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
35063, 1976
694, ASSAULT ON PRECINCT 13
5851, BURNT OFFERINGS
24454, CARRIE
24717, ELVIS
35756, GHOSTS OF MARS
23822, GOD TOLD ME TO
4830, HALLOWEEN
5870, HORROR
24988, JOHN CARPENTER
24081, NEXT STOP, GREENWICH VILLAGE
33115, SHELLEY WINTERS
16551, SQUIRM
12891, TENTACLES
8574, THE DEVIL'S PLAYGROUND
27423, THE FOG
17910, THE OMEN
27003, THE THOMPSONS
10423, THE WITCH WHO CAME FROM THE SEA
20875, TO THE DEVIL A DAUGHTER
36374, VILLAGE OF THE DAMNED
24046, WEREWOLF WOMAN
src, edge_attr, dst
694, directed_by, 24988
694, has_tags, 24988
694, release_year, 35063
694, written_by, 24988
5851, has_genre, 5870
5851, release_year, 35063
24454, has_genre, 5870
24454, has_tags, 5870
24454, release_year, 35063
24717, directed_by, 24988
24717, has_tags, 24988
24717, starred_actors, 33115
35756, directed_by, 24988
35756, has_genre, 5870
35756, has_tags, 24988
35756, written_by, 24988
23822, has_genre, 5870
23822, release_year, 35063
4830, directed_by, 24988
4830, has_genre, 5870
4830, has_tags, 5870
4830, has_tags, 24988
4830, written_by, 24988
24081, release_year, 35063
24081, starred_actors, 33115
16551, has_genre, 5870
16551, release_year, 35063
12891, has_genre, 5870
12891, has_tags, 5870
12891, starred_actors, 33115
8574, release_year, 35063
27423, directed_by, 24988
27423, has_genre, 5870
27423, has_tags, 5870
27423, has_tags, 24988
27423, written_by, 24988
17910, has_genre, 5870
17910, has_tags, 5870
17910, release_year, 35063
27003, has_genre, 5870
10423, has_genre, 5870
10423, release_year, 35063
20875, has_genre, 5870
20875, release_year, 35063
36374, directed_by, 24988
36374, has_genre, 5870
36374, has_tags, 24988
24046, has_genre, 5870
24046, release_year, 35063
Question: For what reason are ELVIS, THE DEVIL'S PLAYGROUND, and THE THOMPSONS associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"ELVIS",
"THE DEVIL'S PLAYGROUND",
"THE THOMPSONS"
],
"valid_edges": [
[
"ASSAULT ON PRECINCT 13",
"directed_by",
"JOHN CARPENTER"
],
[
"ASSAULT ON PRECINCT 13",
"has_tags",
"JOHN CARPENTER"
],
[
"ASSAULT ON PRECINCT 13",
"release_year",
"1976"
],
[
"ASSAULT ON PRECINCT 13",
"written_by",
"JOHN CARPENTER"
],
[
"BURNT OFFERINGS",
"has_genre",
"HORROR"
],
[
"BURNT OFFERINGS",
"release_year",
"1976"
],
[
"CARRIE",
"has_genre",
"HORROR"
],
[
"CARRIE",
"has_tags",
"HORROR"
],
[
"CARRIE",
"release_year",
"1976"
],
[
"ELVIS",
"directed_by",
"JOHN CARPENTER"
],
[
"ELVIS",
"has_tags",
"JOHN CARPENTER"
],
[
"ELVIS",
"starred_actors",
"SHELLEY WINTERS"
],
[
"GHOSTS OF MARS",
"directed_by",
"JOHN CARPENTER"
],
[
"GHOSTS OF MARS",
"has_genre",
"HORROR"
],
[
"GHOSTS OF MARS",
"has_tags",
"JOHN CARPENTER"
],
[
"GHOSTS OF MARS",
"written_by",
"JOHN CARPENTER"
],
[
"GOD TOLD ME TO",
"has_genre",
"HORROR"
],
[
"GOD TOLD ME TO",
"release_year",
"1976"
],
[
"HALLOWEEN",
"directed_by",
"JOHN CARPENTER"
],
[
"HALLOWEEN",
"has_genre",
"HORROR"
],
[
"HALLOWEEN",
"has_tags",
"HORROR"
],
[
"HALLOWEEN",
"has_tags",
"JOHN CARPENTER"
],
[
"HALLOWEEN",
"written_by",
"JOHN CARPENTER"
],
[
"NEXT STOP, GREENWICH VILLAGE",
"release_year",
"1976"
],
[
"NEXT STOP, GREENWICH VILLAGE",
"starred_actors",
"SHELLEY WINTERS"
],
[
"SQUIRM",
"has_genre",
"HORROR"
],
[
"SQUIRM",
"release_year",
"1976"
],
[
"TENTACLES",
"has_genre",
"HORROR"
],
[
"TENTACLES",
"has_tags",
"HORROR"
],
[
"TENTACLES",
"starred_actors",
"SHELLEY WINTERS"
],
[
"THE DEVIL'S PLAYGROUND",
"release_year",
"1976"
],
[
"THE FOG",
"directed_by",
"JOHN CARPENTER"
],
[
"THE FOG",
"has_genre",
"HORROR"
],
[
"THE FOG",
"has_tags",
"HORROR"
],
[
"THE FOG",
"has_tags",
"JOHN CARPENTER"
],
[
"THE FOG",
"written_by",
"JOHN CARPENTER"
],
[
"THE OMEN",
"has_genre",
"HORROR"
],
[
"THE OMEN",
"has_tags",
"HORROR"
],
[
"THE OMEN",
"release_year",
"1976"
],
[
"THE THOMPSONS",
"has_genre",
"HORROR"
],
[
"THE WITCH WHO CAME FROM THE SEA",
"has_genre",
"HORROR"
],
[
"THE WITCH WHO CAME FROM THE SEA",
"release_year",
"1976"
],
[
"TO THE DEVIL A DAUGHTER",
"has_genre",
"HORROR"
],
[
"TO THE DEVIL A DAUGHTER",
"release_year",
"1976"
],
[
"VILLAGE OF THE DAMNED",
"directed_by",
"JOHN CARPENTER"
],
[
"VILLAGE OF THE DAMNED",
"has_genre",
"HORROR"
],
[
"VILLAGE OF THE DAMNED",
"has_tags",
"JOHN CARPENTER"
],
[
"WEREWOLF WOMAN",
"has_genre",
"HORROR"
],
[
"WEREWOLF WOMAN",
"release_year",
"1976"
]
]
}
|
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
29424, 2011
8133, CHURCH
27327, HIGHER GROUND
14878, KABHI HAAN KABHI NAA
21187, KUNDAN SHAH
13383, PRIEST
6754, SOURCE CODE
39525, VERA FARMIGA
src, edge_attr, dst
27327, directed_by, 39525
27327, has_tags, 39525
27327, release_year, 29424
27327, starred_actors, 39525
14878, directed_by, 21187
14878, release_year, 26257
14878, written_by, 21187
13383, has_tags, 8133
13383, has_tags, 13383
13383, release_year, 26257
13383, release_year, 29424
6754, has_tags, 39525
6754, release_year, 29424
6754, starred_actors, 39525
Question: For what reason are CHURCH, HIGHER GROUND, and KUNDAN SHAH associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"CHURCH",
"HIGHER GROUND",
"KUNDAN SHAH"
],
"valid_edges": [
[
"HIGHER GROUND",
"directed_by",
"VERA FARMIGA"
],
[
"HIGHER GROUND",
"has_tags",
"VERA FARMIGA"
],
[
"HIGHER GROUND",
"release_year",
"2011"
],
[
"HIGHER GROUND",
"starred_actors",
"VERA FARMIGA"
],
[
"KABHI HAAN KABHI NAA",
"directed_by",
"KUNDAN SHAH"
],
[
"KABHI HAAN KABHI NAA",
"release_year",
"1994"
],
[
"KABHI HAAN KABHI NAA",
"written_by",
"KUNDAN SHAH"
],
[
"PRIEST",
"has_tags",
"CHURCH"
],
[
"PRIEST",
"has_tags",
"PRIEST"
],
[
"PRIEST",
"release_year",
"1994"
],
[
"PRIEST",
"release_year",
"2011"
],
[
"SOURCE CODE",
"has_tags",
"VERA FARMIGA"
],
[
"SOURCE CODE",
"release_year",
"2011"
],
[
"SOURCE CODE",
"starred_actors",
"VERA FARMIGA"
]
]
}
|
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
16055, 1983
15374, 2005
35497, ANTARCTICA
30907, BAREFOOT GEN
21261, CHARLIE AND THE CHOCOLATE FACTORY
16970, EUREKA
32179, FACTORY
22958, FAMOUS
34231, GENE HACKMAN
36874, JAPANESE
2131, MEL BROOKS
37497, NATIONAL FILM REGISTRY
17109, ROBOTS
34021, RUTGER HAUER
28350, THE BALLAD OF NARAYAMA
28115, THE FAMILY GAME
27465, THE OSTERMAN WEEKEND
3231, THE PRODUCERS
3640, TO BE OR NOT TO BE
19052, UNCOMMON VALOR
32843, UNDER FIRE
13644, YOUNG FRANKENSTEIN
src, edge_attr, dst
35497, in_language, 36874
35497, release_year, 16055
30907, in_language, 36874
30907, release_year, 16055
21261, has_tags, 32179
21261, release_year, 15374
16970, has_tags, 34231
16970, in_language, 36874
16970, release_year, 16055
16970, starred_actors, 34231
16970, starred_actors, 34021
17109, has_tags, 2131
17109, has_tags, 17109
17109, release_year, 15374
28350, in_language, 36874
28350, release_year, 16055
28115, in_language, 36874
28115, release_year, 16055
27465, has_tags, 34021
27465, release_year, 16055
27465, starred_actors, 34021
3231, directed_by, 2131
3231, has_tags, 2131
3231, has_tags, 37497
3231, release_year, 15374
3231, written_by, 2131
3640, has_imdb_votes, 22958
3640, has_tags, 2131
3640, release_year, 16055
19052, has_tags, 34231
19052, release_year, 16055
19052, starred_actors, 34231
32843, has_tags, 34231
32843, release_year, 16055
32843, starred_actors, 34231
13644, directed_by, 2131
13644, has_imdb_votes, 22958
13644, has_tags, 2131
13644, has_tags, 37497
13644, written_by, 2131
Question: How are EUREKA, FACTORY, and MEL BROOKS related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"EUREKA",
"FACTORY",
"MEL BROOKS"
],
"valid_edges": [
[
"ANTARCTICA",
"in_language",
"JAPANESE"
],
[
"ANTARCTICA",
"release_year",
"1983"
],
[
"BAREFOOT GEN",
"in_language",
"JAPANESE"
],
[
"BAREFOOT GEN",
"release_year",
"1983"
],
[
"CHARLIE AND THE CHOCOLATE FACTORY",
"has_tags",
"FACTORY"
],
[
"CHARLIE AND THE CHOCOLATE FACTORY",
"release_year",
"2005"
],
[
"EUREKA",
"has_tags",
"GENE HACKMAN"
],
[
"EUREKA",
"in_language",
"JAPANESE"
],
[
"EUREKA",
"release_year",
"1983"
],
[
"EUREKA",
"starred_actors",
"GENE HACKMAN"
],
[
"EUREKA",
"starred_actors",
"RUTGER HAUER"
],
[
"ROBOTS",
"has_tags",
"MEL BROOKS"
],
[
"ROBOTS",
"has_tags",
"ROBOTS"
],
[
"ROBOTS",
"release_year",
"2005"
],
[
"THE BALLAD OF NARAYAMA",
"in_language",
"JAPANESE"
],
[
"THE BALLAD OF NARAYAMA",
"release_year",
"1983"
],
[
"THE FAMILY GAME",
"in_language",
"JAPANESE"
],
[
"THE FAMILY GAME",
"release_year",
"1983"
],
[
"THE OSTERMAN WEEKEND",
"has_tags",
"RUTGER HAUER"
],
[
"THE OSTERMAN WEEKEND",
"release_year",
"1983"
],
[
"THE OSTERMAN WEEKEND",
"starred_actors",
"RUTGER HAUER"
],
[
"THE PRODUCERS",
"directed_by",
"MEL BROOKS"
],
[
"THE PRODUCERS",
"has_tags",
"MEL BROOKS"
],
[
"THE PRODUCERS",
"has_tags",
"NATIONAL FILM REGISTRY"
],
[
"THE PRODUCERS",
"release_year",
"2005"
],
[
"THE PRODUCERS",
"written_by",
"MEL BROOKS"
],
[
"TO BE OR NOT TO BE",
"has_imdb_votes",
"FAMOUS"
],
[
"TO BE OR NOT TO BE",
"has_tags",
"MEL BROOKS"
],
[
"TO BE OR NOT TO BE",
"release_year",
"1983"
],
[
"UNCOMMON VALOR",
"has_tags",
"GENE HACKMAN"
],
[
"UNCOMMON VALOR",
"release_year",
"1983"
],
[
"UNCOMMON VALOR",
"starred_actors",
"GENE HACKMAN"
],
[
"UNDER FIRE",
"has_tags",
"GENE HACKMAN"
],
[
"UNDER FIRE",
"release_year",
"1983"
],
[
"UNDER FIRE",
"starred_actors",
"GENE HACKMAN"
],
[
"YOUNG FRANKENSTEIN",
"directed_by",
"MEL BROOKS"
],
[
"YOUNG FRANKENSTEIN",
"has_imdb_votes",
"FAMOUS"
],
[
"YOUNG FRANKENSTEIN",
"has_tags",
"MEL BROOKS"
],
[
"YOUNG FRANKENSTEIN",
"has_tags",
"NATIONAL FILM REGISTRY"
],
[
"YOUNG FRANKENSTEIN",
"written_by",
"MEL BROOKS"
]
]
}
|
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
8636, 1930
26762, 2008
13573, ANNA CHRISTIE
15147, GOMORRAH
11565, GOOD
24238, L'AGE D'OR
35505, LUIS BUÑUEL
2414, MACHINE-GUN KELLY
29473, ROBERTO SAVIANO
5057, THE YOUNG ONE
src, edge_attr, dst
13573, has_imdb_rating, 11565
13573, release_year, 8636
15147, release_year, 26762
15147, written_by, 29473
11565, has_imdb_rating, 11565
11565, release_year, 26762
24238, directed_by, 35505
24238, has_tags, 35505
24238, release_year, 8636
24238, written_by, 35505
2414, has_imdb_rating, 11565
5057, directed_by, 35505
5057, has_imdb_rating, 11565
5057, has_tags, 35505
5057, written_by, 35505
Question: For what reason are L'AGE D'OR, MACHINE-GUN KELLY, and ROBERTO SAVIANO associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"L'AGE D'OR",
"MACHINE-GUN KELLY",
"ROBERTO SAVIANO"
],
"valid_edges": [
[
"ANNA CHRISTIE",
"has_imdb_rating",
"GOOD"
],
[
"ANNA CHRISTIE",
"release_year",
"1930"
],
[
"GOMORRAH",
"release_year",
"2008"
],
[
"GOMORRAH",
"written_by",
"ROBERTO SAVIANO"
],
[
"GOOD",
"has_imdb_rating",
"GOOD"
],
[
"GOOD",
"release_year",
"2008"
],
[
"L'AGE D'OR",
"directed_by",
"LUIS BUÑUEL"
],
[
"L'AGE D'OR",
"has_tags",
"LUIS BUÑUEL"
],
[
"L'AGE D'OR",
"release_year",
"1930"
],
[
"L'AGE D'OR",
"written_by",
"LUIS BUÑUEL"
],
[
"MACHINE-GUN KELLY",
"has_imdb_rating",
"GOOD"
],
[
"THE YOUNG ONE",
"directed_by",
"LUIS BUÑUEL"
],
[
"THE YOUNG ONE",
"has_imdb_rating",
"GOOD"
],
[
"THE YOUNG ONE",
"has_tags",
"LUIS BUÑUEL"
],
[
"THE YOUNG ONE",
"written_by",
"LUIS BUÑUEL"
]
]
}
|
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
35798, 2010
656, CRUSH
9045, DAMION POITIER
36212, DRAMA
3079, FREEDOM WRITERS
30437, HUNTER PREY
9359, IMELDA STAUNTON
15038, INDEPENDENCE
35556, OUTSIDE THE LAW
src, edge_attr, dst
656, has_genre, 36212
656, starred_actors, 9359
3079, has_genre, 36212
3079, starred_actors, 9359
3079, written_by, 3079
30437, release_year, 35798
30437, starred_actors, 9045
35556, has_genre, 36212
35556, has_tags, 36212
35556, has_tags, 15038
35556, release_year, 35798
Question: In what context are DAMION POITIER, IMELDA STAUNTON, and INDEPENDENCE connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"DAMION POITIER",
"IMELDA STAUNTON",
"INDEPENDENCE"
],
"valid_edges": [
[
"CRUSH",
"has_genre",
"DRAMA"
],
[
"CRUSH",
"starred_actors",
"IMELDA STAUNTON"
],
[
"FREEDOM WRITERS",
"has_genre",
"DRAMA"
],
[
"FREEDOM WRITERS",
"starred_actors",
"IMELDA STAUNTON"
],
[
"FREEDOM WRITERS",
"written_by",
"FREEDOM WRITERS"
],
[
"HUNTER PREY",
"release_year",
"2010"
],
[
"HUNTER PREY",
"starred_actors",
"DAMION POITIER"
],
[
"OUTSIDE THE LAW",
"has_genre",
"DRAMA"
],
[
"OUTSIDE THE LAW",
"has_tags",
"DRAMA"
],
[
"OUTSIDE THE LAW",
"has_tags",
"INDEPENDENCE"
],
[
"OUTSIDE THE LAW",
"release_year",
"2010"
]
]
}
|
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
27261, 2009
39289, ACTION
38925, CLOUD ATLAS
32331, CONSTANCE COLLIER
36212, DRAMA
14257, ELEPHANT
3342, ERIC DEULEN
25842, ESCAPE FROM NEW YORK
8491, ESCAPE PLAN
27620, FUTURE
33790, MANHATTAN
36943, NEW YORK
4303, NEW YORK CITY
4302, PETER IBBETSON
30919, PRISON
35872, RICH AND FAMOUS
19351, THE COUNT OF MONTE CRISTO
22346, THE DEVIL WEARS PRADA
4552, WEST SIDE STORY
src, edge_attr, dst
25221, has_genre, 36212
25221, release_year, 27261
38925, has_tags, 39289
38925, has_tags, 27620
14257, has_genre, 36212
14257, starred_actors, 3342
25842, has_genre, 39289
25842, has_tags, 39289
25842, has_tags, 27620
25842, has_tags, 36943
25842, has_tags, 4303
25842, has_tags, 30919
25842, release_year, 25221
8491, has_genre, 39289
8491, has_tags, 30919
33790, has_tags, 36943
33790, has_tags, 4303
36943, release_year, 27261
4302, has_genre, 36212
4302, written_by, 32331
30919, has_genre, 36212
30919, has_tags, 30919
35872, has_genre, 39289
35872, release_year, 25221
19351, has_genre, 39289
19351, has_tags, 30919
22346, has_tags, 36943
22346, has_tags, 4303
4552, has_tags, 36943
4552, has_tags, 4303
Question: How are CONSTANCE COLLIER, ERIC DEULEN, and ESCAPE FROM NEW YORK related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"CONSTANCE COLLIER",
"ERIC DEULEN",
"ESCAPE FROM NEW YORK"
],
"valid_edges": [
[
"1981",
"has_genre",
"DRAMA"
],
[
"1981",
"release_year",
"2009"
],
[
"CLOUD ATLAS",
"has_tags",
"ACTION"
],
[
"CLOUD ATLAS",
"has_tags",
"FUTURE"
],
[
"ELEPHANT",
"has_genre",
"DRAMA"
],
[
"ELEPHANT",
"starred_actors",
"ERIC DEULEN"
],
[
"ESCAPE FROM NEW YORK",
"has_genre",
"ACTION"
],
[
"ESCAPE FROM NEW YORK",
"has_tags",
"ACTION"
],
[
"ESCAPE FROM NEW YORK",
"has_tags",
"FUTURE"
],
[
"ESCAPE FROM NEW YORK",
"has_tags",
"NEW YORK"
],
[
"ESCAPE FROM NEW YORK",
"has_tags",
"NEW YORK CITY"
],
[
"ESCAPE FROM NEW YORK",
"has_tags",
"PRISON"
],
[
"ESCAPE FROM NEW YORK",
"release_year",
"1981"
],
[
"ESCAPE PLAN",
"has_genre",
"ACTION"
],
[
"ESCAPE PLAN",
"has_tags",
"PRISON"
],
[
"MANHATTAN",
"has_tags",
"NEW YORK"
],
[
"MANHATTAN",
"has_tags",
"NEW YORK CITY"
],
[
"NEW YORK",
"release_year",
"2009"
],
[
"PETER IBBETSON",
"has_genre",
"DRAMA"
],
[
"PETER IBBETSON",
"written_by",
"CONSTANCE COLLIER"
],
[
"PRISON",
"has_genre",
"DRAMA"
],
[
"PRISON",
"has_tags",
"PRISON"
],
[
"RICH AND FAMOUS",
"has_genre",
"ACTION"
],
[
"RICH AND FAMOUS",
"release_year",
"1981"
],
[
"THE COUNT OF MONTE CRISTO",
"has_genre",
"ACTION"
],
[
"THE COUNT OF MONTE CRISTO",
"has_tags",
"PRISON"
],
[
"THE DEVIL WEARS PRADA",
"has_tags",
"NEW YORK"
],
[
"THE DEVIL WEARS PRADA",
"has_tags",
"NEW YORK CITY"
],
[
"WEST SIDE STORY",
"has_tags",
"NEW YORK"
],
[
"WEST SIDE STORY",
"has_tags",
"NEW YORK CITY"
]
]
}
|
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
29036, A MIDSUMMER NIGHT'S DREAM
8198, A PRAIRIE HOME COMPANION
27672, A ROOM FOR ROMEO BRASS
35603, AGNES BROWNE
21398, AMERICAN PIE
23409, AN IDEAL HUSBAND
8780, ANALYZE THIS
15458, BABY GENIUSES
32415, BEAUTIFUL PEOPLE
26205, BEING JOHN MALKOVICH
24555, BETTER THAN CHOCOLATE
32602, BIG DADDY
18375, BLAST FROM THE PAST
16932, BLUE STREAK
21121, BOWFINGER
5826, BREAKFAST OF CHAMPIONS
27223, BUT FOREVER IN MY MIND
36824, BUT I'M A CHEERLEADER
3291, CATFISH IN BLACK BEAN SAUCE
13901, CHARLIE WILSON'S WAR
24116, COLLEGE
30463, COMEDY
640, COOKIE'S FORTUNE
39353, COTTON MARY
32140, CRAZY IN ALABAMA
16600, CYRUS
36492, DIAMONDS
637, DICK
17219, DO NOT DISTURB
21407, DOGMA
36212, DRAMA
18908, DROP DEAD GORGEOUS
8341, DUDLEY DO-RIGHT
7568, EAST IS EAST
26193, ELECTION
17072, FAREWELL, HOME SWEET HOME
25625, FIRST DAUGHTER
34555, FLAWLESS
17478, FOOLISH
34820, FORCES OF NATURE
5514, FUNNY PEOPLE
6623, GO
14426, GORGEOUS
11817, GUEST HOUSE PARADISO
12650, HAPPY, TEXAS
21485, HELD UP
29729, HIT AND RUNWAY
39622, IDLE HANDS
36573, IN CHINA THEY EAT DOGS
25733, INSPECTOR GADGET
4912, JAKOB THE LIAR
17556, JAWBREAKER
1592, K-911
22333, KING OF COMEDY
13898, LAKE PLACID
7104, LIFE
32468, LOVE STINKS
37138, MAN OF THE CENTURY
37867, MAN ON THE MOON
6649, MANSFIELD PARK
1454, MICKEY BLUE EYES
19598, MOLLY
16428, MUMFORD
16362, MUPPETS FROM SPACE
10000, MY NEIGHBORS THE YAMADAS
5020, MYSTERY MEN
33718, MYSTERY, ALASKA
33072, NEVER BEEN KISSED
16645, NEW WATERFORD GIRL
37812, NICE GUYS SLEEP ALONE
14898, NOTTING HILL
39920, OFFICE SPACE
14718, PAUL DANZIGER
35054, PLAY IT TO THE BONE
34333, PUNCTURE
16964, PUSHING TIN
16974, RUNAWAY BRIDE
19297, SAFE SEX
15252, SCREWED IN TALLINN
32422, SEVEN GIRLFRIENDS
38502, SHE'S ALL THAT
36310, SIAM SUNSET
801, SIMON SEZ
25788, SIMPLY IRRESISTIBLE
3929, SOFT TOILET SEATS
8978, SPLENDOR
27650, STRANGE PLANET
22847, STUART LITTLE
27511, SUPERSTAR
32984, SWEET AND LOWDOWN
905, TEACHING MRS. TINGLE
22407, THE ACTRESS
36394, THE ADVENTURES OF ELMO IN GROUCHLAND
3021, THE BACHELOR
4157, THE BEST MAN
27111, THE BIG KAHUNA
14175, THE BIG TEASE
8605, THE BREAKS
12439, THE INSIDER
844, THE LOVE LETTER
35958, THE MATCH
16694, THE MUSE
35433, THE OTHER SISTER
10260, THE OUT-OF-TOWNERS
2739, THE SAPPHIRES
37200, THE STORY OF US
11235, THE SUBURBANS
38179, THE UNDERGROUND COMEDY MOVIE
26468, THE WAITING GAME
26226, THE WOOD
12626, THREE KINGS
25141, THREE TO TANGO
4723, TIFOSI
14499, TOY STORY 2
24435, TRAILER PARK BOYS
21904, TRICK
23874, TRIPPIN'
16292, TRUE STORY
13101, TUMBLEWEEDS
3569, WHY NOT ME?
1790, WILD WILD WEST
src, edge_attr, dst
13464, has_genre, 30463
13464, has_genre, 36212
13464, has_tags, 30463
13464, release_year, 8486
5620, has_genre, 30463
5620, has_genre, 36212
5620, release_year, 8486
30146, has_genre, 30463
30146, has_genre, 36212
30146, release_year, 8486
29036, has_genre, 30463
29036, release_year, 8486
8198, has_genre, 30463
8198, has_genre, 36212
27672, has_genre, 30463
27672, has_genre, 36212
27672, release_year, 8486
35603, has_genre, 30463
35603, has_genre, 36212
35603, release_year, 8486
21398, has_genre, 30463
21398, has_tags, 30463
21398, release_year, 8486
23409, has_genre, 30463
23409, has_tags, 30463
23409, release_year, 8486
8780, has_genre, 30463
8780, has_tags, 30463
8780, release_year, 8486
15458, has_genre, 30463
15458, release_year, 8486
32415, has_genre, 30463
32415, release_year, 8486
26205, has_genre, 30463
26205, has_genre, 36212
26205, has_tags, 30463
26205, has_tags, 36212
26205, release_year, 8486
24555, has_genre, 30463
24555, release_year, 8486
32602, has_genre, 30463
32602, release_year, 8486
18375, has_genre, 30463
18375, release_year, 8486
16932, has_genre, 30463
16932, release_year, 8486
21121, has_genre, 30463
21121, has_tags, 30463
21121, release_year, 8486
5826, has_genre, 30463
5826, has_tags, 30463
5826, release_year, 8486
27223, has_genre, 30463
27223, release_year, 8486
36824, has_genre, 30463
36824, release_year, 8486
3291, has_genre, 30463
3291, has_genre, 36212
3291, release_year, 8486
13901, has_genre, 30463
13901, has_genre, 36212
24116, has_genre, 30463
24116, has_genre, 36212
640, has_genre, 30463
640, release_year, 8486
39353, release_year, 8486
32140, has_genre, 30463
32140, has_genre, 36212
32140, release_year, 8486
16600, has_genre, 30463
16600, has_genre, 36212
36492, has_genre, 30463
36492, release_year, 8486
637, has_genre, 30463
637, release_year, 8486
17219, has_genre, 30463
17219, release_year, 8486
21407, has_genre, 30463
21407, has_tags, 30463
21407, release_year, 8486
18908, has_genre, 30463
18908, release_year, 8486
8341, has_genre, 30463
8341, release_year, 8486
7568, has_genre, 30463
7568, has_genre, 36212
7568, release_year, 8486
26193, has_genre, 30463
26193, release_year, 8486
17072, has_genre, 30463
17072, release_year, 8486
25625, has_genre, 30463
25625, release_year, 8486
34555, has_genre, 30463
34555, has_genre, 36212
34555, release_year, 8486
17478, has_genre, 30463
17478, has_genre, 36212
17478, release_year, 8486
34820, has_genre, 30463
34820, release_year, 8486
5514, has_genre, 30463
5514, has_genre, 36212
5514, has_tags, 30463
5514, has_tags, 36212
6623, has_genre, 30463
6623, has_tags, 30463
6623, release_year, 8486
14426, has_genre, 30463
14426, release_year, 8486
11817, has_genre, 30463
11817, release_year, 8486
12650, has_genre, 30463
12650, release_year, 8486
21485, has_genre, 30463
21485, release_year, 8486
29729, has_genre, 30463
29729, release_year, 8486
39622, has_genre, 30463
39622, release_year, 8486
36573, has_genre, 30463
36573, release_year, 8486
25733, has_genre, 30463
25733, release_year, 8486
4912, has_genre, 30463
4912, has_genre, 36212
4912, release_year, 8486
17556, has_genre, 30463
17556, release_year, 8486
1592, has_genre, 30463
1592, release_year, 8486
22333, has_genre, 30463
22333, has_genre, 36212
22333, release_year, 8486
13898, has_genre, 30463
13898, release_year, 8486
7104, has_genre, 30463
7104, has_genre, 36212
7104, has_tags, 30463
7104, release_year, 8486
32468, has_genre, 30463
32468, release_year, 8486
37138, has_genre, 30463
37138, release_year, 8486
37867, has_genre, 30463
37867, has_genre, 36212
37867, release_year, 8486
6649, has_genre, 30463
6649, has_genre, 36212
6649, release_year, 8486
1454, has_genre, 30463
1454, has_tags, 30463
1454, release_year, 8486
19598, has_genre, 30463
19598, has_genre, 36212
19598, release_year, 8486
16428, has_genre, 30463
16428, has_genre, 36212
16428, release_year, 8486
16362, has_genre, 30463
16362, release_year, 8486
10000, has_genre, 30463
10000, release_year, 8486
5020, has_genre, 30463
5020, has_tags, 30463
5020, release_year, 8486
33718, has_genre, 30463
33718, has_genre, 36212
33718, release_year, 8486
33072, has_genre, 30463
33072, release_year, 8486
16645, has_genre, 30463
16645, release_year, 8486
37812, has_genre, 30463
37812, release_year, 8486
14898, has_genre, 30463
14898, has_tags, 30463
14898, release_year, 8486
39920, has_genre, 30463
39920, has_tags, 30463
39920, release_year, 8486
35054, has_genre, 30463
35054, has_genre, 36212
35054, release_year, 8486
34333, has_tags, 16292
34333, written_by, 14718
16964, has_genre, 30463
16964, has_genre, 36212
16964, release_year, 8486
16974, has_genre, 30463
16974, release_year, 8486
19297, has_genre, 30463
19297, release_year, 8486
15252, has_genre, 30463
15252, has_genre, 36212
15252, release_year, 8486
32422, has_genre, 30463
32422, release_year, 8486
38502, has_genre, 30463
38502, has_tags, 30463
38502, release_year, 8486
36310, has_genre, 30463
36310, release_year, 8486
801, has_genre, 30463
801, has_tags, 30463
801, release_year, 8486
25788, has_genre, 30463
25788, release_year, 8486
3929, has_genre, 30463
3929, release_year, 8486
8978, has_genre, 30463
8978, release_year, 8486
27650, has_genre, 30463
27650, release_year, 8486
22847, has_genre, 30463
22847, has_tags, 30463
22847, release_year, 8486
27511, has_genre, 30463
27511, release_year, 8486
32984, has_genre, 30463
32984, has_genre, 36212
32984, release_year, 8486
905, has_genre, 30463
905, release_year, 8486
22407, has_genre, 30463
22407, has_genre, 36212
36394, has_genre, 30463
36394, release_year, 8486
3021, has_genre, 30463
3021, release_year, 8486
4157, has_genre, 30463
4157, has_genre, 36212
4157, release_year, 8486
27111, has_genre, 30463
27111, has_genre, 36212
27111, release_year, 8486
14175, has_genre, 30463
14175, release_year, 8486
8605, has_genre, 30463
8605, release_year, 8486
12439, has_genre, 36212
12439, has_tags, 36212
12439, release_year, 8486
844, has_genre, 30463
844, release_year, 8486
35958, has_genre, 30463
35958, release_year, 8486
16694, has_genre, 30463
16694, release_year, 8486
35433, has_genre, 30463
35433, release_year, 8486
10260, has_genre, 30463
10260, release_year, 8486
2739, has_genre, 30463
2739, has_genre, 36212
37200, has_genre, 30463
37200, has_genre, 36212
37200, has_tags, 36212
37200, release_year, 8486
11235, has_genre, 30463
11235, has_genre, 36212
11235, release_year, 8486
38179, has_genre, 30463
38179, release_year, 8486
26468, has_genre, 30463
26468, release_year, 8486
26226, has_genre, 30463
26226, release_year, 8486
12626, has_genre, 30463
12626, has_tags, 30463
12626, release_year, 8486
25141, has_genre, 30463
25141, release_year, 8486
4723, has_genre, 30463
4723, release_year, 8486
14499, has_genre, 30463
14499, release_year, 8486
24435, has_genre, 30463
24435, release_year, 8486
21904, has_genre, 30463
21904, release_year, 8486
23874, has_genre, 30463
23874, release_year, 8486
16292, has_genre, 36212
16292, has_tags, 36212
13101, has_genre, 30463
13101, has_genre, 36212
13101, release_year, 8486
3569, has_genre, 30463
3569, release_year, 8486
1790, has_genre, 30463
1790, has_tags, 30463
1790, release_year, 8486
Question: For what reason are COTTON MARY, PAUL DANZIGER, and THE ACTRESS associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"COTTON MARY",
"PAUL DANZIGER",
"THE ACTRESS"
],
"valid_edges": [
[
"10 THINGS I HATE ABOUT YOU",
"has_genre",
"COMEDY"
],
[
"10 THINGS I HATE ABOUT YOU",
"has_genre",
"DRAMA"
],
[
"10 THINGS I HATE ABOUT YOU",
"has_tags",
"COMEDY"
],
[
"10 THINGS I HATE ABOUT YOU",
"release_year",
"1999"
],
[
"200 CIGARETTES",
"has_genre",
"COMEDY"
],
[
"200 CIGARETTES",
"has_genre",
"DRAMA"
],
[
"200 CIGARETTES",
"release_year",
"1999"
],
[
"A CHRISTMAS CAROL",
"has_genre",
"COMEDY"
],
[
"A CHRISTMAS CAROL",
"has_genre",
"DRAMA"
],
[
"A CHRISTMAS CAROL",
"release_year",
"1999"
],
[
"A MIDSUMMER NIGHT'S DREAM",
"has_genre",
"COMEDY"
],
[
"A MIDSUMMER NIGHT'S DREAM",
"release_year",
"1999"
],
[
"A PRAIRIE HOME COMPANION",
"has_genre",
"COMEDY"
],
[
"A PRAIRIE HOME COMPANION",
"has_genre",
"DRAMA"
],
[
"A ROOM FOR ROMEO BRASS",
"has_genre",
"COMEDY"
],
[
"A ROOM FOR ROMEO BRASS",
"has_genre",
"DRAMA"
],
[
"A ROOM FOR ROMEO BRASS",
"release_year",
"1999"
],
[
"AGNES BROWNE",
"has_genre",
"COMEDY"
],
[
"AGNES BROWNE",
"has_genre",
"DRAMA"
],
[
"AGNES BROWNE",
"release_year",
"1999"
],
[
"AMERICAN PIE",
"has_genre",
"COMEDY"
],
[
"AMERICAN PIE",
"has_tags",
"COMEDY"
],
[
"AMERICAN PIE",
"release_year",
"1999"
],
[
"AN IDEAL HUSBAND",
"has_genre",
"COMEDY"
],
[
"AN IDEAL HUSBAND",
"has_tags",
"COMEDY"
],
[
"AN IDEAL HUSBAND",
"release_year",
"1999"
],
[
"ANALYZE THIS",
"has_genre",
"COMEDY"
],
[
"ANALYZE THIS",
"has_tags",
"COMEDY"
],
[
"ANALYZE THIS",
"release_year",
"1999"
],
[
"BABY GENIUSES",
"has_genre",
"COMEDY"
],
[
"BABY GENIUSES",
"release_year",
"1999"
],
[
"BEAUTIFUL PEOPLE",
"has_genre",
"COMEDY"
],
[
"BEAUTIFUL PEOPLE",
"release_year",
"1999"
],
[
"BEING JOHN MALKOVICH",
"has_genre",
"COMEDY"
],
[
"BEING JOHN MALKOVICH",
"has_genre",
"DRAMA"
],
[
"BEING JOHN MALKOVICH",
"has_tags",
"COMEDY"
],
[
"BEING JOHN MALKOVICH",
"has_tags",
"DRAMA"
],
[
"BEING JOHN MALKOVICH",
"release_year",
"1999"
],
[
"BETTER THAN CHOCOLATE",
"has_genre",
"COMEDY"
],
[
"BETTER THAN CHOCOLATE",
"release_year",
"1999"
],
[
"BIG DADDY",
"has_genre",
"COMEDY"
],
[
"BIG DADDY",
"release_year",
"1999"
],
[
"BLAST FROM THE PAST",
"has_genre",
"COMEDY"
],
[
"BLAST FROM THE PAST",
"release_year",
"1999"
],
[
"BLUE STREAK",
"has_genre",
"COMEDY"
],
[
"BLUE STREAK",
"release_year",
"1999"
],
[
"BOWFINGER",
"has_genre",
"COMEDY"
],
[
"BOWFINGER",
"has_tags",
"COMEDY"
],
[
"BOWFINGER",
"release_year",
"1999"
],
[
"BREAKFAST OF CHAMPIONS",
"has_genre",
"COMEDY"
],
[
"BREAKFAST OF CHAMPIONS",
"has_tags",
"COMEDY"
],
[
"BREAKFAST OF CHAMPIONS",
"release_year",
"1999"
],
[
"BUT FOREVER IN MY MIND",
"has_genre",
"COMEDY"
],
[
"BUT FOREVER IN MY MIND",
"release_year",
"1999"
],
[
"BUT I'M A CHEERLEADER",
"has_genre",
"COMEDY"
],
[
"BUT I'M A CHEERLEADER",
"release_year",
"1999"
],
[
"CATFISH IN BLACK BEAN SAUCE",
"has_genre",
"COMEDY"
],
[
"CATFISH IN BLACK BEAN SAUCE",
"has_genre",
"DRAMA"
],
[
"CATFISH IN BLACK BEAN SAUCE",
"release_year",
"1999"
],
[
"CHARLIE WILSON'S WAR",
"has_genre",
"COMEDY"
],
[
"CHARLIE WILSON'S WAR",
"has_genre",
"DRAMA"
],
[
"COLLEGE",
"has_genre",
"COMEDY"
],
[
"COLLEGE",
"has_genre",
"DRAMA"
],
[
"COOKIE'S FORTUNE",
"has_genre",
"COMEDY"
],
[
"COOKIE'S FORTUNE",
"release_year",
"1999"
],
[
"COTTON MARY",
"release_year",
"1999"
],
[
"CRAZY IN ALABAMA",
"has_genre",
"COMEDY"
],
[
"CRAZY IN ALABAMA",
"has_genre",
"DRAMA"
],
[
"CRAZY IN ALABAMA",
"release_year",
"1999"
],
[
"CYRUS",
"has_genre",
"COMEDY"
],
[
"CYRUS",
"has_genre",
"DRAMA"
],
[
"DIAMONDS",
"has_genre",
"COMEDY"
],
[
"DIAMONDS",
"release_year",
"1999"
],
[
"DICK",
"has_genre",
"COMEDY"
],
[
"DICK",
"release_year",
"1999"
],
[
"DO NOT DISTURB",
"has_genre",
"COMEDY"
],
[
"DO NOT DISTURB",
"release_year",
"1999"
],
[
"DOGMA",
"has_genre",
"COMEDY"
],
[
"DOGMA",
"has_tags",
"COMEDY"
],
[
"DOGMA",
"release_year",
"1999"
],
[
"DROP DEAD GORGEOUS",
"has_genre",
"COMEDY"
],
[
"DROP DEAD GORGEOUS",
"release_year",
"1999"
],
[
"DUDLEY DO-RIGHT",
"has_genre",
"COMEDY"
],
[
"DUDLEY DO-RIGHT",
"release_year",
"1999"
],
[
"EAST IS EAST",
"has_genre",
"COMEDY"
],
[
"EAST IS EAST",
"has_genre",
"DRAMA"
],
[
"EAST IS EAST",
"release_year",
"1999"
],
[
"ELECTION",
"has_genre",
"COMEDY"
],
[
"ELECTION",
"release_year",
"1999"
],
[
"FAREWELL, HOME SWEET HOME",
"has_genre",
"COMEDY"
],
[
"FAREWELL, HOME SWEET HOME",
"release_year",
"1999"
],
[
"FIRST DAUGHTER",
"has_genre",
"COMEDY"
],
[
"FIRST DAUGHTER",
"release_year",
"1999"
],
[
"FLAWLESS",
"has_genre",
"COMEDY"
],
[
"FLAWLESS",
"has_genre",
"DRAMA"
],
[
"FLAWLESS",
"release_year",
"1999"
],
[
"FOOLISH",
"has_genre",
"COMEDY"
],
[
"FOOLISH",
"has_genre",
"DRAMA"
],
[
"FOOLISH",
"release_year",
"1999"
],
[
"FORCES OF NATURE",
"has_genre",
"COMEDY"
],
[
"FORCES OF NATURE",
"release_year",
"1999"
],
[
"FUNNY PEOPLE",
"has_genre",
"COMEDY"
],
[
"FUNNY PEOPLE",
"has_genre",
"DRAMA"
],
[
"FUNNY PEOPLE",
"has_tags",
"COMEDY"
],
[
"FUNNY PEOPLE",
"has_tags",
"DRAMA"
],
[
"GO",
"has_genre",
"COMEDY"
],
[
"GO",
"has_tags",
"COMEDY"
],
[
"GO",
"release_year",
"1999"
],
[
"GORGEOUS",
"has_genre",
"COMEDY"
],
[
"GORGEOUS",
"release_year",
"1999"
],
[
"GUEST HOUSE PARADISO",
"has_genre",
"COMEDY"
],
[
"GUEST HOUSE PARADISO",
"release_year",
"1999"
],
[
"HAPPY, TEXAS",
"has_genre",
"COMEDY"
],
[
"HAPPY, TEXAS",
"release_year",
"1999"
],
[
"HELD UP",
"has_genre",
"COMEDY"
],
[
"HELD UP",
"release_year",
"1999"
],
[
"HIT AND RUNWAY",
"has_genre",
"COMEDY"
],
[
"HIT AND RUNWAY",
"release_year",
"1999"
],
[
"IDLE HANDS",
"has_genre",
"COMEDY"
],
[
"IDLE HANDS",
"release_year",
"1999"
],
[
"IN CHINA THEY EAT DOGS",
"has_genre",
"COMEDY"
],
[
"IN CHINA THEY EAT DOGS",
"release_year",
"1999"
],
[
"INSPECTOR GADGET",
"has_genre",
"COMEDY"
],
[
"INSPECTOR GADGET",
"release_year",
"1999"
],
[
"JAKOB THE LIAR",
"has_genre",
"COMEDY"
],
[
"JAKOB THE LIAR",
