", "has_genre", "COMEDY" ], [ "HOUSEKEEPING", "release_year", "1987" ], [ "HUNK", "has_genre", "COMEDY" ], [ "HUNK", "release_year", "1987" ], [ "INNERSPACE", "has_genre", "COMEDY" ], [ "INNERSPACE", "release_year", "1987" ], [ "ISHTAR", "has_genre", "COMEDY" ], [ "ISHTAR", "release_year", "1987" ], [ "LEIF", "has_genre", "COMEDY" ], [ "LEIF", "release_year", "1987" ], [ "LEONARD PART 6", "has_genre", "COMEDY" ], [ "LEONARD PART 6", "release_year", "1987" ], [ "LETHAL WEAPON", "has_tags", "COMEDY" ], [ "LETHAL WEAPON", "release_year", "1987" ], [ "LIKE FATHER LIKE SON", "has_genre", "COMEDY" ], [ "LIKE FATHER LIKE SON", "release_year", "1987" ], [ "LISA PICARD IS FAMOUS", "directed_by", "GRIFFIN DUNNE" ], [ "LISA PICARD IS FAMOUS", "has_genre", "COMEDY" ], [ "LISA PICARD IS FAMOUS", "starred_actors", "GRIFFIN DUNNE" ], [ "MAID TO ORDER", "has_genre", "COMEDY" ], [ "MAID TO ORDER", "release_year", "1987" ], [ "MAKING MR. RIGHT", "has_genre", "COMEDY" ], [ "MAKING MR. RIGHT", "release_year", "1987" ], [ "MANNEQUIN", "has_genre", "COMEDY" ], [ "MANNEQUIN", "release_year", "1987" ], [ "MOONSTRUCK", "has_genre", "COMEDY" ], [ "MOONSTRUCK", "release_year", "1987" ], [ "MORGAN STEWART'S COMING HOME", "has_genre", "COMEDY" ], [ "MORGAN STEWART'S COMING HOME", "release_year", "1987" ], [ "MOVIE 43", "directed_by", "GRIFFIN DUNNE" ], [ "MOVIE 43", "has_genre", "COMEDY" ], [ "MUNCHIES", "has_genre", "COMEDY" ], [ "MUNCHIES", "release_year", "1987" ], [ "NADINE", "has_genre", "COMEDY" ], [ "NADINE", "release_year", "1987" ], [ "NEXT DAY AIR", "has_genre", "COMEDY" ], [ "NEXT DAY AIR", "starred_actors", "DONALD FAISON" ], [ "OUTRAGEOUS FORTUNE", "has_genre", "COMEDY" ], [ "OUTRAGEOUS FORTUNE", "release_year", "1987" ], [ "OVERBOARD", "has_genre", "COMEDY" ], [ "OVERBOARD", "release_year", "1987" ], [ "PRACTICAL MAGIC", "directed_by", "GRIFFIN DUNNE" ], [ "PRACTICAL MAGIC", "has_genre", "COMEDY" ], [ "PROJECT X", "has_genre", "COMEDY" ], [ "PROJECT X", "release_year", "1987" ], [ "RADIO DAYS", "has_genre", "COMEDY" ], [ "RADIO DAYS", "release_year", "1987" ], [ "RAISING ARIZONA", "has_genre", "COMEDY" ], [ "RAISING ARIZONA", "has_tags", "COMEDY" ], [ "RAISING ARIZONA", "release_year", "1987" ], [ "REAL MEN", "has_genre", "COMEDY" ], [ "REAL MEN", "has_tags", "COMEDY" ], [ "REAL MEN", "release_year", "1987" ], [ "RECKLESS", "directed_by", "JAMES FOLEY" ], [ "RECKLESS", "has_genre", "COMEDY" ], [ "RENT-A-COP", "has_genre", "COMEDY" ], [ "RENT-A-COP", "release_year", "1987" ], [ "RETURN TO HORROR HIGH", "has_genre", "COMEDY" ], [ "RETURN TO HORROR HIGH", "release_year", "1987" ], [ "ROXANNE", "has_genre", "COMEDY" ], [ "ROXANNE", "release_year", "1987" ], [ "SILENT NIGHT, DEADLY NIGHT PART 2", "has_genre", "COMEDY" ], [ "SILENT NIGHT, DEADLY NIGHT PART 2", "release_year", "1987" ], [ "STAKEOUT", "has_genre", "COMEDY" ], [ "STAKEOUT", "release_year", "1987" ], [ "SUMMER SCHOOL", "has_genre", "COMEDY" ], [ "SUMMER SCHOOL", "has_tags", "COMEDY" ], [ "SUMMER SCHOOL", "release_year", "1987" ], [ "SURF NAZIS MUST DIE", "has_genre", "COMEDY" ], [ "SURF NAZIS MUST DIE", "release_year", "1987" ], [ "SWEPT AWAY", "has_genre", "COMEDY" ], [ "SWEPT AWAY", "has_tags", "MADONNA" ], [ "SWEPT AWAY", "starred_actors", "MADONNA" ], [ "TEEN WOLF TOO", "has_genre", "COMEDY" ], [ "TEEN WOLF TOO", "release_year", "1987" ], [ "THE ACCIDENTAL HUSBAND", "directed_by", "GRIFFIN DUNNE" ], [ "THE ACCIDENTAL HUSBAND", "has_genre", "COMEDY" ], [ "THE ALLNIGHTER", "has_genre", "COMEDY" ], [ "THE ALLNIGHTER", "release_year", "1987" ], [ "THE BRAVE LITTLE TOASTER", "has_genre", "COMEDY" ], [ "THE BRAVE LITTLE TOASTER", "release_year", "1987" ], [ "THE FAMILY", "has_genre", "COMEDY" ], [ "THE FAMILY", "release_year", "1987" ], [ "THE HAUNTING", "release_year", "1999" ], [ "THE HAUNTING", "starred_actors", "CLAIRE BLOOM" ], [ "THE MONSTER SQUAD", "has_genre", "COMEDY" ], [ "THE MONSTER SQUAD", "release_year", "1987" ], [ "THE NEXT BEST THING", "has_genre", "COMEDY" ], [ "THE NEXT BEST THING", "has_tags", "MADONNA" ], [ "THE NEXT BEST THING", "starred_actors", "MADONNA" ], [ "THE PICK-UP ARTIST", "has_genre", "COMEDY" ], [ "THE PICK-UP ARTIST", "release_year", "1987" ], [ "THE PRINCESS BRIDE", "has_genre", "COMEDY" ], [ "THE PRINCESS BRIDE", "has_tags", "COMEDY" ], [ "THE PRINCESS BRIDE", "release_year", "1987" ], [ "THE SQUEEZE", "has_genre", "COMEDY" ], [ "THE SQUEEZE", "release_year", "1987" ], [ "THE WITCHES OF EASTWICK", "has_genre", "COMEDY" ], [ "THE WITCHES OF EASTWICK", "release_year", "1987" ], [ "THREE O'CLOCK HIGH", "has_genre", "COMEDY" ], [ "THREE O'CLOCK HIGH", "release_year", "1987" ], [ "THROW MOMMA FROM THE TRAIN", "has_genre", "COMEDY" ], [ "THROW MOMMA FROM THE TRAIN", "has_tags", "COMEDY" ], [ "THROW MOMMA FROM THE TRAIN", "release_year", "1987" ], [ "TIN MEN", "has_genre", "COMEDY" ], [ "TIN MEN", "release_year", "1987" ], [ "TOUGH GUYS DON'T DANCE", "has_genre", "COMEDY" ], [ "TOUGH GUYS DON'T DANCE", "release_year", "1987" ], [ "TRIPPIN'", "has_genre", "COMEDY" ], [ "TRIPPIN'", "release_year", "1999" ], [ "TRIPPIN'", "starred_actors", "DONALD FAISON" ], [ "UPTOWN GIRLS", "has_genre", "COMEDY" ], [ "UPTOWN GIRLS", "starred_actors", "DONALD FAISON" ], [ "WALK LIKE A MAN", "has_genre", "COMEDY" ], [ "WALK LIKE A MAN", "release_year", "1987" ], [ "WHO'S THAT GIRL", "directed_by", "JAMES FOLEY" ], [ "WHO'S THAT GIRL", "has_genre", "COMEDY" ], [ "WHO'S THAT GIRL", "has_tags", "JAMES FOLEY" ], [ "WHO'S THAT GIRL", "has_tags", "MADONNA" ], [ "WHO'S THAT GIRL", "release_year", "1987" ], [ "WHO'S THAT GIRL", "starred_actors", "GRIFFIN DUNNE" ], [ "WHO'S THAT GIRL", "starred_actors", "MADONNA" ], [ "WHO'S THAT GIRL", "written_by", "KEN FINKLEMAN" ], [ "WISH YOU WERE HERE", "has_genre", "COMEDY" ], [ "WISH YOU WERE HERE", "release_year", "1987" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 33908, BARBARA BEDFORD 35148, CLARENCE BROWN 28508, CONQUEST 36066, FANTASY 22582, THE LAST OF THE MOHICANS 13189, THE LOST CONTINENT 29314, TONY BECKLEY 17666, WACLAW GASIOROWSKI src, edge_attr, dst 28508, directed_by, 35148 28508, has_genre, 36066 28508, written_by, 17666 22582, directed_by, 35148 22582, starred_actors, 33908 13189, has_genre, 36066 13189, starred_actors, 29314 Question: How are BARBARA BEDFORD, TONY BECKLEY, and WACLAW GASIOROWSKI related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BARBARA BEDFORD", "TONY BECKLEY", "WACLAW