"has_genre",
"DRAMA"
],
[
"JAKOB THE LIAR",
"release_year",
"1999"
],
[
"JAWBREAKER",
"has_genre",
"COMEDY"
],
[
"JAWBREAKER",
"release_year",
"1999"
],
[
"K-911",
"has_genre",
"COMEDY"
],
[
"K-911",
"release_year",
"1999"
],
[
"KING OF COMEDY",
"has_genre",
"COMEDY"
],
[
"KING OF COMEDY",
"has_genre",
"DRAMA"
],
[
"KING OF COMEDY",
"release_year",
"1999"
],
[
"LAKE PLACID",
"has_genre",
"COMEDY"
],
[
"LAKE PLACID",
"release_year",
"1999"
],
[
"LIFE",
"has_genre",
"COMEDY"
],
[
"LIFE",
"has_genre",
"DRAMA"
],
[
"LIFE",
"has_tags",
"COMEDY"
],
[
"LIFE",
"release_year",
"1999"
],
[
"LOVE STINKS",
"has_genre",
"COMEDY"
],
[
"LOVE STINKS",
"release_year",
"1999"
],
[
"MAN OF THE CENTURY",
"has_genre",
"COMEDY"
],
[
"MAN OF THE CENTURY",
"release_year",
"1999"
],
[
"MAN ON THE MOON",
"has_genre",
"COMEDY"
],
[
"MAN ON THE MOON",
"has_genre",
"DRAMA"
],
[
"MAN ON THE MOON",
"release_year",
"1999"
],
[
"MANSFIELD PARK",
"has_genre",
"COMEDY"
],
[
"MANSFIELD PARK",
"has_genre",
"DRAMA"
],
[
"MANSFIELD PARK",
"release_year",
"1999"
],
[
"MICKEY BLUE EYES",
"has_genre",
"COMEDY"
],
[
"MICKEY BLUE EYES",
"has_tags",
"COMEDY"
],
[
"MICKEY BLUE EYES",
"release_year",
"1999"
],
[
"MOLLY",
"has_genre",
"COMEDY"
],
[
"MOLLY",
"has_genre",
"DRAMA"
],
[
"MOLLY",
"release_year",
"1999"
],
[
"MUMFORD",
"has_genre",
"COMEDY"
],
[
"MUMFORD",
"has_genre",
"DRAMA"
],
[
"MUMFORD",
"release_year",
"1999"
],
[
"MUPPETS FROM SPACE",
"has_genre",
"COMEDY"
],
[
"MUPPETS FROM SPACE",
"release_year",
"1999"
],
[
"MY NEIGHBORS THE YAMADAS",
"has_genre",
"COMEDY"
],
[
"MY NEIGHBORS THE YAMADAS",
"release_year",
"1999"
],
[
"MYSTERY MEN",
"has_genre",
"COMEDY"
],
[
"MYSTERY MEN",
"has_tags",
"COMEDY"
],
[
"MYSTERY MEN",
"release_year",
"1999"
],
[
"MYSTERY, ALASKA",
"has_genre",
"COMEDY"
],
[
"MYSTERY, ALASKA",
"has_genre",
"DRAMA"
],
[
"MYSTERY, ALASKA",
"release_year",
"1999"
],
[
"NEVER BEEN KISSED",
"has_genre",
"COMEDY"
],
[
"NEVER BEEN KISSED",
"release_year",
"1999"
],
[
"NEW WATERFORD GIRL",
"has_genre",
"COMEDY"
],
[
"NEW WATERFORD GIRL",
"release_year",
"1999"
],
[
"NICE GUYS SLEEP ALONE",
"has_genre",
"COMEDY"
],
[
"NICE GUYS SLEEP ALONE",
"release_year",
"1999"
],
[
"NOTTING HILL",
"has_genre",
"COMEDY"
],
[
"NOTTING HILL",
"has_tags",
"COMEDY"
],
[
"NOTTING HILL",
"release_year",
"1999"
],
[
"OFFICE SPACE",
"has_genre",
"COMEDY"
],
[
"OFFICE SPACE",
"has_tags",
"COMEDY"
],
[
"OFFICE SPACE",
"release_year",
"1999"
],
[
"PLAY IT TO THE BONE",
"has_genre",
"COMEDY"
],
[
"PLAY IT TO THE BONE",
"has_genre",
"DRAMA"
],
[
"PLAY IT TO THE BONE",
"release_year",
"1999"
],
[
"PUNCTURE",
"has_tags",
"TRUE STORY"
],
[
"PUNCTURE",
"written_by",
"PAUL DANZIGER"
],
[
"PUSHING TIN",
"has_genre",
"COMEDY"
],
[
"PUSHING TIN",
"has_genre",
"DRAMA"
],
[
"PUSHING TIN",
"release_year",
"1999"
],
[
"RUNAWAY BRIDE",
"has_genre",
"COMEDY"
],
[
"RUNAWAY BRIDE",
"release_year",
"1999"
],
[
"SAFE SEX",
"has_genre",
"COMEDY"
],
[
"SAFE SEX",
"release_year",
"1999"
],
[
"SCREWED IN TALLINN",
"has_genre",
"COMEDY"
],
[
"SCREWED IN TALLINN",
"has_genre",
"DRAMA"
],
[
"SCREWED IN TALLINN",
"release_year",
"1999"
],
[
"SEVEN GIRLFRIENDS",
"has_genre",
"COMEDY"
],
[
"SEVEN GIRLFRIENDS",
"release_year",
"1999"
],
[
"SHE'S ALL THAT",
"has_genre",
"COMEDY"
],
[
"SHE'S ALL THAT",
"has_tags",
"COMEDY"
],
[
"SHE'S ALL THAT",
"release_year",
"1999"
],
[
"SIAM SUNSET",
"has_genre",
"COMEDY"
],
[
"SIAM SUNSET",
"release_year",
"1999"
],
[
"SIMON SEZ",
"has_genre",
"COMEDY"
],
[
"SIMON SEZ",
"has_tags",
"COMEDY"
],
[
"SIMON SEZ",
"release_year",
"1999"
],
[
"SIMPLY IRRESISTIBLE",
"has_genre",
"COMEDY"
],
[
"SIMPLY IRRESISTIBLE",
"release_year",
"1999"
],
[
"SOFT TOILET SEATS",
"has_genre",
"COMEDY"
],
[
"SOFT TOILET SEATS",
"release_year",
"1999"
],
[
"SPLENDOR",
"has_genre",
"COMEDY"
],
[
"SPLENDOR",
"release_year",
"1999"
],
[
"STRANGE PLANET",
"has_genre",
"COMEDY"
],
[
"STRANGE PLANET",
"release_year",
"1999"
],
[
"STUART LITTLE",
"has_genre",
"COMEDY"
],
[
"STUART LITTLE",
"has_tags",
"COMEDY"
],
[
"STUART LITTLE",
"release_year",
"1999"
],
[
"SUPERSTAR",
"has_genre",
"COMEDY"
],
[
"SUPERSTAR",
"release_year",
"1999"
],
[
"SWEET AND LOWDOWN",
"has_genre",
"COMEDY"
],
[
"SWEET AND LOWDOWN",
"has_genre",
"DRAMA"
],
[
"SWEET AND LOWDOWN",
"release_year",
"1999"
],
[
"TEACHING MRS. TINGLE",
"has_genre",
"COMEDY"
],
[
"TEACHING MRS. TINGLE",
"release_year",
"1999"
],
[
"THE ACTRESS",
"has_genre",
"COMEDY"
],
[
"THE ACTRESS",
"has_genre",
"DRAMA"
],
[
"THE ADVENTURES OF ELMO IN GROUCHLAND",
"has_genre",
"COMEDY"
],
[
"THE ADVENTURES OF ELMO IN GROUCHLAND",
"release_year",
"1999"
],
[
"THE BACHELOR",
"has_genre",
"COMEDY"
],
[
"THE BACHELOR",
"release_year",
"1999"
],
[
"THE BEST MAN",
"has_genre",
"COMEDY"
],
[
"THE BEST MAN",
"has_genre",
"DRAMA"
],
[
"THE BEST MAN",
"release_year",
"1999"
],
[
"THE BIG KAHUNA",
"has_genre",
"COMEDY"
],
[
"THE BIG KAHUNA",
"has_genre",
"DRAMA"
],
[
"THE BIG KAHUNA",
"release_year",
"1999"
],
[
"THE BIG TEASE",
"has_genre",
"COMEDY"
],
[
"THE BIG TEASE",
"release_year",
"1999"
],
[
"THE BREAKS",
"has_genre",
"COMEDY"
],
[
"THE BREAKS",
"release_year",
"1999"
],
[
"THE INSIDER",
"has_genre",
"DRAMA"
],
[
"THE INSIDER",
"has_tags",
"DRAMA"
],
[
"THE INSIDER",
"release_year",
"1999"
],
[
"THE LOVE LETTER",
"has_genre",
"COMEDY"
],
[
"THE LOVE LETTER",
"release_year",
"1999"
],
[
"THE MATCH",
"has_genre",
"COMEDY"
],
[
"THE MATCH",
"release_year",
"1999"
],
[
"THE MUSE",
"has_genre",
"COMEDY"
],
[
"THE MUSE",
"release_year",
"1999"
],
[
"THE OTHER SISTER",
"has_genre",
"COMEDY"
],
[
"THE OTHER SISTER",
"release_year",
"1999"
],
[
"THE OUT-OF-TOWNERS",
"has_genre",
"COMEDY"
],
[
"THE OUT-OF-TOWNERS",
"release_year",
"1999"
],
[
"THE SAPPHIRES",
"has_genre",
"COMEDY"
],
[
"THE SAPPHIRES",
"has_genre",
"DRAMA"
],
[
"THE STORY OF US",
"has_genre",
"COMEDY"
],
[
"THE STORY OF US",
"has_genre",
"DRAMA"
],
[
"THE STORY OF US",
"has_tags",
"DRAMA"
],
[
"THE STORY OF US",
"release_year",
"1999"
],
[
"THE SUBURBANS",
"has_genre",
"COMEDY"
],
[
"THE SUBURBANS",
"has_genre",
"DRAMA"
],
[
"THE SUBURBANS",
"release_year",
"1999"
],
[
"THE UNDERGROUND COMEDY MOVIE",
"has_genre",
"COMEDY"
],
[
"THE UNDERGROUND COMEDY MOVIE",
"release_year",
"1999"
],
[
"THE WAITING GAME",
"has_genre",
"COMEDY"
],
[
"THE WAITING GAME",
"release_year",
"1999"
],
[
"THE WOOD",
"has_genre",
"COMEDY"
],
[
"THE WOOD",
"release_year",
"1999"
],
[
"THREE KINGS",
"has_genre",
"COMEDY"
],
[
"THREE KINGS",
"has_tags",
"COMEDY"
],
[
"THREE KINGS",
"release_year",
"1999"
],
[
"THREE TO TANGO",
"has_genre",
"COMEDY"
],
[
"THREE TO TANGO",
"release_year",
"1999"
],
[
"TIFOSI",
"has_genre",
"COMEDY"
],
[
"TIFOSI",
"release_year",
"1999"
],
[
"TOY STORY 2",
"has_genre",
"COMEDY"
],
[
"TOY STORY 2",
"release_year",
"1999"
],
[
"TRAILER PARK BOYS",
"has_genre",
"COMEDY"
],
[
"TRAILER PARK BOYS",
"release_year",
"1999"
],
[
"TRICK",
"has_genre",
"COMEDY"
],
[
"TRICK",
"release_year",
"1999"
],
[
"TRIPPIN'",
"has_genre",
"COMEDY"
],
[
"TRIPPIN'",
"release_year",
"1999"
],
[
"TRUE STORY",
"has_genre",
"DRAMA"
],
[
"TRUE STORY",
"has_tags",
"DRAMA"
],
[
"TUMBLEWEEDS",
"has_genre",
"COMEDY"
],
[
"TUMBLEWEEDS",
"has_genre",
"DRAMA"
],
[
"TUMBLEWEEDS",
"release_year",
"1999"
],
[
"WHY NOT ME?",
"has_genre",
"COMEDY"
],
[
"WHY NOT ME?",
"release_year",
"1999"
],
[
"WILD WILD WEST",
"has_genre",
"COMEDY"
],
[
"WILD WILD WEST",
"has_tags",
"COMEDY"
],
[
"WILD WILD WEST",
"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
8539, 1982
6294, ANIME
14492, DEAD MEN DON'T WEAR PLAID
19194, ENIGMA
29266, FITZCARRALDO
7498, FLIGHTPLAN
6480, GERMAN
9760, LIFE IS ALL YOU GET
18279, METROPOLIS
15145, MYSTERY
6979, PANDORUM
39284, POSSESSION
8988, PROFESSOR LAYTON AND THE ETERNAL DIVA
22384, ROOM 666
9875, THE DRAUGHTSMAN'S CONTRACT
4662, THE GOOD GERMAN
4091, THE LADY VANISHES
src, edge_attr, dst
14492, has_genre, 15145
14492, has_tags, 15145
14492, release_year, 8539
19194, has_genre, 15145
19194, in_language, 6480
29266, in_language, 6480
29266, release_year, 8539
7498, has_genre, 15145
7498, has_tags, 15145
7498, in_language, 6480
9760, in_language, 6480
18279, has_tags, 6294
18279, in_language, 6480
6979, has_genre, 15145
6979, in_language, 6480
39284, has_genre, 15145
39284, in_language, 6480
8988, has_tags, 6294
22384, in_language, 6480
22384, release_year, 8539
9875, has_genre, 15145
9875, release_year, 8539
4662, has_genre, 15145
4662, in_language, 6480
4091, has_genre, 15145
4091, in_language, 6480
Question: How are LIFE IS ALL YOU GET, PROFESSOR LAYTON AND THE ETERNAL DIVA, and THE DRAUGHTSMAN'S CONTRACT related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"LIFE IS ALL YOU GET",
"PROFESSOR LAYTON AND THE ETERNAL DIVA",
"THE DRAUGHTSMAN'S CONTRACT"
],
"valid_edges": [
[
"DEAD MEN DON'T WEAR PLAID",
"has_genre",
"MYSTERY"
],
[
"DEAD MEN DON'T WEAR PLAID",
"has_tags",
"MYSTERY"
],
[
"DEAD MEN DON'T WEAR PLAID",
"release_year",
"1982"
],
[
"ENIGMA",
"has_genre",
"MYSTERY"
],
[
"ENIGMA",
"in_language",
"GERMAN"
],
[
"FITZCARRALDO",
"in_language",
"GERMAN"
],
[
"FITZCARRALDO",
"release_year",
"1982"
],
[
"FLIGHTPLAN",
"has_genre",
"MYSTERY"
],
[
"FLIGHTPLAN",
"has_tags",
"MYSTERY"
],
[
"FLIGHTPLAN",
"in_language",
"GERMAN"
],
[
"LIFE IS ALL YOU GET",
"in_language",
"GERMAN"
],
[
"METROPOLIS",
"has_tags",
"ANIME"
],
[
"METROPOLIS",
"in_language",
"GERMAN"
],
[
"PANDORUM",
"has_genre",
"MYSTERY"
],
[
"PANDORUM",
"in_language",
"GERMAN"
],
[
"POSSESSION",
"has_genre",
"MYSTERY"
],
[
"POSSESSION",
"in_language",
"GERMAN"
],
[
"PROFESSOR LAYTON AND THE ETERNAL DIVA",
"has_tags",
"ANIME"
],
[
"ROOM 666",
"in_language",
"GERMAN"
],
[
"ROOM 666",
"release_year",
"1982"
],
[
"THE DRAUGHTSMAN'S CONTRACT",
"has_genre",
"MYSTERY"
],
[
"THE DRAUGHTSMAN'S CONTRACT",
"release_year",
"1982"
],
[
"THE GOOD GERMAN",
"has_genre",
"MYSTERY"
],
[
"THE GOOD GERMAN",
"in_language",
"GERMAN"
],
[
"THE LADY VANISHES",
"has_genre",
"MYSTERY"
],
[
"THE LADY VANISHES",
"in_language",
"GERMAN"
]
]
}
|
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
11, 1940
25662, DR. CYCLOPS
38055, GEORGE RAFT
5870, HORROR
26724, JEFF KOBER
30256, THE FIRST POWER
17566, THEY DRIVE BY NIGHT
24864, THOMAS COLEY
src, edge_attr, dst
25662, has_genre, 5870
25662, release_year, 11
25662, starred_actors, 24864
30256, has_genre, 5870
30256, starred_actors, 26724
17566, release_year, 11
17566, starred_actors, 38055
Question: For what reason are GEORGE RAFT, JEFF KOBER, and THOMAS COLEY associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"GEORGE RAFT",
"JEFF KOBER",
"THOMAS COLEY"
],
"valid_edges": [
[
"DR. CYCLOPS",
"has_genre",
"HORROR"
],
[
"DR. CYCLOPS",
"release_year",
"1940"
],
[
"DR. CYCLOPS",
"starred_actors",
"THOMAS COLEY"
],
[
"THE FIRST POWER",
"has_genre",
"HORROR"
],
[
"THE FIRST POWER",
"starred_actors",
"JEFF KOBER"
],
[
"THEY DRIVE BY NIGHT",
"release_year",
"1940"
],
[
"THEY DRIVE BY NIGHT",
"starred_actors",
"GEORGE RAFT"
]
]
}
|
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
18131, BABE
18018, CAVALCADE
25760, DAVID HINES
36212, DRAMA
1178, WHORE
src, edge_attr, dst
18131, has_genre, 36212
18018, has_genre, 36212
1178, has_genre, 36212
1178, written_by, 25760
Question: In what context are BABE, CAVALCADE, and DAVID HINES connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"BABE",
"CAVALCADE",
"DAVID HINES"
],
"valid_edges": [
[
"BABE",
"has_genre",
"DRAMA"
],
[
"CAVALCADE",
"has_genre",
"DRAMA"
],
[
"WHORE",
"has_genre",
"DRAMA"
],
[
"WHORE",
"written_by",
"DAVID HINES"
]
]
}
|
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
10702, 1991
22088, A BRIDGE TOO FAR
4763, ADVENTURE
20936, AGUIRRE, THE WRATH OF GOD
31349, ALISTAIR MACLEAN
8284, ANTHONY QUINN
18310, AROUND THE WORLD IN 80 DAYS
31449, BARABBAS
14981, BREAKHEART PASS
554, CABEZA DE VACA
16220, CAPTAIN HORATIO HORNBLOWER R.N.
19194, ENIGMA
30030, EUROPA
2449, EUROTRIP
36066, FANTASY
6853, FIREWALKER
7498, FLIGHTPLAN
6480, GERMAN
8287, GREGORY PECK
15744, HOOK
7458, HUCKLEBERRY FINN
19805, J. LEE THOMPSON
22600, JUDGMENT AT NUREMBERG
30936, KAFKA
14156, KING SOLOMON'S MINES
31533, L. FRANK BAUM
560, LIEBESTRAUM
30157, LOLA
30042, MORTAL THOUGHTS
35462, MYSTERIOUS ISLAND
15145, MYSTERY
38235, NEKROMANTIK 2
39185, NORTH WEST FRONTIER
27106, OZ
15521, OZ THE GREAT AND POWERFUL
6979, PANDORUM
25824, PARADISE
25498, PARIS BELONGS TO US
39284, POSSESSION
31392, RETURN TO OZ
31525, RETURN TO THE BLUE LAGOON
35586, SAHARA
3354, THE BROTHERS GRIMM
3280, THE BUCCANEER
23804, THE COMANCHEROS
17688, THE DEVIL AT 4 O'CLOCK
10001, THE EAGLE HAS LANDED
4662, THE GOOD GERMAN
9166, THE GUNS OF NAVARONE
32856, THE KING AND FOUR QUEENS
4091, THE LADY VANISHES
22393, THE MAGUS
39581, THE WIZ
28776, THE WIZARD OF OZ
37831, TOWN WITHOUT PITY
32079, ULYSSES
33802, UNTIL THE END OF THE WORLD
2175, VON RYAN'S EXPRESS
24117, VOYAGER
29631, WHITE FANG
24155, WORLD WAR II
src, edge_attr, dst
22088, has_tags, 24155
22088, in_language, 6480
20936, has_genre, 4763
20936, has_tags, 4763
20936, has_tags, 6480
20936, in_language, 6480
18310, has_genre, 4763
18310, in_language, 6480
31449, release_year, 22772
31449, starred_actors, 8284
14981, has_tags, 4763
14981, written_by, 31349
554, has_genre, 4763
554, release_year, 10702
16220, has_genre, 4763
16220, has_tags, 8287
16220, starred_actors, 8287
19194, has_genre, 15145
19194, has_tags, 24155
19194, in_language, 6480
30030, has_tags, 24155
30030, in_language, 6480
30030, release_year, 10702
2449, has_genre, 4763
2449, in_language, 6480
6853, directed_by, 19805
6853, has_genre, 4763
7498, has_genre, 15145
7498, has_tags, 15145
7498, in_language, 6480
15744, has_genre, 4763
15744, release_year, 10702
7458, directed_by, 19805
7458, has_genre, 4763
22600, in_language, 6480
22600, release_year, 22772
30936, has_genre, 15145
30936, release_year, 10702
14156, directed_by, 19805
14156, has_genre, 4763
14156, has_tags, 4763
560, has_genre, 15145
560, release_year, 10702
30157, in_language, 6480
30157, release_year, 22772
30042, has_genre, 15145
30042, release_year, 10702
35462, has_genre, 4763
35462, has_tags, 4763
35462, release_year, 22772
38235, in_language, 6480
38235, release_year, 10702
39185, directed_by, 19805
39185, has_genre, 4763
39185, has_tags, 19805
15521, has_genre, 4763
15521, has_genre, 36066
15521, has_tags, 36066
15521, has_tags, 27106
15521, written_by, 31533
6979, has_genre, 15145
6979, in_language, 6480
25824, has_genre, 4763
25824, release_year, 10702
25498, has_genre, 15145
25498, release_year, 22772
39284, has_genre, 15145
39284, in_language, 6480
31392, has_genre, 4763
31392, has_genre, 36066
31392, has_tags, 4763
31392, has_tags, 36066
31392, has_tags, 27106
31392, written_by, 31533
31525, has_genre, 4763
31525, release_year, 10702
35586, has_genre, 4763
35586, has_tags, 24155
3354, has_genre, 4763
3354, has_tags, 4763
3354, in_language, 6480
3280, directed_by, 8284
3280, has_genre, 4763
23804, has_genre, 4763
23804, release_year, 22772
17688, has_genre, 4763
17688, release_year, 22772
10001, has_tags, 6480
10001, has_tags, 24155
10001, in_language, 6480
4662, has_genre, 15145
4662, in_language, 6480
9166, directed_by, 19805
9166, has_genre, 4763
9166, has_tags, 8284
9166, has_tags, 19805
9166, has_tags, 24155
9166, in_language, 6480
9166, release_year, 22772
9166, starred_actors, 8284
9166, starred_actors, 8287
9166, written_by, 31349
32856, has_genre, 4763
32856, has_genre, 15145
4091, has_genre, 15145
4091, in_language, 6480
22393, has_genre, 15145
22393, starred_actors, 8284
39581, has_genre, 4763
39581, has_genre, 36066
39581, has_tags, 27106
39581, written_by, 31533
28776, has_genre, 36066
28776, has_tags, 36066
28776, has_tags, 27106
28776, written_by, 31533
37831, in_language, 6480
37831, release_year, 22772
32079, has_genre, 4763
32079, starred_actors, 8284
33802, has_tags, 6480
33802, in_language, 6480
33802, release_year, 10702
2175, has_genre, 4763
2175, has_tags, 24155
2175, in_language, 6480
24117, in_language, 6480
24117, release_year, 10702
29631, has_genre, 4763
29631, release_year, 10702
Question: How are KAFKA, L. FRANK BAUM, and THE GUNS OF NAVARONE related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"KAFKA",
"L. FRANK BAUM",
"THE GUNS OF NAVARONE"
],
"valid_edges": [
[
"A BRIDGE TOO FAR",
"has_tags",
"WORLD WAR II"
],
[
"A BRIDGE TOO FAR",
"in_language",
"GERMAN"
],
[
"AGUIRRE, THE WRATH OF GOD",
"has_genre",
"ADVENTURE"
],
[
"AGUIRRE, THE WRATH OF GOD",
"has_tags",
"ADVENTURE"
],
[
"AGUIRRE, THE WRATH OF GOD",
"has_tags",
"GERMAN"
],
[
"AGUIRRE, THE WRATH OF GOD",
"in_language",
"GERMAN"
],
[
"AROUND THE WORLD IN 80 DAYS",
"has_genre",
"ADVENTURE"
],
[
"AROUND THE WORLD IN 80 DAYS",
"in_language",
"GERMAN"
],
[
"BARABBAS",
"release_year",
"1961"
],
[
"BARABBAS",
"starred_actors",
"ANTHONY QUINN"
],
[
"BREAKHEART PASS",
"has_tags",
"ADVENTURE"
],
[
"BREAKHEART PASS",
"written_by",
"ALISTAIR MACLEAN"
],
[
"CABEZA DE VACA",
"has_genre",
"ADVENTURE"
],
[
"CABEZA DE VACA",
"release_year",
"1991"
],
[
"CAPTAIN HORATIO HORNBLOWER R.N.",
"has_genre",
"ADVENTURE"
],
[
"CAPTAIN HORATIO HORNBLOWER R.N.",
"has_tags",
"GREGORY PECK"
],
[
"CAPTAIN HORATIO HORNBLOWER R.N.",
"starred_actors",
"GREGORY PECK"
],
[
"ENIGMA",
"has_genre",
"MYSTERY"
],
[
"ENIGMA",
"has_tags",
"WORLD WAR II"
],
[
"ENIGMA",
"in_language",
"GERMAN"
],
[
"EUROPA",
"has_tags",
"WORLD WAR II"
],
[
"EUROPA",
"in_language",
"GERMAN"
],
[
"EUROPA",
"release_year",
"1991"
],
[
"EUROTRIP",
"has_genre",
"ADVENTURE"
],
[
"EUROTRIP",
"in_language",
"GERMAN"
],
[
"FIREWALKER",
"directed_by",
"J. LEE THOMPSON"
],
[
"FIREWALKER",
"has_genre",
"ADVENTURE"
],
[
"FLIGHTPLAN",
"has_genre",
"MYSTERY"
],
[
"FLIGHTPLAN",
"has_tags",
"MYSTERY"
],
[
"FLIGHTPLAN",
"in_language",
"GERMAN"
],
[
"HOOK",
"has_genre",
"ADVENTURE"
],
[
"HOOK",
"release_year",
"1991"
],
[
"HUCKLEBERRY FINN",
"directed_by",
"J. LEE THOMPSON"
],
[
"HUCKLEBERRY FINN",
"has_genre",
"ADVENTURE"
],
[
"JUDGMENT AT NUREMBERG",
"in_language",
"GERMAN"
],
[
"JUDGMENT AT NUREMBERG",
"release_year",
"1961"
],
[
"KAFKA",
"has_genre",
"MYSTERY"
],
[
"KAFKA",
"release_year",
"1991"
],
[
"KING SOLOMON'S MINES",
"directed_by",
"J. LEE THOMPSON"
],
[
"KING SOLOMON'S MINES",
"has_genre",
"ADVENTURE"
],
[
"KING SOLOMON'S MINES",
"has_tags",
"ADVENTURE"
],
[
"LIEBESTRAUM",
"has_genre",
"MYSTERY"
],
[
"LIEBESTRAUM",
"release_year",
"1991"
],
[
"LOLA",
"in_language",
"GERMAN"
],
[
"LOLA",
"release_year",
"1961"
],
[
"MORTAL THOUGHTS",
"has_genre",
"MYSTERY"
],
[
"MORTAL THOUGHTS",
"release_year",
"1991"
],
[
"MYSTERIOUS ISLAND",
"has_genre",
"ADVENTURE"
],
[
"MYSTERIOUS ISLAND",
"has_tags",
"ADVENTURE"
],
[
"MYSTERIOUS ISLAND",
"release_year",
"1961"
],
[
"NEKROMANTIK 2",
"in_language",
"GERMAN"
],
[
"NEKROMANTIK 2",
"release_year",
"1991"
],
[
"NORTH WEST FRONTIER",
"directed_by",
"J. LEE THOMPSON"
],
[
"NORTH WEST FRONTIER",
"has_genre",
"ADVENTURE"
],
[
"NORTH WEST FRONTIER",
"has_tags",
"J. LEE THOMPSON"
],
[
"OZ THE GREAT AND POWERFUL",
"has_genre",
"ADVENTURE"
],
[
"OZ THE GREAT AND POWERFUL",
"has_genre",
"FANTASY"
],
[
"OZ THE GREAT AND POWERFUL",
"has_tags",
"FANTASY"
],
[
"OZ THE GREAT AND POWERFUL",
"has_tags",
"OZ"
],
[
"OZ THE GREAT AND POWERFUL",
"written_by",
"L. FRANK BAUM"
],
[
"PANDORUM",
"has_genre",
"MYSTERY"
],
[
"PANDORUM",
"in_language",
"GERMAN"
],
[
"PARADISE",
"has_genre",
"ADVENTURE"
],
[
"PARADISE",
"release_year",
"1991"
],
[
"PARIS BELONGS TO US",
"has_genre",
"MYSTERY"
],
[
"PARIS BELONGS TO US",
"release_year",
"1961"
],
[
"POSSESSION",
"has_genre",
"MYSTERY"
],
[
"POSSESSION",
"in_language",
"GERMAN"
],
[
"RETURN TO OZ",
"has_genre",
"ADVENTURE"
],
[
"RETURN TO OZ",
"has_genre",
"FANTASY"
],
[
"RETURN TO OZ",
"has_tags",
"ADVENTURE"
],
[
"RETURN TO OZ",
"has_tags",
"FANTASY"
],
[
"RETURN TO OZ",
"has_tags",
"OZ"
],
[
"RETURN TO OZ",
"written_by",
"L. FRANK BAUM"
],
[
"RETURN TO THE BLUE LAGOON",
"has_genre",
"ADVENTURE"
],
[
"RETURN TO THE BLUE LAGOON",
"release_year",
"1991"
],
[
"SAHARA",
"has_genre",
"ADVENTURE"
],
[
"SAHARA",
"has_tags",
"WORLD WAR II"
],
[
"THE BROTHERS GRIMM",
"has_genre",
"ADVENTURE"
],
[
"THE BROTHERS GRIMM",
"has_tags",
"ADVENTURE"
],
[
"THE BROTHERS GRIMM",
"in_language",
"GERMAN"
],
[
"THE BUCCANEER",
"directed_by",
"ANTHONY QUINN"
],
[
"THE BUCCANEER",
"has_genre",
"ADVENTURE"
],
[
"THE COMANCHEROS",
"has_genre",
"ADVENTURE"
],
[
"THE COMANCHEROS",
"release_year",
"1961"
],
[
"THE DEVIL AT 4 O'CLOCK",
"has_genre",
"ADVENTURE"
],
[
"THE DEVIL AT 4 O'CLOCK",
"release_year",
"1961"
],
[
"THE EAGLE HAS LANDED",
"has_tags",
"GERMAN"
],
[
"THE EAGLE HAS LANDED",
"has_tags",
"WORLD WAR II"
],
[
"THE EAGLE HAS LANDED",
"in_language",
"GERMAN"
],
[
"THE GOOD GERMAN",
"has_genre",
"MYSTERY"
],
[
"THE GOOD GERMAN",
"in_language",
"GERMAN"
],
[
"THE GUNS OF NAVARONE",
"directed_by",
"J. LEE THOMPSON"
],
[
"THE GUNS OF NAVARONE",
"has_genre",
"ADVENTURE"
],
[
"THE GUNS OF NAVARONE",
"has_tags",
"ANTHONY QUINN"
],
[
"THE GUNS OF NAVARONE",
"has_tags",
"J. LEE THOMPSON"
],
[
"THE GUNS OF NAVARONE",
"has_tags",
"WORLD WAR II"
],
[
"THE GUNS OF NAVARONE",
"in_language",
"GERMAN"
],
[
"THE GUNS OF NAVARONE",
"release_year",
"1961"
],
[
"THE GUNS OF NAVARONE",
"starred_actors",
"ANTHONY QUINN"
],
[
"THE GUNS OF NAVARONE",
"starred_actors",
"GREGORY PECK"
],
[
"THE GUNS OF NAVARONE",
"written_by",
"ALISTAIR MACLEAN"
],
[
"THE KING AND FOUR QUEENS",
"has_genre",
"ADVENTURE"
],
[
"THE KING AND FOUR QUEENS",
"has_genre",
"MYSTERY"
],
[
"THE LADY VANISHES",
"has_genre",
"MYSTERY"
],
[
"THE LADY VANISHES",
"in_language",
"GERMAN"
],
[
"THE MAGUS",
"has_genre",
"MYSTERY"
],
[
"THE MAGUS",
"starred_actors",
"ANTHONY QUINN"
],
[
"THE WIZ",
"has_genre",
"ADVENTURE"
],
[
"THE WIZ",
"has_genre",
"FANTASY"
],
[
"THE WIZ",
"has_tags",
"OZ"
],
[
"THE WIZ",
"written_by",
"L. FRANK BAUM"
],
[
"THE WIZARD OF OZ",
"has_genre",
"FANTASY"
],
[
"THE WIZARD OF OZ",
"has_tags",
"FANTASY"
],
[
"THE WIZARD OF OZ",
"has_tags",
"OZ"
],
[
"THE WIZARD OF OZ",
"written_by",
"L. FRANK BAUM"
],
[
"TOWN WITHOUT PITY",
"in_language",
"GERMAN"
],
[
"TOWN WITHOUT PITY",
"release_year",
"1961"
],
[
"ULYSSES",
"has_genre",
"ADVENTURE"
],
[
"ULYSSES",
"starred_actors",
"ANTHONY QUINN"
],
[
"UNTIL THE END OF THE WORLD",
"has_tags",
"GERMAN"
],
[
"UNTIL THE END OF THE WORLD",
"in_language",
"GERMAN"
],
[
"UNTIL THE END OF THE WORLD",
"release_year",
"1991"
],
[
"VON RYAN'S EXPRESS",
"has_genre",
"ADVENTURE"
],
[
"VON RYAN'S EXPRESS",
"has_tags",
"WORLD WAR II"
],
[
"VON RYAN'S EXPRESS",
"in_language",
"GERMAN"
],
[
"VOYAGER",
"in_language",
"GERMAN"
],
[
"VOYAGER",
"release_year",
"1991"
],
[
"WHITE FANG",
"has_genre",
"ADVENTURE"
],
[
"WHITE FANG",
"release_year",
"1991"
]
]
}
|
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
36212, DRAMA
27629, GRASS
26966, GREG SESTERO
33520, GREGORY RATOFF
30299, I WAS AN ADVENTURESS
116, MARIJUANA
8639, RETRO PUPPET MASTER
30906, THE ROOM
src, edge_attr, dst
27629, has_tags, 116
27629, release_year, 8486
30299, directed_by, 33520
30299, has_genre, 36212
8639, release_year, 8486
8639, starred_actors, 26966
30906, has_genre, 36212
30906, has_tags, 26966
30906, starred_actors, 26966
Question: In what context are GREG SESTERO, GREGORY RATOFF, and MARIJUANA connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"GREG SESTERO",
"GREGORY RATOFF",
"MARIJUANA"
],
"valid_edges": [
[
"GRASS",
"has_tags",
"MARIJUANA"
],
[
"GRASS",
"release_year",
"1999"
],
[
"I WAS AN ADVENTURESS",
"directed_by",
"GREGORY RATOFF"
],
[
"I WAS AN ADVENTURESS",
"has_genre",
"DRAMA"
],
[
"RETRO PUPPET MASTER",
"release_year",
"1999"
],
[
"RETRO PUPPET MASTER",
"starred_actors",
"GREG SESTERO"
],
[
"THE ROOM",
"has_genre",
"DRAMA"
],
[
"THE ROOM",
"has_tags",
"GREG SESTERO"
],
[
"THE ROOM",
"starred_actors",
"GREG SESTERO"
]
]
}
|
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
3536, ASS BACKWARDS
13203, CHRIS NELSON
30463, COMEDY
13841, DATE AND SWITCH
5163, MAMMA MIA!
761, PHYLLIDA LLOYD
7786, STAND-IN
15432, TAY GARNETT
src, edge_attr, dst
3536, directed_by, 13203
3536, has_genre, 30463
13841, directed_by, 13203
13841, has_genre, 30463
5163, directed_by, 761
5163, has_genre, 30463
7786, directed_by, 15432
7786, has_genre, 30463
Question: In what context are CHRIS NELSON, PHYLLIDA LLOYD, and TAY GARNETT connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"CHRIS NELSON",
"PHYLLIDA LLOYD",
"TAY GARNETT"
],
"valid_edges": [
[
"ASS BACKWARDS",
"directed_by",
"CHRIS NELSON"
],
[
"ASS BACKWARDS",
"has_genre",
"COMEDY"
],
[
"DATE AND SWITCH",
"directed_by",
"CHRIS NELSON"
],
[
"DATE AND SWITCH",
"has_genre",
"COMEDY"
],
[
"MAMMA MIA!",
"directed_by",
"PHYLLIDA LLOYD"
],
[
"MAMMA MIA!",
"has_genre",
"COMEDY"
],
[
"STAND-IN",
"directed_by",
"TAY GARNETT"
],
[
"STAND-IN",
"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
35187, 1948
2763, BLOOD ON THE MOON
1637, BOYZ N THE HOOD
12628, EASTERN PROMISES
11565, GOOD
20941, HAMLET
18773, JOHN SINGLETON
16206, RUSSIAN
26916, VIGGO MORTENSEN
src, edge_attr, dst
2763, release_year, 35187
1637, directed_by, 18773
1637, has_imdb_rating, 11565
1637, has_tags, 18773
1637, written_by, 18773
12628, has_tags, 16206
12628, has_tags, 26916
12628, in_language, 16206
11565, starred_actors, 26916
20941, in_language, 16206
20941, release_year, 35187
Question: How are BLOOD ON THE MOON, EASTERN PROMISES, and JOHN SINGLETON related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"BLOOD ON THE MOON",
"EASTERN PROMISES",
"JOHN SINGLETON"
],
"valid_edges": [
[
"BLOOD ON THE MOON",
"release_year",
"1948"
],
[
"BOYZ N THE HOOD",
"directed_by",
"JOHN SINGLETON"
],
[
"BOYZ N THE HOOD",
"has_imdb_rating",
"GOOD"
],
[
"BOYZ N THE HOOD",
"has_tags",
"JOHN SINGLETON"
],
[
"BOYZ N THE HOOD",
"written_by",
"JOHN SINGLETON"
],
[
"EASTERN PROMISES",
"has_tags",
"RUSSIAN"
],
[
"EASTERN PROMISES",
"has_tags",
"VIGGO MORTENSEN"
],
[
"EASTERN PROMISES",
"in_language",
"RUSSIAN"
],
[
"GOOD",
"starred_actors",
"VIGGO MORTENSEN"
],
[
"HAMLET",
"in_language",
"RUSSIAN"
],
[
"HAMLET",
"release_year",
"1948"
]
]
}
|
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
20233, ANTONIONI
36212, DRAMA
20170, DUTCHMAN
16200, ITALIAN
4832, L'AVVENTURA
38326, L'ECLISSE
32844, LA NOTTE
10551, MICHELANGELO ANTONIONI
6964, MONICA VITTI
23686, RED DESERT
14415, THE WILD LIFE
src, edge_attr, dst
20170, has_genre, 36212
4832, directed_by, 10551
4832, has_tags, 20233
4832, has_tags, 16200
4832, has_tags, 10551
4832, in_language, 16200
4832, starred_actors, 6964
4832, written_by, 10551
38326, directed_by, 10551
38326, has_genre, 36212
38326, has_tags, 20233
38326, has_tags, 10551
38326, in_language, 16200
38326, starred_actors, 6964
38326, written_by, 10551
32844, directed_by, 10551
32844, has_genre, 36212
32844, has_tags, 20233
32844, has_tags, 10551
32844, in_language, 16200
32844, starred_actors, 6964
32844, written_by, 10551
23686, directed_by, 10551
23686, has_tags, 10551
23686, in_language, 16200
23686, starred_actors, 6964
23686, written_by, 10551
14415, has_genre, 36212
Question: For what reason are DUTCHMAN, MONICA VITTI, and THE WILD LIFE associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"DUTCHMAN",
"MONICA VITTI",
"THE WILD LIFE"
],
"valid_edges": [
[
"DUTCHMAN",
"has_genre",
"DRAMA"
],
[
"L'AVVENTURA",
"directed_by",
"MICHELANGELO ANTONIONI"
],
[
"L'AVVENTURA",
"has_tags",
"ANTONIONI"
],
[
"L'AVVENTURA",
"has_tags",
"ITALIAN"
],
[
"L'AVVENTURA",
"has_tags",
"MICHELANGELO ANTONIONI"
],
[
"L'AVVENTURA",
"in_language",
"ITALIAN"
],
[
"L'AVVENTURA",
"starred_actors",
"MONICA VITTI"
],
[
"L'AVVENTURA",
"written_by",
"MICHELANGELO ANTONIONI"
],
[
"L'ECLISSE",
"directed_by",
"MICHELANGELO ANTONIONI"
],
[
"L'ECLISSE",
"has_genre",
"DRAMA"
],
[
"L'ECLISSE",
"has_tags",
"ANTONIONI"
],
[
"L'ECLISSE",
"has_tags",
"MICHELANGELO ANTONIONI"
],
[
"L'ECLISSE",
"in_language",
"ITALIAN"
],
[
"L'ECLISSE",
"starred_actors",
"MONICA VITTI"
],
[
"L'ECLISSE",
"written_by",
"MICHELANGELO ANTONIONI"
],
[
"LA NOTTE",
"directed_by",
"MICHELANGELO ANTONIONI"
],
[
"LA NOTTE",
"has_genre",
"DRAMA"
],
[
"LA NOTTE",
"has_tags",
"ANTONIONI"
],
[
"LA NOTTE",
"has_tags",
"MICHELANGELO ANTONIONI"
],
[
"LA NOTTE",
"in_language",
"ITALIAN"
],
[
"LA NOTTE",
"starred_actors",
"MONICA VITTI"
],
[
"LA NOTTE",
"written_by",
"MICHELANGELO ANTONIONI"
],
[
"RED DESERT",
"directed_by",
"MICHELANGELO ANTONIONI"
],
[
"RED DESERT",
"has_tags",
"MICHELANGELO ANTONIONI"
],
[
"RED DESERT",
"in_language",
"ITALIAN"
],
[
"RED DESERT",
"starred_actors",
"MONICA VITTI"
],
[
"RED DESERT",
"written_by",
"MICHELANGELO ANTONIONI"
],
[
"THE WILD LIFE",
"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
37608, AUSTRALIA
33360, CANDY
18942, DÉSIRÉE
14887, ED HARRIS
38940, HENRY KOSTER
21474, MARLON BRANDO
9336, NICOLE KIDMAN
11713, THE HOURS
38682, THE INSPECTOR GENERAL
src, edge_attr, dst
37608, has_tags, 37608
37608, has_tags, 9336
33360, has_tags, 37608
33360, starred_actors, 21474
18942, directed_by, 38940
18942, starred_actors, 21474
11713, has_tags, 14887
11713, has_tags, 9336
11713, starred_actors, 14887
11713, starred_actors, 9336
38682, directed_by, 38940
38682, has_tags, 38940
Question: In what context are CANDY, ED HARRIS, and THE INSPECTOR GENERAL connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"CANDY",
"ED HARRIS",
"THE INSPECTOR GENERAL"
],
"valid_edges": [
[
"AUSTRALIA",
"has_tags",
"AUSTRALIA"
],
[
"AUSTRALIA",
"has_tags",
"NICOLE KIDMAN"
],
[
"CANDY",
"has_tags",
"AUSTRALIA"
],
[
"CANDY",
"starred_actors",
"MARLON BRANDO"
],
[
"DÉSIRÉE",
"directed_by",
"HENRY KOSTER"
],
[
"DÉSIRÉE",
"starred_actors",
"MARLON BRANDO"
],
[
"THE HOURS",
"has_tags",
"ED HARRIS"
],
[
"THE HOURS",
"has_tags",
"NICOLE KIDMAN"
],
[
"THE HOURS",
"starred_actors",
"ED HARRIS"
],
[
"THE HOURS",
"starred_actors",
"NICOLE KIDMAN"
],
[
"THE INSPECTOR GENERAL",
"directed_by",
"HENRY KOSTER"
],
[
"THE INSPECTOR GENERAL",
"has_tags",
"HENRY KOSTER"
]
]
}
|
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
17505, A LOW DOWN DIRTY SHAME
431, A MAN OF NO IMPORTANCE
36629, A MILLION TO JUAN
29838, A SIMPLE TWIST OF FATE
8837, AIRHEADS
34608, ALAN BENNETT
27410, ANGELS IN THE OUTFIELD
24704, ANGIE
35639, BABY'S DAY OUT
34587, BAD TASTE
1868, BARCELONA
10890, BEVERLY HILLS COP III
31778, BLACK SHEEP
29301, BLANK CHECK
24639, BLANKMAN
34318, CABIN BOY
22539, CAR 54, WHERE ARE YOU?
26883, CEMETERY MAN
16350, CHASERS
35468, CLEAN SLATE
35351, CLERKS
9387, CLIFFORD
30463, COMEDY
21391, CRACKERJACK
25978, DEADLY ADVICE
13424, DON'T DRINK THE WATER
3893, ED WOOD
26709, ERNEST GOES TO SCHOOL
20441, EXIT TO EDEN
24028, FLOUNDERING
22371, FORREST GUMP
6215, FOUR WEDDINGS AND A FUNERAL
36927, FROM BEIJING WITH LOVE
34775, GETTING EVEN WITH DAD
9142, GETTING IN
5585, GREEDY
34489, GUARDING TESS
25670, HAIL CAESAR
20214, HEAVENLY CREATURES
20990, HOLY MATRIMONY
24023, HOUSEBOUND
34412, I LIKE IT LIKE THAT
13163, I LOVE TROUBLE
18096, I.Q.
24832, IN THE ARMY NOW
14341, IT COULD HAPPEN TO YOU
39987, IT RUNS IN THE FAMILY
37202, IT'S PAT
29404, JUNIOR
14878, KABHI HAAN KABHI NAA
18648, LEPRECHAUN 2
19862, LIGHTNING JACK
16780, LITTLE GIANTS
25283, MAVERICK
12620, MILK MONEY
12371, MIXED NUTS
9817, MONKEY TROUBLE
25796, MURIEL'S WEDDING
28963, MY GIRL 2
25168, NEW ZEALAND
760, NICHOLAS HYTNER
4398, NOBODY'S FOOL
32358, NORTH
29694, ONCE WERE WARRIORS
36883, ONLY YOU
24732, PCU
11042, PRINCESS CARABOO
26174, PULP FICTION
22395, RADIOLAND MURDERS
26180, REALITY BITES
25577, RENAISSANCE MAN
24642, SERIAL MOM
1374, SLEEP WITH ME
6144, SPANKING THE MONKEY
7010, SPEECHLESS
35026, STAGGERED
20877, SWIMMING WITH SHARKS
2567, TAMMY AND THE T-REX
25270, THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT
30090, THE AIR UP THERE
3084, THE CAT'S-PAW
13685, THE CHASE
22164, THE COWBOY WAY
9215, THE FAVOR
17956, THE FLINTSTONES
15420, THE HISTORY BOYS
10878, THE HUDSUCKER PROXY
38210, THE INKWELL
38550, THE LITTLE RASCALS
9915, THE MADNESS OF KING GEORGE
23802, THE MASK
29233, THE MONSTER
33982, THE PAPER
26061, THE REF
13917, THE ROAD TO WELLVILLE
17314, THE SANTA CLAUSE
36289, THE SCOUT
33905, THE SEARCH FOR ONE-EYE JIMMY
4767, THE SUM OF US
16762, THREESOME
18195, TRAPPED IN PARADISE
12860, TRUE LIES
33767, TWIN SITTERS
26509, VIOLENCE
15419, WHAT WE DO IN THE SHADOWS
39623, WITH HONORS
src, edge_attr, dst
17505, has_genre, 30463
17505, release_year, 26257
431, has_genre, 30463
431, release_year, 26257
36629, has_genre, 30463
36629, release_year, 26257
29838, has_genre, 30463
29838, release_year, 26257
8837, has_genre, 30463
8837, has_tags, 30463
8837, release_year, 26257
27410, has_genre, 30463
27410, release_year, 26257
24704, has_genre, 30463
24704, release_year, 26257
35639, has_genre, 30463
35639, release_year, 26257
34587, has_genre, 30463
34587, has_tags, 25168
1868, has_genre, 30463
1868, release_year, 26257
10890, has_genre, 30463
10890, has_tags, 30463
10890, release_year, 26257
31778, has_genre, 30463
31778, has_tags, 30463
31778, has_tags, 25168
29301, has_genre, 30463
29301, release_year, 26257
24639, has_genre, 30463
24639, release_year, 26257
34318, has_genre, 30463
34318, release_year, 26257
22539, has_genre, 30463
22539, release_year, 26257
26883, has_genre, 30463
26883, release_year, 26257
16350, has_genre, 30463
16350, release_year, 26257
35468, has_genre, 30463
35468, release_year, 26257
35351, has_genre, 30463
35351, has_tags, 30463
35351, release_year, 26257
9387, has_genre, 30463
9387, release_year, 26257
21391, has_genre, 30463
21391, release_year, 26257
25978, has_genre, 30463
25978, release_year, 26257
13424, has_genre, 30463
13424, release_year, 26257
3893, has_genre, 30463
3893, release_year, 26257
26709, has_genre, 30463
26709, release_year, 26257
20441, has_genre, 30463
20441, release_year, 26257
24028, has_genre, 30463
24028, release_year, 26257
22371, has_tags, 30463
22371, release_year, 26257
6215, has_genre, 30463
6215, has_tags, 30463
6215, release_year, 26257
36927, has_genre, 30463
36927, release_year, 26257
34775, has_genre, 30463
34775, release_year, 26257
9142, has_genre, 30463
9142, release_year, 26257
5585, has_genre, 30463
5585, release_year, 26257
34489, has_genre, 30463
34489, release_year, 26257
25670, has_genre, 30463
25670, release_year, 26257
20214, has_tags, 25168
20214, release_year, 26257
20990, has_genre, 30463
20990, release_year, 26257
24023, has_genre, 30463
24023, has_tags, 25168
34412, has_genre, 30463
34412, release_year, 26257
13163, has_genre, 30463
13163, release_year, 26257
18096, has_genre, 30463
18096, release_year, 26257
24832, has_genre, 30463
24832, release_year, 26257
14341, has_genre, 30463
14341, has_tags, 30463
14341, release_year, 26257
39987, has_genre, 30463
39987, release_year, 26257
37202, has_genre, 30463
37202, release_year, 26257
29404, has_genre, 30463
29404, release_year, 26257
14878, has_genre, 30463
14878, release_year, 26257
18648, has_genre, 30463
18648, release_year, 26257
19862, has_genre, 30463
19862, release_year, 26257
16780, has_genre, 30463
16780, release_year, 26257
25283, has_genre, 30463
25283, has_tags, 30463
25283, release_year, 26257
12620, has_genre, 30463
12620, release_year, 26257
12371, has_genre, 30463
12371, release_year, 26257
9817, has_genre, 30463
9817, release_year, 26257
25796, has_genre, 30463
25796, has_tags, 30463
25796, release_year, 26257
28963, has_genre, 30463
28963, release_year, 26257
4398, has_genre, 30463
4398, release_year, 26257
32358, has_genre, 30463
32358, release_year, 26257
29694, has_tags, 25168
29694, has_tags, 26509
29694, release_year, 26257
36883, has_genre, 30463
36883, release_year, 26257
24732, has_genre, 30463
24732, release_year, 26257
11042, has_genre, 30463
11042, release_year, 26257
26174, has_tags, 30463
26174, has_tags, 26509
26174, release_year, 26257
22395, has_genre, 30463
22395, release_year, 26257
26180, has_genre, 30463
26180, release_year, 26257
25577, has_genre, 30463
25577, release_year, 26257
24642, has_genre, 30463
24642, has_tags, 30463
24642, release_year, 26257
1374, has_genre, 30463
1374, release_year, 26257
6144, has_genre, 30463
6144, release_year, 26257
7010, has_genre, 30463
7010, release_year, 26257
35026, has_genre, 30463
35026, release_year, 26257
20877, has_genre, 30463
20877, release_year, 26257
2567, has_genre, 30463
2567, release_year, 26257
25270, has_genre, 30463
25270, release_year, 26257
30090, has_genre, 30463
30090, has_tags, 30463
30090, release_year, 26257
3084, has_genre, 30463
13685, has_genre, 30463
13685, release_year, 26257
22164, has_genre, 30463
22164, release_year, 26257
9215, has_genre, 30463
9215, release_year, 26257
17956, has_genre, 30463
17956, has_tags, 30463
17956, release_year, 26257
15420, directed_by, 760
15420, has_genre, 30463
15420, has_tags, 760
15420, written_by, 34608
10878, has_genre, 30463
10878, has_tags, 30463
10878, release_year, 26257
38210, has_genre, 30463
38210, release_year, 26257
38550, has_genre, 30463
38550, release_year, 26257
9915, directed_by, 760
9915, has_tags, 760
9915, release_year, 26257
9915, written_by, 34608
23802, has_genre, 30463
23802, has_tags, 30463
23802, release_year, 26257
29233, has_genre, 30463
29233, has_tags, 30463
29233, release_year, 26257
33982, has_genre, 30463
33982, release_year, 26257
26061, has_genre, 30463
26061, has_tags, 30463
26061, release_year, 26257
13917, has_genre, 30463
13917, release_year, 26257
17314, has_genre, 30463
17314, release_year, 26257
36289, has_genre, 30463
36289, release_year, 26257
33905, has_genre, 30463
33905, release_year, 26257
4767, has_genre, 30463
4767, release_year, 26257
16762, has_genre, 30463
16762, has_tags, 30463
16762, release_year, 26257
18195, has_genre, 30463
18195, release_year, 26257
12860, has_genre, 30463
12860, has_tags, 30463
12860, release_year, 26257
33767, has_genre, 30463
33767, release_year, 26257
15419, has_genre, 30463
15419, has_tags, 30463
15419, has_tags, 25168
39623, has_genre, 30463
39623, release_year, 26257
Question: In what context are ALAN BENNETT, ONCE WERE WARRIORS, and THE CAT'S-PAW connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"ALAN BENNETT",
"ONCE WERE WARRIORS",
"THE CAT'S-PAW"
],
"valid_edges": [
[
"A LOW DOWN DIRTY SHAME",
"has_genre",
"COMEDY"
],
[
"A LOW DOWN DIRTY SHAME",
"release_year",
"1994"
],
[
"A MAN OF NO IMPORTANCE",
"has_genre",
"COMEDY"
],
[
"A MAN OF NO IMPORTANCE",
"release_year",
"1994"
],
[
"A MILLION TO JUAN",
"has_genre",
"COMEDY"
],
[
"A MILLION TO JUAN",
"release_year",
"1994"
],
[
"A SIMPLE TWIST OF FATE",
"has_genre",
"COMEDY"
],
[
"A SIMPLE TWIST OF FATE",
"release_year",
"1994"
],
[
"AIRHEADS",
"has_genre",
"COMEDY"
],
[
"AIRHEADS",
"has_tags",
"COMEDY"
],
[
"AIRHEADS",
"release_year",
"1994"
],
[
"ANGELS IN THE OUTFIELD",
"has_genre",
"COMEDY"
],
[
"ANGELS IN THE OUTFIELD",
"release_year",
"1994"
],
[
"ANGIE",
"has_genre",
"COMEDY"
],
[
"ANGIE",
"release_year",
"1994"
],
[
"BABY'S DAY OUT",
"has_genre",
"COMEDY"
],
[
"BABY'S DAY OUT",
"release_year",
"1994"
],
[
"BAD TASTE",
"has_genre",
"COMEDY"
],
[
"BAD TASTE",
"has_tags",
"NEW ZEALAND"
],
[
"BARCELONA",
"has_genre",
"COMEDY"
],
[
"BARCELONA",
"release_year",
"1994"
],
[
"BEVERLY HILLS COP III",
"has_genre",
"COMEDY"
],
[
"BEVERLY HILLS COP III",
"has_tags",
"COMEDY"
],
[
"BEVERLY HILLS COP III",
"release_year",
"1994"
],
[
"BLACK SHEEP",
"has_genre",
"COMEDY"
],
[
"BLACK SHEEP",
"has_tags",
"COMEDY"
],
[
"BLACK SHEEP",
"has_tags",
"NEW ZEALAND"
],
[
"BLANK CHECK",
"has_genre",
"COMEDY"
],
[
"BLANK CHECK",
"release_year",
"1994"
],
[
"BLANKMAN",
"has_genre",
"COMEDY"
],
[
"BLANKMAN",
"release_year",
"1994"
],
[
"CABIN BOY",
"has_genre",
"COMEDY"
],
[
"CABIN BOY",
"release_year",
"1994"
],
[
"CAR 54, WHERE ARE YOU?",
"has_genre",
"COMEDY"
],
[
"CAR 54, WHERE ARE YOU?",
"release_year",
"1994"
],
[
"CEMETERY MAN",
"has_genre",
"COMEDY"
],
[
"CEMETERY MAN",
"release_year",
"1994"
],
[
"CHASERS",
"has_genre",
"COMEDY"
],
[
"CHASERS",
"release_year",
"1994"
],
[
"CLEAN SLATE",
"has_genre",
"COMEDY"
],
[
"CLEAN SLATE",
"release_year",
"1994"
],
[
"CLERKS",
"has_genre",
"COMEDY"
],
[
"CLERKS",
"has_tags",
"COMEDY"
],
[
"CLERKS",
"release_year",
"1994"
],
[
"CLIFFORD",
"has_genre",
"COMEDY"
],
[
"CLIFFORD",
"release_year",
"1994"
],
[
"CRACKERJACK",
"has_genre",
"COMEDY"
],
[
"CRACKERJACK",
"release_year",
"1994"
],
[
"DEADLY ADVICE",
"has_genre",
"COMEDY"
],
[
"DEADLY ADVICE",
"release_year",
"1994"
],
[
"DON'T DRINK THE WATER",
"has_genre",
"COMEDY"
],
[
"DON'T DRINK THE WATER",
"release_year",
"1994"
],
[
"ED WOOD",
"has_genre",
"COMEDY"
],
[
"ED WOOD",
"release_year",
"1994"
],
[
"ERNEST GOES TO SCHOOL",
"has_genre",
"COMEDY"
],
[
"ERNEST GOES TO SCHOOL",
"release_year",
"1994"
],
[
"EXIT TO EDEN",
"has_genre",
"COMEDY"
],
[
"EXIT TO EDEN",
"release_year",
"1994"
],
[
"FLOUNDERING",
"has_genre",
"COMEDY"
],
[
"FLOUNDERING",
"release_year",
"1994"
],
[
"FORREST GUMP",
"has_tags",
"COMEDY"
],
[
"FORREST GUMP",
"release_year",
"1994"
],
[
"FOUR WEDDINGS AND A FUNERAL",
"has_genre",
"COMEDY"
],
[
"FOUR WEDDINGS AND A FUNERAL",
"has_tags",
"COMEDY"
],
[
"FOUR WEDDINGS AND A FUNERAL",
"release_year",
"1994"
],
[
"FROM BEIJING WITH LOVE",
"has_genre",
"COMEDY"
],
[
"FROM BEIJING WITH LOVE",
"release_year",
"1994"
],
[
"GETTING EVEN WITH DAD",
"has_genre",
"COMEDY"
],
[
"GETTING EVEN WITH DAD",
"release_year",
"1994"
],
[
"GETTING IN",
"has_genre",
"COMEDY"
],
[
"GETTING IN",
"release_year",
"1994"
],
[
"GREEDY",
"has_genre",
"COMEDY"
],
[
"GREEDY",
"release_year",
"1994"
],
[
"GUARDING TESS",
"has_genre",
"COMEDY"
],
[
"GUARDING TESS",
"release_year",
"1994"
],
[
"HAIL CAESAR",
"has_genre",
"COMEDY"
],
[
"HAIL CAESAR",
"release_year",
"1994"
],
[
"HEAVENLY CREATURES",
"has_tags",
"NEW ZEALAND"
],
[
"HEAVENLY CREATURES",
"release_year",
"1994"
],
[
"HOLY MATRIMONY",
"has_genre",
"COMEDY"
],
[
"HOLY MATRIMONY",
"release_year",
"1994"
],
[
"HOUSEBOUND",
"has_genre",
"COMEDY"
],
[
"HOUSEBOUND",
"has_tags",
"NEW ZEALAND"
],
[
"I LIKE IT LIKE THAT",
"has_genre",
"COMEDY"
],
[
"I LIKE IT LIKE THAT",
"release_year",
"1994"
],
[
"I LOVE TROUBLE",
"has_genre",
"COMEDY"
],
[
"I LOVE TROUBLE",
"release_year",
"1994"
],
[
"I.Q.",
"has_genre",
"COMEDY"
],
[
"I.Q.",
"release_year",
"1994"
],
[
"IN THE ARMY NOW",
"has_genre",
"COMEDY"
],
[
"IN THE ARMY NOW",
"release_year",
"1994"
],
[
"IT COULD HAPPEN TO YOU",
"has_genre",
"COMEDY"
],
[
"IT COULD HAPPEN TO YOU",
"has_tags",
"COMEDY"
],
[
"IT COULD HAPPEN TO YOU",
"release_year",
"1994"
],
[
"IT RUNS IN THE FAMILY",
"has_genre",
"COMEDY"
],
[
"IT RUNS IN THE FAMILY",
"release_year",
"1994"
],
[
"IT'S PAT",
"has_genre",
"COMEDY"
],
[
"IT'S PAT",
"release_year",
"1994"
],
[
"JUNIOR",
"has_genre",
"COMEDY"
],
[
"JUNIOR",
"release_year",
"1994"
],
[
"KABHI HAAN KABHI NAA",
"has_genre",
"COMEDY"
],
[
"KABHI HAAN KABHI NAA",
"release_year",
"1994"
],
[
"LEPRECHAUN 2",
"has_genre",
"COMEDY"
],
[
"LEPRECHAUN 2",
"release_year",
"1994"
],
[
"LIGHTNING JACK",
"has_genre",
"COMEDY"
],
[
"LIGHTNING JACK",
"release_year",
"1994"
],
[
"LITTLE GIANTS",
"has_genre",
"COMEDY"
],
[
"LITTLE GIANTS",
"release_year",
"1994"
],
[
"MAVERICK",
"has_genre",
"COMEDY"
],
[
"MAVERICK",
"has_tags",
"COMEDY"
],
[
"MAVERICK",
"release_year",
"1994"
],
[
"MILK MONEY",
"has_genre",
"COMEDY"
],
[
"MILK MONEY",
"release_year",
"1994"
],
[
"MIXED NUTS",
"has_genre",
"COMEDY"
],
[
"MIXED NUTS",
"release_year",
"1994"
],
[
"MONKEY TROUBLE",
"has_genre",
"COMEDY"
],
[
"MONKEY TROUBLE",
"release_year",
"1994"
],
[
"MURIEL'S WEDDING",
"has_genre",
"COMEDY"
],
[
"MURIEL'S WEDDING",
"has_tags",
"COMEDY"
],
[
"MURIEL'S WEDDING",
"release_year",
"1994"
],
[
"MY GIRL 2",
"has_genre",
"COMEDY"
],
[
"MY GIRL 2",
"release_year",
"1994"
],
[
"NOBODY'S FOOL",
"has_genre",
"COMEDY"
],
[
"NOBODY'S FOOL",
"release_year",
"1994"
],
[
"NORTH",
"has_genre",
"COMEDY"
],
[
"NORTH",
"release_year",
"1994"
],
[
"ONCE WERE WARRIORS",
"has_tags",
"NEW ZEALAND"
],
[
"ONCE WERE WARRIORS",
"has_tags",
"VIOLENCE"
],
[
"ONCE WERE WARRIORS",
"release_year",
"1994"
],
[
"ONLY YOU",
"has_genre",
"COMEDY"
],
[
"ONLY YOU",
"release_year",
"1994"
],
[
"PCU",
"has_genre",
"COMEDY"
],
[
"PCU",
"release_year",
"1994"
],
[
"PRINCESS CARABOO",
"has_genre",
"COMEDY"
],
[
"PRINCESS CARABOO",
"release_year",
"1994"
],
[
"PULP FICTION",
"has_tags",
"COMEDY"
],
[
"PULP FICTION",
"has_tags",
"VIOLENCE"
],
[
"PULP FICTION",
"release_year",
"1994"
],
[
"RADIOLAND MURDERS",
"has_genre",
"COMEDY"
],
[
"RADIOLAND MURDERS",
"release_year",
"1994"
],
[
"REALITY BITES",
"has_genre",
"COMEDY"
],
[
"REALITY BITES",
"release_year",
"1994"
],
[
"RENAISSANCE MAN",
"has_genre",
"COMEDY"
],
[
"RENAISSANCE MAN",
"release_year",
"1994"
],
[
"SERIAL MOM",
"has_genre",
"COMEDY"
],
[
"SERIAL MOM",
"has_tags",
"COMEDY"
],
[
"SERIAL MOM",
"release_year",
"1994"
],
[
"SLEEP WITH ME",
"has_genre",
"COMEDY"
],
[
"SLEEP WITH ME",
"release_year",
"1994"
],
[
"SPANKING THE MONKEY",
"has_genre",
"COMEDY"
],
[
"SPANKING THE MONKEY",
"release_year",
"1994"
],
[
"SPEECHLESS",
"has_genre",
"COMEDY"
],
[
"SPEECHLESS",
"release_year",
"1994"
],
[
"STAGGERED",
"has_genre",
"COMEDY"
],
[
"STAGGERED",
"release_year",
"1994"
],
[
"SWIMMING WITH SHARKS",
"has_genre",
"COMEDY"
],
[
"SWIMMING WITH SHARKS",
"release_year",
"1994"
],
[
"TAMMY AND THE T-REX",
"has_genre",
"COMEDY"
],
[
"TAMMY AND THE T-REX",
"release_year",
"1994"
],
[
"THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT",
"has_genre",
"COMEDY"
],
[
"THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT",
"release_year",
"1994"
],
[
"THE AIR UP THERE",
"has_genre",
"COMEDY"
],
[
"THE AIR UP THERE",
"has_tags",
"COMEDY"
],
[
"THE AIR UP THERE",
"release_year",
"1994"
],
[
"THE CAT'S-PAW",
"has_genre",
"COMEDY"
],
[
"THE CHASE",
"has_genre",
"COMEDY"
],
[
"THE CHASE",
"release_year",
"1994"
],
[
"THE COWBOY WAY",
"has_genre",
"COMEDY"
],
[
"THE COWBOY WAY",
"release_year",
"1994"
],
[
"THE FAVOR",
"has_genre",
"COMEDY"
],
[
"THE FAVOR",
"release_year",
"1994"
],
[
"THE FLINTSTONES",
"has_genre",
"COMEDY"
],
[
"THE FLINTSTONES",
"has_tags",
"COMEDY"
],
[
"THE FLINTSTONES",
"release_year",
"1994"
],
[
"THE HISTORY BOYS",
"directed_by",
"NICHOLAS HYTNER"
],
[
"THE HISTORY BOYS",
"has_genre",
"COMEDY"
],
[
"THE HISTORY BOYS",
"has_tags",
"NICHOLAS HYTNER"
],
[
"THE HISTORY BOYS",
"written_by",
"ALAN BENNETT"
],
[
"THE HUDSUCKER PROXY",
"has_genre",
"COMEDY"
],
[
"THE HUDSUCKER PROXY",
"has_tags",
"COMEDY"
],
[
"THE HUDSUCKER PROXY",
"release_year",
"1994"
],
[
"THE INKWELL",
"has_genre",
"COMEDY"
],
[
"THE INKWELL",
"release_year",
"1994"
],
[
"THE LITTLE RASCALS",
"has_genre",
"COMEDY"
],
[
"THE LITTLE RASCALS",
"release_year",
"1994"
],
[
"THE MADNESS OF KING GEORGE",
"directed_by",
"NICHOLAS HYTNER"
],
[
"THE MADNESS OF KING GEORGE",
"has_tags",
"NICHOLAS HYTNER"
],
[
"THE MADNESS OF KING GEORGE",
"release_year",
"1994"
],
[
"THE MADNESS OF KING GEORGE",
"written_by",
"ALAN BENNETT"
],
[
"THE MASK",
"has_genre",
"COMEDY"
],
[
"THE MASK",
"has_tags",
"COMEDY"
],
[
"THE MASK",
"release_year",
"1994"
],
[
"THE MONSTER",
"has_genre",
"COMEDY"
],
[
"THE MONSTER",
"has_tags",
"COMEDY"
],
[
"THE MONSTER",
"release_year",
"1994"
],
[
"THE PAPER",
"has_genre",
"COMEDY"
],
[
"THE PAPER",
"release_year",
"1994"
],
[
"THE REF",
"has_genre",
"COMEDY"
],
[
"THE REF",
"has_tags",
"COMEDY"
],
[
"THE REF",
"release_year",
"1994"
],
[
"THE ROAD TO WELLVILLE",
"has_genre",
"COMEDY"
],
[
"THE ROAD TO WELLVILLE",
"release_year",
"1994"
],
[
"THE SANTA CLAUSE",
"has_genre",
"COMEDY"
],
[
"THE SANTA CLAUSE",
"release_year",
"1994"
],
[
"THE SCOUT",
"has_genre",
"COMEDY"
],
[
"THE SCOUT",
"release_year",
"1994"
],
[
"THE SEARCH FOR ONE-EYE JIMMY",
"has_genre",
"COMEDY"
],
[
"THE SEARCH FOR ONE-EYE JIMMY",
"release_year",
"1994"
],
[
"THE SUM OF US",
"has_genre",
"COMEDY"
],
[
"THE SUM OF US",
"release_year",
"1994"
],
[
"THREESOME",
"has_genre",
"COMEDY"
],
[
"THREESOME",
"has_tags",
"COMEDY"
],
[
"THREESOME",
"release_year",
"1994"
],
[
"TRAPPED IN PARADISE",
"has_genre",
"COMEDY"
],
[
"TRAPPED IN PARADISE",
"release_year",
"1994"
],
[
"TRUE LIES",
"has_genre",
"COMEDY"
],
[
"TRUE LIES",
"has_tags",
"COMEDY"
],
[
"TRUE LIES",
"release_year",
"1994"
],
[
"TWIN SITTERS",
"has_genre",
"COMEDY"
],
[
"TWIN SITTERS",
"release_year",
"1994"
],
[
"WHAT WE DO IN THE SHADOWS",
"has_genre",
"COMEDY"
],
[
"WHAT WE DO IN THE SHADOWS",
"has_tags",
"COMEDY"
],
[
"WHAT WE DO IN THE SHADOWS",
"has_tags",
"NEW ZEALAND"
],
[
"WITH HONORS",
"has_genre",
"COMEDY"
],
[
"WITH HONORS",
"release_year",
"1994"
]
]
}
|
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
37224, 1990
8221, A MAN ESCAPED
16566, A MONKEY IN WINTER
19905, A TALE OF SPRINGTIME
30750, A VERY LONG ENGAGEMENT
4133, ACES HIGH
36359, AFTERWARDS
30332, AMOUR
23257, AN UNFORGETTABLE SUMMER
24409, ARARAT
15271, ARIA
24216, ASTERIX AND THE VIKINGS
25570, BEAUTY AND THE BEAST
5122, BEST PICTURE
26908, BLACK MOON
15416, BOYFRIENDS AND GIRLFRIENDS
5978, CAMP DE THIAROYE
5840, CERTIFIED COPY
8520, CHICKEN WITH PLUMS
16536, CYRANO DE BERGERAC
30624, DANCES WITH WOLVES
38827, DANY BOON
33876, DAY FOR NIGHT
3567, DAYS OF GLORY
9709, DE L'AUTRE CÔTÉ DU LIT
17035, DEBTOCRACY
24410, DEMONLOVER
11249, DIARY OF A COUNTRY PRIEST
18025, DÉDÉE D'ANVERS
31783, ENGLISH
32892, ENGLISH VINGLISH
36073, FAT GIRL
34422, FEMALE AGENTS
36601, FLANDERS
1273, FLYBOYS
6966, FORBIDDEN GAMES
26394, FOUR ADVENTURES OF REINETTE AND MIRABELLE
6012, FRENCH
11314, GEORGES BERNANOS
5527, GIGI
26909, GREEN CARD
12085, HAPPY NEW YEAR
23434, HISTORICAL
27285, I WAS A MALE WAR BRIDE
16560, INGLOURIOUS BASTERDS
2944, IS PARIS BURNING?
479, J'ACCUSE!
21922, JANE EYRE
14209, KING OF HEARTS
18630, LA GRANDE ILLUSION
1315, LA PISCINE
24812, LACOMBE, LUCIEN
14601, LES MISÉRABLES
5214, LOOKING FOR ERIC
5422, LOULOU
33041, LUCIE AUBRAC
28455, MARIE ANTOINETTE
26787, MAURICE PIALAT
29660, MAY FOOLS
16925, MAYERLING
12100, MOUCHETTE
37218, MY BEST FRIEND
7974, MY FATHER THE HERO
8817, MY FATHER'S GLORY
26256, MY MOTHER'S CASTLE
6463, NAKED CHILDHOOD
37497, NATIONAL FILM REGISTRY
12152, NOTHING TO DECLARE
21677, ON THE ROAD
32901, ON TOUR
35556, OUTSIDE THE LAW
37499, PARAGRAPH 175
7967, PASSAGE TO MARSEILLE
16348, PERSEPOLIS
29620, POLICE
18480, RENAISSANCE
4689, SABRINA
11723, SHOAH
38271, SNOWPIERCER
17447, SON OF RAMBOW
8436, SPIRITS OF THE DEAD
8764, STELLA
6323, STRAYED
16165, SUPERCONDRIAQUE
13334, SWIMMING POOL
30003, TAKEN
10522, TAKING SIDES
1451, TATIE DANIELLE
9091, THE ADVENTURES OF PICASSO
24625, THE APARTMENT
28971, THE BIG BLUE
31161, THE CHAMBERMAID ON THE TITANIC
7044, THE DAY OF THE JACKAL
21345, THE DREAMERS
38918, THE FAMILY
27040, THE FRENCH CONNECTION
27723, THE HAIRDRESSER'S HUSBAND
15198, THE HUNCHBACK OF NOTRE DAME
16643, THE LAST METRO
22582, THE LAST OF THE MOHICANS
27237, THE LONGEST DAY
21696, THE MAN FROM LONDON
28079, THE MAN WHO PLANTED TREES
19375, THE PASSION OF JOAN OF ARC
8477, THE SCARLET PIMPERNEL
429, THE SEARCH
11663, THE TALL BLOND MAN WITH ONE BLACK SHOE
24261, THE TRUTH ABOUT CHARLIE
36109, THE UNDEFEATED
17568, THE VANISHING
31589, THE WAR IS OVER
19779, UNDER THE BOMBS
11470, UNDER THE SUN OF SATAN
31732, URANUS
10735, VENGEANCE
11659, VIVA MARIA!
22214, WAR
28712, WE WON'T GROW OLD TOGETHER
36026, WESTERN
35593, WOODEN CROSSES
src, edge_attr, dst
8221, has_genre, 22214
8221, has_tags, 6012
8221, in_language, 6012
16566, has_tags, 22214
16566, in_language, 6012
19905, in_language, 6012
19905, release_year, 37224
30750, has_tags, 6012
30750, has_tags, 22214
30750, in_language, 6012
4133, has_genre, 22214
4133, in_language, 6012
36359, in_language, 31783
36359, in_language, 6012
30332, has_tags, 6012
30332, in_language, 31783
30332, in_language, 6012
23257, has_genre, 22214
23257, in_language, 6012
24409, has_tags, 23434
24409, in_language, 6012
15271, in_language, 6012
15271, release_year, 7841
24216, in_language, 31783
24216, in_language, 6012
25570, has_tags, 37497
25570, in_language, 6012
26908, in_language, 31783
26908, in_language, 6012
15416, in_language, 6012
15416, release_year, 7841
5978, has_genre, 22214
5978, in_language, 6012
5840, in_language, 31783
5840, in_language, 6012
8520, in_language, 31783
8520, in_language, 6012
16536, has_tags, 6012
16536, in_language, 31783
16536, in_language, 6012
16536, release_year, 37224
30624, has_genre, 36026
30624, has_tags, 5122
30624, has_tags, 23434
30624, has_tags, 37497
30624, has_tags, 22214
30624, has_tags, 36026
30624, in_language, 31783
30624, release_year, 37224
33876, in_language, 31783
33876, in_language, 6012
3567, has_genre, 22214
3567, has_tags, 22214
3567, in_language, 6012
9709, in_language, 6012
9709, starred_actors, 38827
17035, in_language, 31783
17035, in_language, 6012
24410, in_language, 31783
24410, in_language, 6012
11249, in_language, 6012
11249, written_by, 11314
18025, in_language, 31783
18025, in_language, 6012
32892, in_language, 31783
32892, in_language, 6012
36073, in_language, 31783
36073, in_language, 6012
34422, has_genre, 22214
34422, in_language, 6012
36601, has_genre, 22214
36601, in_language, 6012
1273, has_tags, 22214
1273, in_language, 6012
6966, has_genre, 22214
6966, in_language, 6012
26394, in_language, 6012
26394, release_year, 7841
5527, has_tags, 37497
5527, in_language, 31783
5527, in_language, 6012
26909, in_language, 6012
26909, release_year, 37224
12085, in_language, 6012
12085, release_year, 7841
27285, has_genre, 22214
27285, in_language, 6012
16560, has_genre, 22214
16560, has_tags, 6012
16560, has_tags, 22214
16560, in_language, 6012
2944, has_genre, 22214
2944, in_language, 6012
479, has_genre, 22214
479, in_language, 6012
21922, in_language, 31783
21922, in_language, 6012
14209, has_genre, 22214
14209, in_language, 6012
18630, has_genre, 22214
18630, has_tags, 22214
18630, in_language, 6012
1315, in_language, 31783
1315, in_language, 6012
24812, has_genre, 22214
24812, in_language, 31783
24812, in_language, 6012
14601, has_tags, 23434
14601, in_language, 31783
14601, in_language, 6012
5214, in_language, 31783
5214, in_language, 6012
5422, directed_by, 26787
5422, has_tags, 26787
5422, in_language, 6012
5422, written_by, 26787
33041, has_genre, 22214
33041, in_language, 6012
28455, has_tags, 23434
28455, in_language, 6012
29660, in_language, 6012
29660, release_year, 37224
16925, in_language, 31783
16925, in_language, 6012
12100, in_language, 6012
12100, written_by, 11314
37218, in_language, 6012
37218, starred_actors, 38827
7974, in_language, 31783
7974, in_language, 6012
8817, has_tags, 6012
8817, in_language, 6012
8817, release_year, 37224
26256, has_tags, 6012
26256, in_language, 6012
26256, release_year, 37224
6463, directed_by, 26787
6463, has_tags, 26787
6463, in_language, 6012
6463, written_by, 26787
12152, directed_by, 38827
12152, has_tags, 38827
12152, in_language, 6012
12152, starred_actors, 38827
12152, written_by, 38827
21677, in_language, 31783
21677, in_language, 6012
32901, in_language, 31783
32901, in_language, 6012
35556, has_genre, 22214
35556, has_tags, 6012
35556, has_tags, 22214
35556, in_language, 6012
37499, has_genre, 22214
37499, in_language, 6012
7967, has_genre, 22214
7967, in_language, 6012
16348, has_tags, 6012
16348, has_tags, 22214
16348, in_language, 6012
29620, directed_by, 26787
29620, in_language, 6012
29620, written_by, 26787
18480, in_language, 31783
18480, in_language, 6012
4689, has_tags, 37497
4689, in_language, 6012
11723, has_genre, 22214
11723, in_language, 6012
38271, in_language, 31783
38271, in_language, 6012
17447, in_language, 31783
17447, in_language, 6012
8436, in_language, 31783
8436, in_language, 6012
8764, in_language, 6012
8764, release_year, 37224
6323, has_genre, 22214
6323, in_language, 6012
16165, directed_by, 38827
16165, has_tags, 38827
16165, in_language, 6012
16165, starred_actors, 38827
16165, written_by, 38827
13334, has_tags, 6012
13334, in_language, 31783
13334, in_language, 6012
30003, in_language, 31783
30003, in_language, 6012
10522, has_genre, 22214
10522, in_language, 31783
10522, in_language, 6012
1451, has_tags, 6012
1451, in_language, 6012
1451, release_year, 37224
9091, in_language, 31783
9091, in_language, 6012
24625, has_tags, 5122
24625, in_language, 6012
28971, in_language, 31783
28971, in_language, 6012
31161, in_language, 31783
31161, in_language, 6012
7044, in_language, 31783
7044, in_language, 6012
21345, has_tags, 6012
21345, in_language, 31783
21345, in_language, 6012
38918, in_language, 31783
38918, in_language, 6012
38918, release_year, 7841
27040, has_tags, 5122
27040, has_tags, 37497
27040, in_language, 6012
27723, in_language, 6012
27723, release_year, 37224
15198, in_language, 31783
15198, in_language, 6012
16643, has_genre, 22214
16643, in_language, 6012
22582, has_tags, 23434
22582, in_language, 31783
22582, in_language, 6012
27237, has_tags, 22214
27237, in_language, 6012
21696, in_language, 31783
21696, in_language, 6012
28079, in_language, 6012
28079, release_year, 7841
19375, has_tags, 6012
19375, has_tags, 23434
19375, in_language, 6012
8477, in_language, 31783
8477, in_language, 6012
429, has_genre, 22214
429, in_language, 6012
11663, in_language, 31783
11663, in_language, 6012
24261, in_language, 31783
24261, in_language, 6012
36109, has_genre, 36026
36109, in_language, 6012
17568, in_language, 31783
17568, in_language, 6012
31589, has_genre, 22214
31589, in_language, 6012
19779, has_genre, 22214
19779, in_language, 6012
11470, directed_by, 26787
11470, in_language, 6012
11470, release_year, 7841
11470, starred_actors, 26787
11470, written_by, 11314
11470, written_by, 26787
31732, in_language, 6012
31732, release_year, 37224
10735, in_language, 31783
10735, in_language, 6012
11659, has_tags, 6012
11659, in_language, 31783
11659, in_language, 6012
28712, directed_by, 26787
28712, in_language, 6012
28712, written_by, 26787
36026, in_language, 6012
35593, has_genre, 22214
35593, in_language, 6012
Question: How are DANCES WITH WOLVES, DANY BOON, and UNDER THE SUN OF SATAN related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"DANCES WITH WOLVES",
"DANY BOON",
"UNDER THE SUN OF SATAN"
],
"valid_edges": [
[
"A MAN ESCAPED",
"has_genre",
"WAR"
],
[
"A MAN ESCAPED",
"has_tags",
"FRENCH"
],
[
"A MAN ESCAPED",
"in_language",
"FRENCH"
],
[
"A MONKEY IN WINTER",
"has_tags",
"WAR"
],
[
"A MONKEY IN WINTER",
"in_language",
"FRENCH"
],
[
"A TALE OF SPRINGTIME",
"in_language",
"FRENCH"
],
[
"A TALE OF SPRINGTIME",
"release_year",
"1990"
],
[
"A VERY LONG ENGAGEMENT",
"has_tags",
"FRENCH"
],
[
"A VERY LONG ENGAGEMENT",
"has_tags",
"WAR"
],
[
"A VERY LONG ENGAGEMENT",
"in_language",
"FRENCH"
],
[
"ACES HIGH",
"has_genre",
"WAR"
],
[
"ACES HIGH",
"in_language",
"FRENCH"
],
[
"AFTERWARDS",
"in_language",
"ENGLISH"
],
[
"AFTERWARDS",
"in_language",
"FRENCH"
],
[
"AMOUR",
"has_tags",
"FRENCH"
],
[
"AMOUR",
"in_language",
"ENGLISH"
],
[
"AMOUR",
"in_language",
"FRENCH"
],
[
"AN UNFORGETTABLE SUMMER",
"has_genre",
"WAR"
],
[
"AN UNFORGETTABLE SUMMER",
"in_language",
"FRENCH"
],
[
"ARARAT",
"has_tags",
"HISTORICAL"
],
[
"ARARAT",
"in_language",
"FRENCH"
],
[
"ARIA",
"in_language",
"FRENCH"
],
[
"ARIA",
"release_year",
"1987"
],
[
"ASTERIX AND THE VIKINGS",
"in_language",
"ENGLISH"
],
[
"ASTERIX AND THE VIKINGS",
"in_language",
"FRENCH"
],
[
"BEAUTY AND THE BEAST",
"has_tags",
"NATIONAL FILM REGISTRY"
],
[
"BEAUTY AND THE BEAST",
"in_language",
"FRENCH"
],
[
"BLACK MOON",
"in_language",
"ENGLISH"
],
[
"BLACK MOON",
"in_language",
"FRENCH"
],
[
"BOYFRIENDS AND GIRLFRIENDS",
"in_language",
"FRENCH"
],
[
"BOYFRIENDS AND GIRLFRIENDS",
"release_year",
"1987"
],
[
"CAMP DE THIAROYE",
"has_genre",
"WAR"
],
[
"CAMP DE THIAROYE",
"in_language",
"FRENCH"
],
[
"CERTIFIED COPY",
"in_language",
"ENGLISH"
],
[
"CERTIFIED COPY",
"in_language",
"FRENCH"
],
[