GASIOROWSKI" ], "valid_edges": [ [ "CONQUEST", "directed_by", "CLARENCE BROWN" ], [ "CONQUEST", "has_genre", "FANTASY" ], [ "CONQUEST", "written_by", "WACLAW GASIOROWSKI" ], [ "THE LAST OF THE MOHICANS", "directed_by", "CLARENCE BROWN" ], [ "THE LAST OF THE MOHICANS", "starred_actors", "BARBARA BEDFORD" ], [ "THE LOST CONTINENT", "has_genre", "FANTASY" ], [ "THE LOST CONTINENT", "starred_actors", "TONY BECKLEY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 30113, 101 DALMATIANS 1006, 1996 6094, A CLOCKWORK ORANGE 17822, AMY HOLDEN JONES 14271, BEETHOVEN 14561, BEETHOVEN'S 2ND 20510, BONNIE HUNT 30523, CHEAPER BY THE DOZEN 32379, CHEAPER BY THE DOZEN 2 10509, FAMILY 18521, FLY AWAY HOME 39198, GETTING AWAY WITH MURDER 4798, JINGLE ALL THE WAY 14017, JURASSIC PARK 12949, KAZAAM 6577, SHILOH 9735, SPECIAL EFFECTS 13976, THE ADVENTURES OF PINOCCHIO 14846, THE RICH MAN'S WIFE 6923, THE WHOLE WIDE WORLD 26509, VIOLENCE src, edge_attr, dst 30113, has_genre, 10509 30113, release_year, 1006 6094, has_tags, 14271 6094, has_tags, 26509 14271, has_genre, 10509 14271, has_tags, 20510 14271, has_tags, 10509 14271, starred_actors, 20510 14271, written_by, 17822 14561, has_genre, 10509 14561, has_tags, 20510 14561, starred_actors, 20510 30523, has_genre, 10509 30523, has_tags, 20510 30523, has_tags, 10509 30523, starred_actors, 20510 32379, has_genre, 10509 32379, starred_actors, 20510 18521, has_genre, 10509 18521, release_year, 1006 39198, release_year, 1006 39198, starred_actors, 20510 4798, has_genre, 10509 4798, release_year, 1006 14017, has_tags, 9735 14017, has_tags, 26509 12949, has_genre, 10509 12949, release_year, 1006 6577, has_genre, 10509 6577, release_year, 1006 13976, has_genre, 10509 13976, release_year, 1006 14846, directed_by, 17822 14846, release_year, 1006 14846, written_by, 17822 6923, release_year, 1006 Question: How are BEETHOVEN, SPECIAL EFFECTS, and THE WHOLE WIDE WORLD related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BEETHOVEN", "SPECIAL EFFECTS", "THE WHOLE WIDE WORLD" ], "valid_edges": [ [ "101 DALMATIANS", "has_genre", "FAMILY" ], [ "101 DALMATIANS", "release_year", "1996" ], [ "A CLOCKWORK ORANGE", "has_tags", "BEETHOVEN" ], [ "A CLOCKWORK ORANGE", "has_tags", "VIOLENCE" ], [ "BEETHOVEN", "has_genre", "FAMILY" ], [ "BEETHOVEN", "has_tags", "BONNIE HUNT" ], [ "BEETHOVEN", "has_tags", "FAMILY" ], [ "BEETHOVEN", "starred_actors", "BONNIE HUNT" ], [ "BEETHOVEN", "written_by", "AMY HOLDEN JONES" ], [ "BEETHOVEN'S 2ND", "has_genre", "FAMILY" ], [ "BEETHOVEN'S 2ND", "has_tags", "BONNIE HUNT" ], [ "BEETHOVEN'S 2ND", "starred_actors", "BONNIE HUNT" ], [ "CHEAPER BY THE DOZEN", "has_genre", "FAMILY" ], [ "CHEAPER BY THE DOZEN", "has_tags", "BONNIE HUNT" ], [ "CHEAPER BY THE DOZEN", "has_tags", "FAMILY" ], [ "CHEAPER BY THE DOZEN", "starred_actors", "BONNIE HUNT" ], [ "CHEAPER BY THE DOZEN 2", "has_genre", "FAMILY" ], [ "CHEAPER BY THE DOZEN 2", "starred_actors", "BONNIE HUNT" ], [ "FLY AWAY HOME", "has_genre", "FAMILY" ], [ "FLY AWAY HOME", "release_year", "1996" ], [ "GETTING AWAY WITH MURDER", "release_year", "1996" ], [ "GETTING AWAY WITH MURDER", "starred_actors", "BONNIE HUNT" ], [ "JINGLE ALL THE WAY", "has_genre", "FAMILY" ], [ "JINGLE ALL THE WAY", "release_year", "1996" ], [ "JURASSIC PARK", "has_tags", "SPECIAL EFFECTS" ], [ "JURASSIC PARK", "has_tags", "VIOLENCE" ], [ "KAZAAM", "has_genre", "FAMILY" ], [ "KAZAAM", "release_year", "1996" ], [ "SHILOH", "has_genre", "FAMILY" ], [ "SHILOH", "release_year", "1996" ], [ "THE ADVENTURES OF PINOCCHIO", "has_genre", "FAMILY" ], [ "THE ADVENTURES OF PINOCCHIO", "release_year", "1996" ], [ "THE RICH MAN'S WIFE", "directed_by", "AMY HOLDEN JONES" ], [ "THE RICH MAN'S WIFE", "release_year", "1996" ], [ "THE RICH MAN'S WIFE", "written_by", "AMY HOLDEN JONES" ], [ "THE WHOLE WIDE WORLD", "release_year", "1996" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29145, 10 ITEMS OR LESS 26310, 1947 35845, 2006 21892, 48 SHADES 14242, A FRIEND OF MINE 24039, A GOOD YEAR 8198, A PRAIRIE HOME COMPANION 18514, ACCEPTED 32926, ALIEN AUTOPSY 38447, ALWAYS LEAVE THEM LAUGHING 27024, AMERICAN DREAMZ 23409, AN IDEAL HUSBAND 4963, ANN HARDING 24855, ANOTHER GAY MOVIE 17890, AQUAMARINE 24301, ART SCHOOL CONFIDENTIAL 17133, AS YOU LIKE IT 37155, BACHELOR PARTY VEGAS 36792, BANDIDAS 39257, BARNYARD 34728, BEAUTIFUL OHIO 26356, BEAUTY IN TROUBLE 37161, BEERFEST 38736, BIG MOMMA'S HOUSE 2 5099, BIG NOTHING 31778, BLACK SHEEP 17021, BLIND DATING 26553, BONNEVILLE 36479, BORN TO DANCE 5823, BROTHER BEAR 2 33196, CARS 16659, CASINO ROYALE 7830, CATCH AND RELEASE 18748, CATTLE CALL 11009, CHICKEN RUN 2297, CHRISTMAS EVE 21625, CLERKS II 18016, CLICK 30463, COMEDY 18440, CONFETTI 7685, DATE MOVIE 38345, DECK THE HALLS 29485, DELIRIOUS 3362, DIKKENEK 12012, DON DEFORE 8573, DR. DOLITTLE 3 22658, EMPLOYEE OF THE MONTH 10100, EVERYONE'S HERO 5515, EVIL BONG 8262, FAMILY LAW 13893, FIDO 18217, FIND ME GUILTY 2287, FLUSHED AWAY 40137, FOR YOUR CONSIDERATION 28514, GRANDMA'S BOY 17057, GRAVE DECISIONS 28826, GRAY MATTERS 14375, HIGH SCHOOL MUSICAL 12053, HONEYMOON 15660, HOOT 38589, I DO 16161, I WANT SOMEONE TO EAT CHEESE WITH 10554, I-SEE-YOU.COM 10625, IDIOCRACY 14226, IT HAPPENED ON FIFTH AVENUE 9624, IT'S A BOY GIRL THING 18276, JOHN TUCKER MUST DIE 7986, JUST MY LUCK 26486, KEEPING UP WITH THE STEINS 36745, LAST HOLIDAY 30776, LET'S GO TO PRISON 38412, LIFE WITH FATHER 24376, LITTLE MISS SUNSHINE 34385, LIVE FREE OR DIE 17372, LOL 39979, MADEA'S FAMILY REUNION 27297, MAGIC TOWN 10502, MAN ABOUT TOWN 27801, MAN OF THE YEAR 24324, MATERIAL GIRLS 30166, MONSIEUR VERDOUX 9173, MONSTER HOUSE 26612, MY FAVORITE BRUNETTE 19983, MY SUPER EX-GIRLFRIEND 1268, NACHO LIBRE 3027, NIGHT AT THE MUSEUM 39115, NINA'S HEAVENLY DELIGHTS 13261, OPEN SEASON 24150, OUTSOURCED 17365, OVER THE HEDGE 16124, PENELOPE 2629, PHAT GIRLZ 776, PITER FM 2814, PUCCINI FOR BEGINNERS 31713, ROAD TO RIO 30518, ROMANCE ON THE HIGH SEAS 7011, ROY DEL RUTH 33108, RUNNING SCARED 5766, RUNNING WITH SCISSORS 29696, RV 9228, SCARY MOVIE 4 31315, SCENES OF A SEXUAL NATURE 21609, SCHOOL FOR SCOUNDRELS 24726, SCOOP 26416, SHE'S THE MAN 28126, SHEITAN 3237, SIXTY SIX 38752, SLEEPING DOGS LIE 26930, SLITHER 31073, SLUMMING 10804, SOMETHING IN THE WIND 35507, SONG OF THE THIN MAN 28005, SOUTHLAND TALES 26020, STARTER FOR 10 39786, STICK IT 8998, SWING TIME 38498, TAXIDERMIA 37498, TENACIOUS D IN THE PICK OF DESTINY 23870, THE ANIMAL KINGDOM 15243, THE ART OF CRYING 11415, THE ART OF NEGATIVE THINKING 8318, THE BACHELOR AND THE BOBBY-SOXER 38597, THE BENCHWARMERS 28719, THE BISHOP'S WIFE 21024, THE BOSS OF IT ALL 26285, THE BREAK-UP 36932, THE CAIMAN 3251, THE CURIOSITY OF CHANCE 2102, THE DARWIN AWARDS 22346, THE DEVIL WEARS PRADA 22882, THE DOG PROBLEM 17991, THE EGG AND I 7404, THE EX 16464, THE FOOT FIST WAY 4060, THE GROOMSMEN 15420, THE HISTORY BOYS 26955, THE HOLIDAY 28107, THE LAST KISS 9355, THE MARSH 32781, THE OH IN OHIO 25837, THE PERILS OF PAULINE 21400, THE PINK PANTHER 18162, THE RAVEN 11383, THE SCIENCE OF SLEEP 30746, THE SECRET LIFE OF WALTER MITTY 15558, THE SIN OF HAROLD DIDDLEBOCK 14580, THE TREATMENT 4542, THE VALET 31313, THE WEST POINT STORY 1772, THE WILD 18500, TONY HAYGARTH 12051, UNACCOMPANIED MINORS 36753, VENUS 3778, VICTOR MOORE 31364, WE'RE NOT MARRIED! 