"CHICKEN WITH PLUMS",
"in_language",
"ENGLISH"
],
[
"CHICKEN WITH PLUMS",
"in_language",
"FRENCH"
],
[
"CYRANO DE BERGERAC",
"has_tags",
"FRENCH"
],
[
"CYRANO DE BERGERAC",
"in_language",
"ENGLISH"
],
[
"CYRANO DE BERGERAC",
"in_language",
"FRENCH"
],
[
"CYRANO DE BERGERAC",
"release_year",
"1990"
],
[
"DANCES WITH WOLVES",
"has_genre",
"WESTERN"
],
[
"DANCES WITH WOLVES",
"has_tags",
"BEST PICTURE"
],
[
"DANCES WITH WOLVES",
"has_tags",
"HISTORICAL"
],
[
"DANCES WITH WOLVES",
"has_tags",
"NATIONAL FILM REGISTRY"
],
[
"DANCES WITH WOLVES",
"has_tags",
"WAR"
],
[
"DANCES WITH WOLVES",
"has_tags",
"WESTERN"
],
[
"DANCES WITH WOLVES",
"in_language",
"ENGLISH"
],
[
"DANCES WITH WOLVES",
"release_year",
"1990"
],
[
"DAY FOR NIGHT",
"in_language",
"ENGLISH"
],
[
"DAY FOR NIGHT",
"in_language",
"FRENCH"
],
[
"DAYS OF GLORY",
"has_genre",
"WAR"
],
[
"DAYS OF GLORY",
"has_tags",
"WAR"
],
[
"DAYS OF GLORY",
"in_language",
"FRENCH"
],
[
"DE L'AUTRE CÔTÉ DU LIT",
"in_language",
"FRENCH"
],
[
"DE L'AUTRE CÔTÉ DU LIT",
"starred_actors",
"DANY BOON"
],
[
"DEBTOCRACY",
"in_language",
"ENGLISH"
],
[
"DEBTOCRACY",
"in_language",
"FRENCH"
],
[
"DEMONLOVER",
"in_language",
"ENGLISH"
],
[
"DEMONLOVER",
"in_language",
"FRENCH"
],
[
"DIARY OF A COUNTRY PRIEST",
"in_language",
"FRENCH"
],
[
"DIARY OF A COUNTRY PRIEST",
"written_by",
"GEORGES BERNANOS"
],
[
"DÉDÉE D'ANVERS",
"in_language",
"ENGLISH"
],
[
"DÉDÉE D'ANVERS",
"in_language",
"FRENCH"
],
[
"ENGLISH VINGLISH",
"in_language",
"ENGLISH"
],
[
"ENGLISH VINGLISH",
"in_language",
"FRENCH"
],
[
"FAT GIRL",
"in_language",
"ENGLISH"
],
[
"FAT GIRL",
"in_language",
"FRENCH"
],
[
"FEMALE AGENTS",
"has_genre",
"WAR"
],
[
"FEMALE AGENTS",
"in_language",
"FRENCH"
],
[
"FLANDERS",
"has_genre",
"WAR"
],
[
"FLANDERS",
"in_language",
"FRENCH"
],
[
"FLYBOYS",
"has_tags",
"WAR"
],
[
"FLYBOYS",
"in_language",
"FRENCH"
],
[
"FORBIDDEN GAMES",
"has_genre",
"WAR"
],
[
"FORBIDDEN GAMES",
"in_language",
"FRENCH"
],
[
"FOUR ADVENTURES OF REINETTE AND MIRABELLE",
"in_language",
"FRENCH"
],
[
"FOUR ADVENTURES OF REINETTE AND MIRABELLE",
"release_year",
"1987"
],
[
"GIGI",
"has_tags",
"NATIONAL FILM REGISTRY"
],
[
"GIGI",
"in_language",
"ENGLISH"
],
[
"GIGI",
"in_language",
"FRENCH"
],
[
"GREEN CARD",
"in_language",
"FRENCH"
],
[
"GREEN CARD",
"release_year",
"1990"
],
[
"HAPPY NEW YEAR",
"in_language",
"FRENCH"
],
[
"HAPPY NEW YEAR",
"release_year",
"1987"
],
[
"I WAS A MALE WAR BRIDE",
"has_genre",
"WAR"
],
[
"I WAS A MALE WAR BRIDE",
"in_language",
"FRENCH"
],
[
"INGLOURIOUS BASTERDS",
"has_genre",
"WAR"
],
[
"INGLOURIOUS BASTERDS",
"has_tags",
"FRENCH"
],
[
"INGLOURIOUS BASTERDS",
"has_tags",
"WAR"
],
[
"INGLOURIOUS BASTERDS",
"in_language",
"FRENCH"
],
[
"IS PARIS BURNING?",
"has_genre",
"WAR"
],
[
"IS PARIS BURNING?",
"in_language",
"FRENCH"
],
[
"J'ACCUSE!",
"has_genre",
"WAR"
],
[
"J'ACCUSE!",
"in_language",
"FRENCH"
],
[
"JANE EYRE",
"in_language",
"ENGLISH"
],
[
"JANE EYRE",
"in_language",
"FRENCH"
],
[
"KING OF HEARTS",
"has_genre",
"WAR"
],
[
"KING OF HEARTS",
"in_language",
"FRENCH"
],
[
"LA GRANDE ILLUSION",
"has_genre",
"WAR"
],
[
"LA GRANDE ILLUSION",
"has_tags",
"WAR"
],
[
"LA GRANDE ILLUSION",
"in_language",
"FRENCH"
],
[
"LA PISCINE",
"in_language",
"ENGLISH"
],
[
"LA PISCINE",
"in_language",
"FRENCH"
],
[
"LACOMBE, LUCIEN",
"has_genre",
"WAR"
],
[
"LACOMBE, LUCIEN",
"in_language",
"ENGLISH"
],
[
"LACOMBE, LUCIEN",
"in_language",
"FRENCH"
],
[
"LES MISÉRABLES",
"has_tags",
"HISTORICAL"
],
[
"LES MISÉRABLES",
"in_language",
"ENGLISH"
],
[
"LES MISÉRABLES",
"in_language",
"FRENCH"
],
[
"LOOKING FOR ERIC",
"in_language",
"ENGLISH"
],
[
"LOOKING FOR ERIC",
"in_language",
"FRENCH"
],
[
"LOULOU",
"directed_by",
"MAURICE PIALAT"
],
[
"LOULOU",
"has_tags",
"MAURICE PIALAT"
],
[
"LOULOU",
"in_language",
"FRENCH"
],
[
"LOULOU",
"written_by",
"MAURICE PIALAT"
],
[
"LUCIE AUBRAC",
"has_genre",
"WAR"
],
[
"LUCIE AUBRAC",
"in_language",
"FRENCH"
],
[
"MARIE ANTOINETTE",
"has_tags",
"HISTORICAL"
],
[
"MARIE ANTOINETTE",
"in_language",
"FRENCH"
],
[
"MAY FOOLS",
"in_language",
"FRENCH"
],
[
"MAY FOOLS",
"release_year",
"1990"
],
[
"MAYERLING",
"in_language",
"ENGLISH"
],
[
"MAYERLING",
"in_language",
"FRENCH"
],
[
"MOUCHETTE",
"in_language",
"FRENCH"
],
[
"MOUCHETTE",
"written_by",
"GEORGES BERNANOS"
],
[
"MY BEST FRIEND",
"in_language",
"FRENCH"
],
[
"MY BEST FRIEND",
"starred_actors",
"DANY BOON"
],
[
"MY FATHER THE HERO",
"in_language",
"ENGLISH"
],
[
"MY FATHER THE HERO",
"in_language",
"FRENCH"
],
[
"MY FATHER'S GLORY",
"has_tags",
"FRENCH"
],
[
"MY FATHER'S GLORY",
"in_language",
"FRENCH"
],
[
"MY FATHER'S GLORY",
"release_year",
"1990"
],
[
"MY MOTHER'S CASTLE",
"has_tags",
"FRENCH"
],
[
"MY MOTHER'S CASTLE",
"in_language",
"FRENCH"
],
[
"MY MOTHER'S CASTLE",
"release_year",
"1990"
],
[
"NAKED CHILDHOOD",
"directed_by",
"MAURICE PIALAT"
],
[
"NAKED CHILDHOOD",
"has_tags",
"MAURICE PIALAT"
],
[
"NAKED CHILDHOOD",
"in_language",
"FRENCH"
],
[
"NAKED CHILDHOOD",
"written_by",
"MAURICE PIALAT"
],
[
"NOTHING TO DECLARE",
"directed_by",
"DANY BOON"
],
[
"NOTHING TO DECLARE",
"has_tags",
"DANY BOON"
],
[
"NOTHING TO DECLARE",
"in_language",
"FRENCH"
],
[
"NOTHING TO DECLARE",
"starred_actors",
"DANY BOON"
],
[
"NOTHING TO DECLARE",
"written_by",
"DANY BOON"
],
[
"ON THE ROAD",
"in_language",
"ENGLISH"
],
[
"ON THE ROAD",
"in_language",
"FRENCH"
],
[
"ON TOUR",
"in_language",
"ENGLISH"
],
[
"ON TOUR",
"in_language",
"FRENCH"
],
[
"OUTSIDE THE LAW",
"has_genre",
"WAR"
],
[
"OUTSIDE THE LAW",
"has_tags",
"FRENCH"
],
[
"OUTSIDE THE LAW",
"has_tags",
"WAR"
],
[
"OUTSIDE THE LAW",
"in_language",
"FRENCH"
],
[
"PARAGRAPH 175",
"has_genre",
"WAR"
],
[
"PARAGRAPH 175",
"in_language",
"FRENCH"
],
[
"PASSAGE TO MARSEILLE",
"has_genre",
"WAR"
],
[
"PASSAGE TO MARSEILLE",
"in_language",
"FRENCH"
],
[
"PERSEPOLIS",
"has_tags",
"FRENCH"
],
[
"PERSEPOLIS",
"has_tags",
"WAR"
],
[
"PERSEPOLIS",
"in_language",
"FRENCH"
],
[
"POLICE",
"directed_by",
"MAURICE PIALAT"
],
[
"POLICE",
"in_language",
"FRENCH"
],
[
"POLICE",
"written_by",
"MAURICE PIALAT"
],
[
"RENAISSANCE",
"in_language",
"ENGLISH"
],
[
"RENAISSANCE",
"in_language",
"FRENCH"
],
[
"SABRINA",
"has_tags",
"NATIONAL FILM REGISTRY"
],
[
"SABRINA",
"in_language",
"FRENCH"
],
[
"SHOAH",
"has_genre",
"WAR"
],
[
"SHOAH",
"in_language",
"FRENCH"
],
[
"SNOWPIERCER",
"in_language",
"ENGLISH"
],
[
"SNOWPIERCER",
"in_language",
"FRENCH"
],
[
"SON OF RAMBOW",
"in_language",
"ENGLISH"
],
[
"SON OF RAMBOW",
"in_language",
"FRENCH"
],
[
"SPIRITS OF THE DEAD",
"in_language",
"ENGLISH"
],
[
"SPIRITS OF THE DEAD",
"in_language",
"FRENCH"
],
[
"STELLA",
"in_language",
"FRENCH"
],
[
"STELLA",
"release_year",
"1990"
],
[
"STRAYED",
"has_genre",
"WAR"
],
[
"STRAYED",
"in_language",
"FRENCH"
],
[
"SUPERCONDRIAQUE",
"directed_by",
"DANY BOON"
],
[
"SUPERCONDRIAQUE",
"has_tags",
"DANY BOON"
],
[
"SUPERCONDRIAQUE",
"in_language",
"FRENCH"
],
[
"SUPERCONDRIAQUE",
"starred_actors",
"DANY BOON"
],
[
"SUPERCONDRIAQUE",
"written_by",
"DANY BOON"
],
[
"SWIMMING POOL",
"has_tags",
"FRENCH"
],
[
"SWIMMING POOL",
"in_language",
"ENGLISH"
],
[
"SWIMMING POOL",
"in_language",
"FRENCH"
],
[
"TAKEN",
"in_language",
"ENGLISH"
],
[
"TAKEN",
"in_language",
"FRENCH"
],
[
"TAKING SIDES",
"has_genre",
"WAR"
],
[
"TAKING SIDES",
"in_language",
"ENGLISH"
],
[
"TAKING SIDES",
"in_language",
"FRENCH"
],
[
"TATIE DANIELLE",
"has_tags",
"FRENCH"
],
[
"TATIE DANIELLE",
"in_language",
"FRENCH"
],
[
"TATIE DANIELLE",
"release_year",
"1990"
],
[
"THE ADVENTURES OF PICASSO",
"in_language",
"ENGLISH"
],
[
"THE ADVENTURES OF PICASSO",
"in_language",
"FRENCH"
],
[
"THE APARTMENT",
"has_tags",
"BEST PICTURE"
],
[
"THE APARTMENT",
"in_language",
"FRENCH"
],
[
"THE BIG BLUE",
"in_language",
"ENGLISH"
],
[
"THE BIG BLUE",
"in_language",
"FRENCH"
],
[
"THE CHAMBERMAID ON THE TITANIC",
"in_language",
"ENGLISH"
],
[
"THE CHAMBERMAID ON THE TITANIC",
"in_language",
"FRENCH"
],
[
"THE DAY OF THE JACKAL",
"in_language",
"ENGLISH"
],
[
"THE DAY OF THE JACKAL",
"in_language",
"FRENCH"
],
[
"THE DREAMERS",
"has_tags",
"FRENCH"
],
[
"THE DREAMERS",
"in_language",
"ENGLISH"
],
[
"THE DREAMERS",
"in_language",
"FRENCH"
],
[
"THE FAMILY",
"in_language",
"ENGLISH"
],
[
"THE FAMILY",
"in_language",
"FRENCH"
],
[
"THE FAMILY",
"release_year",
"1987"
],
[
"THE FRENCH CONNECTION",
"has_tags",
"BEST PICTURE"
],
[
"THE FRENCH CONNECTION",
"has_tags",
"NATIONAL FILM REGISTRY"
],
[
"THE FRENCH CONNECTION",
"in_language",
"FRENCH"
],
[
"THE HAIRDRESSER'S HUSBAND",
"in_language",
"FRENCH"
],
[
"THE HAIRDRESSER'S HUSBAND",
"release_year",
"1990"
],
[
"THE HUNCHBACK OF NOTRE DAME",
"in_language",
"ENGLISH"
],
[
"THE HUNCHBACK OF NOTRE DAME",
"in_language",
"FRENCH"
],
[
"THE LAST METRO",
"has_genre",
"WAR"
],
[
"THE LAST METRO",
"in_language",
"FRENCH"
],
[
"THE LAST OF THE MOHICANS",
"has_tags",
"HISTORICAL"
],
[
"THE LAST OF THE MOHICANS",
"in_language",
"ENGLISH"
],
[
"THE LAST OF THE MOHICANS",
"in_language",
"FRENCH"
],
[
"THE LONGEST DAY",
"has_tags",
"WAR"
],
[
"THE LONGEST DAY",
"in_language",
"FRENCH"
],
[
"THE MAN FROM LONDON",
"in_language",
"ENGLISH"
],
[
"THE MAN FROM LONDON",
"in_language",
"FRENCH"
],
[
"THE MAN WHO PLANTED TREES",
"in_language",
"FRENCH"
],
[
"THE MAN WHO PLANTED TREES",
"release_year",
"1987"
],
[
"THE PASSION OF JOAN OF ARC",
"has_tags",
"FRENCH"
],
[
"THE PASSION OF JOAN OF ARC",
"has_tags",
"HISTORICAL"
],
[
"THE PASSION OF JOAN OF ARC",
"in_language",
"FRENCH"
],
[
"THE SCARLET PIMPERNEL",
"in_language",
"ENGLISH"
],
[
"THE SCARLET PIMPERNEL",
"in_language",
"FRENCH"
],
[
"THE SEARCH",
"has_genre",
"WAR"
],
[
"THE SEARCH",
"in_language",
"FRENCH"
],
[
"THE TALL BLOND MAN WITH ONE BLACK SHOE",
"in_language",
"ENGLISH"
],
[
"THE TALL BLOND MAN WITH ONE BLACK SHOE",
"in_language",
"FRENCH"
],
[
"THE TRUTH ABOUT CHARLIE",
"in_language",
"ENGLISH"
],
[
"THE TRUTH ABOUT CHARLIE",
"in_language",
"FRENCH"
],
[
"THE UNDEFEATED",
"has_genre",
"WESTERN"
],
[
"THE UNDEFEATED",
"in_language",
"FRENCH"
],
[
"THE VANISHING",
"in_language",
"ENGLISH"
],
[
"THE VANISHING",
"in_language",
"FRENCH"
],
[
"THE WAR IS OVER",
"has_genre",
"WAR"
],
[
"THE WAR IS OVER",
"in_language",
"FRENCH"
],
[
"UNDER THE BOMBS",
"has_genre",
"WAR"
],
[
"UNDER THE BOMBS",
"in_language",
"FRENCH"
],
[
"UNDER THE SUN OF SATAN",
"directed_by",
"MAURICE PIALAT"
],
[
"UNDER THE SUN OF SATAN",
"in_language",
"FRENCH"
],
[
"UNDER THE SUN OF SATAN",
"release_year",
"1987"
],
[
"UNDER THE SUN OF SATAN",
"starred_actors",
"MAURICE PIALAT"
],
[
"UNDER THE SUN OF SATAN",
"written_by",
"GEORGES BERNANOS"
],
[
"UNDER THE SUN OF SATAN",
"written_by",
"MAURICE PIALAT"
],
[
"URANUS",
"in_language",
"FRENCH"
],
[
"URANUS",
"release_year",
"1990"
],
[
"VENGEANCE",
"in_language",
"ENGLISH"
],
[
"VENGEANCE",
"in_language",
"FRENCH"
],
[
"VIVA MARIA!",
"has_tags",
"FRENCH"
],
[
"VIVA MARIA!",
"in_language",
"ENGLISH"
],
[
"VIVA MARIA!",
"in_language",
"FRENCH"
],
[
"WE WON'T GROW OLD TOGETHER",
"directed_by",
"MAURICE PIALAT"
],
[
"WE WON'T GROW OLD TOGETHER",
"in_language",
"FRENCH"
],
[
"WE WON'T GROW OLD TOGETHER",
"written_by",
"MAURICE PIALAT"
],
[
"WESTERN",
"in_language",
"FRENCH"
],
[
"WOODEN CROSSES",
"has_genre",
"WAR"
],
[
"WOODEN CROSSES",
"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
16055, 1983
17315, 2007
2925, ATONEMENT
30907, BAREFOOT GEN
20266, BEAUFORT
15391, BODY OF WAR
26302, BORN IN FLAMES
1424, CALIFORNIA DREAMIN'
25805, DOCTOR ZHIVAGO
6065, DONALD SUTHERLAND
6943, FALLEN
1033, FRACTURE
33015, GREGORY HOBLIT
33545, HART'S WAR
6036, HEAVY METAL IN BAGHDAD
24224, LIONS FOR LAMBS
28476, MURDER
16348, PERSEPOLIS
31741, PRIMAL FEAR
13081, R
30938, REDACTED
10832, REVOLUTION
35586, SAHARA
30840, SHAKE HANDS WITH THE DEVIL
36258, TALI-IHANTALA 1944
9851, TAXI TO THE DARK SIDE
28461, THE ALAMO
19649, THE COUNTERFEITERS
5893, THE KEY
12691, THE PATRIOT
33742, THE WARLORDS
3640, TO BE OR NOT TO BE
32843, UNDER FIRE
19779, UNDER THE BOMBS
18451, UNTRACEABLE
22214, WAR
src, edge_attr, dst
2925, has_tags, 22214
2925, release_year, 17315
30907, has_tags, 22214
30907, release_year, 16055
20266, has_genre, 22214
20266, release_year, 17315
15391, has_genre, 22214
15391, release_year, 17315
26302, release_year, 16055
1424, has_genre, 22214
1424, release_year, 17315
25805, has_genre, 22214
25805, has_tags, 10832
25805, has_tags, 22214
6943, directed_by, 33015
6943, has_tags, 33015
6943, starred_actors, 6065
1033, directed_by, 33015
1033, has_tags, 33015
1033, has_tags, 28476
1033, has_tags, 13081
1033, release_year, 17315
33545, directed_by, 33015
33545, has_genre, 22214
33545, has_tags, 33015
33545, has_tags, 13081
6036, has_genre, 22214
6036, release_year, 17315
24224, has_genre, 22214
24224, release_year, 17315
16348, has_tags, 10832
16348, has_tags, 22214
16348, release_year, 17315
31741, directed_by, 33015
31741, has_tags, 33015
31741, has_tags, 28476
30938, has_genre, 22214
30938, release_year, 17315
10832, starred_actors, 6065
35586, has_genre, 22214
35586, release_year, 16055
30840, has_genre, 22214
30840, release_year, 17315
36258, has_genre, 22214
36258, release_year, 17315
9851, has_genre, 22214
9851, release_year, 17315
28461, has_genre, 22214
28461, has_tags, 10832
28461, has_tags, 22214
19649, has_genre, 22214
19649, release_year, 17315
5893, has_genre, 22214
5893, release_year, 16055
12691, has_tags, 10832
12691, has_tags, 22214
33742, has_tags, 22214
33742, release_year, 17315
3640, has_genre, 22214
3640, release_year, 16055
32843, has_genre, 22214
32843, release_year, 16055
19779, has_genre, 22214
19779, release_year, 17315
18451, directed_by, 33015
18451, has_tags, 33015
18451, has_tags, 13081
22214, has_tags, 28476
22214, release_year, 17315
Question: In what context are BORN IN FLAMES, GREGORY HOBLIT, and PERSEPOLIS connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"BORN IN FLAMES",
"GREGORY HOBLIT",
"PERSEPOLIS"
],
"valid_edges": [
[
"ATONEMENT",
"has_tags",
"WAR"
],
[
"ATONEMENT",
"release_year",
"2007"
],
[
"BAREFOOT GEN",
"has_tags",
"WAR"
],
[
"BAREFOOT GEN",
"release_year",
"1983"
],
[
"BEAUFORT",
"has_genre",
"WAR"
],
[
"BEAUFORT",
"release_year",
"2007"
],
[
"BODY OF WAR",
"has_genre",
"WAR"
],
[
"BODY OF WAR",
"release_year",
"2007"
],
[
"BORN IN FLAMES",
"release_year",
"1983"
],
[
"CALIFORNIA DREAMIN'",
"has_genre",
"WAR"
],
[
"CALIFORNIA DREAMIN'",
"release_year",
"2007"
],
[
"DOCTOR ZHIVAGO",
"has_genre",
"WAR"
],
[
"DOCTOR ZHIVAGO",
"has_tags",
"REVOLUTION"
],
[
"DOCTOR ZHIVAGO",
"has_tags",
"WAR"
],
[
"FALLEN",
"directed_by",
"GREGORY HOBLIT"
],
[
"FALLEN",
"has_tags",
"GREGORY HOBLIT"
],
[
"FALLEN",
"starred_actors",
"DONALD SUTHERLAND"
],
[
"FRACTURE",
"directed_by",
"GREGORY HOBLIT"
],
[
"FRACTURE",
"has_tags",
"GREGORY HOBLIT"
],
[
"FRACTURE",
"has_tags",
"MURDER"
],
[
"FRACTURE",
"has_tags",
"R"
],
[
"FRACTURE",
"release_year",
"2007"
],
[
"HART'S WAR",
"directed_by",
"GREGORY HOBLIT"
],
[
"HART'S WAR",
"has_genre",
"WAR"
],
[
"HART'S WAR",
"has_tags",
"GREGORY HOBLIT"
],
[
"HART'S WAR",
"has_tags",
"R"
],
[
"HEAVY METAL IN BAGHDAD",
"has_genre",
"WAR"
],
[
"HEAVY METAL IN BAGHDAD",
"release_year",
"2007"
],
[
"LIONS FOR LAMBS",
"has_genre",
"WAR"
],
[
"LIONS FOR LAMBS",
"release_year",
"2007"
],
[
"PERSEPOLIS",
"has_tags",
"REVOLUTION"
],
[
"PERSEPOLIS",
"has_tags",
"WAR"
],
[
"PERSEPOLIS",
"release_year",
"2007"
],
[
"PRIMAL FEAR",
"directed_by",
"GREGORY HOBLIT"
],
[
"PRIMAL FEAR",
"has_tags",
"GREGORY HOBLIT"
],
[
"PRIMAL FEAR",
"has_tags",
"MURDER"
],
[
"REDACTED",
"has_genre",
"WAR"
],
[
"REDACTED",
"release_year",
"2007"
],
[
"REVOLUTION",
"starred_actors",
"DONALD SUTHERLAND"
],
[
"SAHARA",
"has_genre",
"WAR"
],
[
"SAHARA",
"release_year",
"1983"
],
[
"SHAKE HANDS WITH THE DEVIL",
"has_genre",
"WAR"
],
[
"SHAKE HANDS WITH THE DEVIL",
"release_year",
"2007"
],
[
"TALI-IHANTALA 1944",
"has_genre",
"WAR"
],
[
"TALI-IHANTALA 1944",
"release_year",
"2007"
],
[
"TAXI TO THE DARK SIDE",
"has_genre",
"WAR"
],
[
"TAXI TO THE DARK SIDE",
"release_year",
"2007"
],
[
"THE ALAMO",
"has_genre",
"WAR"
],
[
"THE ALAMO",
"has_tags",
"REVOLUTION"
],
[
"THE ALAMO",
"has_tags",
"WAR"
],
[
"THE COUNTERFEITERS",
"has_genre",
"WAR"
],
[
"THE COUNTERFEITERS",
"release_year",
"2007"
],
[
"THE KEY",
"has_genre",
"WAR"
],
[
"THE KEY",
"release_year",
"1983"
],
[
"THE PATRIOT",
"has_tags",
"REVOLUTION"
],
[
"THE PATRIOT",
"has_tags",
"WAR"
],
[
"THE WARLORDS",
"has_tags",
"WAR"
],
[
"THE WARLORDS",
"release_year",
"2007"
],
[
"TO BE OR NOT TO BE",
"has_genre",
"WAR"
],
[
"TO BE OR NOT TO BE",
"release_year",
"1983"
],
[
"UNDER FIRE",
"has_genre",
"WAR"
],
[
"UNDER FIRE",
"release_year",
"1983"
],
[
"UNDER THE BOMBS",
"has_genre",
"WAR"
],
[
"UNDER THE BOMBS",
"release_year",
"2007"
],
[
"UNTRACEABLE",
"directed_by",
"GREGORY HOBLIT"
],
[
"UNTRACEABLE",
"has_tags",
"GREGORY HOBLIT"
],
[
"UNTRACEABLE",
"has_tags",
"R"
],
[
"WAR",
"has_tags",
"MURDER"
],
[
"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
2133, 1998
10045, BD-R
38681, BING CROSBY
4884, BOB HOPE
30463, COMEDY
8426, DANNY KAYE
17144, GRUMPIER OLD MEN
10918, GRUMPY OLD MEN
30818, JACK LEMMON
6956, KNOCK ON WOOD
39629, MARK STEVEN JOHNSON
37141, MEET THE DEEDLES
27102, MELVIN FRANK
7186, MR. BLANDINGS BUILDS HIS DREAM HOUSE
3615, MY FAVORITE BLONDE
12324, NORMAN PANAMA
3548, NOT WITH MY WIFE, YOU DON'T!
39039, ROAD TO UTOPIA
217, SIMON BIRCH
65, STEVE BOYUM
30311, THE COURT JESTER
34071, THE FACTS OF LIFE
12302, THE ROAD TO HONG KONG
10744, WALTER MATTHAU
39802, WHEN IN ROME
src, edge_attr, dst
17144, has_genre, 30463
17144, has_tags, 30463
17144, has_tags, 30818
17144, has_tags, 10744
17144, starred_actors, 30818
17144, starred_actors, 10744
17144, written_by, 39629
10918, has_genre, 30463
10918, has_tags, 30463
10918, has_tags, 30818
10918, has_tags, 10744
10918, starred_actors, 30818
10918, starred_actors, 10744
10918, written_by, 39629
6956, directed_by, 27102
6956, directed_by, 12324
6956, has_genre, 30463
6956, has_tags, 8426
6956, has_tags, 27102
6956, has_tags, 12324
6956, starred_actors, 8426
6956, written_by, 27102
6956, written_by, 12324
37141, directed_by, 65
37141, has_genre, 30463
37141, release_year, 2133
7186, has_genre, 30463
7186, has_tags, 10045
7186, written_by, 27102
7186, written_by, 12324
3615, has_genre, 30463
3615, has_tags, 10045
3615, has_tags, 4884
3615, starred_actors, 4884
3615, written_by, 27102
3615, written_by, 12324
3548, directed_by, 12324
3548, has_genre, 30463
3548, written_by, 27102
3548, written_by, 12324
39039, has_genre, 30463
39039, has_tags, 4884
39039, starred_actors, 38681
39039, starred_actors, 4884
39039, written_by, 27102
39039, written_by, 12324
217, directed_by, 39629
217, has_genre, 30463
217, has_tags, 39629
217, release_year, 2133
217, written_by, 39629
30311, directed_by, 27102
30311, directed_by, 12324
30311, has_genre, 30463
30311, has_tags, 10045
30311, has_tags, 8426
30311, has_tags, 27102
30311, has_tags, 12324
30311, starred_actors, 8426
30311, written_by, 27102
30311, written_by, 12324
34071, directed_by, 27102
34071, has_genre, 30463
34071, starred_actors, 4884
34071, written_by, 27102
34071, written_by, 12324
12302, directed_by, 12324
12302, has_genre, 30463
12302, has_tags, 10045
12302, starred_actors, 38681
12302, starred_actors, 4884
12302, written_by, 12324
39802, directed_by, 39629
39802, has_genre, 30463
Question: In what context are MARK STEVEN JOHNSON, NORMAN PANAMA, and STEVE BOYUM connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"MARK STEVEN JOHNSON",
"NORMAN PANAMA",
"STEVE BOYUM"
],
"valid_edges": [
[
"GRUMPIER OLD MEN",
"has_genre",
"COMEDY"
],
[
"GRUMPIER OLD MEN",
"has_tags",
"COMEDY"
],
[
"GRUMPIER OLD MEN",
"has_tags",
"JACK LEMMON"
],
[
"GRUMPIER OLD MEN",
"has_tags",
"WALTER MATTHAU"
],
[
"GRUMPIER OLD MEN",
"starred_actors",
"JACK LEMMON"
],
[
"GRUMPIER OLD MEN",
"starred_actors",
"WALTER MATTHAU"
],
[
"GRUMPIER OLD MEN",
"written_by",
"MARK STEVEN JOHNSON"
],
[
"GRUMPY OLD MEN",
"has_genre",
"COMEDY"
],
[
"GRUMPY OLD MEN",
"has_tags",
"COMEDY"
],
[
"GRUMPY OLD MEN",
"has_tags",
"JACK LEMMON"
],
[
"GRUMPY OLD MEN",
"has_tags",
"WALTER MATTHAU"
],
[
"GRUMPY OLD MEN",
"starred_actors",
"JACK LEMMON"
],
[
"GRUMPY OLD MEN",
"starred_actors",
"WALTER MATTHAU"
],
[
"GRUMPY OLD MEN",
"written_by",
"MARK STEVEN JOHNSON"
],
[
"KNOCK ON WOOD",
"directed_by",
"MELVIN FRANK"
],
[
"KNOCK ON WOOD",
"directed_by",
"NORMAN PANAMA"
],
[
"KNOCK ON WOOD",
"has_genre",
"COMEDY"
],
[
"KNOCK ON WOOD",
"has_tags",
"DANNY KAYE"
],
[
"KNOCK ON WOOD",
"has_tags",
"MELVIN FRANK"
],
[
"KNOCK ON WOOD",
"has_tags",
"NORMAN PANAMA"
],
[
"KNOCK ON WOOD",
"starred_actors",
"DANNY KAYE"
],
[
"KNOCK ON WOOD",
"written_by",
"MELVIN FRANK"
],
[
"KNOCK ON WOOD",
"written_by",
"NORMAN PANAMA"
],
[
"MEET THE DEEDLES",
"directed_by",
"STEVE BOYUM"
],
[
"MEET THE DEEDLES",
"has_genre",
"COMEDY"
],
[
"MEET THE DEEDLES",
"release_year",
"1998"
],
[
"MR. BLANDINGS BUILDS HIS DREAM HOUSE",
"has_genre",
"COMEDY"
],
[
"MR. BLANDINGS BUILDS HIS DREAM HOUSE",
"has_tags",
"BD-R"
],
[
"MR. BLANDINGS BUILDS HIS DREAM HOUSE",
"written_by",
"MELVIN FRANK"
],
[
"MR. BLANDINGS BUILDS HIS DREAM HOUSE",
"written_by",
"NORMAN PANAMA"
],
[
"MY FAVORITE BLONDE",
"has_genre",
"COMEDY"
],
[
"MY FAVORITE BLONDE",
"has_tags",
"BD-R"
],
[
"MY FAVORITE BLONDE",
"has_tags",
"BOB HOPE"
],
[
"MY FAVORITE BLONDE",
"starred_actors",
"BOB HOPE"
],
[
"MY FAVORITE BLONDE",
"written_by",
"MELVIN FRANK"
],
[
"MY FAVORITE BLONDE",
"written_by",
"NORMAN PANAMA"
],
[
"NOT WITH MY WIFE, YOU DON'T!",
"directed_by",
"NORMAN PANAMA"
],
[
"NOT WITH MY WIFE, YOU DON'T!",
"has_genre",
"COMEDY"
],
[
"NOT WITH MY WIFE, YOU DON'T!",
"written_by",
"MELVIN FRANK"
],
[
"NOT WITH MY WIFE, YOU DON'T!",
"written_by",
"NORMAN PANAMA"
],
[
"ROAD TO UTOPIA",
"has_genre",
"COMEDY"
],
[
"ROAD TO UTOPIA",
"has_tags",
"BOB HOPE"
],
[
"ROAD TO UTOPIA",
"starred_actors",
"BING CROSBY"
],
[
"ROAD TO UTOPIA",
"starred_actors",
"BOB HOPE"
],
[
"ROAD TO UTOPIA",
"written_by",
"MELVIN FRANK"
],
[
"ROAD TO UTOPIA",
"written_by",
"NORMAN PANAMA"
],
[
"SIMON BIRCH",
"directed_by",
"MARK STEVEN JOHNSON"
],
[
"SIMON BIRCH",
"has_genre",
"COMEDY"
],
[
"SIMON BIRCH",
"has_tags",
"MARK STEVEN JOHNSON"
],
[
"SIMON BIRCH",
"release_year",
"1998"
],
[
"SIMON BIRCH",
"written_by",
"MARK STEVEN JOHNSON"
],
[
"THE COURT JESTER",
"directed_by",
"MELVIN FRANK"
],
[
"THE COURT JESTER",
"directed_by",
"NORMAN PANAMA"
],
[
"THE COURT JESTER",
"has_genre",
"COMEDY"
],
[
"THE COURT JESTER",
"has_tags",
"BD-R"
],
[
"THE COURT JESTER",
"has_tags",
"DANNY KAYE"
],
[
"THE COURT JESTER",
"has_tags",
"MELVIN FRANK"
],
[
"THE COURT JESTER",
"has_tags",
"NORMAN PANAMA"
],
[
"THE COURT JESTER",
"starred_actors",
"DANNY KAYE"
],
[
"THE COURT JESTER",
"written_by",
"MELVIN FRANK"
],
[
"THE COURT JESTER",
"written_by",
"NORMAN PANAMA"
],
[
"THE FACTS OF LIFE",
"directed_by",
"MELVIN FRANK"
],
[
"THE FACTS OF LIFE",
"has_genre",
"COMEDY"
],
[
"THE FACTS OF LIFE",
"starred_actors",
"BOB HOPE"
],
[
"THE FACTS OF LIFE",
"written_by",
"MELVIN FRANK"
],
[
"THE FACTS OF LIFE",
"written_by",
"NORMAN PANAMA"
],
[
"THE ROAD TO HONG KONG",
"directed_by",
"NORMAN PANAMA"
],
[
"THE ROAD TO HONG KONG",
"has_genre",
"COMEDY"
],
[
"THE ROAD TO HONG KONG",
"has_tags",
"BD-R"
],
[
"THE ROAD TO HONG KONG",
"starred_actors",
"BING CROSBY"
],
[
"THE ROAD TO HONG KONG",
"starred_actors",
"BOB HOPE"
],
[
"THE ROAD TO HONG KONG",
"written_by",
"NORMAN PANAMA"
],
[
"WHEN IN ROME",
"directed_by",
"MARK STEVEN JOHNSON"
],
[
"WHEN IN ROME",
"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
14004, 1955
38097, 1985
21282, A GUY AND A GAL
31859, LASSE HALLSTRÖM
7649, MAN WITH THE GUN
14392, MORE ABOUT THE CHILDREN OF NOISY VILLAGE
31562, MY LIFE AS A DOG
3856, SMOOTH TALK
32687, SWEDISH
11486, THE CHILDREN OF NOISY VILLAGE
26071, THE HYPNOTIST
19659, THE UNKNOWN SOLDIER
src, edge_attr, dst
21282, directed_by, 31859
21282, in_language, 32687
21282, written_by, 31859
7649, release_year, 14004
14392, directed_by, 31859
14392, in_language, 32687
31562, directed_by, 31859
31562, has_tags, 31859
31562, has_tags, 32687
31562, in_language, 32687
31562, release_year, 38097
31562, written_by, 31859
3856, release_year, 38097
11486, directed_by, 31859
11486, in_language, 32687
26071, directed_by, 31859
26071, in_language, 32687
26071, written_by, 31859
19659, release_year, 14004
19659, release_year, 38097
Question: For what reason are A GUY AND A GAL, MAN WITH THE GUN, and SMOOTH TALK associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"A GUY AND A GAL",
"MAN WITH THE GUN",
"SMOOTH TALK"
],
"valid_edges": [
[
"A GUY AND A GAL",
"directed_by",
"LASSE HALLSTRÖM"
],
[
"A GUY AND A GAL",
"in_language",
"SWEDISH"
],
[
"A GUY AND A GAL",
"written_by",
"LASSE HALLSTRÖM"
],
[
"MAN WITH THE GUN",
"release_year",
"1955"
],
[
"MORE ABOUT THE CHILDREN OF NOISY VILLAGE",
"directed_by",
"LASSE HALLSTRÖM"
],
[
"MORE ABOUT THE CHILDREN OF NOISY VILLAGE",
"in_language",
"SWEDISH"
],
[
"MY LIFE AS A DOG",
"directed_by",
"LASSE HALLSTRÖM"
],
[
"MY LIFE AS A DOG",
"has_tags",
"LASSE HALLSTRÖM"
],
[
"MY LIFE AS A DOG",
"has_tags",
"SWEDISH"
],
[
"MY LIFE AS A DOG",
"in_language",
"SWEDISH"
],
[
"MY LIFE AS A DOG",
"release_year",
"1985"
],
[
"MY LIFE AS A DOG",
"written_by",
"LASSE HALLSTRÖM"
],
[
"SMOOTH TALK",
"release_year",
"1985"
],
[
"THE CHILDREN OF NOISY VILLAGE",
"directed_by",
"LASSE HALLSTRÖM"
],
[
"THE CHILDREN OF NOISY VILLAGE",
"in_language",
"SWEDISH"
],
[
"THE HYPNOTIST",
"directed_by",
"LASSE HALLSTRÖM"
],
[
"THE HYPNOTIST",
"in_language",
"SWEDISH"
],
[
"THE HYPNOTIST",
"written_by",
"LASSE HALLSTRÖM"
],
[
"THE UNKNOWN SOLDIER",
"release_year",
"1955"
],
[
"THE UNKNOWN SOLDIER",
"release_year",
"1985"
]
]
}
|
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
37707, DRACULA'S DAUGHTER
5870, HORROR
10608, MAGIC
26644, OK
38265, THE DEVIL-DOLL
23802, THE MASK
36578, THE PEOPLE UNDER THE STAIRS
13780, THE WALKING DEAD
14809, WIFE VS. SECRETARY
src, edge_attr, dst
37707, has_genre, 5870
37707, release_year, 6253
10608, has_genre, 5870
38265, has_genre, 5870
38265, release_year, 6253
23802, has_tags, 10608
23802, has_tags, 26644
36578, has_genre, 5870
13780, has_genre, 5870
13780, release_year, 6253
14809, release_year, 6253
Question: In what context are OK, THE PEOPLE UNDER THE STAIRS, and WIFE VS. SECRETARY connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"OK",
"THE PEOPLE UNDER THE STAIRS",
"WIFE VS. SECRETARY"
],
"valid_edges": [
[
"DRACULA'S DAUGHTER",
"has_genre",
"HORROR"
],
[
"DRACULA'S DAUGHTER",
"release_year",
"1936"
],
[
"MAGIC",
"has_genre",
"HORROR"
],
[
"THE DEVIL-DOLL",
"has_genre",
"HORROR"
],
[
"THE DEVIL-DOLL",
"release_year",
"1936"
],
[
"THE MASK",
"has_tags",
"MAGIC"
],
[
"THE MASK",
"has_tags",
"OK"
],
[
"THE PEOPLE UNDER THE STAIRS",
"has_genre",
"HORROR"
],
[
"THE WALKING DEAD",
"has_genre",
"HORROR"
],
[
"THE WALKING DEAD",
"release_year",
"1936"
],
[
"WIFE VS. SECRETARY",
"release_year",
"1936"
]
]
}
|
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
2133, 1998
29424, 2011
34781, A DANGEROUS METHOD
35101, ABDUCTION
22365, KEIRA KNIGHTLEY
38783, LAST NIGHT
22833, ROBERT COSTANZO
37634, TAYLOR LAUTNER
1905, WITH FRIENDS LIKE THESE...
src, edge_attr, dst
34781, has_tags, 22365
34781, release_year, 29424
34781, starred_actors, 22365
35101, has_tags, 37634
35101, release_year, 29424
38783, has_tags, 22365
38783, release_year, 2133
38783, starred_actors, 22365
1905, release_year, 2133
1905, starred_actors, 22833
Question: How are KEIRA KNIGHTLEY, ROBERT COSTANZO, and TAYLOR LAUTNER related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"KEIRA KNIGHTLEY",
"ROBERT COSTANZO",
"TAYLOR LAUTNER"
],
"valid_edges": [
[
"A DANGEROUS METHOD",
"has_tags",
"KEIRA KNIGHTLEY"
],
[
"A DANGEROUS METHOD",
"release_year",
"2011"
],
[
"A DANGEROUS METHOD",
"starred_actors",
"KEIRA KNIGHTLEY"
],
[
"ABDUCTION",
"has_tags",
"TAYLOR LAUTNER"
],
[
"ABDUCTION",
"release_year",
"2011"
],
[
"LAST NIGHT",
"has_tags",
"KEIRA KNIGHTLEY"
],
[
"LAST NIGHT",
"release_year",
"1998"
],
[
"LAST NIGHT",
"starred_actors",
"KEIRA KNIGHTLEY"
],
[
"WITH FRIENDS LIKE THESE...",
"release_year",
"1998"
],
[
"WITH FRIENDS LIKE THESE...",
"starred_actors",
"ROBERT COSTANZO"
]
]
}
|
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
3458, 1951
27261, 2009
12088, ACCIDENT
26158, ANOTHER MAN'S POISON
23227, ARMORED
9367, BETTE DAVIS
4197, BLUEBEARD
37883, BROKEN EMBRACES
29300, DEAD RINGER
8381, DETOUR
6932, M
29624, MADAME SIN
33763, MOONSTRUCK
36943, NEW YORK
410, NORMAN JEWISON
12428, RAGE
40046, STRANGERS ON A TRAIN
4337, THE CRY OF THE OWL
21338, THE GIRL WHO PLAYED WITH FIRE
33948, THE LETTER
10959, THE PROWLER
37148, THE SECRET IN THEIR EYES
35993, THE STEPFATHER
24811, THRILLER
28071, WHAT EVER HAPPENED TO BABY JANE?
src, edge_attr, dst
12088, has_genre, 24811
12088, release_year, 27261
26158, release_year, 3458
26158, starred_actors, 9367
23227, has_genre, 24811
23227, release_year, 27261
4197, has_genre, 24811
4197, release_year, 27261
37883, has_genre, 24811
37883, release_year, 27261
29300, has_genre, 24811
29300, starred_actors, 9367
8381, has_genre, 24811
8381, release_year, 27261
6932, has_genre, 24811
6932, release_year, 3458
29624, has_genre, 24811
29624, starred_actors, 9367
33763, directed_by, 410
33763, has_tags, 36943
33763, has_tags, 410
36943, release_year, 27261
12428, has_genre, 24811
12428, release_year, 27261
40046, has_genre, 24811
40046, release_year, 3458
4337, has_genre, 24811
4337, release_year, 27261
21338, has_tags, 24811
21338, release_year, 27261
33948, has_genre, 24811
33948, has_tags, 9367
33948, starred_actors, 9367
10959, has_genre, 24811
10959, release_year, 3458
37148, has_genre, 24811
37148, release_year, 27261
35993, has_genre, 24811
35993, release_year, 27261
28071, has_genre, 24811
28071, has_tags, 9367
28071, starred_actors, 9367
Question: For what reason are ANOTHER MAN'S POISON, BROKEN EMBRACES, and NORMAN JEWISON associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"ANOTHER MAN'S POISON",
"BROKEN EMBRACES",
"NORMAN JEWISON"
],
"valid_edges": [
[
"ACCIDENT",
"has_genre",
"THRILLER"
],
[
"ACCIDENT",
"release_year",
"2009"
],
[
"ANOTHER MAN'S POISON",
"release_year",
"1951"
],
[
"ANOTHER MAN'S POISON",
"starred_actors",
"BETTE DAVIS"
],
[
"ARMORED",
"has_genre",
"THRILLER"
],
[
"ARMORED",
"release_year",
"2009"
],
[
"BLUEBEARD",
"has_genre",
"THRILLER"
],
[
"BLUEBEARD",
"release_year",
"2009"
],
[
"BROKEN EMBRACES",
"has_genre",
"THRILLER"
],
[
"BROKEN EMBRACES",
"release_year",
"2009"
],
[
"DEAD RINGER",
"has_genre",
"THRILLER"
],
[
"DEAD RINGER",
"starred_actors",
"BETTE DAVIS"
],
[
"DETOUR",
"has_genre",
"THRILLER"
],
[
"DETOUR",
"release_year",
"2009"
],
[
"M",
"has_genre",
"THRILLER"
],
[
"M",
"release_year",
"1951"
],
[
"MADAME SIN",
"has_genre",
"THRILLER"
],
[
"MADAME SIN",
"starred_actors",
"BETTE DAVIS"
],
[
"MOONSTRUCK",
"directed_by",
"NORMAN JEWISON"
],
[
"MOONSTRUCK",
"has_tags",
"NEW YORK"
],
[
"MOONSTRUCK",
"has_tags",
"NORMAN JEWISON"
],
[
"NEW YORK",
"release_year",
"2009"
],
[
"RAGE",
"has_genre",
"THRILLER"
],
[
"RAGE",
"release_year",
"2009"
],
[
"STRANGERS ON A TRAIN",
"has_genre",
"THRILLER"
],
[
"STRANGERS ON A TRAIN",
"release_year",
"1951"
],
[
"THE CRY OF THE OWL",
"has_genre",
"THRILLER"
],
[
"THE CRY OF THE OWL",
"release_year",
"2009"
],
[
"THE GIRL WHO PLAYED WITH FIRE",
"has_tags",
"THRILLER"
],
[
"THE GIRL WHO PLAYED WITH FIRE",
"release_year",
"2009"
],
[
"THE LETTER",
"has_genre",
"THRILLER"
],
[
"THE LETTER",
"has_tags",
"BETTE DAVIS"
],
[
"THE LETTER",
"starred_actors",
"BETTE DAVIS"
],
[
"THE PROWLER",
"has_genre",
"THRILLER"
],
[
"THE PROWLER",
"release_year",
"1951"
],
[
"THE SECRET IN THEIR EYES",
"has_genre",
"THRILLER"
],
[
"THE SECRET IN THEIR EYES",
"release_year",
"2009"
],
[
"THE STEPFATHER",
"has_genre",
"THRILLER"
],
[
"THE STEPFATHER",
"release_year",
"2009"
],
[
"WHAT EVER HAPPENED TO BABY JANE?",
"has_genre",
"THRILLER"
],
[
"WHAT EVER HAPPENED TO BABY JANE?",
"has_tags",
"BETTE DAVIS"
],
[
"WHAT EVER HAPPENED TO BABY JANE?",
"starred_actors",
"BETTE DAVIS"
]
]
}
|
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
34742, ATLANTIS, THE LOST CONTINENT
6589, CALLE 54
17035, DEBTOCRACY
12841, DOCUMENTARY
26751, EARTH
690, FLAMENCO
23106, LAND WITHOUT BREAD
39673, LOS OLVIDADOS
35505, LUIS BUÑUEL
38195, ROBINSON CRUSOE
28557, SAL PONTI
7556, SPANISH
27171, TEENAGE PAPARAZZO
13882, THAT OBSCURE OBJECT OF DESIRE
26605, THE CRIMINAL LIFE OF ARCHIBALDO DE LA CRUZ
15347, THE DISCREET CHARM OF THE BOURGEOISIE
27570, THE EXTERMINATING ANGEL
14832, TRISTANA
15034, VIRIDIANA
src, edge_attr, dst
34742, release_year, 22772
34742, starred_actors, 28557
6589, has_genre, 12841
6589, in_language, 7556
17035, has_genre, 12841
17035, in_language, 7556
26751, has_genre, 12841
26751, in_language, 7556
690, has_genre, 12841
690, in_language, 7556
23106, directed_by, 35505
23106, has_genre, 12841
23106, has_tags, 35505
23106, written_by, 35505
39673, directed_by, 35505
39673, has_tags, 35505
39673, in_language, 7556
39673, written_by, 35505
38195, directed_by, 35505
38195, has_tags, 35505
38195, in_language, 7556
38195, written_by, 35505
27171, has_genre, 12841
13882, directed_by, 35505
13882, has_tags, 35505
13882, in_language, 7556
13882, written_by, 35505
26605, directed_by, 35505
26605, has_tags, 35505
26605, in_language, 7556
26605, written_by, 35505
15347, directed_by, 35505
15347, has_tags, 35505
15347, in_language, 7556
15347, written_by, 35505
27570, directed_by, 35505
27570, has_tags, 35505
27570, in_language, 7556
27570, written_by, 35505
14832, directed_by, 35505
14832, has_tags, 35505
14832, in_language, 7556
14832, written_by, 35505
15034, directed_by, 35505
15034, has_tags, 35505
15034, in_language, 7556
15034, release_year, 22772
15034, written_by, 35505
Question: How are SAL PONTI, TEENAGE PAPARAZZO, and VIRIDIANA related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"SAL PONTI",
"TEENAGE PAPARAZZO",
"VIRIDIANA"
],
"valid_edges": [
[
"ATLANTIS, THE LOST CONTINENT",
"release_year",
"1961"
],
[
"ATLANTIS, THE LOST CONTINENT",
"starred_actors",
"SAL PONTI"
],
[
"CALLE 54",
"has_genre",
"DOCUMENTARY"
],
[
"CALLE 54",
"in_language",
"SPANISH"
],
[
"DEBTOCRACY",
"has_genre",
"DOCUMENTARY"
],
[
"DEBTOCRACY",
"in_language",
"SPANISH"
],
[
"EARTH",
"has_genre",
"DOCUMENTARY"
],
[
"EARTH",
"in_language",
"SPANISH"
],
[
"FLAMENCO",
"has_genre",
"DOCUMENTARY"
],
[
"FLAMENCO",
"in_language",
"SPANISH"
],
[
"LAND WITHOUT BREAD",
"directed_by",
"LUIS BUÑUEL"
],
[
"LAND WITHOUT BREAD",
"has_genre",
"DOCUMENTARY"
],
[
"LAND WITHOUT BREAD",
"has_tags",
"LUIS BUÑUEL"
],
[
"LAND WITHOUT BREAD",
"written_by",
"LUIS BUÑUEL"
],
[
"LOS OLVIDADOS",
"directed_by",
"LUIS BUÑUEL"
],
[
"LOS OLVIDADOS",
"has_tags",
"LUIS BUÑUEL"
],
[
"LOS OLVIDADOS",
"in_language",
"SPANISH"
],
[
"LOS OLVIDADOS",
"written_by",
"LUIS BUÑUEL"
],
[
"ROBINSON CRUSOE",
"directed_by",
"LUIS BUÑUEL"
],
[
"ROBINSON CRUSOE",
"has_tags",
"LUIS BUÑUEL"
],
[
"ROBINSON CRUSOE",
"in_language",
"SPANISH"
],
[
"ROBINSON CRUSOE",
"written_by",
"LUIS BUÑUEL"
],
[
"TEENAGE PAPARAZZO",
"has_genre",
"DOCUMENTARY"
],
[
"THAT OBSCURE OBJECT OF DESIRE",
"directed_by",
"LUIS BUÑUEL"
],
[
"THAT OBSCURE OBJECT OF DESIRE",
"has_tags",
"LUIS BUÑUEL"
],
[
"THAT OBSCURE OBJECT OF DESIRE",
"in_language",
"SPANISH"
],
[
"THAT OBSCURE OBJECT OF DESIRE",
"written_by",
"LUIS BUÑUEL"
],
[
"THE CRIMINAL LIFE OF ARCHIBALDO DE LA CRUZ",
"directed_by",
"LUIS BUÑUEL"
],
[
"THE CRIMINAL LIFE OF ARCHIBALDO DE LA CRUZ",
"has_tags",
"LUIS BUÑUEL"
],
[
"THE CRIMINAL LIFE OF ARCHIBALDO DE LA CRUZ",
"in_language",
"SPANISH"
],
[
"THE CRIMINAL LIFE OF ARCHIBALDO DE LA CRUZ",
"written_by",
"LUIS BUÑUEL"
],
[
"THE DISCREET CHARM OF THE BOURGEOISIE",
"directed_by",
"LUIS BUÑUEL"
],
[
"THE DISCREET CHARM OF THE BOURGEOISIE",
"has_tags",
"LUIS BUÑUEL"
],
[
"THE DISCREET CHARM OF THE BOURGEOISIE",
"in_language",
"SPANISH"
],
[
"THE DISCREET CHARM OF THE BOURGEOISIE",
"written_by",
"LUIS BUÑUEL"
],
[
"THE EXTERMINATING ANGEL",
"directed_by",
"LUIS BUÑUEL"
],
[
"THE EXTERMINATING ANGEL",
"has_tags",
"LUIS BUÑUEL"
],
[
"THE EXTERMINATING ANGEL",
"in_language",
"SPANISH"
],
[
"THE EXTERMINATING ANGEL",
"written_by",
"LUIS BUÑUEL"
],
[
"TRISTANA",
"directed_by",
"LUIS BUÑUEL"
],
[
"TRISTANA",
"has_tags",
"LUIS BUÑUEL"
],
[
"TRISTANA",
"in_language",
"SPANISH"
],
[
"TRISTANA",
"written_by",
"LUIS BUÑUEL"
],
[
"VIRIDIANA",
"directed_by",
"LUIS BUÑUEL"
],
[
"VIRIDIANA",
"has_tags",
"LUIS BUÑUEL"
],
[
"VIRIDIANA",
"in_language",
"SPANISH"
],
[
"VIRIDIANA",
"release_year",
"1961"
],
[
"VIRIDIANA",
"written_by",
"LUIS BUÑUEL"
]
]
}
|
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
10293, CONSPIRACY
36212, DRAMA
16970, EUREKA
26708, GOOD WILL HUNTING
22139, JFK
20643, MATT DAMON
18997, THE DEPARTED
16072, THE RAINMAKER
15424, ZACHARY SKLAR
src, edge_attr, dst
10293, has_genre, 36212
16970, has_genre, 36212
26708, has_genre, 36212
26708, has_tags, 20643
26708, starred_actors, 20643
26708, written_by, 20643
22139, has_tags, 10293
22139, written_by, 15424
18997, has_genre, 36212
18997, has_tags, 20643
18997, starred_actors, 20643
16072, has_genre, 36212
16072, has_tags, 20643
16072, starred_actors, 20643
Question: In what context are EUREKA, THE RAINMAKER, and ZACHARY SKLAR connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"EUREKA",
"THE RAINMAKER",
"ZACHARY SKLAR"
],
"valid_edges": [
[
"CONSPIRACY",
"has_genre",
"DRAMA"
],
[
"EUREKA",
"has_genre",
"DRAMA"
],
[
"GOOD WILL HUNTING",
"has_genre",
"DRAMA"
],
[
"GOOD WILL HUNTING",
"has_tags",
"MATT DAMON"
],
[
"GOOD WILL HUNTING",
"starred_actors",
"MATT DAMON"
],
[
"GOOD WILL HUNTING",
"written_by",
"MATT DAMON"
],
[
"JFK",
"has_tags",
"CONSPIRACY"
],
[
"JFK",
"written_by",
"ZACHARY SKLAR"
],
[
"THE DEPARTED",
"has_genre",
"DRAMA"
],
[
"THE DEPARTED",
"has_tags",
"MATT DAMON"
],
[
"THE DEPARTED",
"starred_actors",
"MATT DAMON"
],
[
"THE RAINMAKER",
"has_genre",
"DRAMA"
],
[
"THE RAINMAKER",
"has_tags",
"MATT DAMON"
],
[
"THE RAINMAKER",
"starred_actors",
"MATT DAMON"
]
]
}
|
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
29815, A SHORT FILM ABOUT JOHN BOLTON
3216, APPLE JACK
32628, BOUNDIN'
31783, ENGLISH
13108, FRANKENSTEIN
23419, HANGOVER SQUARE
34055, HARVIE KRUMPET
35319, HOPE SPRINGS
28169, IN THE CUT
6425, IT'S ALL ABOUT LOVE
37963, JOHNNY ENGLISH
25787, KOPPS
18336, LAST LIFE IN THE UNIVERSE
17704, NED KELLY
2971, PETER O'BRIEN
3491, PUMZI
3416, SARABAND
36899, SHORT
31200, SVIDD NEGER
13334, SWIMMING POOL
21345, THE DREAMERS
5956, THE LONG AND SHORT OF IT
28919, THE RETURN
12883, THE SLEEPING DICTIONARY
27063, TOUCHING THE VOID
10238, UNDERWORLD
src, edge_attr, dst
29815, has_genre, 36899
29815, release_year, 1097
3216, has_genre, 36899
3216, release_year, 1097
32628, has_genre, 36899
32628, has_tags, 36899
32628, release_year, 1097
13108, has_genre, 36899
13108, has_tags, 36899
13108, in_language, 31783
23419, in_language, 31783
34055, has_genre, 36899
34055, has_tags, 36899
34055, release_year, 1097
35319, in_language, 31783
35319, release_year, 1097
28169, in_language, 31783
28169, release_year, 1097
6425, in_language, 31783
6425, release_year, 1097
37963, in_language, 31783
37963, release_year, 1097
25787, in_language, 31783
25787, release_year, 1097
18336, in_language, 31783
18336, release_year, 1097
17704, in_language, 31783
17704, release_year, 1097
3491, has_genre, 36899
3491, in_language, 31783
3416, in_language, 31783
3416, release_year, 1097
31200, in_language, 31783
31200, release_year, 1097
13334, in_language, 31783
13334, release_year, 1097
21345, in_language, 31783
21345, release_year, 1097
5956, has_genre, 36899
5956, release_year, 1097
28919, release_year, 1097
28919, starred_actors, 2971
12883, in_language, 31783
12883, release_year, 1097
27063, in_language, 31783
27063, release_year, 1097
10238, in_language, 31783
10238, release_year, 1097
Question: For what reason are A SHORT FILM ABOUT JOHN BOLTON, HANGOVER SQUARE, and PETER O'BRIEN associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"A SHORT FILM ABOUT JOHN BOLTON",
"HANGOVER SQUARE",
"PETER O'BRIEN"
],
"valid_edges": [
[
"A SHORT FILM ABOUT JOHN BOLTON",
"has_genre",
"SHORT"
],
[
"A SHORT FILM ABOUT JOHN BOLTON",
"release_year",
"2003"
],
[
"APPLE JACK",
"has_genre",
"SHORT"
],
[
"APPLE JACK",
"release_year",
"2003"
],
[
"BOUNDIN'",
"has_genre",
"SHORT"
],
[
"BOUNDIN'",
"has_tags",
"SHORT"
],
[
"BOUNDIN'",
"release_year",
"2003"
],
[
"FRANKENSTEIN",
"has_genre",
"SHORT"
],
[
"FRANKENSTEIN",
"has_tags",
"SHORT"
],
[
"FRANKENSTEIN",
"in_language",
"ENGLISH"
],
[
"HANGOVER SQUARE",
"in_language",
"ENGLISH"
],
[
"HARVIE KRUMPET",
"has_genre",
"SHORT"
],
[
"HARVIE KRUMPET",
"has_tags",
"SHORT"
],
[
"HARVIE KRUMPET",
"release_year",
"2003"
],
[
"HOPE SPRINGS",
"in_language",
"ENGLISH"
],
[
"HOPE SPRINGS",
"release_year",
"2003"
],
[
"IN THE CUT",
"in_language",
"ENGLISH"
],
[
"IN THE CUT",
"release_year",
"2003"
],
[
"IT'S ALL ABOUT LOVE",
"in_language",
"ENGLISH"
],
[
"IT'S ALL ABOUT LOVE",
"release_year",
"2003"
],
[
"JOHNNY ENGLISH",
"in_language",
"ENGLISH"
],
[
"JOHNNY ENGLISH",
"release_year",
"2003"
],
[
"KOPPS",
"in_language",
"ENGLISH"
],
[
"KOPPS",
"release_year",
"2003"
],
[
"LAST LIFE IN THE UNIVERSE",
"in_language",
"ENGLISH"
],
[
"LAST LIFE IN THE UNIVERSE",
"release_year",
"2003"
],
[
"NED KELLY",
"in_language",
"ENGLISH"
],
[
"NED KELLY",
"release_year",
"2003"
],
[
"PUMZI",
"has_genre",
"SHORT"
],
[
"PUMZI",
"in_language",
"ENGLISH"
],
[
"SARABAND",
"in_language",
"ENGLISH"
],
[
"SARABAND",
"release_year",
"2003"
],
[
"SVIDD NEGER",
"in_language",
"ENGLISH"
],
[
"SVIDD NEGER",
"release_year",
"2003"
],
[
"SWIMMING POOL",
"in_language",
"ENGLISH"
],
[
"SWIMMING POOL",
"release_year",
"2003"
],
[
"THE DREAMERS",
"in_language",
"ENGLISH"
],
[
"THE DREAMERS",
"release_year",
"2003"
],
[
"THE LONG AND SHORT OF IT",
"has_genre",
"SHORT"
],
[
"THE LONG AND SHORT OF IT",
"release_year",
"2003"
],
[
"THE RETURN",
"release_year",
"2003"
],
[
"THE RETURN",
"starred_actors",
"PETER O'BRIEN"
],
[
"THE SLEEPING DICTIONARY",
"in_language",
"ENGLISH"
],
[
"THE SLEEPING DICTIONARY",
"release_year",
"2003"
],
[
"TOUCHING THE VOID",
"in_language",
"ENGLISH"
],
[
"TOUCHING THE VOID",
"release_year",
"2003"
],
[
"UNDERWORLD",
"in_language",
"ENGLISH"
],
[
"UNDERWORLD",
"release_year",
"2003"
]
]
}
|
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
39813, 1971
6094, A CLOCKWORK ORANGE
11774, BEDKNOBS AND BROOMSTICKS
23417, DAUGHTERS OF DARKNESS
31783, ENGLISH
19921, FLORA FAUNA
19686, GEORGE B. SEITZ
15765, HAMSUN
17619, LIV ULLMANN
24601, LOST HORIZON
20992, MACBETH
21095, MAX VON SYDOW
35163, SHATTER DEAD
9448, SILENCE
25888, THE BURGLARS
22582, THE LAST OF THE MOHICANS
15196, THE NIGHT VISITOR
10133, UNKNOWN
src, edge_attr, dst
6094, in_language, 31783
6094, release_year, 39813
11774, in_language, 31783
11774, release_year, 39813
23417, in_language, 31783
23417, release_year, 39813
15765, has_tags, 21095
15765, in_language, 31783
15765, starred_actors, 21095
24601, in_language, 31783
24601, starred_actors, 17619
20992, in_language, 31783
20992, release_year, 39813
35163, has_imdb_votes, 10133
35163, starred_actors, 19921
9448, in_language, 31783
9448, release_year, 39813
25888, in_language, 31783
25888, release_year, 39813
22582, directed_by, 19686
22582, in_language, 31783
15196, in_language, 31783
15196, release_year, 39813
15196, starred_actors, 17619
15196, starred_actors, 21095
10133, in_language, 31783
Question: In what context are FLORA FAUNA, GEORGE B. SEITZ, and THE NIGHT VISITOR connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"FLORA FAUNA",
"GEORGE B. SEITZ",
"THE NIGHT VISITOR"
],
"valid_edges": [
[
"A CLOCKWORK ORANGE",
"in_language",
"ENGLISH"
],
[
"A CLOCKWORK ORANGE",
"release_year",
"1971"
],
[
"BEDKNOBS AND BROOMSTICKS",
"in_language",
"ENGLISH"
],
[
"BEDKNOBS AND BROOMSTICKS",
"release_year",
"1971"
],
[
"DAUGHTERS OF DARKNESS",
"in_language",
"ENGLISH"
],
[
"DAUGHTERS OF DARKNESS",
"release_year",
"1971"
],
[
"HAMSUN",
"has_tags",
"MAX VON SYDOW"
],
[
"HAMSUN",
"in_language",
"ENGLISH"
],
[
"HAMSUN",
"starred_actors",
"MAX VON SYDOW"
],
[
"LOST HORIZON",
"in_language",
"ENGLISH"
],
[
"LOST HORIZON",
"starred_actors",
"LIV ULLMANN"
],
[
"MACBETH",
"in_language",
"ENGLISH"
],
[
"MACBETH",
"release_year",
"1971"
],
[
"SHATTER DEAD",
"has_imdb_votes",
"UNKNOWN"
],
[
"SHATTER DEAD",
"starred_actors",
"FLORA FAUNA"
],
[
"SILENCE",
"in_language",
"ENGLISH"
],
[
"SILENCE",
"release_year",
"1971"
],
[
"THE BURGLARS",
"in_language",
"ENGLISH"
],
[
"THE BURGLARS",
"release_year",
"1971"
],
[
"THE LAST OF THE MOHICANS",
"directed_by",
"GEORGE B. SEITZ"
],
[
"THE LAST OF THE MOHICANS",
"in_language",
"ENGLISH"
],
[
"THE NIGHT VISITOR",
"in_language",
"ENGLISH"
],
[
"THE NIGHT VISITOR",
"release_year",
"1971"
],
[
"THE NIGHT VISITOR",
"starred_actors",
"LIV ULLMANN"
],
[
"THE NIGHT VISITOR",
"starred_actors",
"MAX VON SYDOW"
],
[
"UNKNOWN",
"in_language",
"ENGLISH"
]
]
}
|
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
37224, 1990
20279, A SHOCK TO THE SYSTEM
35673, ANOTHER 48 HRS.
446, ANTHONY HOPKINS
32747, BULLET
12802, CHICAGO JOE AND THE SHOWGIRL
33387, CITY OF GOD
14724, CRIME
19418, DAVID LEVIEN
36982, DESPERATE HOURS
26944, DICK TRACY
19225, FOREIGN
1033, FRACTURE
22449, GOODFELLAS
17938, HANNIBAL
8464, INTERNAL AFFAIRS
32375, JOHNNY HANDSOME
37094, KING OF NEW YORK
22247, MEN OF RESPECT
27773, MIAMI BLUES
9692, MICHAEL CIMINO
6842, MICKEY ROURKE
24586, MIMI ROGERS
4523, RED DRAGON
18757, REVENGE
22512, RUNNER RUNNER
30672, SHORT TIME
20595, SOMEONE TO WATCH OVER ME
35843, SPUN
25488, STATE OF GRACE
31555, THE FRESHMAN
28177, THE KRAYS
34862, THE POPE OF GREENWICH VILLAGE
13761, THE ROOKIE
27836, THE SILENCE OF THE LAMBS
17362, THUNDERBOLT AND LIGHTFOOT
34824, WHITE SANDS
18038, WILD AT HEART
5888, YEAR OF THE DRAGON
src, edge_attr, dst
20279, has_genre, 14724
20279, release_year, 37224
35673, has_genre, 14724
35673, has_tags, 14724
35673, release_year, 37224
32747, has_genre, 14724
32747, starred_actors, 6842
32747, written_by, 6842
12802, has_genre, 14724
12802, release_year, 37224
33387, has_genre, 14724
33387, has_tags, 14724
33387, has_tags, 19225
36982, directed_by, 9692
36982, has_genre, 14724
36982, has_tags, 24586
36982, release_year, 37224
36982, starred_actors, 446
36982, starred_actors, 6842
36982, starred_actors, 24586
26944, has_genre, 14724
26944, release_year, 37224
1033, has_genre, 14724
1033, has_tags, 446
1033, starred_actors, 446
22449, has_genre, 14724
22449, has_tags, 14724
22449, release_year, 37224
17938, has_genre, 14724
17938, has_tags, 446
17938, starred_actors, 446
8464, has_genre, 14724
8464, release_year, 37224
32375, has_genre, 14724
32375, starred_actors, 6842
37094, has_tags, 14724
37094, release_year, 37224
22247, has_genre, 14724
22247, release_year, 37224
27773, has_genre, 14724
27773, release_year, 37224
4523, has_genre, 14724
4523, has_tags, 446
4523, starred_actors, 446
18757, has_genre, 14724
18757, release_year, 37224
22512, has_genre, 14724
22512, written_by, 19418
30672, has_genre, 14724
30672, release_year, 37224
20595, has_genre, 14724
20595, starred_actors, 24586
35843, has_genre, 14724
35843, has_tags, 6842
35843, starred_actors, 6842
25488, has_genre, 14724
25488, release_year, 37224
31555, has_genre, 14724
31555, release_year, 37224
28177, has_genre, 14724
28177, release_year, 37224
34862, has_genre, 14724
34862, starred_actors, 6842
13761, has_genre, 14724
13761, release_year, 37224
27836, has_tags, 446
27836, has_tags, 14724
17362, directed_by, 9692
17362, has_genre, 14724
17362, written_by, 9692
34824, has_genre, 14724
34824, starred_actors, 6842
18038, has_genre, 14724
18038, release_year, 37224
5888, directed_by, 9692
5888, has_genre, 14724
5888, starred_actors, 6842
5888, written_by, 9692
Question: How are DAVID LEVIEN, DESPERATE HOURS, and FOREIGN related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"DAVID LEVIEN",
"DESPERATE HOURS",
"FOREIGN"
],
"valid_edges": [
[
"A SHOCK TO THE SYSTEM",
"has_genre",
"CRIME"
],
[
"A SHOCK TO THE SYSTEM",
"release_year",
"1990"
],
[
"ANOTHER 48 HRS.",
"has_genre",
"CRIME"
],
[
"ANOTHER 48 HRS.",
"has_tags",
"CRIME"
],
[
"ANOTHER 48 HRS.",
"release_year",
"1990"
],
[
"BULLET",
"has_genre",
"CRIME"
],
[
"BULLET",
"starred_actors",
"MICKEY ROURKE"
],
[
"BULLET",
"written_by",
"MICKEY ROURKE"
],
[
"CHICAGO JOE AND THE SHOWGIRL",
"has_genre",
"CRIME"
],
[
"CHICAGO JOE AND THE SHOWGIRL",
"release_year",
"1990"
],
[
"CITY OF GOD",
"has_genre",
"CRIME"
],
[
"CITY OF GOD",
"has_tags",
"CRIME"
],
[
"CITY OF GOD",
"has_tags",
"FOREIGN"
],
[
"DESPERATE HOURS",
"directed_by",
"MICHAEL CIMINO"
],
[
"DESPERATE HOURS",
"has_genre",
"CRIME"
],
[
"DESPERATE HOURS",
"has_tags",
"MIMI ROGERS"
],
[
"DESPERATE HOURS",
"release_year",
"1990"
],
[
"DESPERATE HOURS",
"starred_actors",
"ANTHONY HOPKINS"
],
[
"DESPERATE HOURS",
"starred_actors",
"MICKEY ROURKE"
],
[
"DESPERATE HOURS",
"starred_actors",
"MIMI ROGERS"
],
[
"DICK TRACY",
"has_genre",
"CRIME"
],
[
"DICK TRACY",
"release_year",
"1990"
],
[
"FRACTURE",
"has_genre",
"CRIME"
],
[
"FRACTURE",
"has_tags",
"ANTHONY HOPKINS"
],
[
"FRACTURE",
"starred_actors",
"ANTHONY HOPKINS"
],
[
"GOODFELLAS",
"has_genre",
"CRIME"
],
[
"GOODFELLAS",
"has_tags",
"CRIME"
],
[
"GOODFELLAS",
"release_year",
"1990"
],
[
"HANNIBAL",
"has_genre",
"CRIME"
],
[
"HANNIBAL",
"has_tags",
"ANTHONY HOPKINS"
],
[
"HANNIBAL",
"starred_actors",
"ANTHONY HOPKINS"
],
[
"INTERNAL AFFAIRS",
"has_genre",
"CRIME"
],
[
"INTERNAL AFFAIRS",
"release_year",
"1990"
],
[
"JOHNNY HANDSOME",
"has_genre",
"CRIME"
],
[
"JOHNNY HANDSOME",
"starred_actors",
"MICKEY ROURKE"
],
[
"KING OF NEW YORK",
"has_tags",
"CRIME"
],
[
"KING OF NEW YORK",
"release_year",
"1990"
],
[
"MEN OF RESPECT",
"has_genre",
"CRIME"
],
[
"MEN OF RESPECT",
"release_year",
"1990"
],
[
"MIAMI BLUES",
"has_genre",
"CRIME"
],
[
"MIAMI BLUES",
"release_year",
"1990"
],
[
"RED DRAGON",
"has_genre",
"CRIME"
],
[
"RED DRAGON",
"has_tags",
"ANTHONY HOPKINS"
],
[
"RED DRAGON",
"starred_actors",
"ANTHONY HOPKINS"
],
[
"REVENGE",
"has_genre",
"CRIME"
],
[
"REVENGE",
"release_year",
"1990"
],
[
"RUNNER RUNNER",
"has_genre",
"CRIME"
],
[
"RUNNER RUNNER",
"written_by",
"DAVID LEVIEN"
],
[
"SHORT TIME",
"has_genre",
"CRIME"
],
[
"SHORT TIME",
"release_year",
"1990"
],
[
"SOMEONE TO WATCH OVER ME",
"has_genre",
"CRIME"
],
[
"SOMEONE TO WATCH OVER ME",
"starred_actors",
"MIMI ROGERS"
],
[
"SPUN",
"has_genre",
"CRIME"
],
[
"SPUN",
"has_tags",
"MICKEY ROURKE"
],
[
"SPUN",
"starred_actors",
"MICKEY ROURKE"
],
[
"STATE OF GRACE",
"has_genre",
"CRIME"
],
[
"STATE OF GRACE",
"release_year",
"1990"
],
[
"THE FRESHMAN",
"has_genre",
"CRIME"
],
[
"THE FRESHMAN",
"release_year",
"1990"
],
[
"THE KRAYS",
"has_genre",
"CRIME"
],
[
"THE KRAYS",
"release_year",
"1990"
],
[
"THE POPE OF GREENWICH VILLAGE",
"has_genre",
"CRIME"
],
[
"THE POPE OF GREENWICH VILLAGE",
"starred_actors",
"MICKEY ROURKE"
],
[
"THE ROOKIE",
"has_genre",
"CRIME"
],
[
"THE ROOKIE",
"release_year",
"1990"
],
[
"THE SILENCE OF THE LAMBS",
"has_tags",
"ANTHONY HOPKINS"
],
[
"THE SILENCE OF THE LAMBS",
"has_tags",
"CRIME"
],
[
"THUNDERBOLT AND LIGHTFOOT",
"directed_by",
"MICHAEL CIMINO"
],
[
"THUNDERBOLT AND LIGHTFOOT",
"has_genre",
"CRIME"
],
[
"THUNDERBOLT AND LIGHTFOOT",
"written_by",
"MICHAEL CIMINO"
],
[
"WHITE SANDS",
"has_genre",
"CRIME"
],
[
"WHITE SANDS",
"starred_actors",
"MICKEY ROURKE"
],
[
"WILD AT HEART",
"has_genre",
"CRIME"
],
[
"WILD AT HEART",
"release_year",
"1990"
],
[
"YEAR OF THE DRAGON",
"directed_by",
"MICHAEL CIMINO"
],
[
"YEAR OF THE DRAGON",
"has_genre",
"CRIME"
],
[
"YEAR OF THE DRAGON",
"starred_actors",
"MICKEY ROURKE"
],
[
"YEAR OF THE DRAGON",
"written_by",
"MICHAEL CIMINO"
]
]
}
|
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
29424, 2011
9189, 50 CENT
1520, A CHRISTMAS KISS
20586, ALEXANDER PUSHKIN
16739, NEW YEAR'S EVE
18987, ONEGIN
8379, ROMANCE
24874, SETUP
5529, THIN ICE
6338, W.E.
27708, WUTHERING HEIGHTS
19794, YOU ARE THE APPLE OF MY EYE
src, edge_attr, dst
1520, has_genre, 8379
1520, release_year, 29424
16739, has_genre, 8379
16739, release_year, 29424
18987, release_year, 8486
18987, written_by, 20586
8379, release_year, 8486
24874, release_year, 29424
24874, starred_actors, 9189
5529, has_genre, 8379
5529, release_year, 29424
6338, has_genre, 8379
6338, release_year, 29424
27708, has_genre, 8379
27708, release_year, 29424
19794, has_genre, 8379
19794, release_year, 29424
Question: For what reason are 50 CENT, ALEXANDER PUSHKIN, and YOU ARE THE APPLE OF MY EYE associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"50 CENT",
"ALEXANDER PUSHKIN",
"YOU ARE THE APPLE OF MY EYE"
],
"valid_edges": [
[
"A CHRISTMAS KISS",
"has_genre",
"ROMANCE"
],
[
"A CHRISTMAS KISS",
"release_year",
"2011"
],
[
"NEW YEAR'S EVE",
"has_genre",
"ROMANCE"
],
[
"NEW YEAR'S EVE",
"release_year",
"2011"
],
[
"ONEGIN",
"release_year",
"1999"
],
[
"ONEGIN",
"written_by",
"ALEXANDER PUSHKIN"
],
[
"ROMANCE",
"release_year",
"1999"
],
[
"SETUP",
"release_year",
"2011"
],
[
"SETUP",
"starred_actors",
"50 CENT"
],
[
"THIN ICE",
"has_genre",
"ROMANCE"
],
[
"THIN ICE",
"release_year",
"2011"
],
[
"W.E.",
"has_genre",
"ROMANCE"
],
[
"W.E.",
"release_year",
"2011"
],
[
"WUTHERING HEIGHTS",
"has_genre",
"ROMANCE"
],
[
"WUTHERING HEIGHTS",
"release_year",
"2011"
],
[
"YOU ARE THE APPLE OF MY EYE",
"has_genre",
"ROMANCE"
],
[
"YOU ARE THE APPLE OF MY EYE",
"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
35845, 2006
6181, ALL THE KING'S MEN
1193, ALWAYS
36593, BLACK CHRISTMAS
15961, DON
7492, ETHEL LINA WHITE
14023, GLORY ROAD
27616, JOSH LUCAS
11333, KURT RUSSELL
11340, NIGHT OF THE LIVING DEAD 3D
31674, PHILIPPE LEFEBVRE
18559, POSEIDON
28729, REMAKE
2373, RICHARD DREYFUSS
21609, SCHOOL FOR SCOUNDRELS
37807, TELL NO ONE
18997, THE DEPARTED
15462, THE HILLS HAVE EYES
4091, THE LADY VANISHES
36917, THE LAKE HOUSE
17910, THE OMEN
22751, THE WICKER MAN
23568, VANILLA SKY
src, edge_attr, dst
6181, has_tags, 28729
6181, release_year, 35845
1193, has_tags, 28729
1193, starred_actors, 2373
36593, has_tags, 28729
36593, release_year, 35845
15961, has_tags, 28729
15961, release_year, 35845
14023, release_year, 35845
14023, starred_actors, 27616
11340, has_tags, 28729
11340, release_year, 35845
18559, has_tags, 28729
18559, release_year, 35845
18559, starred_actors, 27616
18559, starred_actors, 11333
18559, starred_actors, 2373
21609, has_tags, 28729
21609, release_year, 35845
37807, release_year, 35845
37807, written_by, 31674
18997, has_tags, 28729
18997, release_year, 35845
15462, has_tags, 28729
15462, release_year, 35845
4091, has_tags, 28729
4091, written_by, 7492
36917, has_tags, 28729
36917, release_year, 35845
17910, has_tags, 28729
17910, release_year, 35845
22751, has_tags, 28729
22751, release_year, 35845
23568, has_tags, 28729
23568, starred_actors, 11333
Question: For what reason are ETHEL LINA WHITE, PHILIPPE LEFEBVRE, and POSEIDON associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"ETHEL LINA WHITE",
"PHILIPPE LEFEBVRE",
"POSEIDON"
],
"valid_edges": [
[
"ALL THE KING'S MEN",
"has_tags",
"REMAKE"
],
[
"ALL THE KING'S MEN",
"release_year",
"2006"
],
[
"ALWAYS",
"has_tags",
"REMAKE"
],
[
"ALWAYS",
"starred_actors",
"RICHARD DREYFUSS"
],
[
"BLACK CHRISTMAS",
"has_tags",
"REMAKE"
],
[
"BLACK CHRISTMAS",
"release_year",
"2006"
],
[
"DON",
"has_tags",
"REMAKE"
],
[
"DON",
"release_year",
"2006"
],
[
"GLORY ROAD",
"release_year",
"2006"
],
[
"GLORY ROAD",
"starred_actors",
"JOSH LUCAS"
],
[
"NIGHT OF THE LIVING DEAD 3D",
"has_tags",
"REMAKE"
],
[
"NIGHT OF THE LIVING DEAD 3D",
"release_year",
"2006"
],
[
"POSEIDON",
"has_tags",
"REMAKE"
],
[
"POSEIDON",
"release_year",
"2006"
],
[
"POSEIDON",
"starred_actors",
"JOSH LUCAS"
],
[
"POSEIDON",
"starred_actors",
"KURT RUSSELL"
],
[
"POSEIDON",
"starred_actors",
"RICHARD DREYFUSS"
],
[
"SCHOOL FOR SCOUNDRELS",
"has_tags",
"REMAKE"
],
[
"SCHOOL FOR SCOUNDRELS",
"release_year",
"2006"
],
[
"TELL NO ONE",
"release_year",
"2006"
],
[
"TELL NO ONE",
"written_by",
"PHILIPPE LEFEBVRE"
],
[
"THE DEPARTED",
"has_tags",
"REMAKE"
],
[
"THE DEPARTED",
"release_year",
"2006"
],
[
"THE HILLS HAVE EYES",
"has_tags",
"REMAKE"
],
[
"THE HILLS HAVE EYES",
"release_year",
"2006"
],
[
"THE LADY VANISHES",
"has_tags",
"REMAKE"
],
[
"THE LADY VANISHES",
"written_by",
"ETHEL LINA WHITE"
],
[
"THE LAKE HOUSE",
"has_tags",
"REMAKE"
],
[
"THE LAKE HOUSE",
"release_year",
"2006"
],
[
"THE OMEN",
"has_tags",
"REMAKE"
],
[
"THE OMEN",
"release_year",
"2006"
],
[
"THE WICKER MAN",
"has_tags",
"REMAKE"
],
[
"THE WICKER MAN",
"release_year",
"2006"
],
[
"VANILLA SKY",
"has_tags",
"REMAKE"
],
[
"VANILLA SKY",
"starred_actors",
"KURT RUSSELL"
]
]
}
|
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
2452, 13 ASSASSINS
21931, 1941
7841, 1987
30907, BAREFOOT GEN
25943, BAT*21
34734, BATTLE OF THE BULGE
3626, CHRISTIAN BALE
25285, COME AND SEE
10293, CONSPIRACY
2710, DEPARTURES
36212, DRAMA
22028, EMPIRE OF THE SUN
13834, FLYING TIGERS
39145, FURY
14853, GO FOR BROKE!
22091, GRAVE OF THE FIREFLIES
15765, HAMSUN
12994, HARAKIRI
24940, HOPE AND GLORY
15343, IN DARKNESS
8248, JAPAN
36874, JAPANESE
28149, JOHN MALKOVICH
21224, KIKUJIRO
35247, KURT COBAIN
4794, LAST DAYS
19809, LATE SPRING
21197, LIGHT IT UP
38294, MRS. MINIVER
8747, MUNICH
27289, NA
25709, NOBODY KNOWS
34288, ONLY YESTERDAY
234, PEARL HARBOR
18584, PRINCESS MONONOKE
30919, PRISON
11570, RASHOMON
35586, SAHARA
34329, SCHINDLER'S LIST
20932, SEVEN SAMURAI
11124, STALINGRAD
26730, STEVEN SPIELBERG
33839, SWING KIDS
27210, THE BEST YEARS OF OUR LIVES
36692, THE CAINE MUTINY
23189, THE FIGHTER
34462, THE FLOWERS OF WAR
6424, THE GREAT ESCAPE
35027, THE KILLING FIELDS
12614, THE PIANIST
21548, THE SUN
9390, THE UNTOUCHABLES
18076, THE WIND RISES
13374, THRONE OF BLOOD
16940, TORA! TORA! TORA!
4527, UGETSU
8984, USHER RAYMOND
22214, WAR
16601, WAR HORSE
24623, WHISPER OF THE HEART
24155, WORLD WAR II
15904, YANKS
54, YOJIMBO
src, edge_attr, dst
2452, has_tags, 8248
2452, in_language, 36874
21931, directed_by, 26730
21931, in_language, 36874
30907, has_tags, 22214
30907, in_language, 36874
25943, has_genre, 22214
25943, has_tags, 27289
34734, has_genre, 22214
34734, has_tags, 24155
25285, has_genre, 22214
25285, has_tags, 24155
10293, has_genre, 22214
10293, has_tags, 24155
2710, has_tags, 8248
2710, in_language, 36874
22028, directed_by, 26730
22028, has_genre, 22214
22028, has_tags, 3626
22028, has_tags, 8248
22028, has_tags, 28149
22028, has_tags, 27289
22028, has_tags, 30919
22028, has_tags, 26730
22028, has_tags, 22214
22028, has_tags, 24155
22028, in_language, 36874
22028, release_year, 7841
22028, starred_actors, 3626
22028, starred_actors, 28149
13834, has_genre, 22214
13834, has_tags, 24155
39145, has_genre, 22214
39145, has_tags, 22214
39145, has_tags, 24155
14853, has_genre, 22214
14853, in_language, 36874
22091, has_genre, 22214
22091, has_tags, 8248
22091, has_tags, 22214
22091, in_language, 36874
15765, has_genre, 22214
15765, has_tags, 24155
12994, has_tags, 8248
12994, has_tags, 36874
12994, in_language, 36874
24940, has_tags, 24155
24940, release_year, 7841
15343, has_genre, 22214
15343, has_tags, 22214
15343, has_tags, 24155
21224, has_tags, 8248
21224, in_language, 36874
4794, has_genre, 36212
4794, has_tags, 35247
19809, has_tags, 8248
19809, in_language, 36874
21197, has_genre, 36212
21197, starred_actors, 8984
38294, has_genre, 22214
38294, has_tags, 24155
8747, directed_by, 26730
8747, has_tags, 26730
8747, has_tags, 22214
25709, has_tags, 8248
25709, in_language, 36874
34288, has_tags, 8248
34288, in_language, 36874
234, has_tags, 8248
234, has_tags, 22214
234, in_language, 36874
18584, has_tags, 8248
18584, has_tags, 36874
18584, in_language, 36874
30919, has_genre, 36212
30919, has_tags, 30919
11570, has_tags, 8248
11570, in_language, 36874
35586, has_genre, 22214
35586, has_tags, 24155
34329, directed_by, 26730
34329, has_tags, 26730
34329, has_tags, 22214
20932, has_tags, 8248
20932, in_language, 36874
11124, has_genre, 22214
11124, has_tags, 24155
33839, has_tags, 24155
33839, starred_actors, 3626
27210, has_genre, 22214
27210, has_tags, 24155
36692, has_genre, 22214
36692, has_tags, 24155
23189, has_tags, 3626
23189, has_tags, 22214
23189, starred_actors, 3626
34462, has_genre, 22214
34462, has_tags, 3626
34462, in_language, 36874
34462, starred_actors, 3626
6424, has_tags, 30919
6424, has_tags, 22214
6424, has_tags, 24155
35027, has_genre, 22214
35027, has_tags, 28149
35027, has_tags, 22214
35027, starred_actors, 28149
12614, has_genre, 22214
12614, has_tags, 22214
12614, has_tags, 24155
21548, has_tags, 8248
21548, has_tags, 22214
21548, has_tags, 24155
21548, in_language, 36874
9390, has_tags, 27289
9390, release_year, 7841
18076, has_tags, 8248
18076, has_tags, 24155
18076, in_language, 36874
13374, has_tags, 8248
13374, has_tags, 36874
13374, in_language, 36874
16940, has_tags, 36874
16940, has_tags, 22214
16940, in_language, 36874
4527, has_tags, 8248
4527, in_language, 36874
16601, directed_by, 26730
16601, has_genre, 22214
16601, has_tags, 26730
16601, has_tags, 22214
24623, has_tags, 8248
24623, in_language, 36874
15904, has_genre, 22214
15904, has_tags, 24155
54, has_tags, 8248
54, in_language, 36874
Question: In what context are EMPIRE OF THE SUN, KURT COBAIN, and USHER RAYMOND connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"EMPIRE OF THE SUN",
"KURT COBAIN",
"USHER RAYMOND"
],
"valid_edges": [
[
"13 ASSASSINS",
"has_tags",
"JAPAN"
],
[
"13 ASSASSINS",
"in_language",
"JAPANESE"
],
[
"1941",
"directed_by",
"STEVEN SPIELBERG"
],
[
"1941",
"in_language",
"JAPANESE"
],
[
"BAREFOOT GEN",
"has_tags",
"WAR"
],
[
"BAREFOOT GEN",
"in_language",
"JAPANESE"
],
[
"BAT*21",
"has_genre",
"WAR"
],
[
"BAT*21",
"has_tags",
"NA"
],
[
"BATTLE OF THE BULGE",
"has_genre",
"WAR"
],
[
"BATTLE OF THE BULGE",
"has_tags",
"WORLD WAR II"
],
[
"COME AND SEE",
"has_genre",
"WAR"
],
[
"COME AND SEE",
"has_tags",
"WORLD WAR II"
],
[
"CONSPIRACY",
"has_genre",
"WAR"
],
[
"CONSPIRACY",
"has_tags",
"WORLD WAR II"
],
[
"DEPARTURES",
"has_tags",
"JAPAN"
],
[
"DEPARTURES",
"in_language",
"JAPANESE"
],
[
"EMPIRE OF THE SUN",
"directed_by",
"STEVEN SPIELBERG"
],
[
"EMPIRE OF THE SUN",
"has_genre",
"WAR"
],
[
"EMPIRE OF THE SUN",
"has_tags",
"CHRISTIAN BALE"
],
[
"EMPIRE OF THE SUN",
"has_tags",
"JAPAN"
],
[
"EMPIRE OF THE SUN",
"has_tags",
"JOHN MALKOVICH"
],
[
"EMPIRE OF THE SUN",
"has_tags",
"NA"
],
[
"EMPIRE OF THE SUN",
"has_tags",
"PRISON"
],
[
"EMPIRE OF THE SUN",
"has_tags",
"STEVEN SPIELBERG"
],
[
"EMPIRE OF THE SUN",
"has_tags",
"WAR"
],
[
"EMPIRE OF THE SUN",
"has_tags",
"WORLD WAR II"
],
[
"EMPIRE OF THE SUN",
"in_language",
"JAPANESE"
],
[
"EMPIRE OF THE SUN",
"release_year",
"1987"
],
[
"EMPIRE OF THE SUN",
"starred_actors",
"CHRISTIAN BALE"
],
[
"EMPIRE OF THE SUN",
"starred_actors",
"JOHN MALKOVICH"
],
[
"FLYING TIGERS",
"has_genre",
"WAR"
],
[
"FLYING TIGERS",
"has_tags",
"WORLD WAR II"
],
[
"FURY",
"has_genre",
"WAR"
],
[
"FURY",
"has_tags",
"WAR"
],
[
"FURY",
"has_tags",
"WORLD WAR II"
],
[
"GO FOR BROKE!",
"has_genre",
"WAR"
],
[
"GO FOR BROKE!",
"in_language",
"JAPANESE"
],
[
"GRAVE OF THE FIREFLIES",
"has_genre",
"WAR"
],
[
"GRAVE OF THE FIREFLIES",
"has_tags",
"JAPAN"
],
[
"GRAVE OF THE FIREFLIES",
"has_tags",
"WAR"
],
[
"GRAVE OF THE FIREFLIES",
"in_language",
"JAPANESE"
],
[
"HAMSUN",
"has_genre",
"WAR"
],
[
"HAMSUN",
"has_tags",
"WORLD WAR II"
],
[
"HARAKIRI",
"has_tags",
"JAPAN"
],
[
"HARAKIRI",
"has_tags",
"JAPANESE"
],
[
"HARAKIRI",
"in_language",
"JAPANESE"
],
[
"HOPE AND GLORY",
"has_tags",
"WORLD WAR II"
],
[
"HOPE AND GLORY",
"release_year",
"1987"
],
[
"IN DARKNESS",
"has_genre",
"WAR"
],
[
"IN DARKNESS",
"has_tags",
"WAR"
],
[
"IN DARKNESS",
"has_tags",
"WORLD WAR II"
],
[
"KIKUJIRO",
"has_tags",
"JAPAN"
],
[
"KIKUJIRO",
"in_language",
"JAPANESE"
],
[
"LAST DAYS",
"has_genre",
"DRAMA"
],
[
"LAST DAYS",
"has_tags",
"KURT COBAIN"
],
[
"LATE SPRING",
"has_tags",
"JAPAN"
],
[
"LATE SPRING",
"in_language",
"JAPANESE"
],
[
"LIGHT IT UP",
"has_genre",
"DRAMA"
],
[
"LIGHT IT UP",
"starred_actors",
"USHER RAYMOND"
],
[
"MRS. MINIVER",
"has_genre",
"WAR"
],
[
"MRS. MINIVER",
"has_tags",
"WORLD WAR II"
],
[
"MUNICH",
"directed_by",
"STEVEN SPIELBERG"
],
[
"MUNICH",
"has_tags",
"STEVEN SPIELBERG"
],
[
"MUNICH",
"has_tags",
"WAR"
],
[
"NOBODY KNOWS",
"has_tags",
"JAPAN"
],
[
"NOBODY KNOWS",
"in_language",
"JAPANESE"
],
[
"ONLY YESTERDAY",
"has_tags",
"JAPAN"
],
[
"ONLY YESTERDAY",
"in_language",
"JAPANESE"
],
[
"PEARL HARBOR",
"has_tags",
"JAPAN"
],
[
"PEARL HARBOR",
"has_tags",
"WAR"
],
[
"PEARL HARBOR",
"in_language",
"JAPANESE"
],
[
"PRINCESS MONONOKE",
"has_tags",
"JAPAN"
],
[
"PRINCESS MONONOKE",
"has_tags",
"JAPANESE"
],
[
"PRINCESS MONONOKE",
"in_language",
"JAPANESE"
],
[
"PRISON",
"has_genre",
"DRAMA"
],
[
"PRISON",
"has_tags",
"PRISON"
],
[
"RASHOMON",
"has_tags",
"JAPAN"
],
[
"RASHOMON",
"in_language",
"JAPANESE"
],
[
"SAHARA",
"has_genre",
"WAR"
],
[
"SAHARA",
"has_tags",
"WORLD WAR II"
],
[
"SCHINDLER'S LIST",
"directed_by",
"STEVEN SPIELBERG"
],
[
"SCHINDLER'S LIST",
"has_tags",
"STEVEN SPIELBERG"
],
[
"SCHINDLER'S LIST",
"has_tags",
"WAR"
],
[
"SEVEN SAMURAI",
"has_tags",
"JAPAN"
],
[
"SEVEN SAMURAI",
"in_language",
"JAPANESE"
],
[
"STALINGRAD",
"has_genre",
"WAR"
],
[
"STALINGRAD",
"has_tags",
"WORLD WAR II"
],
[
"SWING KIDS",
"has_tags",
"WORLD WAR II"
],
[
"SWING KIDS",
"starred_actors",
"CHRISTIAN BALE"
],
[
"THE BEST YEARS OF OUR LIVES",
"has_genre",
"WAR"
],
[
"THE BEST YEARS OF OUR LIVES",
"has_tags",
"WORLD WAR II"
],
[
"THE CAINE MUTINY",
"has_genre",
"WAR"
],
[
"THE CAINE MUTINY",
"has_tags",
"WORLD WAR II"
],
[
"THE FIGHTER",
"has_tags",
"CHRISTIAN BALE"
],
[
"THE FIGHTER",
"has_tags",
"WAR"
],
[
"THE FIGHTER",
"starred_actors",
"CHRISTIAN BALE"
],
[
"THE FLOWERS OF WAR",
"has_genre",
"WAR"
],
[
"THE FLOWERS OF WAR",
"has_tags",
"CHRISTIAN BALE"
],
[
"THE FLOWERS OF WAR",
"in_language",
"JAPANESE"
],
[
"THE FLOWERS OF WAR",
"starred_actors",
"CHRISTIAN BALE"
],
[
"THE GREAT ESCAPE",
"has_tags",
"PRISON"
],
[
"THE GREAT ESCAPE",
"has_tags",
"WAR"
],
[
"THE GREAT ESCAPE",
"has_tags",
"WORLD WAR II"
],
[
"THE KILLING FIELDS",
"has_genre",
"WAR"
],
[
"THE KILLING FIELDS",
"has_tags",
"JOHN MALKOVICH"
],
[
"THE KILLING FIELDS",
"has_tags",
"WAR"
],
[
"THE KILLING FIELDS",
"starred_actors",
"JOHN MALKOVICH"
],
[
"THE PIANIST",
"has_genre",
"WAR"
],
[
"THE PIANIST",
"has_tags",
"WAR"
],
[
"THE PIANIST",
"has_tags",
"WORLD WAR II"
],
[
"THE SUN",
"has_tags",
"JAPAN"
],
[
"THE SUN",
"has_tags",
"WAR"
],
[
"THE SUN",
"has_tags",
"WORLD WAR II"
],
[
"THE SUN",
"in_language",
"JAPANESE"
],
[
"THE UNTOUCHABLES",
"has_tags",
"NA"
],
[
"THE UNTOUCHABLES",
"release_year",
"1987"
],
[
"THE WIND RISES",
"has_tags",
"JAPAN"
],
[
"THE WIND RISES",
"has_tags",
"WORLD WAR II"
],
[
"THE WIND RISES",
"in_language",
"JAPANESE"
],
[
"THRONE OF BLOOD",
"has_tags",
"JAPAN"
],
[
"THRONE OF BLOOD",
"has_tags",
"JAPANESE"
],
[
"THRONE OF BLOOD",
"in_language",
"JAPANESE"
],
[
"TORA! TORA! TORA!",
"has_tags",
"JAPANESE"
],
[
"TORA! TORA! TORA!",
"has_tags",
"WAR"
],
[
"TORA! TORA! TORA!",
"in_language",
"JAPANESE"
],
[
"UGETSU",
"has_tags",
"JAPAN"
],
[
"UGETSU",
"in_language",
"JAPANESE"
],
[
"WAR HORSE",
"directed_by",
"STEVEN SPIELBERG"
],
[
"WAR HORSE",
"has_genre",
"WAR"
],
[
"WAR HORSE",
"has_tags",
"STEVEN SPIELBERG"
],
[
"WAR HORSE",
"has_tags",
"WAR"
],
[
"WHISPER OF THE HEART",
"has_tags",
"JAPAN"
],
[
"WHISPER OF THE HEART",
"in_language",
"JAPANESE"
],
[
"YANKS",
"has_genre",
"WAR"
],
[
"YANKS",
"has_tags",
"WORLD WAR II"
],
[
"YOJIMBO",
"has_tags",
"JAPAN"
],
[
"YOJIMBO",
"in_language",
"JAPANESE"
]