20986, WEDDING DAZE 36581, YOU, ME AND DUPREE 14841, ZIEGFELD FOLLIES src, edge_attr, dst 29145, has_genre, 30463 29145, has_tags, 30463 29145, release_year, 35845 21892, has_genre, 30463 21892, release_year, 35845 14242, has_genre, 30463 14242, release_year, 35845 24039, has_genre, 30463 24039, release_year, 35845 8198, has_genre, 30463 8198, release_year, 35845 18514, has_genre, 30463 18514, release_year, 35845 32926, has_genre, 30463 32926, release_year, 35845 38447, directed_by, 7011 38447, has_genre, 30463 27024, has_genre, 30463 27024, has_tags, 30463 27024, release_year, 35845 23409, has_genre, 30463 23409, has_tags, 30463 23409, release_year, 26310 24855, has_genre, 30463 24855, release_year, 35845 17890, has_genre, 30463 17890, release_year, 35845 24301, has_genre, 30463 24301, release_year, 35845 17133, has_genre, 30463 17133, release_year, 35845 37155, has_genre, 30463 37155, release_year, 35845 36792, has_genre, 30463 36792, release_year, 35845 39257, has_genre, 30463 39257, release_year, 35845 34728, has_genre, 30463 34728, release_year, 35845 26356, has_genre, 30463 26356, release_year, 35845 37161, has_genre, 30463 37161, release_year, 35845 38736, has_genre, 30463 38736, release_year, 35845 5099, has_genre, 30463 5099, has_tags, 30463 5099, release_year, 35845 31778, has_genre, 30463 31778, has_tags, 30463 31778, release_year, 35845 17021, has_genre, 30463 17021, release_year, 35845 26553, has_genre, 30463 26553, release_year, 35845 36479, directed_by, 7011 36479, has_genre, 30463 5823, has_genre, 30463 5823, release_year, 35845 33196, has_genre, 30463 33196, has_tags, 30463 33196, release_year, 35845 16659, has_genre, 30463 16659, release_year, 35845 7830, has_genre, 30463 7830, release_year, 35845 18748, has_genre, 30463 18748, release_year, 35845 11009, has_genre, 30463 11009, starred_actors, 18500 2297, has_genre, 30463 2297, release_year, 26310 21625, has_genre, 30463 21625, has_tags, 30463 21625, release_year, 35845 18016, has_genre, 30463 18016, has_tags, 30463 18016, release_year, 35845 18440, has_genre, 30463 18440, release_year, 35845 7685, has_genre, 30463 7685, has_tags, 30463 7685, release_year, 35845 38345, has_genre, 30463 38345, release_year, 35845 29485, has_genre, 30463 29485, release_year, 35845 3362, has_genre, 30463 3362, release_year, 35845 8573, has_genre, 30463 8573, release_year, 35845 22658, has_genre, 30463 22658, has_tags, 30463 22658, release_year, 35845 10100, has_genre, 30463 10100, release_year, 35845 5515, has_genre, 30463 5515, release_year, 35845 8262, has_genre, 30463 8262, release_year, 35845 13893, has_genre, 30463 13893, has_tags, 30463 13893, release_year, 35845 18217, has_genre, 30463 18217, release_year, 35845 2287, has_genre, 30463 2287, release_year, 35845 40137, has_genre, 30463 40137, release_year, 35845 28514, has_genre, 30463 28514, release_year, 35845 17057, has_genre, 30463 17057, release_year, 35845 28826, has_genre, 30463 28826, release_year, 35845 14375, has_genre, 30463 14375, release_year, 35845 12053, has_genre, 30463 12053, release_year, 26310 15660, has_genre, 30463 15660, release_year, 35845 38589, has_genre, 30463 38589, release_year, 35845 16161, has_genre, 30463 16161, release_year, 35845 10554, has_genre, 30463 10554, release_year, 35845 10625, has_genre, 30463 10625, release_year, 35845 14226, directed_by, 7011 14226, has_genre, 30463 14226, has_tags, 7011 14226, release_year, 26310 14226, starred_actors, 4963 14226, starred_actors, 12012 14226, starred_actors, 3778 9624, has_genre, 30463 9624, release_year, 35845 18276, has_genre, 30463 18276, release_year, 35845 7986, has_genre, 30463 7986, release_year, 35845 26486, has_genre, 30463 26486, release_year, 35845 36745, has_genre, 30463 36745, release_year, 35845 30776, has_genre, 30463 30776, release_year, 35845 38412, has_genre, 30463 38412, release_year, 26310 24376, has_genre, 30463 24376, has_tags, 30463 24376, release_year, 35845 34385, has_genre, 30463 34385, release_year, 35845 17372, has_genre, 30463 17372, release_year, 35845 39979, has_genre, 30463 39979, release_year, 35845 27297, has_genre, 30463 27297, release_year, 26310 10502, has_genre, 30463 10502, release_year, 35845 27801, has_genre, 30463 27801, has_tags, 30463 27801, release_year, 35845 24324, has_genre, 30463 24324, release_year, 35845 30166, has_genre, 30463 30166, release_year, 26310 9173, has_genre, 30463 9173, release_year, 35845 26612, has_genre, 30463 26612, release_year, 26310 19983, has_genre, 30463 19983, release_year, 35845 1268, has_genre, 30463 1268, has_tags, 30463 1268, release_year, 35845 3027, has_genre, 30463 3027, release_year, 35845 39115, has_genre, 30463 39115, release_year, 35845 13261, has_genre, 30463 13261, has_tags, 30463 13261, release_year, 35845 24150, has_genre, 30463 24150, has_tags, 30463 24150, release_year, 35845 17365, has_genre, 30463 17365, release_year, 35845 16124, has_genre, 30463 16124, release_year, 35845 2629, has_genre, 30463 2629, release_year, 35845 776, has_genre, 30463 776, release_year, 35845 2814, has_genre, 30463 2814, release_year, 35845 31713, has_genre, 30463 31713, release_year, 26310 30518, has_genre, 30463 30518, starred_actors, 12012 33108, has_genre, 30463 33108, release_year, 35845 5766, has_genre, 30463 5766, release_year, 35845 29696, has_genre, 30463 29696, has_tags, 30463 29696, release_year, 35845 9228, has_genre, 30463 9228, release_year, 35845 31315, has_genre, 30463 31315, release_year, 35845 21609, has_genre, 30463 21609, has_tags, 30463 21609, release_year, 35845 24726, has_genre, 