]
}
|
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
17893, A PROMISE
12800, ANNA CHLUMSKY
26512, BEWARE OF PITY
10492, BURNING SECRET
546, CLÉMENTINE POIDATZ
30463, COMEDY
6519, DAN AYKROYD
36212, DRAMA
6012, FRENCH
14669, FRONTIER OF THE DAWN
4472, JAMIE LEE CURTIS
28455, MARIE ANTOINETTE
33507, MY GIRL
28963, MY GIRL 2
35478, STEFAN ZWEIG
35565, THE GRAND BUDAPEST HOTEL
src, edge_attr, dst
17893, has_genre, 36212
17893, written_by, 35478
26512, has_genre, 36212
26512, written_by, 35478
10492, has_genre, 36212
10492, written_by, 35478
14669, in_language, 6012
14669, starred_actors, 546
28455, has_genre, 36212
28455, in_language, 6012
28455, written_by, 35478
33507, has_genre, 36212
33507, has_tags, 12800
33507, has_tags, 6519
33507, has_tags, 36212
33507, has_tags, 4472
33507, starred_actors, 12800
33507, starred_actors, 6519
33507, starred_actors, 4472
28963, has_genre, 30463
28963, has_genre, 36212
28963, has_tags, 12800
28963, has_tags, 6519
28963, has_tags, 4472
28963, starred_actors, 12800
28963, starred_actors, 6519
28963, starred_actors, 4472
35565, has_genre, 30463
35565, written_by, 35478
Question: In what context are ANNA CHLUMSKY, CLÉMENTINE POIDATZ, and STEFAN ZWEIG connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"ANNA CHLUMSKY",
"CLÉMENTINE POIDATZ",
"STEFAN ZWEIG"
],
"valid_edges": [
[
"A PROMISE",
"has_genre",
"DRAMA"
],
[
"A PROMISE",
"written_by",
"STEFAN ZWEIG"
],
[
"BEWARE OF PITY",
"has_genre",
"DRAMA"
],
[
"BEWARE OF PITY",
"written_by",
"STEFAN ZWEIG"
],
[
"BURNING SECRET",
"has_genre",
"DRAMA"
],
[
"BURNING SECRET",
"written_by",
"STEFAN ZWEIG"
],
[
"FRONTIER OF THE DAWN",
"in_language",
"FRENCH"
],
[
"FRONTIER OF THE DAWN",
"starred_actors",
"CLÉMENTINE POIDATZ"
],
[
"MARIE ANTOINETTE",
"has_genre",
"DRAMA"
],
[
"MARIE ANTOINETTE",
"in_language",
"FRENCH"
],
[
"MARIE ANTOINETTE",
"written_by",
"STEFAN ZWEIG"
],
[
"MY GIRL",
"has_genre",
"DRAMA"
],
[
"MY GIRL",
"has_tags",
"ANNA CHLUMSKY"
],
[
"MY GIRL",
"has_tags",
"DAN AYKROYD"
],
[
"MY GIRL",
"has_tags",
"DRAMA"
],
[
"MY GIRL",
"has_tags",
"JAMIE LEE CURTIS"
],
[
"MY GIRL",
"starred_actors",
"ANNA CHLUMSKY"
],
[
"MY GIRL",
"starred_actors",
"DAN AYKROYD"
],
[
"MY GIRL",
"starred_actors",
"JAMIE LEE CURTIS"
],
[
"MY GIRL 2",
"has_genre",
"COMEDY"
],
[
"MY GIRL 2",
"has_genre",
"DRAMA"
],
[
"MY GIRL 2",
"has_tags",
"ANNA CHLUMSKY"
],
[
"MY GIRL 2",
"has_tags",
"DAN AYKROYD"
],
[
"MY GIRL 2",
"has_tags",
"JAMIE LEE CURTIS"
],
[
"MY GIRL 2",
"starred_actors",
"ANNA CHLUMSKY"
],
[
"MY GIRL 2",
"starred_actors",
"DAN AYKROYD"
],
[
"MY GIRL 2",
"starred_actors",
"JAMIE LEE CURTIS"
],
[
"THE GRAND BUDAPEST HOTEL",
"has_genre",
"COMEDY"
],
[
"THE GRAND BUDAPEST HOTEL",
"written_by",
"STEFAN ZWEIG"
]
]
}
|
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
28367, ALICE WU
13205, CAITLIN STASEY
30463, COMEDY
36212, DRAMA
31648, FRIGHT NIGHT
460, LORD LOVE A DUCK
253, OVERBOARD
18518, RODDY MCDOWALL
2135, SAVING FACE
35353, TOMORROW, WHEN THE WAR BEGAN
src, edge_attr, dst
31648, has_genre, 30463
31648, has_tags, 18518
31648, starred_actors, 18518
460, has_genre, 30463
460, starred_actors, 18518
253, has_genre, 30463
253, has_tags, 18518
2135, directed_by, 28367
2135, has_genre, 30463
2135, has_genre, 36212
2135, written_by, 28367
35353, has_genre, 36212
35353, starred_actors, 13205
Question: For what reason are ALICE WU, CAITLIN STASEY, and RODDY MCDOWALL associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"ALICE WU",
"CAITLIN STASEY",
"RODDY MCDOWALL"
],
"valid_edges": [
[
"FRIGHT NIGHT",
"has_genre",
"COMEDY"
],
[
"FRIGHT NIGHT",
"has_tags",
"RODDY MCDOWALL"
],
[
"FRIGHT NIGHT",
"starred_actors",
"RODDY MCDOWALL"
],
[
"LORD LOVE A DUCK",
"has_genre",
"COMEDY"
],
[
"LORD LOVE A DUCK",
"starred_actors",
"RODDY MCDOWALL"
],
[
"OVERBOARD",
"has_genre",
"COMEDY"
],
[
"OVERBOARD",
"has_tags",
"RODDY MCDOWALL"
],
[
"SAVING FACE",
"directed_by",
"ALICE WU"
],
[
"SAVING FACE",
"has_genre",
"COMEDY"
],
[
"SAVING FACE",
"has_genre",
"DRAMA"
],
[
"SAVING FACE",
"written_by",
"ALICE WU"
],
[
"TOMORROW, WHEN THE WAR BEGAN",
"has_genre",
"DRAMA"
],
[
"TOMORROW, WHEN THE WAR BEGAN",
"starred_actors",
"CAITLIN STASEY"
]
]
}
|
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
35798, 2010
22713, A VIEW TO A KILL
23960, ATROCIOUS
27477, BIUTIFUL
20749, BLACK BREAD
29151, BOND
16659, CASINO ROYALE
23921, CUBA
27374, DIAMONDS ARE FOREVER
14754, DIE ANOTHER DAY
14763, DR. NO
30877, EVEN THE RAIN
29461, FOR YOUR EYES ONLY
10187, FROM RUSSIA WITH LOVE
3650, GOLDENEYE
35589, GOLDFINGER
1719, JAMES BOND
19452, JULIA'S EYES
21430, KITES
7984, LICENCE TO KILL
24001, LIVE AND LET DIE
23892, MOONRAKER
15932, MR. NICE
19289, NEVER SAY NEVER AGAIN
37940, OCTOPUSSY
9679, ON HER MAJESTY'S SECRET SERVICE
14616, OUTLAND
9720, QUANTUM OF SOLACE
34806, ROOM IN ROME
36591, SEAN CONNERY
28395, SPACE
7556, SPANISH
31985, STRAWBERRY AND CHOCOLATE
35188, THE BEST AND THE BRIGHTEST
35393, THE LAST CIRCUS
26870, THE LIVING DAYLIGHTS
38373, THE MAN WITH THE GOLDEN GUN
17126, THE MOSQUITO NET
16147, THE SILENT HOUSE
5226, THE SPY WHO LOVED ME
492, THE WORLD IS NOT ENOUGH
28460, THUNDERBALL
29775, TOMORROW NEVER DIES
31658, YOU ONLY LIVE TWICE
src, edge_attr, dst
22713, has_tags, 29151
22713, has_tags, 1719
23960, in_language, 7556
23960, release_year, 35798
27477, in_language, 7556
27477, release_year, 35798
20749, in_language, 7556
20749, release_year, 35798
16659, has_tags, 29151
16659, has_tags, 1719
23921, in_language, 7556
23921, starred_actors, 36591
27374, has_tags, 29151
27374, has_tags, 1719
27374, has_tags, 36591
27374, starred_actors, 36591
14754, has_tags, 29151
14754, has_tags, 1719
14763, has_tags, 29151
14763, has_tags, 1719
14763, has_tags, 36591
14763, starred_actors, 36591
30877, has_tags, 7556
30877, in_language, 7556
30877, release_year, 35798
29461, has_tags, 29151
29461, has_tags, 1719
10187, has_tags, 29151
10187, has_tags, 1719
10187, has_tags, 36591
10187, starred_actors, 36591
3650, has_tags, 29151
3650, has_tags, 1719
3650, in_language, 7556
35589, has_tags, 29151
35589, has_tags, 1719
35589, has_tags, 36591
35589, starred_actors, 36591
19452, in_language, 7556
19452, release_year, 35798
21430, in_language, 7556
21430, release_year, 35798
7984, has_tags, 29151
7984, has_tags, 1719
24001, has_tags, 29151
24001, has_tags, 1719
24001, has_tags, 36591
23892, has_tags, 29151
23892, has_tags, 1719
23892, has_tags, 28395
15932, in_language, 7556
15932, release_year, 35798
19289, has_tags, 29151
19289, has_tags, 1719
19289, has_tags, 36591
19289, starred_actors, 36591
37940, has_tags, 29151
37940, has_tags, 1719
9679, has_tags, 29151
9679, has_tags, 1719
14616, has_tags, 36591
14616, has_tags, 28395
14616, starred_actors, 36591
9720, has_tags, 29151
9720, has_tags, 1719
34806, in_language, 7556
34806, release_year, 35798
31985, has_tags, 23921
31985, in_language, 7556
35188, release_year, 35798
35393, in_language, 7556
35393, release_year, 35798
26870, has_tags, 29151
26870, has_tags, 1719
38373, has_tags, 29151
38373, has_tags, 1719
17126, in_language, 7556
17126, release_year, 35798
16147, in_language, 7556
16147, release_year, 35798
5226, has_tags, 29151
5226, has_tags, 1719
492, has_tags, 29151
492, has_tags, 1719
28460, has_tags, 29151
28460, has_tags, 1719
28460, has_tags, 36591
28460, starred_actors, 36591
29775, has_tags, 29151
29775, has_tags, 1719
31658, has_tags, 29151
31658, has_tags, 1719
31658, has_tags, 36591
31658, has_tags, 28395
31658, starred_actors, 36591
Question: For what reason are STRAWBERRY AND CHOCOLATE, THE BEST AND THE BRIGHTEST, and YOU ONLY LIVE TWICE associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"STRAWBERRY AND CHOCOLATE",
"THE BEST AND THE BRIGHTEST",
"YOU ONLY LIVE TWICE"
],
"valid_edges": [
[
"A VIEW TO A KILL",
"has_tags",
"BOND"
],
[
"A VIEW TO A KILL",
"has_tags",
"JAMES BOND"
],
[
"ATROCIOUS",
"in_language",
"SPANISH"
],
[
"ATROCIOUS",
"release_year",
"2010"
],
[
"BIUTIFUL",
"in_language",
"SPANISH"
],
[
"BIUTIFUL",
"release_year",
"2010"
],
[
"BLACK BREAD",
"in_language",
"SPANISH"
],
[
"BLACK BREAD",
"release_year",
"2010"
],
[
"CASINO ROYALE",
"has_tags",
"BOND"
],
[
"CASINO ROYALE",
"has_tags",
"JAMES BOND"
],
[
"CUBA",
"in_language",
"SPANISH"
],
[
"CUBA",
"starred_actors",
"SEAN CONNERY"
],
[
"DIAMONDS ARE FOREVER",
"has_tags",
"BOND"
],
[
"DIAMONDS ARE FOREVER",
"has_tags",
"JAMES BOND"
],
[
"DIAMONDS ARE FOREVER",
"has_tags",
"SEAN CONNERY"
],
[
"DIAMONDS ARE FOREVER",
"starred_actors",
"SEAN CONNERY"
],
[
"DIE ANOTHER DAY",
"has_tags",
"BOND"
],
[
"DIE ANOTHER DAY",
"has_tags",
"JAMES BOND"
],
[
"DR. NO",
"has_tags",
"BOND"
],
[
"DR. NO",
"has_tags",
"JAMES BOND"
],
[
"DR. NO",
"has_tags",
"SEAN CONNERY"
],
[
"DR. NO",
"starred_actors",
"SEAN CONNERY"
],
[
"EVEN THE RAIN",
"has_tags",
"SPANISH"
],
[
"EVEN THE RAIN",
"in_language",
"SPANISH"
],
[
"EVEN THE RAIN",
"release_year",
"2010"
],
[
"FOR YOUR EYES ONLY",
"has_tags",
"BOND"
],
[
"FOR YOUR EYES ONLY",
"has_tags",
"JAMES BOND"
],
[
"FROM RUSSIA WITH LOVE",
"has_tags",
"BOND"
],
[
"FROM RUSSIA WITH LOVE",
"has_tags",
"JAMES BOND"
],
[
"FROM RUSSIA WITH LOVE",
"has_tags",
"SEAN CONNERY"
],
[
"FROM RUSSIA WITH LOVE",
"starred_actors",
"SEAN CONNERY"
],
[
"GOLDENEYE",
"has_tags",
"BOND"
],
[
"GOLDENEYE",
"has_tags",
"JAMES BOND"
],
[
"GOLDENEYE",
"in_language",
"SPANISH"
],
[
"GOLDFINGER",
"has_tags",
"BOND"
],
[
"GOLDFINGER",
"has_tags",
"JAMES BOND"
],
[
"GOLDFINGER",
"has_tags",
"SEAN CONNERY"
],
[
"GOLDFINGER",
"starred_actors",
"SEAN CONNERY"
],
[
"JULIA'S EYES",
"in_language",
"SPANISH"
],
[
"JULIA'S EYES",
"release_year",
"2010"
],
[
"KITES",
"in_language",
"SPANISH"
],
[
"KITES",
"release_year",
"2010"
],
[
"LICENCE TO KILL",
"has_tags",
"BOND"
],
[
"LICENCE TO KILL",
"has_tags",
"JAMES BOND"
],
[
"LIVE AND LET DIE",
"has_tags",
"BOND"
],
[
"LIVE AND LET DIE",
"has_tags",
"JAMES BOND"
],
[
"LIVE AND LET DIE",
"has_tags",
"SEAN CONNERY"
],
[
"MOONRAKER",
"has_tags",
"BOND"
],
[
"MOONRAKER",
"has_tags",
"JAMES BOND"
],
[
"MOONRAKER",
"has_tags",
"SPACE"
],
[
"MR. NICE",
"in_language",
"SPANISH"
],
[
"MR. NICE",
"release_year",
"2010"
],
[
"NEVER SAY NEVER AGAIN",
"has_tags",
"BOND"
],
[
"NEVER SAY NEVER AGAIN",
"has_tags",
"JAMES BOND"
],
[
"NEVER SAY NEVER AGAIN",
"has_tags",
"SEAN CONNERY"
],
[
"NEVER SAY NEVER AGAIN",
"starred_actors",
"SEAN CONNERY"
],
[
"OCTOPUSSY",
"has_tags",
"BOND"
],
[
"OCTOPUSSY",
"has_tags",
"JAMES BOND"
],
[
"ON HER MAJESTY'S SECRET SERVICE",
"has_tags",
"BOND"
],
[
"ON HER MAJESTY'S SECRET SERVICE",
"has_tags",
"JAMES BOND"
],
[
"OUTLAND",
"has_tags",
"SEAN CONNERY"
],
[
"OUTLAND",
"has_tags",
"SPACE"
],
[
"OUTLAND",
"starred_actors",
"SEAN CONNERY"
],
[
"QUANTUM OF SOLACE",
"has_tags",
"BOND"
],
[
"QUANTUM OF SOLACE",
"has_tags",
"JAMES BOND"
],
[
"ROOM IN ROME",
"in_language",
"SPANISH"
],
[
"ROOM IN ROME",
"release_year",
"2010"
],
[
"STRAWBERRY AND CHOCOLATE",
"has_tags",
"CUBA"
],
[
"STRAWBERRY AND CHOCOLATE",
"in_language",
"SPANISH"
],
[
"THE BEST AND THE BRIGHTEST",
"release_year",
"2010"
],
[
"THE LAST CIRCUS",
"in_language",
"SPANISH"
],
[
"THE LAST CIRCUS",
"release_year",
"2010"
],
[
"THE LIVING DAYLIGHTS",
"has_tags",
"BOND"
],
[
"THE LIVING DAYLIGHTS",
"has_tags",
"JAMES BOND"
],
[
"THE MAN WITH THE GOLDEN GUN",
"has_tags",
"BOND"
],
[
"THE MAN WITH THE GOLDEN GUN",
"has_tags",
"JAMES BOND"
],
[
"THE MOSQUITO NET",
"in_language",
"SPANISH"
],
[
"THE MOSQUITO NET",
"release_year",
"2010"
],
[
"THE SILENT HOUSE",
"in_language",
"SPANISH"
],
[
"THE SILENT HOUSE",
"release_year",
"2010"
],
[
"THE SPY WHO LOVED ME",
"has_tags",
"BOND"
],
[
"THE SPY WHO LOVED ME",
"has_tags",
"JAMES BOND"
],
[
"THE WORLD IS NOT ENOUGH",
"has_tags",
"BOND"
],
[
"THE WORLD IS NOT ENOUGH",
"has_tags",
"JAMES BOND"
],
[
"THUNDERBALL",
"has_tags",
"BOND"
],
[
"THUNDERBALL",
"has_tags",
"JAMES BOND"
],
[
"THUNDERBALL",
"has_tags",
"SEAN CONNERY"
],
[
"THUNDERBALL",
"starred_actors",
"SEAN CONNERY"
],
[
"TOMORROW NEVER DIES",
"has_tags",
"BOND"
],
[
"TOMORROW NEVER DIES",
"has_tags",
"JAMES BOND"
],
[
"YOU ONLY LIVE TWICE",
"has_tags",
"BOND"
],
[
"YOU ONLY LIVE TWICE",
"has_tags",
"JAMES BOND"
],
[
"YOU ONLY LIVE TWICE",
"has_tags",
"SEAN CONNERY"
],
[
"YOU ONLY LIVE TWICE",
"has_tags",
"SPACE"
],
[
"YOU ONLY LIVE TWICE",
"starred_actors",
"SEAN CONNERY"
]
]
}
|
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
17307, DANA RANGA
12841, DOCUMENTARY
9257, EAST SIDE STORY
35055, GRAHAM DORRINGTON
21489, SPAWN
4773, THE WHITE DIAMOND
37617, THERESA RANDLE
src, edge_attr, dst
9257, directed_by, 17307
9257, has_genre, 12841
9257, release_year, 14259
9257, written_by, 17307
21489, release_year, 14259
21489, starred_actors, 37617
4773, has_genre, 12841
4773, has_tags, 12841
4773, starred_actors, 35055
Question: In what context are DANA RANGA, GRAHAM DORRINGTON, and THERESA RANDLE connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"DANA RANGA",
"GRAHAM DORRINGTON",
"THERESA RANDLE"
],
"valid_edges": [
[
"EAST SIDE STORY",
"directed_by",
"DANA RANGA"
],
[
"EAST SIDE STORY",
"has_genre",
"DOCUMENTARY"
],
[
"EAST SIDE STORY",
"release_year",
"1997"
],
[
"EAST SIDE STORY",
"written_by",
"DANA RANGA"
],
[
"SPAWN",
"release_year",
"1997"
],
[
"SPAWN",
"starred_actors",
"THERESA RANDLE"
],
[
"THE WHITE DIAMOND",
"has_genre",
"DOCUMENTARY"
],
[
"THE WHITE DIAMOND",
"has_tags",
"DOCUMENTARY"
],
[
"THE WHITE DIAMOND",
"starred_actors",
"GRAHAM DORRINGTON"
]
]
}
|
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
724, 1979
6718, A FAREWELL TO ARMS
28235, A KIND OF LOVING
12649, A LITTLE ROMANCE
8221, A MAN ESCAPED
16566, A MONKEY IN WINTER
37987, A ROOM WITH A VIEW
38344, A STREETCAR NAMED DESIRE
10341, ADVENTURES OF DON JUAN
7463, ALL QUIET ON THE WESTERN FRONT
15918, ALL THAT HEAVEN ALLOWS
8714, AN AMERICAN IN PARIS
36963, ANNA KARENINA
10045, BD-R
4592, BEAU TRAVAIL
34744, BEING THERE
17905, BILLY BUDD
16400, BILLY ROSE'S JUMBO
11547, BROKEBACK MOUNTAIN
21584, BUNNY LAKE IS MISSING
35953, BUTCH CASSIDY AND THE SUNDANCE KID
13302, CHAPTER TWO
25344, CONFIDENTIALLY YOURS
16536, CYRANO DE BERGERAC
23229, DAVID AND LISA
20538, DIANE LANE
11249, DIARY OF A COUNTRY PRIEST
36196, DR. EHRLICH'S MAGIC BULLET
24540, EYES WITHOUT A FACE
6012, FRENCH
8001, GAY PURR-EE
18042, GEORGE ROY HILL
5527, GIGI
20693, GONE WITH THE WIND
19871, GYPSY
20263, HAIR
20941, HAMLET
26383, I CONFESS
27285, I WAS A MALE WAR BRIDE
7539, IVANHOE
847, JACK THE GIANT KILLER
21922, JANE EYRE
10530, JULES AND JIM
14209, KING OF HEARTS
38326, L'ECLISSE
33519, LA HAINE
14525, LA JETÉE
2687, LAURENCE OLIVIER
30029, LAWRENCE OF ARABIA
35149, LE BEAU SERGE
39572, LES COUSINS
30157, LOLA
16925, MAYERLING
25334, MERRILL'S MARAUDERS
36083, MIRANDA
31657, MON ONCLE
5237, MURPHY'S ROMANCE
31907, MUTINY ON THE BOUNTY
17576, MY BRILLIANT CAREER
12358, MY FAVORITE SEASON
5338, NINOTCHKA
34012, NORMAN BURNSTINE
18184, OKLAHOMA!
10329, ONLY TWO CAN PLAY
31134, PARIS
9622, PERIOD OF ADJUSTMENT
29693, PICKPOCKET
33032, PORT OF SHADOWS
24745, PURPLE NOON
1405, QUADROPHENIA
7960, QUALITY STREET
6773, REAL LIFE
6297, REBECCA
21858, REQUIEM FOR A HEAVYWEIGHT
4848, RIDE THE HIGH COUNTRY
15938, RIFIFI
10299, ROLLER BOOGIE
8379, ROMANCE
2738, ROMEO AND JULIET
6603, SEX IS COMEDY
6119, SLEUTH
31624, SPELLBOUND
8436, SPIRITS OF THE DEAD
15194, STORY OF WOMEN
23429, SUMMERTIME
36865, SUNDAYS AND CYBELE
2766, TARAS BULBA
18902, TESS
8220, THAT HAMILTON WOMAN
24625, THE APARTMENT
15003, THE BATTLE OF ALGIERS
17361, THE BRAIN THAT WOULDN'T DIE
34737, THE BRIDE WORE BLACK
3354, THE BROTHERS GRIMM
3028, THE CHAPMAN REPORT
12339, THE CHINA SYNDROME
10812, THE CONSTANT NYMPH
24771, THE FIFTH MUSKETEER
38257, THE HAPPY TIME
11168, THE HUMAN FACTOR
15198, THE HUNCHBACK OF NOTRE DAME
25529, THE ILLUSIONIST
6836, THE IMMORTAL STORY
19104, THE IN-LAWS
1443, THE ITALIAN JOB
888, THE JAZZ SINGER
1236, THE L-SHAPED ROOM
4091, THE LADY VANISHES
12121, THE LONELINESS OF THE LONG DISTANCE RUNNER
27237, THE LONGEST DAY
31569, THE LOVE PARADE
4182, THE MAN IN THE IRON MASK
33513, THE MAN WHO LOVED WOMEN
36235, THE MAN WHO SHOT LIBERTY VALANCE
29773, THE MANCHURIAN CANDIDATE
32297, THE MERRY WIDOW
2672, THE MIRACLE WORKER
28118, THE MUSIC MAN
9580, THE PIRATES OF BLOOD RIVER
25144, THE PRINCE AND THE SHOWGIRL
31851, THE PRISONER OF ZENDA
12302, THE ROAD TO HONG KONG
8477, THE SCARLET PIMPERNEL
39278, THE STING
36903, THE SUITOR
30491, THE TRIAL
13722, THE TRIAL OF JOAN OF ARC
29678, THE UMBRELLAS OF CHERBOURG
17568, THE VANISHING
36283, THE WONDERFUL WORLD OF THE BROTHERS GRIMM
24789, TO HAVE AND HAVE NOT
12764, TO KILL A MOCKINGBIRD
3029, TRIPLE CROSS
22356, VENICE
11659, VIVA MARIA!
28071, WHAT EVER HAPPENED TO BABY JANE?
36233, WHERE THE BOYS ARE
15674, WHITE SHADOWS IN THE SOUTH SEAS
5673, WILD GUITAR
22774, WISE BLOOD
27708, WUTHERING HEIGHTS
38760, Z
23675, ZERO FOR CONDUCT
27175, ZULU DAWN
src, edge_attr, dst
6718, has_genre, 8379
6718, has_tags, 10045
28235, has_tags, 10045
28235, release_year, 3863
12649, directed_by, 18042
12649, has_genre, 8379
12649, has_tags, 10045
12649, has_tags, 20538
12649, has_tags, 18042
12649, has_tags, 2687
12649, has_tags, 31134
12649, has_tags, 22356
12649, in_language, 6012
12649, release_year, 724
12649, starred_actors, 20538
12649, starred_actors, 2687
8221, has_tags, 10045
8221, has_tags, 6012
8221, in_language, 6012
16566, in_language, 6012
16566, release_year, 3863
37987, has_genre, 8379
37987, has_tags, 10045
38344, has_tags, 10045
38344, starred_actors, 20538
10341, has_genre, 8379
10341, has_tags, 10045
7463, has_tags, 10045
7463, release_year, 724
15918, has_genre, 8379
15918, has_tags, 10045
8714, has_tags, 10045
8714, has_tags, 31134
36963, has_tags, 10045
36963, has_tags, 22356
4592, has_tags, 10045
4592, in_language, 6012
34744, has_tags, 10045
34744, release_year, 724
17905, has_tags, 10045
17905, release_year, 3863
16400, has_genre, 8379
16400, has_tags, 10045
16400, release_year, 3863
11547, has_genre, 8379
11547, has_tags, 10045
11547, has_tags, 8379
21584, has_tags, 10045
21584, starred_actors, 2687
35953, directed_by, 18042
35953, has_tags, 10045
35953, has_tags, 18042
13302, has_tags, 10045
13302, release_year, 724
25344, has_tags, 10045
25344, in_language, 6012
16536, has_tags, 10045
16536, has_tags, 6012
16536, in_language, 6012
23229, has_tags, 10045
23229, release_year, 3863
11249, has_tags, 10045
11249, in_language, 6012
36196, has_tags, 10045
36196, written_by, 34012
24540, has_tags, 10045
24540, in_language, 6012
8001, has_tags, 10045
8001, release_year, 3863
5527, has_tags, 10045
5527, in_language, 6012
20693, has_genre, 8379
20693, has_tags, 10045
20693, has_tags, 8379
19871, has_tags, 10045
19871, release_year, 3863
20263, has_tags, 10045
20263, release_year, 724
20941, directed_by, 2687
20941, has_tags, 10045
20941, has_tags, 2687
26383, has_tags, 10045
26383, in_language, 6012
27285, has_tags, 10045
27285, in_language, 6012
7539, has_genre, 8379
7539, has_tags, 10045
847, has_tags, 10045
847, release_year, 3863
21922, has_tags, 10045
21922, in_language, 6012
10530, has_tags, 6012
10530, in_language, 6012
10530, release_year, 3863
14209, has_tags, 10045
14209, in_language, 6012
38326, has_tags, 10045
38326, release_year, 3863
33519, has_tags, 10045
33519, has_tags, 6012
33519, has_tags, 31134
33519, in_language, 6012
14525, in_language, 6012
14525, release_year, 3863
30029, has_tags, 10045
30029, release_year, 3863
35149, has_tags, 10045
35149, in_language, 6012
39572, has_tags, 10045
39572, in_language, 6012
30157, has_tags, 10045
30157, in_language, 6012
16925, has_tags, 10045
16925, in_language, 6012
25334, has_tags, 10045
25334, release_year, 3863
36083, has_genre, 8379
36083, has_tags, 10045
31657, has_tags, 10045
31657, in_language, 6012
5237, has_genre, 8379
5237, has_tags, 10045
31907, has_tags, 10045
31907, release_year, 3863
17576, has_genre, 8379
17576, has_tags, 10045
17576, release_year, 724
12358, has_tags, 10045
12358, in_language, 6012
5338, has_genre, 8379
5338, has_tags, 10045
5338, has_tags, 31134
18184, has_genre, 8379
18184, has_tags, 10045
10329, has_tags, 10045
10329, release_year, 3863
31134, in_language, 6012
9622, directed_by, 18042
9622, has_tags, 10045
9622, release_year, 3863
29693, has_tags, 10045
29693, in_language, 6012
33032, has_tags, 10045
33032, in_language, 6012
24745, has_tags, 10045
24745, in_language, 6012
1405, has_tags, 10045
1405, release_year, 724
7960, has_genre, 8379
7960, has_tags, 10045
6773, has_tags, 10045
6773, release_year, 724
6297, has_tags, 10045
6297, has_tags, 2687
6297, starred_actors, 2687
21858, has_tags, 10045
21858, release_year, 3863
4848, has_tags, 10045
4848, release_year, 3863
15938, has_tags, 10045
15938, in_language, 6012
10299, has_tags, 10045
10299, release_year, 724
8379, in_language, 6012
2738, has_genre, 8379
2738, has_tags, 10045
2738, has_tags, 8379
6603, has_tags, 10045
6603, in_language, 6012
6119, has_tags, 10045
6119, has_tags, 2687
6119, starred_actors, 2687
31624, has_genre, 8379
31624, has_tags, 10045
8436, has_tags, 10045
8436, in_language, 6012
15194, has_tags, 10045
15194, in_language, 6012
23429, has_genre, 8379
23429, has_tags, 10045
23429, has_tags, 8379
36865, in_language, 6012
36865, release_year, 3863
2766, has_tags, 10045
2766, release_year, 3863
18902, has_genre, 8379
18902, has_tags, 10045
18902, release_year, 724
8220, has_tags, 10045
8220, starred_actors, 2687
24625, has_tags, 10045
24625, in_language, 6012
15003, has_tags, 10045
15003, has_tags, 6012
15003, in_language, 6012
17361, has_tags, 10045
17361, release_year, 3863
34737, has_tags, 10045
34737, in_language, 6012
3354, has_tags, 10045
3354, in_language, 6012
3028, has_tags, 10045
3028, release_year, 3863
12339, has_tags, 10045
12339, release_year, 724
10812, has_genre, 8379
10812, has_tags, 10045
24771, has_tags, 10045
24771, release_year, 724
38257, has_tags, 10045
38257, in_language, 6012
11168, has_tags, 10045
11168, release_year, 724
15198, has_tags, 10045
15198, has_tags, 31134
15198, in_language, 6012
25529, has_tags, 10045
25529, in_language, 6012
6836, has_tags, 10045
6836, in_language, 6012
19104, has_tags, 10045
19104, release_year, 724
1443, has_tags, 10045
1443, has_tags, 22356
888, has_tags, 10045
888, starred_actors, 2687
1236, has_tags, 10045
1236, release_year, 3863
4091, has_tags, 10045
4091, release_year, 724
12121, has_tags, 10045
12121, release_year, 3863
27237, in_language, 6012
27237, release_year, 3863
31569, has_tags, 10045
31569, in_language, 6012
4182, has_genre, 8379
4182, has_tags, 10045
33513, has_tags, 10045
33513, in_language, 6012
36235, has_tags, 10045
36235, release_year, 3863
29773, has_tags, 10045
29773, release_year, 3863
32297, has_tags, 10045
32297, in_language, 6012
2672, has_tags, 10045
2672, release_year, 3863
28118, has_tags, 10045
28118, release_year, 3863
9580, has_tags, 10045
9580, release_year, 3863
25144, directed_by, 2687
25144, has_tags, 10045
31851, has_tags, 10045
31851, release_year, 724
12302, has_tags, 10045
12302, release_year, 3863
8477, has_tags, 10045
8477, in_language, 6012
39278, directed_by, 18042
39278, has_tags, 10045
39278, has_tags, 18042
36903, in_language, 6012
36903, release_year, 3863
30491, has_tags, 10045
30491, release_year, 3863
13722, has_tags, 10045
13722, in_language, 6012
13722, release_year, 3863
29678, has_tags, 10045
29678, has_tags, 6012
29678, in_language, 6012
17568, has_tags, 10045
17568, in_language, 6012
36283, has_tags, 10045
36283, release_year, 3863
24789, has_genre, 8379
24789, has_tags, 10045
12764, has_tags, 10045
12764, release_year, 3863
3029, has_tags, 10045
3029, in_language, 6012
11659, has_tags, 10045
11659, has_tags, 6012
11659, in_language, 6012
28071, has_tags, 10045
28071, release_year, 3863
36233, has_genre, 8379
36233, has_tags, 10045
15674, has_genre, 8379
15674, has_tags, 10045
5673, release_year, 3863
22774, has_tags, 10045
22774, release_year, 724
27708, has_genre, 8379
27708, has_tags, 10045
38760, has_tags, 10045
38760, in_language, 6012
23675, has_tags, 10045
23675, has_tags, 6012
23675, in_language, 6012
27175, has_tags, 10045
27175, release_year, 724
Question: How are A LITTLE ROMANCE, NORMAN BURNSTINE, and WILD GUITAR related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"A LITTLE ROMANCE",
"NORMAN BURNSTINE",
"WILD GUITAR"
],
"valid_edges": [
[
"A FAREWELL TO ARMS",
"has_genre",
"ROMANCE"
],
[
"A FAREWELL TO ARMS",
"has_tags",
"BD-R"
],
[
"A KIND OF LOVING",
"has_tags",
"BD-R"
],
[
"A KIND OF LOVING",
"release_year",
"1962"
],
[
"A LITTLE ROMANCE",
"directed_by",
"GEORGE ROY HILL"
],
[
"A LITTLE ROMANCE",
"has_genre",
"ROMANCE"
],
[
"A LITTLE ROMANCE",
"has_tags",
"BD-R"
],
[
"A LITTLE ROMANCE",
"has_tags",
"DIANE LANE"
],
[
"A LITTLE ROMANCE",
"has_tags",
"GEORGE ROY HILL"
],
[
"A LITTLE ROMANCE",
"has_tags",
"LAURENCE OLIVIER"
],
[
"A LITTLE ROMANCE",
"has_tags",
"PARIS"
],
[
"A LITTLE ROMANCE",
"has_tags",
"VENICE"
],
[
"A LITTLE ROMANCE",
"in_language",
"FRENCH"
],
[
"A LITTLE ROMANCE",
"release_year",
"1979"
],
[
"A LITTLE ROMANCE",
"starred_actors",
"DIANE LANE"
],
[
"A LITTLE ROMANCE",
"starred_actors",
"LAURENCE OLIVIER"
],
[
"A MAN ESCAPED",
"has_tags",
"BD-R"
],
[
"A MAN ESCAPED",
"has_tags",
"FRENCH"
],
[
"A MAN ESCAPED",
"in_language",
"FRENCH"
],
[
"A MONKEY IN WINTER",
"in_language",
"FRENCH"
],
[
"A MONKEY IN WINTER",
"release_year",
"1962"
],
[
"A ROOM WITH A VIEW",
"has_genre",
"ROMANCE"
],
[
"A ROOM WITH A VIEW",
"has_tags",
"BD-R"
],
[
"A STREETCAR NAMED DESIRE",
"has_tags",
"BD-R"
],
[
"A STREETCAR NAMED DESIRE",
"starred_actors",
"DIANE LANE"
],
[
"ADVENTURES OF DON JUAN",
"has_genre",
"ROMANCE"
],
[
"ADVENTURES OF DON JUAN",
"has_tags",
"BD-R"
],
[
"ALL QUIET ON THE WESTERN FRONT",
"has_tags",
"BD-R"
],
[
"ALL QUIET ON THE WESTERN FRONT",
"release_year",
"1979"
],
[
"ALL THAT HEAVEN ALLOWS",
"has_genre",
"ROMANCE"
],
[
"ALL THAT HEAVEN ALLOWS",
"has_tags",
"BD-R"
],
[
"AN AMERICAN IN PARIS",
"has_tags",
"BD-R"
],
[
"AN AMERICAN IN PARIS",
"has_tags",
"PARIS"
],
[
"ANNA KARENINA",
"has_tags",
"BD-R"
],
[
"ANNA KARENINA",
"has_tags",
"VENICE"
],
[
"BEAU TRAVAIL",
"has_tags",
"BD-R"
],
[
"BEAU TRAVAIL",
"in_language",
"FRENCH"
],
[
"BEING THERE",
"has_tags",
"BD-R"
],
[
"BEING THERE",
"release_year",
"1979"
],
[
"BILLY BUDD",
"has_tags",
"BD-R"
],
[
"BILLY BUDD",
"release_year",
"1962"
],
[
"BILLY ROSE'S JUMBO",
"has_genre",
"ROMANCE"
],
[
"BILLY ROSE'S JUMBO",
"has_tags",
"BD-R"
],
[
"BILLY ROSE'S JUMBO",
"release_year",
"1962"
],
[
"BROKEBACK MOUNTAIN",
"has_genre",
"ROMANCE"
],
[
"BROKEBACK MOUNTAIN",
"has_tags",
"BD-R"
],
[
"BROKEBACK MOUNTAIN",
"has_tags",
"ROMANCE"
],
[
"BUNNY LAKE IS MISSING",
"has_tags",
"BD-R"
],
[
"BUNNY LAKE IS MISSING",
"starred_actors",
"LAURENCE OLIVIER"
],
[
"BUTCH CASSIDY AND THE SUNDANCE KID",
"directed_by",
"GEORGE ROY HILL"
],
[
"BUTCH CASSIDY AND THE SUNDANCE KID",
"has_tags",
"BD-R"
],
[
"BUTCH CASSIDY AND THE SUNDANCE KID",
"has_tags",
"GEORGE ROY HILL"
],
[
"CHAPTER TWO",
"has_tags",
"BD-R"
],
[
"CHAPTER TWO",
"release_year",
"1979"
],
[
"CONFIDENTIALLY YOURS",
"has_tags",
"BD-R"
],
[
"CONFIDENTIALLY YOURS",
"in_language",
"FRENCH"
],
[
"CYRANO DE BERGERAC",
"has_tags",
"BD-R"
],
[
"CYRANO DE BERGERAC",
"has_tags",
"FRENCH"
],
[
"CYRANO DE BERGERAC",
"in_language",
"FRENCH"
],
[
"DAVID AND LISA",
"has_tags",
"BD-R"
],
[
"DAVID AND LISA",
"release_year",
"1962"
],
[
"DIARY OF A COUNTRY PRIEST",
"has_tags",
"BD-R"
],
[
"DIARY OF A COUNTRY PRIEST",
"in_language",
"FRENCH"
],
[
"DR. EHRLICH'S MAGIC BULLET",
"has_tags",
"BD-R"
],
[
"DR. EHRLICH'S MAGIC BULLET",
"written_by",
"NORMAN BURNSTINE"
],
[
"EYES WITHOUT A FACE",
"has_tags",
"BD-R"
],
[
"EYES WITHOUT A FACE",
"in_language",
"FRENCH"
],
[
"GAY PURR-EE",
"has_tags",
"BD-R"
],
[
"GAY PURR-EE",
"release_year",
"1962"
],
[
"GIGI",
"has_tags",
"BD-R"
],
[
"GIGI",
"in_language",
"FRENCH"
],
[
"GONE WITH THE WIND",
"has_genre",
"ROMANCE"
],
[
"GONE WITH THE WIND",
"has_tags",
"BD-R"
],
[
"GONE WITH THE WIND",
"has_tags",
"ROMANCE"
],
[
"GYPSY",
"has_tags",
"BD-R"
],
[
"GYPSY",
"release_year",
"1962"
],
[
"HAIR",
"has_tags",
"BD-R"
],
[
"HAIR",
"release_year",
"1979"
],
[
"HAMLET",
"directed_by",
"LAURENCE OLIVIER"
],
[
"HAMLET",
"has_tags",
"BD-R"
],
[
"HAMLET",
"has_tags",
"LAURENCE OLIVIER"
],
[
"I CONFESS",
"has_tags",
"BD-R"
],
[
"I CONFESS",
"in_language",
"FRENCH"
],
[
"I WAS A MALE WAR BRIDE",
"has_tags",
"BD-R"
],
[
"I WAS A MALE WAR BRIDE",
"in_language",
"FRENCH"
],
[
"IVANHOE",
"has_genre",
"ROMANCE"
],
[
"IVANHOE",
"has_tags",
"BD-R"
],
[
"JACK THE GIANT KILLER",
"has_tags",
"BD-R"
],
[
"JACK THE GIANT KILLER",
"release_year",
"1962"
],
[
"JANE EYRE",
"has_tags",
"BD-R"
],
[
"JANE EYRE",
"in_language",
"FRENCH"
],
[
"JULES AND JIM",
"has_tags",
"FRENCH"
],
[
"JULES AND JIM",
"in_language",
"FRENCH"
],
[
"JULES AND JIM",
"release_year",
"1962"
],
[
"KING OF HEARTS",
"has_tags",
"BD-R"
],
[
"KING OF HEARTS",
"in_language",
"FRENCH"
],
[
"L'ECLISSE",
"has_tags",
"BD-R"
],
[
"L'ECLISSE",
"release_year",
"1962"
],
[
"LA HAINE",
"has_tags",
"BD-R"
],
[
"LA HAINE",
"has_tags",
"FRENCH"
],
[
"LA HAINE",
"has_tags",
"PARIS"
],
[
"LA HAINE",
"in_language",
"FRENCH"
],
[
"LA JETÉE",
"in_language",
"FRENCH"
],
[
"LA JETÉE",
"release_year",
"1962"
],
[
"LAWRENCE OF ARABIA",
"has_tags",
"BD-R"
],
[
"LAWRENCE OF ARABIA",
"release_year",
"1962"
],
[
"LE BEAU SERGE",
"has_tags",
"BD-R"
],
[
"LE BEAU SERGE",
"in_language",
"FRENCH"
],
[
"LES COUSINS",
"has_tags",
"BD-R"
],
[
"LES COUSINS",
"in_language",
"FRENCH"
],
[
"LOLA",
"has_tags",
"BD-R"
],
[
"LOLA",
"in_language",
"FRENCH"
],
[
"MAYERLING",
"has_tags",
"BD-R"
],
[
"MAYERLING",
"in_language",
"FRENCH"
],
[
"MERRILL'S MARAUDERS",
"has_tags",
"BD-R"
],
[
"MERRILL'S MARAUDERS",
"release_year",
"1962"
],
[
"MIRANDA",
"has_genre",
"ROMANCE"
],
[
"MIRANDA",
"has_tags",
"BD-R"
],
[
"MON ONCLE",
"has_tags",
"BD-R"
],
[
"MON ONCLE",
"in_language",
"FRENCH"
],
[
"MURPHY'S ROMANCE",
"has_genre",
"ROMANCE"
],
[
"MURPHY'S ROMANCE",
"has_tags",
"BD-R"
],
[
"MUTINY ON THE BOUNTY",
"has_tags",
"BD-R"
],
[
"MUTINY ON THE BOUNTY",
"release_year",
"1962"
],
[
"MY BRILLIANT CAREER",
"has_genre",
"ROMANCE"
],
[
"MY BRILLIANT CAREER",
"has_tags",
"BD-R"
],
[
"MY BRILLIANT CAREER",
"release_year",
"1979"
],
[
"MY FAVORITE SEASON",
"has_tags",
"BD-R"
],
[
"MY FAVORITE SEASON",
"in_language",
"FRENCH"
],
[
"NINOTCHKA",
"has_genre",
"ROMANCE"
],
[
"NINOTCHKA",
"has_tags",
"BD-R"
],
[
"NINOTCHKA",
"has_tags",
"PARIS"
],
[
"OKLAHOMA!",
"has_genre",
"ROMANCE"
],
[
"OKLAHOMA!",
"has_tags",
"BD-R"
],
[
"ONLY TWO CAN PLAY",
"has_tags",
"BD-R"
],
[
"ONLY TWO CAN PLAY",
"release_year",
"1962"
],
[
"PARIS",
"in_language",
"FRENCH"
],
[
"PERIOD OF ADJUSTMENT",
"directed_by",
"GEORGE ROY HILL"
],
[
"PERIOD OF ADJUSTMENT",
"has_tags",
"BD-R"
],
[
"PERIOD OF ADJUSTMENT",
"release_year",
"1962"
],
[
"PICKPOCKET",
"has_tags",
"BD-R"
],
[
"PICKPOCKET",
"in_language",
"FRENCH"
],
[
"PORT OF SHADOWS",
"has_tags",
"BD-R"
],
[
"PORT OF SHADOWS",
"in_language",
"FRENCH"
],
[
"PURPLE NOON",
"has_tags",
"BD-R"
],
[
"PURPLE NOON",
"in_language",
"FRENCH"
],
[
"QUADROPHENIA",
"has_tags",
"BD-R"
],
[
"QUADROPHENIA",
"release_year",
"1979"
],
[
"QUALITY STREET",
"has_genre",
"ROMANCE"
],
[
"QUALITY STREET",
"has_tags",
"BD-R"
],
[
"REAL LIFE",
"has_tags",
"BD-R"
],
[
"REAL LIFE",
"release_year",
"1979"
],
[
"REBECCA",
"has_tags",
"BD-R"
],
[
"REBECCA",
"has_tags",
"LAURENCE OLIVIER"
],
[
"REBECCA",
"starred_actors",
"LAURENCE OLIVIER"
],
[
"REQUIEM FOR A HEAVYWEIGHT",
"has_tags",
"BD-R"
],
[
"REQUIEM FOR A HEAVYWEIGHT",
"release_year",
"1962"
],
[
"RIDE THE HIGH COUNTRY",
"has_tags",
"BD-R"
],
[
"RIDE THE HIGH COUNTRY",
"release_year",
"1962"
],
[
"RIFIFI",
"has_tags",
"BD-R"
],
[
"RIFIFI",
"in_language",
"FRENCH"
],
[
"ROLLER BOOGIE",
"has_tags",
"BD-R"
],
[
"ROLLER BOOGIE",
"release_year",
"1979"
],
[
"ROMANCE",
"in_language",
"FRENCH"
],
[
"ROMEO AND JULIET",
"has_genre",
"ROMANCE"
],
[
"ROMEO AND JULIET",
"has_tags",
"BD-R"
],
[
"ROMEO AND JULIET",
"has_tags",
"ROMANCE"
],
[
"SEX IS COMEDY",
"has_tags",
"BD-R"
],
[
"SEX IS COMEDY",
"in_language",
"FRENCH"
],
[
"SLEUTH",
"has_tags",
"BD-R"
],
[
"SLEUTH",
"has_tags",
"LAURENCE OLIVIER"
],
[
"SLEUTH",
"starred_actors",
"LAURENCE OLIVIER"
],
[
"SPELLBOUND",
"has_genre",
"ROMANCE"
],
[
"SPELLBOUND",
"has_tags",
"BD-R"
],
[
"SPIRITS OF THE DEAD",
"has_tags",
"BD-R"
],
[
"SPIRITS OF THE DEAD",
"in_language",
"FRENCH"
],
[
"STORY OF WOMEN",
"has_tags",
"BD-R"
],
[
"STORY OF WOMEN",
"in_language",
"FRENCH"
],
[
"SUMMERTIME",
"has_genre",
"ROMANCE"
],
[
"SUMMERTIME",
"has_tags",
"BD-R"
],
[
"SUMMERTIME",
"has_tags",
"ROMANCE"
],
[
"SUNDAYS AND CYBELE",
"in_language",
"FRENCH"
],
[
"SUNDAYS AND CYBELE",
"release_year",
"1962"
],
[
"TARAS BULBA",
"has_tags",
"BD-R"
],
[
"TARAS BULBA",
"release_year",
"1962"
],
[
"TESS",
"has_genre",
"ROMANCE"
],
[
"TESS",
"has_tags",
"BD-R"
],
[
"TESS",
"release_year",
"1979"
],
[
"THAT HAMILTON WOMAN",
"has_tags",
"BD-R"
],
[
"THAT HAMILTON WOMAN",
"starred_actors",
"LAURENCE OLIVIER"
],
[
"THE APARTMENT",
"has_tags",
"BD-R"
],
[
"THE APARTMENT",
"in_language",
"FRENCH"
],
[
"THE BATTLE OF ALGIERS",
"has_tags",
"BD-R"
],
[
"THE BATTLE OF ALGIERS",
"has_tags",
"FRENCH"
],
[
"THE BATTLE OF ALGIERS",
"in_language",
"FRENCH"
],
[
"THE BRAIN THAT WOULDN'T DIE",
"has_tags",
"BD-R"
],
[
"THE BRAIN THAT WOULDN'T DIE",
"release_year",
"1962"
],
[
"THE BRIDE WORE BLACK",
"has_tags",
"BD-R"
],
[
"THE BRIDE WORE BLACK",
"in_language",
"FRENCH"
],
[
"THE BROTHERS GRIMM",
"has_tags",
"BD-R"
],
[
"THE BROTHERS GRIMM",
"in_language",
"FRENCH"
],
[
"THE CHAPMAN REPORT",
"has_tags",
"BD-R"
],
[
"THE CHAPMAN REPORT",
"release_year",
"1962"
],
[
"THE CHINA SYNDROME",
"has_tags",
"BD-R"
],
[
"THE CHINA SYNDROME",
"release_year",
"1979"
],
[
"THE CONSTANT NYMPH",
"has_genre",
"ROMANCE"
],
[
"THE CONSTANT NYMPH",
"has_tags",
"BD-R"
],
[
"THE FIFTH MUSKETEER",
"has_tags",
"BD-R"
],
[
"THE FIFTH MUSKETEER",
"release_year",
"1979"
],
[
"THE HAPPY TIME",
"has_tags",
"BD-R"
],
[
"THE HAPPY TIME",
"in_language",
"FRENCH"
],
[
"THE HUMAN FACTOR",
"has_tags",
"BD-R"
],
[
"THE HUMAN FACTOR",
"release_year",
"1979"
],
[
"THE HUNCHBACK OF NOTRE DAME",
"has_tags",
"BD-R"
],
[
"THE HUNCHBACK OF NOTRE DAME",
"has_tags",
"PARIS"
],
[
"THE HUNCHBACK OF NOTRE DAME",
"in_language",
"FRENCH"
],
[
"THE ILLUSIONIST",
"has_tags",
"BD-R"
],
[
"THE ILLUSIONIST",
"in_language",
"FRENCH"
],
[
"THE IMMORTAL STORY",
"has_tags",
"BD-R"
],
[
"THE IMMORTAL STORY",
"in_language",
"FRENCH"
],
[
"THE IN-LAWS",
"has_tags",
"BD-R"
],
[
"THE IN-LAWS",
"release_year",
"1979"
],
[
"THE ITALIAN JOB",
"has_tags",
"BD-R"
],
[
"THE ITALIAN JOB",
"has_tags",
"VENICE"
],
[
"THE JAZZ SINGER",
"has_tags",
"BD-R"
],
[
"THE JAZZ SINGER",
"starred_actors",
"LAURENCE OLIVIER"
],
[
"THE L-SHAPED ROOM",
"has_tags",
"BD-R"
],
[
"THE L-SHAPED ROOM",
"release_year",
"1962"
],
[
"THE LADY VANISHES",
"has_tags",
"BD-R"
],
[
"THE LADY VANISHES",
"release_year",
"1979"
],
[
"THE LONELINESS OF THE LONG DISTANCE RUNNER",
"has_tags",
"BD-R"
],
[
"THE LONELINESS OF THE LONG DISTANCE RUNNER",
"release_year",
"1962"
],
[
"THE LONGEST DAY",
"in_language",
"FRENCH"
],
[
"THE LONGEST DAY",
"release_year",
"1962"
],
[
"THE LOVE PARADE",
"has_tags",
"BD-R"
],
[
"THE LOVE PARADE",
"in_language",
"FRENCH"
],
[
"THE MAN IN THE IRON MASK",
"has_genre",
"ROMANCE"
],
[
"THE MAN IN THE IRON MASK",
"has_tags",
"BD-R"
],
[
"THE MAN WHO LOVED WOMEN",
"has_tags",
"BD-R"
],
[
"THE MAN WHO LOVED WOMEN",
"in_language",
"FRENCH"
],
[
"THE MAN WHO SHOT LIBERTY VALANCE",
"has_tags",
"BD-R"
],
[
"THE MAN WHO SHOT LIBERTY VALANCE",
"release_year",
"1962"
],
[
"THE MANCHURIAN CANDIDATE",
"has_tags",
"BD-R"
],
[
"THE MANCHURIAN CANDIDATE",
"release_year",
"1962"
],
[
"THE MERRY WIDOW",
"has_tags",
"BD-R"
],
[
"THE MERRY WIDOW",
"in_language",
"FRENCH"
],
[
"THE MIRACLE WORKER",
"has_tags",
"BD-R"
],
[
"THE MIRACLE WORKER",
"release_year",
"1962"
],
[
"THE MUSIC MAN",
"has_tags",
"BD-R"
],
[
"THE MUSIC MAN",
"release_year",
"1962"
],
[
"THE PIRATES OF BLOOD RIVER",
"has_tags",
"BD-R"
],
[
"THE PIRATES OF BLOOD RIVER",
"release_year",
"1962"
],
[
"THE PRINCE AND THE SHOWGIRL",
"directed_by",
"LAURENCE OLIVIER"
],
[
"THE PRINCE AND THE SHOWGIRL",
"has_tags",
"BD-R"
],
[
"THE PRISONER OF ZENDA",
"has_tags",
"BD-R"
],
[
"THE PRISONER OF ZENDA",
"release_year",
"1979"
],
[
"THE ROAD TO HONG KONG",
"has_tags",
"BD-R"
],
[
"THE ROAD TO HONG KONG",
"release_year",
"1962"
],
[
"THE SCARLET PIMPERNEL",
"has_tags",
"BD-R"
],
[
"THE SCARLET PIMPERNEL",
"in_language",
"FRENCH"
],
[
"THE STING",
"directed_by",
"GEORGE ROY HILL"
],
[
"THE STING",
"has_tags",
"BD-R"
],
[
"THE STING",
"has_tags",
"GEORGE ROY HILL"
],
[
"THE SUITOR",
"in_language",
"FRENCH"
],
[
"THE SUITOR",
"release_year",
"1962"
],
[
"THE TRIAL",
"has_tags",
"BD-R"
],
[
"THE TRIAL",
"release_year",
"1962"
],
[
"THE TRIAL OF JOAN OF ARC",
"has_tags",
"BD-R"
],
[
"THE TRIAL OF JOAN OF ARC",
"in_language",
"FRENCH"
],
[
"THE TRIAL OF JOAN OF ARC",
"release_year",
"1962"
],
[
"THE UMBRELLAS OF CHERBOURG",
"has_tags",
"BD-R"
],
[
"THE UMBRELLAS OF CHERBOURG",
"has_tags",
"FRENCH"
],
[
"THE UMBRELLAS OF CHERBOURG",
"in_language",
"FRENCH"
],
[
"THE VANISHING",
"has_tags",
"BD-R"
],
[
"THE VANISHING",
"in_language",
"FRENCH"
],
[
"THE WONDERFUL WORLD OF THE BROTHERS GRIMM",
"has_tags",
"BD-R"
],
[
"THE WONDERFUL WORLD OF THE BROTHERS GRIMM",
"release_year",
"1962"
],
[
"TO HAVE AND HAVE NOT",
"has_genre",
"ROMANCE"
],
[
"TO HAVE AND HAVE NOT",
"has_tags",
"BD-R"
],
[
"TO KILL A MOCKINGBIRD",
"has_tags",
"BD-R"
],
[
"TO KILL A MOCKINGBIRD",
"release_year",
"1962"
],
[
"TRIPLE CROSS",
"has_tags",
"BD-R"
],
[
"TRIPLE CROSS",
"in_language",
"FRENCH"
],
[
"VIVA MARIA!",
"has_tags",
"BD-R"
],
[
"VIVA MARIA!",
"has_tags",
"FRENCH"
],
[
"VIVA MARIA!",
"in_language",
"FRENCH"
],
[
"WHAT EVER HAPPENED TO BABY JANE?",
"has_tags",
"BD-R"
],
[
"WHAT EVER HAPPENED TO BABY JANE?",
"release_year",
"1962"
],
[
"WHERE THE BOYS ARE",
"has_genre",
"ROMANCE"
],
[
"WHERE THE BOYS ARE",
"has_tags",
"BD-R"
],
[
"WHITE SHADOWS IN THE SOUTH SEAS",
"has_genre",
"ROMANCE"
],
[
"WHITE SHADOWS IN THE SOUTH SEAS",
"has_tags",
"BD-R"
],
[
"WILD GUITAR",
"release_year",
"1962"
],
[
"WISE BLOOD",
"has_tags",
"BD-R"
],
[
"WISE BLOOD",
"release_year",
"1979"
],
[
"WUTHERING HEIGHTS",
"has_genre",
"ROMANCE"
],
[
"WUTHERING HEIGHTS",
"has_tags",
"BD-R"
],
[
"Z",
"has_tags",
"BD-R"
],
[
"Z",
"in_language",
"FRENCH"
],
[
"ZERO FOR CONDUCT",
"has_tags",
"BD-R"
],
[
"ZERO FOR CONDUCT",
"has_tags",
"FRENCH"
],
[
"ZERO FOR CONDUCT",
"in_language",
"FRENCH"
],
[
"ZULU DAWN",
"has_tags",
"BD-R"
],
[
"ZULU DAWN",
"release_year",
"1979"
]
]
}
|
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
21931, 1941
24525, 1984
30146, A CHRISTMAS CAROL
33088, CARMEN
7631, KATHLEEN TURNER
31225, ROAD TO ZANZIBAR
32090, ROBERT ZEMECKIS
28221, ROMANCING THE STONE
7556, SPANISH
13491, THE DEVIL'S BACKBONE
959, THE HIT
31772, WHAT HAVE I DONE TO DESERVE THIS?