30463 24726, release_year, 35845 26416, has_genre, 30463 26416, release_year, 35845 28126, has_genre, 30463 28126, release_year, 35845 3237, has_genre, 30463 3237, release_year, 35845 38752, has_genre, 30463 38752, release_year, 35845 26930, has_genre, 30463 26930, has_tags, 30463 26930, release_year, 35845 31073, has_genre, 30463 31073, release_year, 35845 10804, has_genre, 30463 10804, release_year, 26310 35507, has_genre, 30463 35507, release_year, 26310 28005, has_genre, 30463 28005, has_tags, 30463 28005, release_year, 35845 26020, has_genre, 30463 26020, has_tags, 30463 26020, release_year, 35845 39786, has_genre, 30463 39786, release_year, 35845 8998, has_genre, 30463 8998, starred_actors, 3778 38498, has_genre, 30463 38498, release_year, 35845 37498, has_genre, 30463 37498, has_tags, 30463 37498, release_year, 35845 23870, has_genre, 30463 23870, starred_actors, 4963 15243, has_genre, 30463 15243, release_year, 35845 11415, has_genre, 30463 11415, release_year, 35845 8318, has_genre, 30463 8318, release_year, 26310 38597, has_genre, 30463 38597, release_year, 35845 28719, has_genre, 30463 28719, release_year, 26310 21024, has_genre, 30463 21024, release_year, 35845 26285, has_genre, 30463 26285, has_tags, 30463 26285, release_year, 35845 36932, has_genre, 30463 36932, release_year, 35845 3251, has_genre, 30463 3251, release_year, 35845 2102, has_genre, 30463 2102, release_year, 35845 22346, has_genre, 30463 22346, has_tags, 30463 22346, release_year, 35845 22882, has_genre, 30463 22882, release_year, 35845 17991, has_genre, 30463 17991, release_year, 26310 7404, has_genre, 30463 7404, release_year, 35845 16464, has_genre, 30463 16464, release_year, 35845 4060, has_genre, 30463 4060, release_year, 35845 15420, has_genre, 30463 15420, release_year, 35845 26955, has_genre, 30463 26955, release_year, 35845 28107, has_genre, 30463 28107, release_year, 35845 9355, release_year, 35845 32781, has_genre, 30463 32781, release_year, 35845 25837, has_genre, 30463 25837, release_year, 26310 21400, has_genre, 30463 21400, release_year, 35845 18162, has_genre, 30463 18162, release_year, 35845 11383, has_genre, 30463 11383, release_year, 35845 30746, has_genre, 30463 30746, release_year, 26310 15558, has_genre, 30463 15558, release_year, 26310 14580, has_genre, 30463 14580, release_year, 35845 4542, has_genre, 30463 4542, has_tags, 30463 4542, release_year, 35845 31313, directed_by, 7011 31313, has_genre, 30463 1772, has_genre, 30463 1772, release_year, 35845 12051, has_genre, 30463 12051, release_year, 35845 36753, has_genre, 30463 36753, release_year, 35845 31364, has_genre, 30463 31364, starred_actors, 3778 20986, has_genre, 30463 20986, release_year, 35845 36581, has_genre, 30463 36581, release_year, 35845 14841, directed_by, 7011 14841, has_genre, 30463 Question: For what reason are IT HAPPENED ON FIFTH AVENUE, THE MARSH, and TONY HAYGARTH associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "IT HAPPENED ON FIFTH AVENUE", "THE MARSH", "TONY HAYGARTH" ], "valid_edges": [ [ "10 ITEMS OR LESS", "has_genre", "COMEDY" ], [ "10 ITEMS OR LESS", "has_tags", "COMEDY" ], [ "10 ITEMS OR LESS", "release_year", "2006" ], [ "48 SHADES", "has_genre", "COMEDY" ], [ "48 SHADES", "release_year", "2006" ], [ "A FRIEND OF MINE", "has_genre", "COMEDY" ], [ "A FRIEND OF MINE", "release_year", "2006" ], [ "A GOOD YEAR", "has_genre", "COMEDY" ], [ "A GOOD YEAR", "release_year", "2006" ], [ "A PRAIRIE HOME COMPANION", "has_genre", "COMEDY" ], [ "A PRAIRIE HOME COMPANION", "release_year", "2006" ], [ "ACCEPTED", "has_genre", "COMEDY" ], [ "ACCEPTED", "release_year", "2006" ], [ "ALIEN AUTOPSY", "has_genre", "COMEDY" ], [ "ALIEN AUTOPSY", "release_year", "2006" ], [ "ALWAYS LEAVE THEM LAUGHING", "directed_by", "ROY DEL RUTH" ], [ "ALWAYS LEAVE THEM LAUGHING", "has_genre", "COMEDY" ], [ "AMERICAN DREAMZ", "has_genre", "COMEDY" ], [ "AMERICAN DREAMZ", "has_tags", "COMEDY" ], [ "AMERICAN DREAMZ", "release_year", "2006" ], [ "AN IDEAL HUSBAND", "has_genre", "COMEDY" ], [ "AN IDEAL HUSBAND", "has_tags", "COMEDY" ], [ "AN IDEAL HUSBAND", "release_year", "1947" ], [ "ANOTHER GAY MOVIE", "has_genre", "COMEDY" ], [ "ANOTHER GAY MOVIE", "release_year", "2006" ], [ "AQUAMARINE", "has_genre", "COMEDY" ], [ "AQUAMARINE", "release_year", "2006" ], [ "ART SCHOOL CONFIDENTIAL", "has_genre", "COMEDY" ], [ "ART SCHOOL CONFIDENTIAL", "release_year", "2006" ], [ "AS YOU LIKE IT", "has_genre", "COMEDY" ], [ "AS YOU LIKE IT", "release_year", "2006" ], [ "BACHELOR PARTY VEGAS", "has_genre", "COMEDY" ], [ "BACHELOR PARTY VEGAS", "release_year", "2006" ], [ "BANDIDAS", "has_genre", "COMEDY" ], [ "BANDIDAS", "release_year", "2006" ], [ "BARNYARD", "has_genre", "COMEDY" ], [ "BARNYARD", "release_year", "2006" ], [ "BEAUTIFUL OHIO", "has_genre", "COMEDY" ], [ "BEAUTIFUL OHIO", "release_year", "2006" ], [ "BEAUTY IN TROUBLE", "has_genre", "COMEDY" ], [ "BEAUTY IN TROUBLE", "release_year", "2006" ], [ "BEERFEST", "has_genre", "COMEDY" ], [ "BEERFEST", "release_year", "2006" ], [ "BIG MOMMA'S HOUSE 2", "has_genre", "COMEDY" ], [ "BIG MOMMA'S HOUSE 2", "release_year", "2006" ], [ "BIG NOTHING", "has_genre", "COMEDY" ], [ "BIG NOTHING", "has_tags", "COMEDY" ], [ "BIG NOTHING", "release_year", "2006" ], [ "BLACK SHEEP", "has_genre", "COMEDY" ], [ "BLACK SHEEP", "has_tags", "COMEDY" ], [ "BLACK SHEEP", "release_year", "2006" ], [ "BLIND DATING", "has_genre", "COMEDY" ], [ "BLIND DATING", "release_year", "2006" ], [ "BONNEVILLE", "has_genre", "COMEDY" ], [ "BONNEVILLE", "release_year", "2006" ], [ "BORN TO DANCE", "directed_by", "ROY DEL RUTH" ], [ "BORN TO DANCE", "has_genre", "COMEDY" ], [ "BROTHER BEAR 2", "has_genre", "COMEDY" ], [ "BROTHER BEAR 2", "release_year", "2006" ], [ "CARS", "has_genre", "COMEDY" ], [ "CARS", "has_tags", "COMEDY" ], [ "CARS", "release_year", "2006" ], [ "CASINO ROYALE", "has_genre", "COMEDY" ], [ "CASINO ROYALE", "release_year", "2006" ], [ "CATCH AND RELEASE", "has_genre", "COMEDY" ], [ "CATCH AND RELEASE", "release_year", "2006" ], [ "CATTLE CALL", "has_genre", "COMEDY" ], [ "CATTLE CALL", "release_year", "2006" ], [ "CHICKEN RUN", "has_genre", "COMEDY" ], [ "CHICKEN RUN", "starred_actors", "TONY HAYGARTH" ], [ "CHRISTMAS EVE", "has_genre", "COMEDY" ], [ "CHRISTMAS EVE", "release_year", "1947" ], [ "CLERKS II", "has_genre", "COMEDY" ], [ "CLERKS II", "has_tags", "COMEDY" ], [ "CLERKS II", "release_year", "2006" ], [ "CLICK", "has_genre", "COMEDY" ], [ "CLICK", "has_tags", "COMEDY" ], [ "CLICK", "release_year", "2006" ], [ "CONFETTI", "has_genre", "COMEDY" ], [ "CONFETTI", "release_year", "2006" ], [ "DATE MOVIE", "has_genre", "COMEDY" ], [ "DATE MOVIE", "has_tags", "COMEDY" ], [ "DATE MOVIE", "release_year", "2006" ], [ "DECK THE HALLS", "has_genre", "COMEDY" ], [ "DECK THE HALLS", "release_year", "2006" ], [ "DELIRIOUS", "has_genre", "COMEDY" ], [ "DELIRIOUS", "release_year", "2006" ], [ "DIKKENEK", "has_genre", "COMEDY" ], [ "DIKKENEK", "release_year", "2006" ], [ "DR. DOLITTLE 3", "has_genre", "COMEDY" ], [ "DR. DOLITTLE 3", "release_year", "2006" ], [ "EMPLOYEE OF THE MONTH", "has_genre", "COMEDY" ], [ "EMPLOYEE OF THE MONTH", "has_tags", "COMEDY" ], [ "EMPLOYEE OF THE MONTH", "release_year", "2006" ], [ "EVERYONE'S HERO", "has_genre", "COMEDY" ], [ "EVERYONE'S HERO", "release_year", "2006" ], [ "EVIL BONG", "has_genre", "COMEDY" ], [ "EVIL BONG", "release_year", "2006" ], [ "FAMILY LAW", "has_genre", "COMEDY" ], [ "FAMILY LAW", "release_year", "2006" ], [ "FIDO", "has_genre", "COMEDY" ], [ "FIDO", "has_tags", "COMEDY" ], [ "FIDO", "release_year", "2006" ], [ "FIND ME GUILTY", "has_genre", "COMEDY" ], [ "FIND ME GUILTY", "release_year", "2006" ], [ "FLUSHED AWAY", "has_genre", "COMEDY" ], [ "FLUSHED AWAY", "release_year", "2006" ], [ "FOR YOUR CONSIDERATION", "has_genre", "COMEDY" ], [ "FOR YOUR CONSIDERATION", "release_year", "2006" ], [ "GRANDMA'S BOY", "has_genre", "COMEDY" ], [ "GRANDMA'S BOY", "release_year", "2006" ], [ "GRAVE DECISIONS", "has_genre", "COMEDY" ], [ "GRAVE DECISIONS", "release_year", "2006" ], [ "GRAY MATTERS", "has_genre", "COMEDY" ], [ "GRAY MATTERS", "release_year", "2006" ], [ "HIGH SCHOOL MUSICAL", "has_genre", "COMEDY" ], [ "HIGH SCHOOL MUSICAL", "release_year", "2006" ], [ "HONEYMOON", "has_genre", "COMEDY" ], [ "HONEYMOON", "release_year", "1947" ], [ "HOOT", "has_genre", "COMEDY" ], [ "HOOT", "release_year", "2006" ], [ "I DO", "has_genre", "COMEDY" ], [ "I DO", "release_year", "2006" ], [ "I WANT SOMEONE TO EAT CHEESE WITH", "has_genre", "COMEDY" ], [ "I WANT SOMEONE TO EAT CHEESE WITH", "release_year", "2006" ], [ "I-SEE-YOU.COM", "has_genre", "COMEDY" ], [ "I-SEE-YOU.COM", "release_year", "2006" ], [ "IDIOCRACY", "has_genre", "COMEDY" ], [ "IDIOCRACY", "release_year", "2006" ], [ "IT HAPPENED ON FIFTH AVENUE", "directed_by", "ROY DEL RUTH" ], [ "IT HAPPENED ON FIFTH AVENUE", "has_genre", "COMEDY" ], [ "IT HAPPENED ON FIFTH AVENUE", "has_tags", "ROY DEL RUTH" ], [ "IT HAPPENED ON FIFTH AVENUE", "release_year", "1947" ], [ "IT HAPPENED ON FIFTH AVENUE", "starred_actors", "ANN HARDING" ], [ "IT HAPPENED ON FIFTH AVENUE", "starred_actors", "DON DEFORE" ], [ "IT HAPPENED ON FIFTH AVENUE", "starred_actors", "VICTOR MOORE" ], [ "IT'S A BOY GIRL THING", "has_genre", "COMEDY" ], [ "IT'S A BOY GIRL THING", "release_year", "2006" ], [ "JOHN TUCKER MUST DIE", "has_genre", "COMEDY" ], [ "JOHN TUCKER MUST DIE", "release_year", "2006" ], [ "JUST MY LUCK", "has_genre", "COMEDY" ], [ "JUST MY LUCK", "release_year", "2006" ], [ "KEEPING UP WITH THE STEINS", "has_genre", "COMEDY" ], [ "KEEPING UP WITH THE STEINS", "release_year", "2006" ], [ "LAST HOLIDAY", "has_genre", "COMEDY" ], [ "LAST HOLIDAY", "release_year", "2006" ], [ "LET'S GO TO PRISON", "has_genre", "COMEDY" ], [ "LET'S GO TO PRISON", "release_year", "2006" ], [ "LIFE WITH FATHER", "has_genre", "COMEDY" ], [ "LIFE WITH FATHER", "release_year", "1947" ], [ "LITTLE MISS SUNSHINE", "has_genre", "COMEDY" ], [ "LITTLE MISS SUNSHINE", "has_tags", "COMEDY" ], [ "LITTLE MISS SUNSHINE", "release_year", "2006" ], [ "LIVE FREE OR DIE", "has_genre", "COMEDY" ], [ "LIVE FREE OR DIE", "release_year", "2006" ], [ "LOL", "has_genre", "COMEDY" ], [ "LOL", "release_year", "2006" ], [ "MADEA'S FAMILY REUNION", "has_genre", "COMEDY" ], [ "MADEA'S FAMILY REUNION", "release_year", "2006" ], [ "MAGIC TOWN", "has_genre", "COMEDY" ], [ "MAGIC TOWN", "release_year", "1947" ], [ "MAN ABOUT TOWN", "has_genre", "COMEDY" ], [ "MAN ABOUT TOWN", "release_year", "2006" ], [ "MAN OF THE YEAR", "has_genre", "COMEDY" ], [ "MAN OF THE YEAR", "has_tags", "COMEDY" ], [ "MAN OF THE YEAR", "release_year", "2006" ], [ "MATERIAL GIRLS", "has_genre", "COMEDY" ], [ "MATERIAL GIRLS", "release_year", "2006" ], [ "MONSIEUR VERDOUX", "has_genre", "COMEDY" ], [ "MONSIEUR VERDOUX", "release_year", "1947" ], [ "MONSTER HOUSE", "has_genre", "COMEDY" ], [ "MONSTER HOUSE", "release_year", "2006" ], [ "MY FAVORITE BRUNETTE", "has_genre", "COMEDY" ], [ "MY FAVORITE BRUNETTE", "release_year", "1947" ], [ "MY SUPER EX-GIRLFRIEND", "has_genre", "COMEDY" ], [ "MY SUPER EX-GIRLFRIEND", "release_year", "2006" ], [ "NACHO LIBRE", "has_genre", "COMEDY" ], [ "NACHO LIBRE", "has_tags", "COMEDY" ], [ "NACHO LIBRE", "release_year", "2006" ], [ "NIGHT AT THE MUSEUM", "has_genre", "COMEDY" ], [ "NIGHT AT THE MUSEUM", "release_year", "2006" ], [ "NINA'S HEAVENLY DELIGHTS", "has_genre", "COMEDY" ], [ "NINA'S HEAVENLY DELIGHTS", "release_year", "2006" ], [ "OPEN SEASON", "has_genre", "COMEDY" ], [ "OPEN SEASON", "has_tags", "COMEDY" ], [ "OPEN SEASON", "release_year", "2006" ], [ "OUTSOURCED", "has_genre", "COMEDY" ], [ "OUTSOURCED", "has_tags", "COMEDY" ], [ "OUTSOURCED", "release_year", "2006" ], [ "OVER THE HEDGE", "has_genre", "COMEDY" ], [ "OVER THE HEDGE", "release_year", "2006" ], [ "PENELOPE", "has_genre", "COMEDY" ], [ "PENELOPE", "release_year", "2006" ], [ "PHAT GIRLZ", "has_genre", "COMEDY" ], [ "PHAT GIRLZ", "release_year", "2006" ], [ "PITER FM", "has_genre", "COMEDY" ], [ "PITER FM", "release_year", "2006" ], [ "PUCCINI FOR BEGINNERS", "has_genre", "COMEDY" ], [ "PUCCINI FOR BEGINNERS", "release_year", "2006" ], [ "ROAD TO RIO", "has_genre", "COMEDY" ], [ "ROAD TO RIO", "release_year", "1947" ], [ "ROMANCE ON THE HIGH SEAS", "has_genre", "COMEDY" ], [ "ROMANCE ON THE HIGH SEAS", "starred_actors", "DON DEFORE" ], [ "RUNNING SCARED", "has_genre", "COMEDY" ], [ "RUNNING SCARED", "release_year", "2006" ], [ "RUNNING WITH SCISSORS", "has_genre", "COMEDY" ], [ "RUNNING WITH SCISSORS", "release_year", "2006" ], [ "RV", "has_genre", "COMEDY" ], [ "RV", "has_tags", "COMEDY" ], [ "RV", "release_year", "2006" ], [ "SCARY MOVIE 4", "has_genre", "COMEDY" ], [ "SCARY MOVIE 4", "release_year", "2006" ], [ "SCENES OF A SEXUAL NATURE", "has_genre", "COMEDY" ], [ "SCENES OF A SEXUAL NATURE", "release_year", "2006" ], [ "SCHOOL FOR