3912, WHO FRAMED ROGER RABBIT
src, edge_attr, dst
21931, written_by, 32090
30146, directed_by, 32090
30146, release_year, 24525
30146, written_by, 32090
33088, in_language, 7556
33088, release_year, 24525
31225, release_year, 21931
28221, directed_by, 32090
28221, has_tags, 7631
28221, has_tags, 32090
28221, release_year, 24525
28221, starred_actors, 7631
13491, has_tags, 7556
13491, in_language, 7556
959, in_language, 7556
959, release_year, 24525
31772, in_language, 7556
31772, release_year, 24525
3912, directed_by, 32090
3912, has_tags, 7631
3912, has_tags, 32090
Question: In what context are ROAD TO ZANZIBAR, ROMANCING THE STONE, and THE DEVIL'S BACKBONE connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"ROAD TO ZANZIBAR",
"ROMANCING THE STONE",
"THE DEVIL'S BACKBONE"
],
"valid_edges": [
[
"1941",
"written_by",
"ROBERT ZEMECKIS"
],
[
"A CHRISTMAS CAROL",
"directed_by",
"ROBERT ZEMECKIS"
],
[
"A CHRISTMAS CAROL",
"release_year",
"1984"
],
[
"A CHRISTMAS CAROL",
"written_by",
"ROBERT ZEMECKIS"
],
[
"CARMEN",
"in_language",
"SPANISH"
],
[
"CARMEN",
"release_year",
"1984"
],
[
"ROAD TO ZANZIBAR",
"release_year",
"1941"
],
[
"ROMANCING THE STONE",
"directed_by",
"ROBERT ZEMECKIS"
],
[
"ROMANCING THE STONE",
"has_tags",
"KATHLEEN TURNER"
],
[
"ROMANCING THE STONE",
"has_tags",
"ROBERT ZEMECKIS"
],
[
"ROMANCING THE STONE",
"release_year",
"1984"
],
[
"ROMANCING THE STONE",
"starred_actors",
"KATHLEEN TURNER"
],
[
"THE DEVIL'S BACKBONE",
"has_tags",
"SPANISH"
],
[
"THE DEVIL'S BACKBONE",
"in_language",
"SPANISH"
],
[
"THE HIT",
"in_language",
"SPANISH"
],
[
"THE HIT",
"release_year",
"1984"
],
[
"WHAT HAVE I DONE TO DESERVE THIS?",
"in_language",
"SPANISH"
],
[
"WHAT HAVE I DONE TO DESERVE THIS?",
"release_year",
"1984"
],
[
"WHO FRAMED ROGER RABBIT",
"directed_by",
"ROBERT ZEMECKIS"
],
[
"WHO FRAMED ROGER RABBIT",
"has_tags",
"KATHLEEN TURNER"
],
[
"WHO FRAMED ROGER RABBIT",
"has_tags",
"ROBERT ZEMECKIS"
]
]
}
|
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
29410, AND NOW MY LOVE
204, CELINE AND JULIE GO BOATING
32474, EMMANUELLE
6012, FRENCH
37514, GOING PLACES
11864, I AM A SEX ADDICT
24812, LACOMBE, LUCIEN
9603, PIERROT LE FOU
27784, SEX
30692, THE APPRENTICESHIP OF DUDDY KRAVITZ
18900, THE MAN WHO SLEEPS
src, edge_attr, dst
29410, in_language, 6012
29410, release_year, 31196
204, in_language, 6012
204, release_year, 31196
32474, has_tags, 27784
32474, in_language, 6012
32474, release_year, 31196
37514, in_language, 6012
37514, release_year, 31196
11864, has_tags, 27784
24812, in_language, 6012
24812, release_year, 31196
9603, in_language, 6012
30692, release_year, 31196
18900, in_language, 6012
18900, release_year, 31196
Question: In what context are I AM A SEX ADDICT, PIERROT LE FOU, and THE APPRENTICESHIP OF DUDDY KRAVITZ connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"I AM A SEX ADDICT",
"PIERROT LE FOU",
"THE APPRENTICESHIP OF DUDDY KRAVITZ"
],
"valid_edges": [
[
"AND NOW MY LOVE",
"in_language",
"FRENCH"
],
[
"AND NOW MY LOVE",
"release_year",
"1974"
],
[
"CELINE AND JULIE GO BOATING",
"in_language",
"FRENCH"
],
[
"CELINE AND JULIE GO BOATING",
"release_year",
"1974"
],
[
"EMMANUELLE",
"has_tags",
"SEX"
],
[
"EMMANUELLE",
"in_language",
"FRENCH"
],
[
"EMMANUELLE",
"release_year",
"1974"
],
[
"GOING PLACES",
"in_language",
"FRENCH"
],
[
"GOING PLACES",
"release_year",
"1974"
],
[
"I AM A SEX ADDICT",
"has_tags",
"SEX"
],
[
"LACOMBE, LUCIEN",
"in_language",
"FRENCH"
],
[
"LACOMBE, LUCIEN",
"release_year",
"1974"
],
[
"PIERROT LE FOU",
"in_language",
"FRENCH"
],
[
"THE APPRENTICESHIP OF DUDDY KRAVITZ",
"release_year",
"1974"
],
[
"THE MAN WHO SLEEPS",
"in_language",
"FRENCH"
],
[
"THE MAN WHO SLEEPS",
"release_year",
"1974"
]
]
}
|
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
26633, 1989
21385, AMANECE, QUE NO ES POCO
25251, COP
24044, IMMEDIATE FAMILY
4233, JAMES WOODS
7659, JUSTINE BATEMAN
30331, LESLEY ANN WARREN
21059, SATISFACTION
7556, SPANISH
34750, THE BOOST
34188, TRUE BELIEVER
29650, WOMEN ON THE VERGE OF A NERVOUS BREAKDOWN
10596, WORTH WINNING
src, edge_attr, dst
21385, has_tags, 7556
21385, in_language, 7556
21385, release_year, 26633
25251, release_year, 17480
25251, starred_actors, 4233
25251, starred_actors, 30331
24044, release_year, 26633
24044, starred_actors, 4233
21059, release_year, 17480
21059, starred_actors, 7659
34750, release_year, 17480
34750, starred_actors, 4233
34188, has_tags, 4233
34188, release_year, 26633
34188, starred_actors, 4233
29650, has_tags, 7556
29650, in_language, 7556
29650, release_year, 17480
10596, release_year, 26633
10596, starred_actors, 30331
Question: In what context are AMANECE, QUE NO ES POCO, COP, and JUSTINE BATEMAN connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"AMANECE, QUE NO ES POCO",
"COP",
"JUSTINE BATEMAN"
],
"valid_edges": [
[
"AMANECE, QUE NO ES POCO",
"has_tags",
"SPANISH"
],
[
"AMANECE, QUE NO ES POCO",
"in_language",
"SPANISH"
],
[
"AMANECE, QUE NO ES POCO",
"release_year",
"1989"
],
[
"COP",
"release_year",
"1988"
],
[
"COP",
"starred_actors",
"JAMES WOODS"
],
[
"COP",
"starred_actors",
"LESLEY ANN WARREN"
],
[
"IMMEDIATE FAMILY",
"release_year",
"1989"
],
[
"IMMEDIATE FAMILY",
"starred_actors",
"JAMES WOODS"
],
[
"SATISFACTION",
"release_year",
"1988"
],
[
"SATISFACTION",
"starred_actors",
"JUSTINE BATEMAN"
],
[
"THE BOOST",
"release_year",
"1988"
],
[
"THE BOOST",
"starred_actors",
"JAMES WOODS"
],
[
"TRUE BELIEVER",
"has_tags",
"JAMES WOODS"
],
[
"TRUE BELIEVER",
"release_year",
"1989"
],
[
"TRUE BELIEVER",
"starred_actors",
"JAMES WOODS"
],
[
"WOMEN ON THE VERGE OF A NERVOUS BREAKDOWN",
"has_tags",
"SPANISH"
],
[
"WOMEN ON THE VERGE OF A NERVOUS BREAKDOWN",
"in_language",
"SPANISH"
],
[
"WOMEN ON THE VERGE OF A NERVOUS BREAKDOWN",
"release_year",
"1988"
],
[
"WORTH WINNING",
"release_year",
"1989"
],
[
"WORTH WINNING",
"starred_actors",
"LESLEY ANN WARREN"
]
]
}
|
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
28306, 71 FRAGMENTS OF A CHRONOLOGY OF CHANCE
14242, A FRIEND OF MINE
1668, ASTERIX CONQUERS AMERICA
12242, BACKBEAT
30715, FELIDAE
24028, FLOUNDERING
6480, GERMAN
35431, GRACE IS GONE
23462, JOHN CUSACK
15750, S.F.W.
18758, STEPHEN DORFF
13917, THE ROAD TO WELLVILLE
src, edge_attr, dst
28306, in_language, 6480
28306, release_year, 26257
14242, in_language, 6480
1668, in_language, 6480
1668, release_year, 26257
12242, in_language, 6480
12242, release_year, 26257
12242, starred_actors, 18758
30715, in_language, 6480
30715, release_year, 26257
24028, release_year, 26257
24028, starred_actors, 23462
24028, written_by, 23462
35431, has_tags, 23462
35431, starred_actors, 23462
15750, release_year, 26257
15750, starred_actors, 18758
13917, release_year, 26257
13917, starred_actors, 23462
Question: In what context are A FRIEND OF MINE, GRACE IS GONE, and S.F.W. connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"A FRIEND OF MINE",
"GRACE IS GONE",
"S.F.W."
],
"valid_edges": [
[
"71 FRAGMENTS OF A CHRONOLOGY OF CHANCE",
"in_language",
"GERMAN"
],
[
"71 FRAGMENTS OF A CHRONOLOGY OF CHANCE",
"release_year",
"1994"
],
[
"A FRIEND OF MINE",
"in_language",
"GERMAN"
],
[
"ASTERIX CONQUERS AMERICA",
"in_language",
"GERMAN"
],
[
"ASTERIX CONQUERS AMERICA",
"release_year",
"1994"
],
[
"BACKBEAT",
"in_language",
"GERMAN"
],
[
"BACKBEAT",
"release_year",
"1994"
],
[
"BACKBEAT",
"starred_actors",
"STEPHEN DORFF"
],
[
"FELIDAE",
"in_language",
"GERMAN"
],
[
"FELIDAE",
"release_year",
"1994"
],
[
"FLOUNDERING",
"release_year",
"1994"
],
[
"FLOUNDERING",
"starred_actors",
"JOHN CUSACK"
],
[
"FLOUNDERING",
"written_by",
"JOHN CUSACK"
],
[
"GRACE IS GONE",
"has_tags",
"JOHN CUSACK"
],
[
"GRACE IS GONE",
"starred_actors",
"JOHN CUSACK"
],
[
"S.F.W.",
"release_year",
"1994"
],
[
"S.F.W.",
"starred_actors",
"STEPHEN DORFF"
],
[
"THE ROAD TO WELLVILLE",
"release_year",
"1994"
],
[
"THE ROAD TO WELLVILLE",
"starred_actors",
"JOHN CUSACK"
]
]
}
|
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
14004, 1955
6718, A FAREWELL TO ARMS
12649, A LITTLE ROMANCE
24319, A PASSAGE TO INDIA
37987, A ROOM WITH A VIEW
10341, ADVENTURES OF DON JUAN
36358, ALEC GUINNESS
3700, ALEXANDER MACKENDRICK
15918, ALL THAT HEAVEN ALLOWS
25314, ARTHUR LAURENTS
17570, BAD DAY AT BLACK ROCK
10045, BD-R
15771, BENGAZI
16400, BILLY ROSE'S JUMBO
7812, BONJOUR TRISTESSE
11547, BROKEBACK MOUNTAIN
7004, CECIL PARKER
30463, COMEDY
25607, CREATURE WITH THE ATOM BRAIN
39336, DAVID LEAN
25805, DOCTOR ZHIVAGO
36212, DRAMA
15533, EALING STUDIOS
24883, EAST OF EDEN
20693, GONE WITH THE WIND
4709, GREAT EXPECTATIONS
12244, GUYS AND DOLLS
19871, GYPSY
20400, HOBSON'S CHOICE
33504, IT CAME FROM BENEATH THE SEA
7539, IVANHOE
1064, LAND OF THE PHARAOHS
30029, LAWRENCE OF ARABIA
13376, LOVE IS A MANY-SPLENDORED THING
2686, MARTY
36083, MIRANDA
5237, MURPHY'S ROMANCE
17576, MY BRILLIANT CAREER
5338, NINOTCHKA
18184, OKLAHOMA!
15644, OLIVER TWIST
439, PICNIC
7960, QUALITY STREET
19383, REBEL WITHOUT A CAUSE
15938, RIFIFI
8379, ROMANCE
2738, ROMEO AND JULIET
17096, RUDY WURLITZER
30447, RYAN'S DAUGHTER
36843, SMILES OF A SUMMER NIGHT
31624, SPELLBOUND
23429, SUMMERTIME
18902, TESS
36857, THE BRIDGE ON THE RIVER KWAI
23978, THE COBWEB
10812, THE CONSTANT NYMPH
30311, THE COURT JESTER
30690, THE LADYKILLERS
4182, THE MAN IN THE IRON MASK
19329, THE MAN IN THE WHITE SUIT
404, THE MAN WITH THE GOLDEN ARM
27599, THE NIGHT OF THE HUNTER
35764, THE PASSIONATE FRIENDS
18274, THE ROSE TATTOO
25574, THE SEVEN YEAR ITCH
32709, THE WAY WE WERE
14471, THIS HAPPY BREED
24789, TO HAVE AND HAVE NOT
24117, VOYAGER
36233, WHERE THE BOYS ARE
15674, WHITE SHADOWS IN THE SOUTH SEAS
27708, WUTHERING HEIGHTS
src, edge_attr, dst
6718, has_genre, 8379
6718, has_tags, 10045
12649, has_genre, 8379
12649, has_tags, 10045
24319, directed_by, 39336
24319, has_tags, 10045
24319, has_tags, 39336
24319, written_by, 39336
37987, has_genre, 8379
37987, has_tags, 10045
10341, has_genre, 8379
10341, has_tags, 10045
15918, has_genre, 8379
15918, has_tags, 10045
15918, release_year, 14004
17570, has_tags, 10045
17570, release_year, 14004
15771, has_tags, 10045
15771, release_year, 14004
16400, has_genre, 8379
16400, has_tags, 10045
7812, has_tags, 10045
7812, written_by, 25314
11547, has_genre, 8379
11547, has_tags, 10045
11547, has_tags, 8379
25607, has_tags, 10045
25607, release_year, 14004
25805, directed_by, 39336
25805, has_genre, 8379
25805, has_tags, 39336
24883, has_tags, 10045
24883, release_year, 14004
20693, has_genre, 8379
20693, has_tags, 10045
20693, has_tags, 8379
4709, directed_by, 39336
4709, has_tags, 10045
4709, has_tags, 39336
4709, written_by, 39336
12244, has_tags, 10045
12244, release_year, 14004
19871, has_tags, 10045
19871, written_by, 25314
20400, directed_by, 39336
20400, has_tags, 10045
20400, has_tags, 39336
20400, written_by, 39336
33504, has_tags, 10045
33504, release_year, 14004
7539, has_genre, 8379
7539, has_tags, 10045
1064, has_tags, 10045
1064, release_year, 14004
30029, directed_by, 39336
30029, has_tags, 10045
30029, has_tags, 39336
13376, has_genre, 8379
13376, release_year, 14004
2686, has_tags, 10045
2686, release_year, 14004
36083, has_genre, 8379
36083, has_tags, 10045
5237, has_genre, 8379
5237, has_tags, 10045
17576, has_genre, 8379
17576, has_tags, 10045
5338, has_genre, 8379
5338, has_tags, 10045
18184, has_genre, 8379
18184, has_tags, 10045
18184, release_year, 14004
15644, directed_by, 39336
15644, has_tags, 10045
15644, has_tags, 39336
15644, written_by, 39336
439, has_tags, 10045
439, release_year, 14004
7960, has_genre, 8379
7960, has_tags, 10045
19383, has_tags, 10045
19383, release_year, 14004
15938, has_tags, 10045
15938, release_year, 14004
8379, has_genre, 36212
2738, has_genre, 8379
2738, has_tags, 10045
2738, has_tags, 8379
30447, directed_by, 39336
30447, has_tags, 10045
30447, has_tags, 39336
36843, has_tags, 10045
36843, release_year, 14004
31624, has_genre, 8379
31624, has_tags, 10045
23429, directed_by, 39336
23429, has_genre, 8379
23429, has_tags, 10045
23429, has_tags, 39336
23429, has_tags, 8379
23429, release_year, 14004
23429, written_by, 25314
23429, written_by, 39336
18902, has_genre, 8379
18902, has_tags, 10045
36857, directed_by, 39336
36857, has_tags, 10045
36857, has_tags, 39336
23978, has_tags, 10045
23978, release_year, 14004
10812, has_genre, 8379
10812, has_tags, 10045
30311, has_tags, 10045
30311, release_year, 14004
30690, directed_by, 3700
30690, has_genre, 30463
30690, has_tags, 36358
30690, has_tags, 3700
30690, has_tags, 10045
30690, has_tags, 30463
30690, has_tags, 15533
30690, release_year, 14004
30690, starred_actors, 36358
30690, starred_actors, 7004
4182, has_genre, 8379
4182, has_tags, 10045
19329, directed_by, 3700
19329, has_genre, 30463
19329, has_tags, 36358
19329, has_tags, 3700
19329, has_tags, 15533
19329, starred_actors, 36358
19329, starred_actors, 7004
19329, written_by, 3700
404, has_tags, 10045
404, release_year, 14004
27599, has_tags, 10045
27599, release_year, 14004
35764, directed_by, 39336
35764, has_tags, 10045
35764, has_tags, 39336
35764, written_by, 39336
18274, has_tags, 10045
18274, release_year, 14004
25574, has_tags, 10045
25574, release_year, 14004
32709, has_tags, 10045
32709, written_by, 25314
14471, directed_by, 39336
14471, has_tags, 10045
14471, has_tags, 39336
14471, written_by, 39336
24789, has_genre, 8379
24789, has_tags, 10045
24117, has_genre, 36212
24117, written_by, 17096
36233, has_genre, 8379
36233, has_tags, 10045
15674, has_genre, 8379
15674, has_tags, 10045
27708, has_genre, 8379
27708, has_tags, 10045
Question: In what context are CECIL PARKER, RUDY WURLITZER, and SUMMERTIME connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"CECIL PARKER",
"RUDY WURLITZER",
"SUMMERTIME"
],
"valid_edges": [
[
"A FAREWELL TO ARMS",
"has_genre",
"ROMANCE"
],
[
"A FAREWELL TO ARMS",
"has_tags",
"BD-R"
],
[
"A LITTLE ROMANCE",
"has_genre",
"ROMANCE"
],
[
"A LITTLE ROMANCE",
"has_tags",
"BD-R"
],
[
"A PASSAGE TO INDIA",
"directed_by",
"DAVID LEAN"
],
[
"A PASSAGE TO INDIA",
"has_tags",
"BD-R"
],
[
"A PASSAGE TO INDIA",
"has_tags",
"DAVID LEAN"
],
[
"A PASSAGE TO INDIA",
"written_by",
"DAVID LEAN"
],
[
"A ROOM WITH A VIEW",
"has_genre",
"ROMANCE"
],
[
"A ROOM WITH A VIEW",
"has_tags",
"BD-R"
],
[
"ADVENTURES OF DON JUAN",
"has_genre",
"ROMANCE"
],
[
"ADVENTURES OF DON JUAN",
"has_tags",
"BD-R"
],
[
"ALL THAT HEAVEN ALLOWS",
"has_genre",
"ROMANCE"
],
[
"ALL THAT HEAVEN ALLOWS",
"has_tags",
"BD-R"
],
[
"ALL THAT HEAVEN ALLOWS",
"release_year",
"1955"
],
[
"BAD DAY AT BLACK ROCK",
"has_tags",
"BD-R"
],
[
"BAD DAY AT BLACK ROCK",
"release_year",
"1955"
],
[
"BENGAZI",
"has_tags",
"BD-R"
],
[
"BENGAZI",
"release_year",
"1955"
],
[
"BILLY ROSE'S JUMBO",
"has_genre",
"ROMANCE"
],
[
"BILLY ROSE'S JUMBO",
"has_tags",
"BD-R"
],
[
"BONJOUR TRISTESSE",
"has_tags",
"BD-R"
],
[
"BONJOUR TRISTESSE",
"written_by",
"ARTHUR LAURENTS"
],
[
"BROKEBACK MOUNTAIN",
"has_genre",
"ROMANCE"
],
[
"BROKEBACK MOUNTAIN",
"has_tags",
"BD-R"
],
[
"BROKEBACK MOUNTAIN",
"has_tags",
"ROMANCE"
],
[
"CREATURE WITH THE ATOM BRAIN",
"has_tags",
"BD-R"
],
[
"CREATURE WITH THE ATOM BRAIN",
"release_year",
"1955"
],
[
"DOCTOR ZHIVAGO",
"directed_by",
"DAVID LEAN"
],
[
"DOCTOR ZHIVAGO",
"has_genre",
"ROMANCE"
],
[
"DOCTOR ZHIVAGO",
"has_tags",
"DAVID LEAN"
],
[
"EAST OF EDEN",
"has_tags",
"BD-R"
],
[
"EAST OF EDEN",
"release_year",
"1955"
],
[
"GONE WITH THE WIND",
"has_genre",
"ROMANCE"
],
[
"GONE WITH THE WIND",
"has_tags",
"BD-R"
],
[
"GONE WITH THE WIND",
"has_tags",
"ROMANCE"
],
[
"GREAT EXPECTATIONS",
"directed_by",
"DAVID LEAN"
],
[
"GREAT EXPECTATIONS",
"has_tags",
"BD-R"
],
[
"GREAT EXPECTATIONS",
"has_tags",
"DAVID LEAN"
],
[
"GREAT EXPECTATIONS",
"written_by",
"DAVID LEAN"
],
[
"GUYS AND DOLLS",
"has_tags",
"BD-R"
],
[
"GUYS AND DOLLS",
"release_year",
"1955"
],
[
"GYPSY",
"has_tags",
"BD-R"
],
[
"GYPSY",
"written_by",
"ARTHUR LAURENTS"
],
[
"HOBSON'S CHOICE",
"directed_by",
"DAVID LEAN"
],
[
"HOBSON'S CHOICE",
"has_tags",
"BD-R"
],
[
"HOBSON'S CHOICE",
"has_tags",
"DAVID LEAN"
],
[
"HOBSON'S CHOICE",
"written_by",
"DAVID LEAN"
],
[
"IT CAME FROM BENEATH THE SEA",
"has_tags",
"BD-R"
],
[
"IT CAME FROM BENEATH THE SEA",
"release_year",
"1955"
],
[
"IVANHOE",
"has_genre",
"ROMANCE"
],
[
"IVANHOE",
"has_tags",
"BD-R"
],
[
"LAND OF THE PHARAOHS",
"has_tags",
"BD-R"
],
[
"LAND OF THE PHARAOHS",
"release_year",
"1955"
],
[
"LAWRENCE OF ARABIA",
"directed_by",
"DAVID LEAN"
],
[
"LAWRENCE OF ARABIA",
"has_tags",
"BD-R"
],
[
"LAWRENCE OF ARABIA",
"has_tags",
"DAVID LEAN"
],
[
"LOVE IS A MANY-SPLENDORED THING",
"has_genre",
"ROMANCE"
],
[
"LOVE IS A MANY-SPLENDORED THING",
"release_year",
"1955"
],
[
"MARTY",
"has_tags",
"BD-R"
],
[
"MARTY",
"release_year",
"1955"
],
[
"MIRANDA",
"has_genre",
"ROMANCE"
],
[
"MIRANDA",
"has_tags",
"BD-R"
],
[
"MURPHY'S ROMANCE",
"has_genre",
"ROMANCE"
],
[
"MURPHY'S ROMANCE",
"has_tags",
"BD-R"
],
[
"MY BRILLIANT CAREER",
"has_genre",
"ROMANCE"
],
[
"MY BRILLIANT CAREER",
"has_tags",
"BD-R"
],
[
"NINOTCHKA",
"has_genre",
"ROMANCE"
],
[
"NINOTCHKA",
"has_tags",
"BD-R"
],
[
"OKLAHOMA!",
"has_genre",
"ROMANCE"
],
[
"OKLAHOMA!",
"has_tags",
"BD-R"
],
[
"OKLAHOMA!",
"release_year",
"1955"
],
[
"OLIVER TWIST",
"directed_by",
"DAVID LEAN"
],
[
"OLIVER TWIST",
"has_tags",
"BD-R"
],
[
"OLIVER TWIST",
"has_tags",
"DAVID LEAN"
],
[
"OLIVER TWIST",
"written_by",
"DAVID LEAN"
],
[
"PICNIC",
"has_tags",
"BD-R"
],
[
"PICNIC",
"release_year",
"1955"
],
[
"QUALITY STREET",
"has_genre",
"ROMANCE"
],
[
"QUALITY STREET",
"has_tags",
"BD-R"
],
[
"REBEL WITHOUT A CAUSE",
"has_tags",
"BD-R"
],
[
"REBEL WITHOUT A CAUSE",
"release_year",
"1955"
],
[
"RIFIFI",
"has_tags",
"BD-R"
],
[
"RIFIFI",
"release_year",
"1955"
],
[
"ROMANCE",
"has_genre",
"DRAMA"
],
[
"ROMEO AND JULIET",
"has_genre",
"ROMANCE"
],
[
"ROMEO AND JULIET",
"has_tags",
"BD-R"
],
[
"ROMEO AND JULIET",
"has_tags",
"ROMANCE"
],
[
"RYAN'S DAUGHTER",
"directed_by",
"DAVID LEAN"
],
[
"RYAN'S DAUGHTER",
"has_tags",
"BD-R"
],
[
"RYAN'S DAUGHTER",
"has_tags",
"DAVID LEAN"
],
[
"SMILES OF A SUMMER NIGHT",
"has_tags",
"BD-R"
],
[
"SMILES OF A SUMMER NIGHT",
"release_year",
"1955"
],
[
"SPELLBOUND",
"has_genre",
"ROMANCE"
],
[
"SPELLBOUND",
"has_tags",
"BD-R"
],
[
"SUMMERTIME",
"directed_by",
"DAVID LEAN"
],
[
"SUMMERTIME",
"has_genre",
"ROMANCE"
],
[
"SUMMERTIME",
"has_tags",
"BD-R"
],
[
"SUMMERTIME",
"has_tags",
"DAVID LEAN"
],
[
"SUMMERTIME",
"has_tags",
"ROMANCE"
],
[
"SUMMERTIME",
"release_year",
"1955"
],
[
"SUMMERTIME",
"written_by",
"ARTHUR LAURENTS"
],
[
"SUMMERTIME",
"written_by",
"DAVID LEAN"
],
[
"TESS",
"has_genre",
"ROMANCE"
],
[
"TESS",
"has_tags",
"BD-R"
],
[
"THE BRIDGE ON THE RIVER KWAI",
"directed_by",
"DAVID LEAN"
],
[
"THE BRIDGE ON THE RIVER KWAI",
"has_tags",
"BD-R"
],
[
"THE BRIDGE ON THE RIVER KWAI",
"has_tags",
"DAVID LEAN"
],
[
"THE COBWEB",
"has_tags",
"BD-R"
],
[
"THE COBWEB",
"release_year",
"1955"
],
[
"THE CONSTANT NYMPH",
"has_genre",
"ROMANCE"
],
[
"THE CONSTANT NYMPH",
"has_tags",
"BD-R"
],
[
"THE COURT JESTER",
"has_tags",
"BD-R"
],
[
"THE COURT JESTER",
"release_year",
"1955"
],
[
"THE LADYKILLERS",
"directed_by",
"ALEXANDER MACKENDRICK"
],
[
"THE LADYKILLERS",
"has_genre",
"COMEDY"
],
[
"THE LADYKILLERS",
"has_tags",
"ALEC GUINNESS"
],
[
"THE LADYKILLERS",
"has_tags",
"ALEXANDER MACKENDRICK"
],
[
"THE LADYKILLERS",
"has_tags",
"BD-R"
],
[
"THE LADYKILLERS",
"has_tags",
"COMEDY"
],
[
"THE LADYKILLERS",
"has_tags",
"EALING STUDIOS"
],
[
"THE LADYKILLERS",
"release_year",
"1955"
],
[
"THE LADYKILLERS",
"starred_actors",
"ALEC GUINNESS"
],
[
"THE LADYKILLERS",
"starred_actors",
"CECIL PARKER"
],
[
"THE MAN IN THE IRON MASK",
"has_genre",
"ROMANCE"
],
[
"THE MAN IN THE IRON MASK",
"has_tags",
"BD-R"
],
[
"THE MAN IN THE WHITE SUIT",
"directed_by",
"ALEXANDER MACKENDRICK"
],
[
"THE MAN IN THE WHITE SUIT",
"has_genre",
"COMEDY"
],
[
"THE MAN IN THE WHITE SUIT",
"has_tags",
"ALEC GUINNESS"
],
[
"THE MAN IN THE WHITE SUIT",
"has_tags",
"ALEXANDER MACKENDRICK"
],
[
"THE MAN IN THE WHITE SUIT",
"has_tags",
"EALING STUDIOS"
],
[
"THE MAN IN THE WHITE SUIT",
"starred_actors",
"ALEC GUINNESS"
],
[
"THE MAN IN THE WHITE SUIT",
"starred_actors",
"CECIL PARKER"
],
[
"THE MAN IN THE WHITE SUIT",
"written_by",
"ALEXANDER MACKENDRICK"
],
[
"THE MAN WITH THE GOLDEN ARM",
"has_tags",
"BD-R"
],
[
"THE MAN WITH THE GOLDEN ARM",
"release_year",
"1955"
],
[
"THE NIGHT OF THE HUNTER",
"has_tags",
"BD-R"
],
[
"THE NIGHT OF THE HUNTER",
"release_year",
"1955"
],
[
"THE PASSIONATE FRIENDS",
"directed_by",
"DAVID LEAN"
],
[
"THE PASSIONATE FRIENDS",
"has_tags",
"BD-R"
],
[
"THE PASSIONATE FRIENDS",
"has_tags",
"DAVID LEAN"
],
[
"THE PASSIONATE FRIENDS",
"written_by",
"DAVID LEAN"
],
[
"THE ROSE TATTOO",
"has_tags",
"BD-R"
],
[
"THE ROSE TATTOO",
"release_year",
"1955"
],
[
"THE SEVEN YEAR ITCH",
"has_tags",
"BD-R"
],
[
"THE SEVEN YEAR ITCH",
"release_year",
"1955"
],
[
"THE WAY WE WERE",
"has_tags",
"BD-R"
],
[
"THE WAY WE WERE",
"written_by",
"ARTHUR LAURENTS"
],
[
"THIS HAPPY BREED",
"directed_by",
"DAVID LEAN"
],
[
"THIS HAPPY BREED",
"has_tags",
"BD-R"
],
[
"THIS HAPPY BREED",
"has_tags",
"DAVID LEAN"
],
[
"THIS HAPPY BREED",
"written_by",
"DAVID LEAN"
],
[
"TO HAVE AND HAVE NOT",
"has_genre",
"ROMANCE"
],
[
"TO HAVE AND HAVE NOT",
"has_tags",
"BD-R"
],
[
"VOYAGER",
"has_genre",
"DRAMA"
],
[
"VOYAGER",
"written_by",
"RUDY WURLITZER"
],
[
"WHERE THE BOYS ARE",
"has_genre",
"ROMANCE"
],
[
"WHERE THE BOYS ARE",
"has_tags",
"BD-R"
],
[
"WHITE SHADOWS IN THE SOUTH SEAS",
"has_genre",
"ROMANCE"
],
[
"WHITE SHADOWS IN THE SOUTH SEAS",
"has_tags",
"BD-R"
],
[
"WUTHERING HEIGHTS",
"has_genre",
"ROMANCE"
],
[
"WUTHERING HEIGHTS",
"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
12998, 1
34136, 12 O'CLOCK BOYS
14259, 1997
26762, 2008
1421, 2013
20458, AFTER TILLER
38351, AFTERGLOW
38638, AN APOLOGY TO ELEPHANTS
39137, AS GOOD AS IT GETS
23223, BELLE
29432, BLACKFISH
36248, BURDEN OF DREAMS
28990, CITIZEN KOCH
13734, CITY OF EMBER
9203, CUTIE AND THE BOXER
37423, DIRTY WARS
12841, DOCUMENTARY
8427, DOWNLOADED
9257, EAST SIDE STORY
15436, EPIC
16328, EVE'S BAYOU
3229, FACING ALI
19376, FINDING VIVIAN MAIER
17215, FIRE IN THE BLOOD
35533, GENERATION IRON
11565, GOOD
26282, GOOD HAIR
23477, HAWKING
12545, HOW TO LIVE FOREVER
2722, INSIDE LLEWYN DAVIS
14877, IS THE MAN WHO IS TALL HAPPY?