SCOUNDRELS", "has_genre", "COMEDY" ], [ "SCHOOL FOR SCOUNDRELS", "has_tags", "COMEDY" ], [ "SCHOOL FOR SCOUNDRELS", "release_year", "2006" ], [ "SCOOP", "has_genre", "COMEDY" ], [ "SCOOP", "release_year", "2006" ], [ "SHE'S THE MAN", "has_genre", "COMEDY" ], [ "SHE'S THE MAN", "release_year", "2006" ], [ "SHEITAN", "has_genre", "COMEDY" ], [ "SHEITAN", "release_year", "2006" ], [ "SIXTY SIX", "has_genre", "COMEDY" ], [ "SIXTY SIX", "release_year", "2006" ], [ "SLEEPING DOGS LIE", "has_genre", "COMEDY" ], [ "SLEEPING DOGS LIE", "release_year", "2006" ], [ "SLITHER", "has_genre", "COMEDY" ], [ "SLITHER", "has_tags", "COMEDY" ], [ "SLITHER", "release_year", "2006" ], [ "SLUMMING", "has_genre", "COMEDY" ], [ "SLUMMING", "release_year", "2006" ], [ "SOMETHING IN THE WIND", "has_genre", "COMEDY" ], [ "SOMETHING IN THE WIND", "release_year", "1947" ], [ "SONG OF THE THIN MAN", "has_genre", "COMEDY" ], [ "SONG OF THE THIN MAN", "release_year", "1947" ], [ "SOUTHLAND TALES", "has_genre", "COMEDY" ], [ "SOUTHLAND TALES", "has_tags", "COMEDY" ], [ "SOUTHLAND TALES", "release_year", "2006" ], [ "STARTER FOR 10", "has_genre", "COMEDY" ], [ "STARTER FOR 10", "has_tags", "COMEDY" ], [ "STARTER FOR 10", "release_year", "2006" ], [ "STICK IT", "has_genre", "COMEDY" ], [ "STICK IT", "release_year", "2006" ], [ "SWING TIME", "has_genre", "COMEDY" ], [ "SWING TIME", "starred_actors", "VICTOR MOORE" ], [ "TAXIDERMIA", "has_genre", "COMEDY" ], [ "TAXIDERMIA", "release_year", "2006" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "has_genre", "COMEDY" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "has_tags", "COMEDY" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "release_year", "2006" ], [ "THE ANIMAL KINGDOM", "has_genre", "COMEDY" ], [ "THE ANIMAL KINGDOM", "starred_actors", "ANN HARDING" ], [ "THE ART OF CRYING", "has_genre", "COMEDY" ], [ "THE ART OF CRYING", "release_year", "2006" ], [ "THE ART OF NEGATIVE THINKING", "has_genre", "COMEDY" ], [ "THE ART OF NEGATIVE THINKING", "release_year", "2006" ], [ "THE BACHELOR AND THE BOBBY-SOXER", "has_genre", "COMEDY" ], [ "THE BACHELOR AND THE BOBBY-SOXER", "release_year", "1947" ], [ "THE BENCHWARMERS", "has_genre", "COMEDY" ], [ "THE BENCHWARMERS", "release_year", "2006" ], [ "THE BISHOP'S WIFE", "has_genre", "COMEDY" ], [ "THE BISHOP'S WIFE", "release_year", "1947" ], [ "THE BOSS OF IT ALL", "has_genre", "COMEDY" ], [ "THE BOSS OF IT ALL", "release_year", "2006" ], [ "THE BREAK-UP", "has_genre", "COMEDY" ], [ "THE BREAK-UP", "has_tags", "COMEDY" ], [ "THE BREAK-UP", "release_year", "2006" ], [ "THE CAIMAN", "has_genre", "COMEDY" ], [ "THE CAIMAN", "release_year", "2006" ], [ "THE CURIOSITY OF CHANCE", "has_genre", "COMEDY" ], [ "THE CURIOSITY OF CHANCE", "release_year", "2006" ], [ "THE DARWIN AWARDS", "has_genre", "COMEDY" ], [ "THE DARWIN AWARDS", "release_year", "2006" ], [ "THE DEVIL WEARS PRADA", "has_genre", "COMEDY" ], [ "THE DEVIL WEARS PRADA", "has_tags", "COMEDY" ], [ "THE DEVIL WEARS PRADA", "release_year", "2006" ], [ "THE DOG PROBLEM", "has_genre", "COMEDY" ], [ "THE DOG PROBLEM", "release_year", "2006" ], [ "THE EGG AND I", "has_genre", "COMEDY" ], [ "THE EGG AND I", "release_year", "1947" ], [ "THE EX", "has_genre", "COMEDY" ], [ "THE EX", "release_year", "2006" ], [ "THE FOOT FIST WAY", "has_genre", "COMEDY" ], [ "THE FOOT FIST WAY", "release_year", "2006" ], [ "THE GROOMSMEN", "has_genre", "COMEDY" ], [ "THE GROOMSMEN", "release_year", "2006" ], [ "THE HISTORY BOYS", "has_genre", "COMEDY" ], [ "THE HISTORY BOYS", "release_year", "2006" ], [ "THE HOLIDAY", "has_genre", "COMEDY" ], [ "THE HOLIDAY", "release_year", "2006" ], [ "THE LAST KISS", "has_genre", "COMEDY" ], [ "THE LAST KISS", "release_year", "2006" ], [ "THE MARSH", "release_year", "2006" ], [ "THE OH IN OHIO", "has_genre", "COMEDY" ], [ "THE OH IN OHIO", "release_year", "2006" ], [ "THE PERILS OF PAULINE", "has_genre", "COMEDY" ], [ "THE PERILS OF PAULINE", "release_year", "1947" ], [ "THE PINK PANTHER", "has_genre", "COMEDY" ], [ "THE PINK PANTHER", "release_year", "2006" ], [ "THE RAVEN", "has_genre", "COMEDY" ], [ "THE RAVEN", "release_year", "2006" ], [ "THE SCIENCE OF SLEEP", "has_genre", "COMEDY" ], [ "THE SCIENCE OF SLEEP", "release_year", "2006" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "COMEDY" ], [ "THE SECRET LIFE OF WALTER MITTY", "release_year", "1947" ], [ "THE SIN OF HAROLD DIDDLEBOCK", "has_genre", "COMEDY" ], [ "THE SIN OF HAROLD DIDDLEBOCK", "release_year", "1947" ], [ "THE TREATMENT", "has_genre", "COMEDY" ], [ "THE TREATMENT", "release_year", "2006" ], [ "THE VALET", "has_genre", "COMEDY" ], [ "THE VALET", "has_tags", "COMEDY" ], [ "THE VALET", "release_year", "2006" ], [ "THE WEST POINT STORY", "directed_by", "ROY DEL RUTH" ], [ "THE WEST POINT STORY", "has_genre", "COMEDY" ], [ "THE WILD", "has_genre", "COMEDY" ], [ "THE WILD", "release_year", "2006" ], [ "UNACCOMPANIED MINORS", "has_genre", "COMEDY" ], [ "UNACCOMPANIED MINORS", "release_year", "2006" ], [ "VENUS", "has_genre", "COMEDY" ], [ "VENUS", "release_year", "2006" ], [ "WE'RE NOT MARRIED!", "has_genre", "COMEDY" ], [ "WE'RE NOT MARRIED!", "starred_actors", "VICTOR MOORE" ], [ "WEDDING DAZE", "has_genre", "COMEDY" ], [ "WEDDING DAZE", "release_year", "2006" ], [ "YOU, ME AND DUPREE", "has_genre", "COMEDY" ], [ "YOU, ME AND DUPREE", "release_year", "2006" ], [ "ZIEGFELD FOLLIES", "directed_by", "ROY DEL RUTH" ], [ "ZIEGFELD FOLLIES", "has_genre", "COMEDY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36096, CARROLL O'CONNOR 30463, COMEDY 16632, DOCTORS' WIVES 36212, DRAMA 6012, FRENCH 7569, IN THE BEGINNING 26924, JEAN DUJARDIN 1372, RETURN TO ME 39795, THE ARTIST 4632, XAVIER GIANNOLI src, edge_attr, dst 16632, has_genre, 36212 16632, starred_actors, 36096 7569, directed_by, 4632 7569, has_genre, 36212 7569, in_language, 6012 7569, written_by, 4632 1372, has_genre, 30463 1372, has_genre, 36212 1372, starred_actors, 36096 39795, has_genre, 30463 39795, has_genre, 36212 39795, has_tags, 36212 39795, has_tags, 6012 39795, has_tags, 26924 39795, in_language, 6012 39795, starred_actors, 26924 Question: For what reason are CARROLL O'CONNOR, JEAN DUJARDIN, and XAVIER GIANNOLI associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CARROLL O'CONNOR", "JEAN DUJARDIN", "XAVIER GIANNOLI" ], "valid_edges": [ [ "DOCTORS' WIVES", "has_genre", "DRAMA" ], [ "DOCTORS' WIVES", "starred_actors", "CARROLL O'CONNOR" ], [ "IN THE BEGINNING", "directed_by", "XAVIER GIANNOLI" ], [ "IN THE BEGINNING", "has_genre", "DRAMA" ], [ "IN THE BEGINNING", "in_language", "FRENCH" ], [ "IN THE BEGINNING", "written_by", "XAVIER GIANNOLI" ], [ "RETURN TO ME", "has_genre", "COMEDY" ], [ "RETURN TO ME", "has_genre", "DRAMA" ], [ "RETURN TO ME", "starred_actors", "CARROLL O'CONNOR" ], [ "THE ARTIST", "has_genre", "COMEDY" ], [ "THE ARTIST", "has_genre", "DRAMA" ], [ "THE ARTIST", "has_tags", "DRAMA" ], [ "THE ARTIST", "has_tags", "FRENCH" ], [ "THE ARTIST", "has_tags", "JEAN DUJARDIN" ], [ "THE ARTIST", "in_language", "FRENCH" ], [ "THE ARTIST", "starred_actors", "JEAN DUJARDIN" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 11953, ALAN JOHNSON 30463, COMEDY 30164, THE CLOSET 17571, THE INTERNSHIP 3640, TO BE OR NOT TO BE src, edge_attr, dst 30164, has_genre, 30463 30164, has_tags, 30463 17571, has_genre, 30463 3640, directed_by, 11953 3640, has_genre, 30463 3640, has_tags, 30463 Question: In what context are ALAN JOHNSON, THE CLOSET, and THE INTERNSHIP connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ALAN JOHNSON", "THE CLOSET", "THE INTERNSHIP" ], "valid_edges": [ [ "THE CLOSET", "has_genre", "COMEDY" ], [ "THE CLOSET", "has_tags", "COMEDY" ], [ "THE INTERNSHIP", "has_genre", "COMEDY" ], [ "TO BE OR NOT TO BE", "directed_by", "ALAN JOHNSON" ], [ "TO BE OR NOT TO BE", "has_genre", "COMEDY" ], [ "TO BE OR NOT TO BE", "has_tags", "COMEDY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 658, 2012 15907, CHINA 274, COCKNEYS VS ZOMBIES 8585, DEATH BY CHINA 4709, GREAT EXPECTATIONS 36, JAVIER BARDEM 7566, KAHAANI 17319, LONDON 19118, MUSEUM HOURS 3339, MY BROTHER THE DEVIL 38131, PARAMBRATA CHATTERJEE 29281, PLOT 20985, RALPH FIENNES 20187, SKYFALL 16103, THE AVENGERS 22733, THE DARK KNIGHT RISES 9918, TO THE WONDER 23853, WRATH OF THE TITANS src, edge_attr, dst 274, has_tags, 17319 274, release_year, 658 8585, has_tags, 15907 8585, release_year, 658 4709, release_year, 658 4709, starred_actors, 20985 7566, release_year, 658 7566, starred_actors, 38131 19118, release_year, 658 3339, has_tags, 17319 3339, release_year, 658 20187, has_tags, 15907 20187, has_tags, 36 20187, has_tags, 17319 20187, has_tags, 29281 20187, has_tags, 20985 20187, release_year, 658 20187, starred_actors, 36 20187, starred_actors, 20985 16103, has_tags, 20985 16103, release_year, 658 16103, starred_actors, 20985 22733, has_tags, 29281 22733, release_year, 658 9918, release_year, 658 9918, starred_actors, 36 23853, release_year, 658 23853, starred_actors, 20985 Question: In what context are MUSEUM HOURS, PARAMBRATA CHATTERJEE, and SKYFALL connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "MUSEUM HOURS", "PARAMBRATA CHATTERJEE", "SKYFALL" ], "valid_edges": [ [ "COCKNEYS VS ZOMBIES", "has_tags", "LONDON" ], [ "COCKNEYS VS ZOMBIES", "release_year", "2012" ], [ "DEATH BY CHINA", "has_tags", "CHINA" ], [ "DEATH BY CHINA", "release_year", "2012" ], [ "GREAT EXPECTATIONS", "release_year", "2012" ], [ "GREAT EXPECTATIONS", "starred_actors", "RALPH FIENNES" ], [ "KAHAANI", "release_year", "2012" ], [ "KAHAANI", "starred_actors", "PARAMBRATA CHATTERJEE" ], [ "MUSEUM HOURS", "release_year", "2012" ], [ "MY BROTHER THE DEVIL", "has_tags", "LONDON" ], [ "MY BROTHER THE DEVIL", "release_year", "2012" ], [ "SKYFALL", "has_tags", "CHINA" ], [ "SKYFALL", "has_tags", "JAVIER BARDEM" ], [ "SKYFALL", "has_tags", "LONDON" ], [ "SKYFALL", "has_tags", "PLOT" ], [ "SKYFALL", "has_tags", "RALPH FIENNES" ], [ "SKYFALL", "release_year", "2012" ], [ "SKYFALL", "starred_actors", "JAVIER BARDEM" ], [ "SKYFALL", "starred_actors", "RALPH FIENNES" ], [ "THE AVENGERS", "has_tags", "RALPH FIENNES" ], [ "THE AVENGERS", "release_year", "2012" ], [ "THE AVENGERS", "starred_actors", "RALPH FIENNES" ], [ "THE DARK KNIGHT RISES", "has_tags", "PLOT" ], [ "THE DARK KNIGHT RISES", "release_year", "2012" ], [ "TO THE WONDER", "release_year", "2012" ], [ "TO THE WONDER", "starred_actors", "JAVIER BARDEM" ], [ "WRATH OF THE TITANS", "release_year", "2012" ], [ "WRATH OF THE TITANS", "starred_actors", "RALPH FIENNES" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26619, ADELAIDE KANE 11475, ALEXANDER NEVSKY 5870, HORROR 37146, MAGIC MAN 13937, RHIAN RAMOS 6427, THE PURGE 15562, THE ROAD 24811, THRILLER src, edge_attr, dst 37146, has_genre, 24811 37146, starred_actors, 11475 6427, has_genre, 5870 6427, has_genre, 24811 6427, starred_actors, 26619 15562, has_genre, 5870 15562, starred_actors, 13937 Question: For what reason are ADELAIDE KANE, ALEXANDER NEVSKY, and RHIAN RAMOS associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ADELAIDE KANE", "ALEXANDER NEVSKY", "RHIAN RAMOS" ], "valid_edges": [ [ "MAGIC MAN", "has_genre", "THRILLER" ], [ "MAGIC MAN", "starred_actors", "ALEXANDER NEVSKY" ], [ "THE PURGE", "has_genre", "HORROR" ], [ "THE PURGE", "has_genre", "THRILLER" ], [ "THE PURGE", "starred_actors", "ADELAIDE KANE" ], [ "THE ROAD", "has_genre", "HORROR" ], [ "THE ROAD", "starred_actors", "RHIAN RAMOS" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1567, 1954 7841, 1987 12954, BEAR'S KISS 10218, BLACK WIDOW 35452, BOPE 30265, BRAZIL 39480, CHARLTON HESTON 34528, DARK CITY 31254, ELITE SQUAD 36066, FANTASY 37039, ORIGINAL 27643, PLANET OF THE APES 8379, ROMANCE 7394, SOME KIND OF WONDERFUL 6260, SPIRITED AWAY 19351, THE COUNT OF MONTE CRISTO 27995, THE FAR COUNTRY 36977, THE GIRL WHO LEAPT THROUGH TIME 29048, THE NAKED JUNGLE 29641, THE PRINCESS BRIDE 28776, THE WIZARD OF OZ src, edge_attr, dst 12954, has_genre, 36066 12954, has_genre, 8379 10218, release_year, 1567 10218, release_year, 7841 30265, has_tags, 36066 34528, has_tags, 37039 34528, starred_actors, 39480 31254, has_tags, 35452 31254, has_tags, 30265 27643, has_tags, 39480 27643, has_tags, 37039 27643, starred_actors, 39480 7394, has_genre, 8379 7394, has_tags, 8379 7394, release_year, 7841 6260, has_tags, 36066 6260, has_tags, 37039 19351, has_genre, 8379 19351, release_year, 1567 27995, has_genre, 8379 27995, release_year, 1567 36977, has_tags, 37039 36977, has_tags, 8379 29048, release_year, 1567 29048, starred_actors, 39480 29641, has_tags, 36066 29641, has_tags, 37039 29641, has_tags, 8379 29641, release_year, 7841 28776, has_genre, 36066 28776, has_tags, 36066 28776, has_tags, 37039 Question: In what context are BOPE, THE NAKED JUNGLE, and THE PRINCESS BRIDE connected? Your output must be ONLY the PATH block.

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{ "style": "rule" }

{ "entities": [ "BOPE", "THE NAKED JUNGLE", "THE PRINCESS BRIDE" ], "valid_edges": [ [ "BEAR'S KISS", "has_genre", "FANTASY" ], [ "BEAR'S KISS", "has_genre", "ROMANCE" ], [ "BLACK WIDOW", "release_year", "1954" ], [ "BLACK WIDOW", "release_year", "1987" ], [ "BRAZIL", "has_tags", "FANTASY" ], [ "DARK CITY", "has_tags", "ORIGINAL" ], [ "DARK CITY", "starred_actors", "CHARLTON HESTON" ], [ "ELITE SQUAD", "has_tags", "BOPE" ], [ "ELITE SQUAD", "has_tags", "BRAZIL" ], [ "PLANET OF THE APES", "has_tags", "CHARLTON HESTON" ], [ "PLANET OF THE APES", "has_tags", "ORIGINAL" ], [ "PLANET OF THE APES", "starred_actors", "CHARLTON HESTON" ], [ "SOME KIND OF WONDERFUL", "has_genre", "ROMANCE" ], [ "SOME KIND OF WONDERFUL", "has_tags", "ROMANCE" ], [ "SOME KIND OF WONDERFUL", "release_year", "1987" ], [ "SPIRITED AWAY", "has_tags", "FANTASY" ], [ "SPIRITED AWAY", "has_tags", "ORIGINAL" ], [ "THE COUNT OF MONTE CRISTO", "has_genre", "ROMANCE" ], [ "THE COUNT OF MONTE CRISTO", "release_year", "1954" ], [ "THE FAR COUNTRY", "has_genre", "ROMANCE" ], [ "THE FAR COUNTRY", "release_year", "1954" ], [ "THE GIRL WHO LEAPT THROUGH TIME", "has_tags", "ORIGINAL" ], [ "THE GIRL WHO LEAPT THROUGH TIME", "has_tags", "ROMANCE" ], [ "THE NAKED JUNGLE", "release_year", "1954" ], [ "THE NAKED JUNGLE", "starred_actors", "CHARLTON HESTON" ], [ "THE PRINCESS BRIDE", "has_tags", "FANTASY" ], [ "THE PRINCESS BRIDE", "has_tags", "ORIGINAL" ], [ "THE PRINCESS BRIDE", "has_tags", "ROMANCE" ], [ "THE PRINCESS BRIDE", "release_year", "1987" ], [ "THE WIZARD OF OZ", "has_genre", "FANTASY" ], [ "THE WIZARD OF OZ", "has_tags", "FANTASY" ], [ "THE WIZARD OF OZ", "has_tags", "ORIGINAL" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3702, 1995 1006, 1996 658, 2012 30870, BEAUTIFUL CREATURES 17794, BERNARDO BERTOLUCCI 38196, CHAIN REACTION 7349, EMPIRE RECORDS 39351, HEAVY 29418, JEREMY IRONS 14601, LES MISÉRABLES 14931, LIBERAL ARTS 9640, LIV TYLER 34611, ME AND YOU 38043, PUSHER 15348, RACHEL WEISZ 29038, STEALING BEAUTY 35366, THE BOURNE LEGACY 10924, THE PEBBLE AND THE PENGUIN 15504, THE WORDS src, edge_attr, dst 30870, starred_actors, 29418 30870, starred_actors, 15348 38196, release_year, 1006 38196, starred_actors, 15348 7349, has_tags, 9640 7349, release_year, 3702 39351, release_year, 3702 39351, starred_actors, 9640 14601, release_year, 3702 14601, release_year, 658 14931, release_year, 658 34611, directed_by, 17794 34611, release_year, 658 34611, written_by, 17794 38043, release_year, 1006 38043, release_year, 658 29038, directed_by, 17794 29038, has_tags, 17794 29038, has_tags, 29418 29038, has_tags, 9640 29038, has_tags, 15348 29038, release_year, 1006 29038, written_by, 17794 35366, has_tags, 15348 35366, release_year, 658 10924, release_year, 3702 15504, has_tags, 29418 15504, release_year, 658 15504, starred_actors, 29418 Question: How are LIBERAL ARTS, STEALING BEAUTY, and THE PEBBLE AND THE PENGUIN related? Your output must be ONLY the PATH block.

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{ "style": "rule" }

{ "entities": [ "LIBERAL ARTS", "STEALING BEAUTY", "THE PEBBLE AND THE PENGUIN" ], "valid_edges": [ [ "BEAUTIFUL CREATURES", "starred_actors", "JEREMY IRONS" ], [ "BEAUTIFUL CREATURES", "starred_actors", "RACHEL WEISZ" ], [ "CHAIN REACTION", "release_year", "1996" ], [ "CHAIN REACTION", "starred_actors", "RACHEL WEISZ" ], [ "EMPIRE RECORDS", "has_tags", "LIV TYLER" ], [ "EMPIRE RECORDS", "release_year", "1995" ], [ "HEAVY", "release_year", "1995" ], [ "HEAVY", "starred_actors", "LIV TYLER" ], [ "LES MISÉRABLES", "release_year", "1995" ], [ "LES MISÉRABLES", "release_year", "2012" ], [ "LIBERAL ARTS", "release_year", "2012" ], [ "ME AND YOU", "directed_by", "BERNARDO BERTOLUCCI" ], [ "ME AND YOU", "release_year", "2012" ], [ "ME AND YOU", "written_by", "BERNARDO BERTOLUCCI" ], [ "PUSHER", "release_year", "1996" ], [ "PUSHER", "release_year", "2012" ], [ "STEALING BEAUTY", "directed_by", "BERNARDO BERTOLUCCI" ], [ "STEALING BEAUTY", "has_tags", "BERNARDO BERTOLUCCI" ], [ "STEALING BEAUTY", "has_tags", "JEREMY IRONS" ], [ "STEALING BEAUTY", "has_tags", "LIV TYLER" ], [ "STEALING BEAUTY", "has_tags", "RACHEL WEISZ" ], [ "STEALING BEAUTY", "release_year", "1996" ], [ "STEALING BEAUTY", "written_by", "BERNARDO BERTOLUCCI" ], [ "THE BOURNE LEGACY", "has_tags", "RACHEL WEISZ" ], [ "THE BOURNE LEGACY", "release_year", "2012" ], [ "THE PEBBLE AND THE PENGUIN", "release_year", "1995" ], [ "THE WORDS", "has_tags", "JEREMY IRONS" ], [ "THE WORDS", "release_year", "2012" ], [ "THE WORDS", "starred_actors", "JEREMY IRONS" ] ] }