11781, JEANNE DUPRAU
13157, LEVEL FIVE
16179, LIFE OF A KING
8292, LINSANITY
36735, LITTLE DIETER NEEDS TO FLY
995, MIDNIGHT IN THE GARDEN OF GOOD AND EVIL
1224, MIRAGE MEN
27936, MONSTERS UNIVERSITY
29944, MY PRAIRIE HOME
19162, PANDORA'S PROMISE
827, RACING DREAMS
4123, RED OBSESSION
27935, ROSEANNA'S GRAVE
24676, SEDUCED AND ABANDONED
33332, SHED NO TEARS
39567, SOUND CITY
30357, STOKER
28141, TALES FROM THE ORGAN TRADE
10948, THE ARMSTRONG LIE
33667, THE CONGRESS
31055, THE CRASH REEL
33043, THE LONG WAY HOME
15128, THE MISSING PICTURE
23919, THE RETURN TO HOMS
15570, THE UNBELIEVERS
38742, THE UNKNOWN KNOWN
18382, TIM'S VERMEER
28819, UNDER THE SKIN
7558, WE ARE THE BEST!
19824, WHEN JEWS WERE FUNNY
38727, WHO THE HELL IS JULIETTE?
20105, WORLD WAR Z
src, edge_attr, dst
12998, has_genre, 12841
12998, release_year, 1421
34136, has_genre, 12841
34136, release_year, 1421
20458, has_genre, 12841
20458, release_year, 1421
38351, has_imdb_rating, 11565
38351, release_year, 14259
38638, has_genre, 12841
38638, release_year, 1421
39137, has_imdb_rating, 11565
39137, release_year, 14259
23223, has_imdb_rating, 11565
23223, release_year, 1421
29432, has_genre, 12841
29432, release_year, 1421
36248, has_genre, 12841
36248, has_imdb_rating, 11565
28990, has_genre, 12841
28990, release_year, 1421
13734, release_year, 26762
13734, written_by, 11781
9203, has_genre, 12841
9203, release_year, 1421
37423, has_genre, 12841
37423, release_year, 1421
8427, has_genre, 12841
8427, release_year, 1421
9257, has_genre, 12841
9257, release_year, 14259
15436, has_imdb_rating, 11565
15436, release_year, 1421
16328, has_imdb_rating, 11565
16328, release_year, 14259
3229, has_genre, 12841
3229, has_imdb_rating, 11565
19376, has_genre, 12841
19376, release_year, 1421
17215, has_genre, 12841
17215, release_year, 1421
35533, has_genre, 12841
35533, release_year, 1421
11565, has_imdb_rating, 11565
11565, release_year, 26762
26282, has_genre, 12841
26282, has_imdb_rating, 11565
26282, has_tags, 12841
23477, has_genre, 12841
23477, release_year, 1421
12545, has_genre, 12841
12545, has_imdb_rating, 11565
2722, has_imdb_rating, 11565
2722, release_year, 1421
14877, has_genre, 12841
14877, has_tags, 12841
14877, release_year, 1421
13157, has_genre, 12841
13157, release_year, 14259
16179, has_imdb_rating, 11565
16179, release_year, 1421
8292, has_genre, 12841
8292, release_year, 1421
36735, has_genre, 12841
36735, release_year, 14259
995, has_imdb_rating, 11565
995, release_year, 14259
1224, has_genre, 12841
1224, release_year, 1421
27936, has_imdb_rating, 11565
27936, release_year, 1421
29944, has_genre, 12841
29944, release_year, 1421
19162, has_genre, 12841
19162, release_year, 1421
827, has_genre, 12841
827, has_imdb_rating, 11565
4123, has_genre, 12841
4123, release_year, 1421
27935, has_imdb_rating, 11565
27935, release_year, 14259
24676, has_genre, 12841
24676, release_year, 1421
33332, has_imdb_rating, 11565
33332, release_year, 1421
39567, has_genre, 12841
39567, release_year, 1421
30357, has_imdb_rating, 11565
30357, release_year, 1421
28141, has_genre, 12841
28141, release_year, 1421
10948, has_genre, 12841
10948, release_year, 1421
33667, has_genre, 12841
33667, release_year, 1421
31055, has_genre, 12841
31055, release_year, 1421
33043, has_genre, 12841
33043, release_year, 14259
15128, has_genre, 12841
15128, release_year, 1421
23919, has_genre, 12841
23919, release_year, 1421
15570, has_genre, 12841
15570, release_year, 1421
38742, has_genre, 12841
38742, release_year, 1421
18382, has_genre, 12841
18382, has_tags, 12841
18382, release_year, 1421
28819, release_year, 14259
28819, release_year, 1421
7558, has_imdb_rating, 11565
7558, release_year, 1421
19824, has_genre, 12841
19824, release_year, 1421
38727, has_genre, 12841
38727, release_year, 14259
20105, has_imdb_rating, 11565
20105, release_year, 1421
Question: In what context are EVE'S BAYOU, JEANNE DUPRAU, and PANDORA'S PROMISE connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"EVE'S BAYOU",
"JEANNE DUPRAU",
"PANDORA'S PROMISE"
],
"valid_edges": [
[
"1",
"has_genre",
"DOCUMENTARY"
],
[
"1",
"release_year",
"2013"
],
[
"12 O'CLOCK BOYS",
"has_genre",
"DOCUMENTARY"
],
[
"12 O'CLOCK BOYS",
"release_year",
"2013"
],
[
"AFTER TILLER",
"has_genre",
"DOCUMENTARY"
],
[
"AFTER TILLER",
"release_year",
"2013"
],
[
"AFTERGLOW",
"has_imdb_rating",
"GOOD"
],
[
"AFTERGLOW",
"release_year",
"1997"
],
[
"AN APOLOGY TO ELEPHANTS",
"has_genre",
"DOCUMENTARY"
],
[
"AN APOLOGY TO ELEPHANTS",
"release_year",
"2013"
],
[
"AS GOOD AS IT GETS",
"has_imdb_rating",
"GOOD"
],
[
"AS GOOD AS IT GETS",
"release_year",
"1997"
],
[
"BELLE",
"has_imdb_rating",
"GOOD"
],
[
"BELLE",
"release_year",
"2013"
],
[
"BLACKFISH",
"has_genre",
"DOCUMENTARY"
],
[
"BLACKFISH",
"release_year",
"2013"
],
[
"BURDEN OF DREAMS",
"has_genre",
"DOCUMENTARY"
],
[
"BURDEN OF DREAMS",
"has_imdb_rating",
"GOOD"
],
[
"CITIZEN KOCH",
"has_genre",
"DOCUMENTARY"
],
[
"CITIZEN KOCH",
"release_year",
"2013"
],
[
"CITY OF EMBER",
"release_year",
"2008"
],
[
"CITY OF EMBER",
"written_by",
"JEANNE DUPRAU"
],
[
"CUTIE AND THE BOXER",
"has_genre",
"DOCUMENTARY"
],
[
"CUTIE AND THE BOXER",
"release_year",
"2013"
],
[
"DIRTY WARS",
"has_genre",
"DOCUMENTARY"
],
[
"DIRTY WARS",
"release_year",
"2013"
],
[
"DOWNLOADED",
"has_genre",
"DOCUMENTARY"
],
[
"DOWNLOADED",
"release_year",
"2013"
],
[
"EAST SIDE STORY",
"has_genre",
"DOCUMENTARY"
],
[
"EAST SIDE STORY",
"release_year",
"1997"
],
[
"EPIC",
"has_imdb_rating",
"GOOD"
],
[
"EPIC",
"release_year",
"2013"
],
[
"EVE'S BAYOU",
"has_imdb_rating",
"GOOD"
],
[
"EVE'S BAYOU",
"release_year",
"1997"
],
[
"FACING ALI",
"has_genre",
"DOCUMENTARY"
],
[
"FACING ALI",
"has_imdb_rating",
"GOOD"
],
[
"FINDING VIVIAN MAIER",
"has_genre",
"DOCUMENTARY"
],
[
"FINDING VIVIAN MAIER",
"release_year",
"2013"
],
[
"FIRE IN THE BLOOD",
"has_genre",
"DOCUMENTARY"
],
[
"FIRE IN THE BLOOD",
"release_year",
"2013"
],
[
"GENERATION IRON",
"has_genre",
"DOCUMENTARY"
],
[
"GENERATION IRON",
"release_year",
"2013"
],
[
"GOOD",
"has_imdb_rating",
"GOOD"
],
[
"GOOD",
"release_year",
"2008"
],
[
"GOOD HAIR",
"has_genre",
"DOCUMENTARY"
],
[
"GOOD HAIR",
"has_imdb_rating",
"GOOD"
],
[
"GOOD HAIR",
"has_tags",
"DOCUMENTARY"
],
[
"HAWKING",
"has_genre",
"DOCUMENTARY"
],
[
"HAWKING",
"release_year",
"2013"
],
[
"HOW TO LIVE FOREVER",
"has_genre",
"DOCUMENTARY"
],
[
"HOW TO LIVE FOREVER",
"has_imdb_rating",
"GOOD"
],
[
"INSIDE LLEWYN DAVIS",
"has_imdb_rating",
"GOOD"
],
[
"INSIDE LLEWYN DAVIS",
"release_year",
"2013"
],
[
"IS THE MAN WHO IS TALL HAPPY?",
"has_genre",
"DOCUMENTARY"
],
[
"IS THE MAN WHO IS TALL HAPPY?",
"has_tags",
"DOCUMENTARY"
],
[
"IS THE MAN WHO IS TALL HAPPY?",
"release_year",
"2013"
],
[
"LEVEL FIVE",
"has_genre",
"DOCUMENTARY"
],
[
"LEVEL FIVE",
"release_year",
"1997"
],
[
"LIFE OF A KING",
"has_imdb_rating",
"GOOD"
],
[
"LIFE OF A KING",
"release_year",
"2013"
],
[
"LINSANITY",
"has_genre",
"DOCUMENTARY"
],
[
"LINSANITY",
"release_year",
"2013"
],
[
"LITTLE DIETER NEEDS TO FLY",
"has_genre",
"DOCUMENTARY"
],
[
"LITTLE DIETER NEEDS TO FLY",
"release_year",
"1997"
],
[
"MIDNIGHT IN THE GARDEN OF GOOD AND EVIL",
"has_imdb_rating",
"GOOD"
],
[
"MIDNIGHT IN THE GARDEN OF GOOD AND EVIL",
"release_year",
"1997"
],
[
"MIRAGE MEN",
"has_genre",
"DOCUMENTARY"
],
[
"MIRAGE MEN",
"release_year",
"2013"
],
[
"MONSTERS UNIVERSITY",
"has_imdb_rating",
"GOOD"
],
[
"MONSTERS UNIVERSITY",
"release_year",
"2013"
],
[
"MY PRAIRIE HOME",
"has_genre",
"DOCUMENTARY"
],
[
"MY PRAIRIE HOME",
"release_year",
"2013"
],
[
"PANDORA'S PROMISE",
"has_genre",
"DOCUMENTARY"
],
[
"PANDORA'S PROMISE",
"release_year",
"2013"
],
[
"RACING DREAMS",
"has_genre",
"DOCUMENTARY"
],
[
"RACING DREAMS",
"has_imdb_rating",
"GOOD"
],
[
"RED OBSESSION",
"has_genre",
"DOCUMENTARY"
],
[
"RED OBSESSION",
"release_year",
"2013"
],
[
"ROSEANNA'S GRAVE",
"has_imdb_rating",
"GOOD"
],
[
"ROSEANNA'S GRAVE",
"release_year",
"1997"
],
[
"SEDUCED AND ABANDONED",
"has_genre",
"DOCUMENTARY"
],
[
"SEDUCED AND ABANDONED",
"release_year",
"2013"
],
[
"SHED NO TEARS",
"has_imdb_rating",
"GOOD"
],
[
"SHED NO TEARS",
"release_year",
"2013"
],
[
"SOUND CITY",
"has_genre",
"DOCUMENTARY"
],
[
"SOUND CITY",
"release_year",
"2013"
],
[
"STOKER",
"has_imdb_rating",
"GOOD"
],
[
"STOKER",
"release_year",
"2013"
],
[
"TALES FROM THE ORGAN TRADE",
"has_genre",
"DOCUMENTARY"
],
[
"TALES FROM THE ORGAN TRADE",
"release_year",
"2013"
],
[
"THE ARMSTRONG LIE",
"has_genre",
"DOCUMENTARY"
],
[
"THE ARMSTRONG LIE",
"release_year",
"2013"
],
[
"THE CONGRESS",
"has_genre",
"DOCUMENTARY"
],
[
"THE CONGRESS",
"release_year",
"2013"
],
[
"THE CRASH REEL",
"has_genre",
"DOCUMENTARY"
],
[
"THE CRASH REEL",
"release_year",
"2013"
],
[
"THE LONG WAY HOME",
"has_genre",
"DOCUMENTARY"
],
[
"THE LONG WAY HOME",
"release_year",
"1997"
],
[
"THE MISSING PICTURE",
"has_genre",
"DOCUMENTARY"
],
[
"THE MISSING PICTURE",
"release_year",
"2013"
],
[
"THE RETURN TO HOMS",
"has_genre",
"DOCUMENTARY"
],
[
"THE RETURN TO HOMS",
"release_year",
"2013"
],
[
"THE UNBELIEVERS",
"has_genre",
"DOCUMENTARY"
],
[
"THE UNBELIEVERS",
"release_year",
"2013"
],
[
"THE UNKNOWN KNOWN",
"has_genre",
"DOCUMENTARY"
],
[
"THE UNKNOWN KNOWN",
"release_year",
"2013"
],
[
"TIM'S VERMEER",
"has_genre",
"DOCUMENTARY"
],
[
"TIM'S VERMEER",
"has_tags",
"DOCUMENTARY"
],
[
"TIM'S VERMEER",
"release_year",
"2013"
],
[
"UNDER THE SKIN",
"release_year",
"1997"
],
[
"UNDER THE SKIN",
"release_year",
"2013"
],
[
"WE ARE THE BEST!",
"has_imdb_rating",
"GOOD"
],
[
"WE ARE THE BEST!",
"release_year",
"2013"
],
[
"WHEN JEWS WERE FUNNY",
"has_genre",
"DOCUMENTARY"
],
[
"WHEN JEWS WERE FUNNY",
"release_year",
"2013"
],
[
"WHO THE HELL IS JULIETTE?",
"has_genre",
"DOCUMENTARY"
],
[
"WHO THE HELL IS JULIETTE?",
"release_year",
"1997"
],
[
"WORLD WAR Z",
"has_imdb_rating",
"GOOD"
],
[
"WORLD WAR Z",
"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
13464, 10 THINGS I HATE ABOUT YOU
8486, 1999
5620, 200 CIGARETTES
6776, 2000
30146, A CHRISTMAS CAROL
29036, A MIDSUMMER NIGHT'S DREAM
27672, A ROOM FOR ROMEO BRASS
35603, AGNES BROWNE
21398, AMERICAN PIE
23409, AN IDEAL HUSBAND
8780, ANALYZE THIS
15458, BABY GENIUSES
32415, BEAUTIFUL PEOPLE
26205, BEING JOHN MALKOVICH
24555, BETTER THAN CHOCOLATE
32602, BIG DADDY
18375, BLAST FROM THE PAST
16932, BLUE STREAK
21121, BOWFINGER
5826, BREAKFAST OF CHAMPIONS
27223, BUT FOREVER IN MY MIND
36824, BUT I'M A CHEERLEADER
3291, CATFISH IN BLACK BEAN SAUCE
30463, COMEDY
640, COOKIE'S FORTUNE
32140, CRAZY IN ALABAMA
36492, DIAMONDS
637, DICK
17219, DO NOT DISTURB
21407, DOGMA
18908, DROP DEAD GORGEOUS
8341, DUDLEY DO-RIGHT
7568, EAST IS EAST
26193, ELECTION
17072, FAREWELL, HOME SWEET HOME
25625, FIRST DAUGHTER
34555, FLAWLESS
17478, FOOLISH
34820, FORCES OF NATURE
6623, GO
14426, GORGEOUS
11817, GUEST HOUSE PARADISO
12650, HAPPY, TEXAS
21485, HELD UP
11900, HIGH SCHOOL HIGH
29729, HIT AND RUNWAY
5870, HORROR
6546, HOT SHOTS!
39622, IDLE HANDS
36573, IN CHINA THEY EAT DOGS
25733, INSPECTOR GADGET
4912, JAKOB THE LIAR
17556, JAWBREAKER
1592, K-911
22333, KING OF COMEDY
13898, LAKE PLACID
7104, LIFE
32468, LOVE STINKS
27174, MAIN HOON NA
37138, MAN OF THE CENTURY
37867, MAN ON THE MOON
6649, MANSFIELD PARK
1454, MICKEY BLUE EYES
19598, MOLLY
16428, MUMFORD
16362, MUPPETS FROM SPACE
10000, MY NEIGHBORS THE YAMADAS
5020, MYSTERY MEN
33718, MYSTERY, ALASKA
33072, NEVER BEEN KISSED
16645, NEW WATERFORD GIRL
37812, NICE GUYS SLEEP ALONE
14898, NOTTING HILL
39920, OFFICE SPACE
27541, PARODY
35054, PLAY IT TO THE BONE
16964, PUSHING TIN
11728, REPOSSESSED
16974, RUNAWAY BRIDE
19297, SAFE SEX
4160, SCARY MOVIE
32591, SCREAM 3
15252, SCREWED IN TALLINN
32422, SEVEN GIRLFRIENDS
38502, SHE'S ALL THAT
36310, SIAM SUNSET
801, SIMON SEZ
25788, SIMPLY IRRESISTIBLE
3929, SOFT TOILET SEATS
8978, SPLENDOR
14077, SPOOF
27650, STRANGE PLANET
22847, STUART LITTLE
27511, SUPERSTAR
32984, SWEET AND LOWDOWN
905, TEACHING MRS. TINGLE
36394, THE ADVENTURES OF ELMO IN GROUCHLAND
3021, THE BACHELOR
4157, THE BEST MAN
19540, THE BIG BUS
27111, THE BIG KAHUNA
14175, THE BIG TEASE
8605, THE BREAKS
844, THE LOVE LETTER
35958, THE MATCH
16694, THE MUSE
35433, THE OTHER SISTER
10260, THE OUT-OF-TOWNERS
37200, THE STORY OF US
11235, THE SUBURBANS
38179, THE UNDERGROUND COMEDY MOVIE
26468, THE WAITING GAME
26226, THE WOOD
12626, THREE KINGS
25141, THREE TO TANGO
4723, TIFOSI
14499, TOY STORY 2
24435, TRAILER PARK BOYS
21904, TRICK
23874, TRIPPIN'
13101, TUMBLEWEEDS
31227, TWO HANDS
3569, WHY NOT ME?
1790, WILD WILD WEST
13644, YOUNG FRANKENSTEIN
src, edge_attr, dst
13464, has_genre, 30463
13464, has_tags, 30463
13464, release_year, 8486
5620, has_genre, 30463
5620, release_year, 8486
30146, has_genre, 30463
30146, release_year, 8486
29036, has_genre, 30463
29036, release_year, 8486
27672, has_genre, 30463
27672, release_year, 8486
35603, has_genre, 30463
35603, release_year, 8486
21398, has_genre, 30463
21398, has_tags, 30463
21398, release_year, 8486
23409, has_genre, 30463
23409, has_tags, 30463
23409, release_year, 8486
8780, has_genre, 30463
8780, has_tags, 30463
8780, release_year, 8486
15458, has_genre, 30463
15458, release_year, 8486
32415, has_genre, 30463
32415, release_year, 8486
26205, has_genre, 30463
26205, has_tags, 30463
26205, release_year, 8486
24555, has_genre, 30463
24555, release_year, 8486
32602, has_genre, 30463
32602, release_year, 8486
18375, has_genre, 30463
18375, release_year, 8486
16932, has_genre, 30463
16932, release_year, 8486
21121, has_genre, 30463
21121, has_tags, 30463
21121, release_year, 8486
5826, has_genre, 30463
5826, has_tags, 30463
5826, release_year, 8486
27223, has_genre, 30463
27223, release_year, 8486
36824, has_genre, 30463
36824, release_year, 8486
3291, has_genre, 30463
3291, release_year, 8486
640, has_genre, 30463
640, release_year, 8486
32140, has_genre, 30463
32140, release_year, 8486
36492, has_genre, 30463
36492, release_year, 8486
637, has_genre, 30463
637, release_year, 8486
17219, has_genre, 30463
17219, release_year, 8486
21407, has_genre, 30463
21407, has_tags, 30463
21407, release_year, 8486
18908, has_genre, 30463
18908, release_year, 8486
8341, has_genre, 30463
8341, release_year, 8486
7568, has_genre, 30463
7568, release_year, 8486
26193, has_genre, 30463
26193, release_year, 8486
17072, has_genre, 30463
17072, release_year, 8486
25625, has_genre, 30463
25625, release_year, 8486
34555, has_genre, 30463
34555, release_year, 8486
17478, has_genre, 30463
17478, release_year, 8486
34820, has_genre, 30463
34820, release_year, 8486
6623, has_genre, 30463
6623, has_tags, 30463
6623, release_year, 8486
14426, has_genre, 30463
14426, release_year, 8486
11817, has_genre, 30463
11817, release_year, 8486
12650, has_genre, 30463
12650, release_year, 8486
21485, has_genre, 30463
21485, release_year, 8486
11900, has_genre, 30463
11900, has_tags, 30463
11900, has_tags, 14077
29729, has_genre, 30463
29729, release_year, 8486
6546, has_genre, 30463
6546, has_tags, 30463
6546, has_tags, 14077
39622, has_genre, 30463
39622, release_year, 8486
36573, has_genre, 30463
36573, release_year, 8486
25733, has_genre, 30463
25733, release_year, 8486
4912, has_genre, 30463
4912, release_year, 8486
17556, has_genre, 30463
17556, release_year, 8486
1592, has_genre, 30463
1592, release_year, 8486
22333, has_genre, 30463
22333, release_year, 8486
13898, has_genre, 30463
13898, release_year, 8486
7104, has_genre, 30463
7104, has_tags, 30463
7104, release_year, 8486
32468, has_genre, 30463
32468, release_year, 8486
27174, has_genre, 30463
37138, has_genre, 30463
37138, release_year, 8486
37867, has_genre, 30463
37867, release_year, 8486
6649, has_genre, 30463
6649, release_year, 8486
1454, has_genre, 30463
1454, has_tags, 30463
1454, release_year, 8486
19598, has_genre, 30463
19598, release_year, 8486
16428, has_genre, 30463
16428, release_year, 8486
16362, has_genre, 30463
16362, release_year, 8486
10000, has_genre, 30463
10000, release_year, 8486
5020, has_genre, 30463
5020, has_tags, 30463
5020, release_year, 8486
33718, has_genre, 30463
33718, release_year, 8486
33072, has_genre, 30463
33072, release_year, 8486
16645, has_genre, 30463
16645, release_year, 8486
37812, has_genre, 30463
37812, release_year, 8486
14898, has_genre, 30463
14898, has_tags, 30463
14898, release_year, 8486
39920, has_genre, 30463
39920, has_tags, 30463
39920, release_year, 8486
35054, has_genre, 30463
35054, release_year, 8486
16964, has_genre, 30463
16964, release_year, 8486
11728, has_genre, 30463
11728, has_genre, 5870
11728, has_tags, 14077
16974, has_genre, 30463
16974, release_year, 8486
19297, has_genre, 30463
19297, release_year, 8486
4160, has_genre, 30463
4160, has_tags, 30463
4160, has_tags, 5870
4160, has_tags, 27541
4160, has_tags, 14077
4160, release_year, 6776
32591, has_genre, 5870
32591, has_tags, 14077
32591, release_year, 6776
15252, has_genre, 30463
15252, release_year, 8486
32422, has_genre, 30463
32422, release_year, 8486
38502, has_genre, 30463
38502, has_tags, 30463
38502, release_year, 8486
36310, has_genre, 30463
36310, release_year, 8486
801, has_genre, 30463
801, has_tags, 30463
801, release_year, 8486
25788, has_genre, 30463
25788, release_year, 8486
3929, has_genre, 30463
3929, release_year, 8486
8978, has_genre, 30463
8978, release_year, 8486
27650, has_genre, 30463
27650, release_year, 8486
22847, has_genre, 30463
22847, has_tags, 30463
22847, release_year, 8486
27511, has_genre, 30463
27511, release_year, 8486
32984, has_genre, 30463
32984, release_year, 8486
905, has_genre, 30463
905, release_year, 8486
36394, has_genre, 30463
36394, release_year, 8486
3021, has_genre, 30463
3021, release_year, 8486
4157, has_genre, 30463
4157, release_year, 8486
19540, has_genre, 30463
19540, has_tags, 30463
19540, has_tags, 14077
27111, has_genre, 30463
27111, release_year, 8486
14175, has_genre, 30463
14175, release_year, 8486
8605, has_genre, 30463
8605, release_year, 8486
844, has_genre, 30463
844, release_year, 8486
35958, has_genre, 30463
35958, release_year, 8486
16694, has_genre, 30463
16694, release_year, 8486
35433, has_genre, 30463
35433, release_year, 8486
10260, has_genre, 30463
10260, release_year, 8486
37200, has_genre, 30463
37200, release_year, 8486
11235, has_genre, 30463
11235, release_year, 8486
38179, has_genre, 30463
38179, release_year, 8486
26468, has_genre, 30463
26468, release_year, 8486
26226, has_genre, 30463
26226, release_year, 8486
12626, has_genre, 30463
12626, has_tags, 30463
12626, release_year, 8486
25141, has_genre, 30463
25141, release_year, 8486
4723, has_genre, 30463
4723, release_year, 8486
14499, has_genre, 30463
14499, release_year, 8486
24435, has_genre, 30463
24435, release_year, 8486
21904, has_genre, 30463
21904, release_year, 8486
23874, has_genre, 30463
23874, release_year, 8486
13101, has_genre, 30463
13101, release_year, 8486
31227, release_year, 8486
3569, has_genre, 30463
3569, release_year, 8486
1790, has_genre, 30463
1790, has_tags, 30463
1790, release_year, 8486
13644, has_genre, 30463
13644, has_tags, 30463
13644, has_tags, 27541
13644, has_tags, 14077
Question: For what reason are MAIN HOON NA, SPOOF, and TWO HANDS associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"MAIN HOON NA",
"SPOOF",
"TWO HANDS"
],
"valid_edges": [
[
"10 THINGS I HATE ABOUT YOU",
"has_genre",
"COMEDY"
],
[
"10 THINGS I HATE ABOUT YOU",
"has_tags",
"COMEDY"
],
[
"10 THINGS I HATE ABOUT YOU",
"release_year",
"1999"
],
[
"200 CIGARETTES",
"has_genre",
"COMEDY"
],
[
"200 CIGARETTES",
"release_year",
"1999"
],
[
"A CHRISTMAS CAROL",
"has_genre",
"COMEDY"
],
[
"A CHRISTMAS CAROL",
"release_year",
"1999"
],
[
"A MIDSUMMER NIGHT'S DREAM",
"has_genre",
"COMEDY"
],
[
"A MIDSUMMER NIGHT'S DREAM",
"release_year",
"1999"
],
[
"A ROOM FOR ROMEO BRASS",
"has_genre",
"COMEDY"
],
[
"A ROOM FOR ROMEO BRASS",
"release_year",
"1999"
],
[
"AGNES BROWNE",
"has_genre",
"COMEDY"
],
[
"AGNES BROWNE",
"release_year",
"1999"
],
[
"AMERICAN PIE",
"has_genre",
"COMEDY"
],
[
"AMERICAN PIE",
"has_tags",
"COMEDY"
],
[
"AMERICAN PIE",
"release_year",
"1999"
],
[
"AN IDEAL HUSBAND",
"has_genre",
"COMEDY"
],
[
"AN IDEAL HUSBAND",
"has_tags",
"COMEDY"
],
[
"AN IDEAL HUSBAND",
"release_year",
"1999"
],
[
"ANALYZE THIS",
"has_genre",
"COMEDY"
],
[
"ANALYZE THIS",
"has_tags",
"COMEDY"
],
[
"ANALYZE THIS",
"release_year",
"1999"
],
[
"BABY GENIUSES",
"has_genre",
"COMEDY"
],
[
"BABY GENIUSES",
"release_year",
"1999"
],
[
"BEAUTIFUL PEOPLE",
"has_genre",
"COMEDY"
],
[
"BEAUTIFUL PEOPLE",
"release_year",
"1999"
],
[
"BEING JOHN MALKOVICH",
"has_genre",
"COMEDY"
],
[
"BEING JOHN MALKOVICH",
"has_tags",
"COMEDY"
],
[
"BEING JOHN MALKOVICH",
"release_year",
"1999"
],
[
"BETTER THAN CHOCOLATE",
"has_genre",
"COMEDY"
],
[
"BETTER THAN CHOCOLATE",
"release_year",
"1999"
],
[
"BIG DADDY",
"has_genre",
"COMEDY"
],
[
"BIG DADDY",
"release_year",
"1999"
],
[
"BLAST FROM THE PAST",
"has_genre",
"COMEDY"
],
[
"BLAST FROM THE PAST",
"release_year",
"1999"
],
[
"BLUE STREAK",
"has_genre",
"COMEDY"
],
[
"BLUE STREAK",
"release_year",
"1999"
],
[
"BOWFINGER",
"has_genre",
"COMEDY"
],
[
"BOWFINGER",
"has_tags",
"COMEDY"
],
[
"BOWFINGER",
"release_year",
"1999"
],
[
"BREAKFAST OF CHAMPIONS",
"has_genre",
"COMEDY"
],
[
"BREAKFAST OF CHAMPIONS",
"has_tags",
"COMEDY"
],
[
"BREAKFAST OF CHAMPIONS",
"release_year",
"1999"
],
[
"BUT FOREVER IN MY MIND",
"has_genre",
"COMEDY"
],
[
"BUT FOREVER IN MY MIND",
"release_year",
"1999"
],
[
"BUT I'M A CHEERLEADER",
"has_genre",
"COMEDY"
],
[
"BUT I'M A CHEERLEADER",
"release_year",
"1999"
],
[
"CATFISH IN BLACK BEAN SAUCE",
"has_genre",
"COMEDY"
],
[
"CATFISH IN BLACK BEAN SAUCE",
"release_year",
"1999"
],
[
"COOKIE'S FORTUNE",
"has_genre",
"COMEDY"
],
[
"COOKIE'S FORTUNE",
"release_year",
"1999"
],
[
"CRAZY IN ALABAMA",
"has_genre",
"COMEDY"
],
[
"CRAZY IN ALABAMA",
"release_year",
"1999"
],
[
"DIAMONDS",
"has_genre",
"COMEDY"
],
[
"DIAMONDS",
"release_year",
"1999"
],
[
"DICK",
"has_genre",
"COMEDY"
],
[
"DICK",
"release_year",
"1999"
],
[
"DO NOT DISTURB",
"has_genre",
"COMEDY"
],
[
"DO NOT DISTURB",
"release_year",
"1999"
],
[
"DOGMA",
"has_genre",
"COMEDY"
],
[
"DOGMA",
"has_tags",
"COMEDY"
],
[
"DOGMA",
"release_year",
"1999"
],
[
"DROP DEAD GORGEOUS",
"has_genre",
"COMEDY"
],
[
"DROP DEAD GORGEOUS",
"release_year",
"1999"
],
[
"DUDLEY DO-RIGHT",
"has_genre",
"COMEDY"
],
[
"DUDLEY DO-RIGHT",
"release_year",
"1999"
],
[
"EAST IS EAST",
"has_genre",
"COMEDY"
],
[
"EAST IS EAST",
"release_year",
"1999"
],
[
"ELECTION",
"has_genre",
"COMEDY"
],
[
"ELECTION",
"release_year",
"1999"
],
[
"FAREWELL, HOME SWEET HOME",
"has_genre",
"COMEDY"
],
[
"FAREWELL, HOME SWEET HOME",
"release_year",
"1999"
],
[
"FIRST DAUGHTER",
"has_genre",
"COMEDY"
],
[
"FIRST DAUGHTER",
"release_year",
"1999"
],
[
"FLAWLESS",
"has_genre",
"COMEDY"
],
[
"FLAWLESS",
"release_year",
"1999"
],
[
"FOOLISH",
"has_genre",
"COMEDY"
],
[
"FOOLISH",
"release_year",
"1999"
],
[
"FORCES OF NATURE",
"has_genre",
"COMEDY"
],
[
"FORCES OF NATURE",
"release_year",
"1999"
],
[
"GO",
"has_genre",
"COMEDY"
],
[
"GO",
"has_tags",
"COMEDY"
],
[
"GO",
"release_year",
"1999"
],
[
"GORGEOUS",
"has_genre",
"COMEDY"
],
[
"GORGEOUS",
"release_year",
"1999"
],
[
"GUEST HOUSE PARADISO",
"has_genre",
"COMEDY"
],
[
"GUEST HOUSE PARADISO",
"release_year",
"1999"
],
[
"HAPPY, TEXAS",
"has_genre",
"COMEDY"
],
[
"HAPPY, TEXAS",
"release_year",
"1999"
],
[
"HELD UP",
"has_genre",
"COMEDY"
],
[
"HELD UP",
"release_year",
"1999"
],
[
"HIGH SCHOOL HIGH",
"has_genre",
"COMEDY"
],
[
"HIGH SCHOOL HIGH",
"has_tags",
"COMEDY"
],
[
"HIGH SCHOOL HIGH",
"has_tags",
"SPOOF"
],
[
"HIT AND RUNWAY",
"has_genre",
"COMEDY"
],
[
"HIT AND RUNWAY",
"release_year",
"1999"
],
[
"HOT SHOTS!",
"has_genre",
"COMEDY"
],
[
"HOT SHOTS!",
"has_tags",
"COMEDY"
],
[
"HOT SHOTS!",
"has_tags",
"SPOOF"
],
[
"IDLE HANDS",
"has_genre",
"COMEDY"
],
[
"IDLE HANDS",
"release_year",
"1999"
],
[
"IN CHINA THEY EAT DOGS",
"has_genre",
"COMEDY"
],
[
"IN CHINA THEY EAT DOGS",
"release_year",
"1999"
],
[
"INSPECTOR GADGET",
"has_genre",
"COMEDY"
],
[
"INSPECTOR GADGET",
"release_year",
"1999"
],
[
"JAKOB THE LIAR",
"has_genre",
"COMEDY"
],
[
"JAKOB THE LIAR",
"release_year",
"1999"
],
[
"JAWBREAKER",
"has_genre",
"COMEDY"
],
[
"JAWBREAKER",
"release_year",
"1999"
],
[
"K-911",
"has_genre",
"COMEDY"
],
[
"K-911",
"release_year",
"1999"
],
[
"KING OF COMEDY",
"has_genre",
"COMEDY"
],
[
"KING OF COMEDY",
"release_year",
"1999"
],
[
"LAKE PLACID",
"has_genre",
"COMEDY"
],
[
"LAKE PLACID",
"release_year",
"1999"
],
[
"LIFE",
"has_genre",
"COMEDY"
],
[
"LIFE",
"has_tags",
"COMEDY"
],
[
"LIFE",
"release_year",
"1999"
],
[
"LOVE STINKS",
"has_genre",
"COMEDY"
],
[
"LOVE STINKS",
"release_year",
"1999"
],
[
"MAIN HOON NA",
"has_genre",
"COMEDY"
],
[
"MAN OF THE CENTURY",
"has_genre",
"COMEDY"
],
[
"MAN OF THE CENTURY",
"release_year",
"1999"
],
[
"MAN ON THE MOON",
"has_genre",
"COMEDY"
],
[
"MAN ON THE MOON",
"release_year",
"1999"
],
[
"MANSFIELD PARK",
"has_genre",
"COMEDY"
],
[
"MANSFIELD PARK",
"release_year",
"1999"
],
[
"MICKEY BLUE EYES",
"has_genre",
"COMEDY"
],
[
"MICKEY BLUE EYES",
"has_tags",
"COMEDY"
],
[
"MICKEY BLUE EYES",
"release_year",
"1999"
],
[
"MOLLY",
"has_genre",
"COMEDY"
],
[
"MOLLY",
"release_year",
"1999"
],
[
"MUMFORD",
"has_genre",
"COMEDY"
],
[
"MUMFORD",
"release_year",
"1999"
],
[
"MUPPETS FROM SPACE",
"has_genre",
"COMEDY"
],
[
"MUPPETS FROM SPACE",
"release_year",
"1999"
],
[
"MY NEIGHBORS THE YAMADAS",
"has_genre",
"COMEDY"
],
[
"MY NEIGHBORS THE YAMADAS",
"release_year",
"1999"
],
[
"MYSTERY MEN",
"has_genre",
"COMEDY"
],
[
"MYSTERY MEN",
"has_tags",
"COMEDY"
],
[
"MYSTERY MEN",
"release_year",
"1999"
],
[
"MYSTERY, ALASKA",
"has_genre",
"COMEDY"
],
[
"MYSTERY, ALASKA",
"release_year",
"1999"
],
[
"NEVER BEEN KISSED",
"has_genre",
"COMEDY"
],
[
"NEVER BEEN KISSED",
"release_year",
"1999"
],
[
"NEW WATERFORD GIRL",
"has_genre",
"COMEDY"
],
[
"NEW WATERFORD GIRL",
"release_year",
"1999"
],
[
"NICE GUYS SLEEP ALONE",
"has_genre",
"COMEDY"
],
[
"NICE GUYS SLEEP ALONE",
"release_year",
"1999"
],
[
"NOTTING HILL",
"has_genre",
"COMEDY"
],
[
"NOTTING HILL",
"has_tags",
"COMEDY"
],
[
"NOTTING HILL",
"release_year",
"1999"
],
[
"OFFICE SPACE",
"has_genre",
"COMEDY"
],
[
"OFFICE SPACE",
"has_tags",
"COMEDY"
],
[
"OFFICE SPACE",
"release_year",
"1999"
],
[
"PLAY IT TO THE BONE",
"has_genre",
"COMEDY"
],
[
"PLAY IT TO THE BONE",
"release_year",
"1999"
],
[
"PUSHING TIN",
"has_genre",
"COMEDY"
],
[
"PUSHING TIN",
"release_year",
"1999"
],
[
"REPOSSESSED",
"has_genre",
"COMEDY"
],
[
"REPOSSESSED",
"has_genre",
"HORROR"
],
[
"REPOSSESSED",
"has_tags",
"SPOOF"
],
[
"RUNAWAY BRIDE",
"has_genre",
"COMEDY"
],
[
"RUNAWAY BRIDE",
"release_year",
"1999"
],
[
"SAFE SEX",
"has_genre",
"COMEDY"
],
[
"SAFE SEX",
"release_year",
"1999"
],
[
"SCARY MOVIE",
"has_genre",
"COMEDY"
],
[
"SCARY MOVIE",
"has_tags",
"COMEDY"
],
[
"SCARY MOVIE",
"has_tags",
"HORROR"
],
[
"SCARY MOVIE",
"has_tags",
"PARODY"
],
[
"SCARY MOVIE",
"has_tags",
"SPOOF"
],
[
"SCARY MOVIE",
"release_year",
"2000"
],
[
"SCREAM 3",
"has_genre",
"HORROR"
],
[
"SCREAM 3",
"has_tags",
"SPOOF"
],
[
"SCREAM 3",
"release_year",
"2000"
],
[
"SCREWED IN TALLINN",
"has_genre",
"COMEDY"
],
[
"SCREWED IN TALLINN",
"release_year",
"1999"
],
[
"SEVEN GIRLFRIENDS",
"has_genre",
"COMEDY"
],
[
"SEVEN GIRLFRIENDS",
"release_year",
"1999"
],
[
"SHE'S ALL THAT",
"has_genre",
"COMEDY"
],
[
"SHE'S ALL THAT",
"has_tags",
"COMEDY"
],
[
"SHE'S ALL THAT",
"release_year",
"1999"
],
[
"SIAM SUNSET",
"has_genre",
"COMEDY"
],
[
"SIAM SUNSET",
"release_year",
"1999"
],
[
"SIMON SEZ",
"has_genre",
"COMEDY"
],
[
"SIMON SEZ",
"has_tags",
"COMEDY"
],
[
"SIMON SEZ",
"release_year",
"1999"
],
[
"SIMPLY IRRESISTIBLE",
"has_genre",
"COMEDY"
],
[
"SIMPLY IRRESISTIBLE",
"release_year",
"1999"
],
[
"SOFT TOILET SEATS",
"has_genre",
"COMEDY"
],
[
"SOFT TOILET SEATS",
"release_year",
"1999"
],
[
"SPLENDOR",
"has_genre",
"COMEDY"
],
[
"SPLENDOR",
"release_year",
"1999"
],
[
"STRANGE PLANET",
"has_genre",
"COMEDY"
],
[
"STRANGE PLANET",
"release_year",
"1999"
],
[
"STUART LITTLE",
"has_genre",
"COMEDY"
],
[
"STUART LITTLE",
"has_tags",
"COMEDY"
],
[
"STUART LITTLE",
"release_year",
"1999"
],
[
"SUPERSTAR",
"has_genre",
"COMEDY"
],
[
"SUPERSTAR",
"release_year",
"1999"
],
[
"SWEET AND LOWDOWN",
"has_genre",
"COMEDY"
],
[
"SWEET AND LOWDOWN",
"release_year",
"1999"
],
[
"TEACHING MRS. TINGLE",
"has_genre",
"COMEDY"
],
[
"TEACHING MRS. TINGLE",
"release_year",
"1999"
],
[
"THE ADVENTURES OF ELMO IN GROUCHLAND",
"has_genre",
"COMEDY"
],
[
"THE ADVENTURES OF ELMO IN GROUCHLAND",
"release_year",
"1999"
],
[
"THE BACHELOR",
"has_genre",
"COMEDY"
],
[
"THE BACHELOR",
"release_year",
"1999"
],
[
"THE BEST MAN",
"has_genre",
"COMEDY"
],
[
"THE BEST MAN",
"release_year",
"1999"
],
[
"THE BIG BUS",
"has_genre",
"COMEDY"
],
[
"THE BIG BUS",
"has_tags",
"COMEDY"
],
[
"THE BIG BUS",
"has_tags",
"SPOOF"
],
[
"THE BIG KAHUNA",
"has_genre",
"COMEDY"
],
[
"THE BIG KAHUNA",
"release_year",
"1999"
],
[
"THE BIG TEASE",
"has_genre",
"COMEDY"
],
[
"THE BIG TEASE",
"release_year",
"1999"
],
[
"THE BREAKS",
"has_genre",
"COMEDY"
],
[
"THE BREAKS",
"release_year",
"1999"
],
[
"THE LOVE LETTER",
"has_genre",
"COMEDY"
],
[
"THE LOVE LETTER",
"release_year",
"1999"
],
[
"THE MATCH",
"has_genre",
"COMEDY"
],
[
"THE MATCH",
"release_year",
"1999"
],
[
"THE MUSE",
"has_genre",
"COMEDY"
],
[
"THE MUSE",
"release_year",
"1999"
],
[
"THE OTHER SISTER",
"has_genre",
"COMEDY"
],
[
"THE OTHER SISTER",
"release_year",
"1999"
],
[
"THE OUT-OF-TOWNERS",
"has_genre",
"COMEDY"
],
[
"THE OUT-OF-TOWNERS",
"release_year",
"1999"
],
[
"THE STORY OF US",
"has_genre",
"COMEDY"
],
[
"THE STORY OF US",
"release_year",
"1999"
],
[
"THE SUBURBANS",
"has_genre",
"COMEDY"
],
[
"THE SUBURBANS",
"release_year",
"1999"
],
[
"THE UNDERGROUND COMEDY MOVIE",
"has_genre",
"COMEDY"
],
[
"THE UNDERGROUND COMEDY MOVIE",
"release_year",
"1999"
],
[
"THE WAITING GAME",
"has_genre",
"COMEDY"
],
[
"THE WAITING GAME",
"release_year",
"1999"
],
[
"THE WOOD",
"has_genre",
"COMEDY"
],
[
"THE WOOD",
"release_year",
"1999"
],
[
"THREE KINGS",
"has_genre",
"COMEDY"
],
[
"THREE KINGS",
"has_tags",
"COMEDY"
],
[
"THREE KINGS",
"release_year",
"1999"
],
[
"THREE TO TANGO",
"has_genre",
"COMEDY"
],
[
"THREE TO TANGO",
"release_year",
"1999"
],
[
"TIFOSI",
"has_genre",
"COMEDY"
],
[
"TIFOSI",
"release_year",
"1999"
],
[
"TOY STORY 2",
"has_genre",
"COMEDY"
],
[
"TOY STORY 2",
"release_year",
"1999"
],
[
"TRAILER PARK BOYS",
"has_genre",
"COMEDY"
],
[
"TRAILER PARK BOYS",
"release_year",
"1999"
],
[
"TRICK",
"has_genre",
"COMEDY"
],
[
"TRICK",
"release_year",
"1999"
],
[
"TRIPPIN'",
"has_genre",
"COMEDY"
],
[
"TRIPPIN'",
"release_year",
"1999"
],
[
"TUMBLEWEEDS",
"has_genre",
"COMEDY"
],
[
"TUMBLEWEEDS",
"release_year",
"1999"
],
[
"TWO HANDS",
"release_year",
"1999"
],
[
"WHY NOT ME?",
"has_genre",
"COMEDY"
],
[
"WHY NOT ME?",
"release_year",
"1999"
],
[
"WILD WILD WEST",
"has_genre",
"COMEDY"
],
[
"WILD WILD WEST",
"has_tags",
"COMEDY"
],
[
"WILD WILD WEST",
"release_year",
"1999"
],
[
"YOUNG FRANKENSTEIN",
"has_genre",
"COMEDY"
],
[
"YOUNG FRANKENSTEIN",
"has_tags",
"COMEDY"
],
[
"YOUNG FRANKENSTEIN",
"has_tags",
"PARODY"
],
[
"YOUNG FRANKENSTEIN",
"has_tags",
"SPOOF"
]
]
}
|
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
15374, 2005
588, FRAGILE
28945, MARCH OF THE PENGUINS
1672, PENGUINS
31553, STEVE FABER
1771, WEDDING CRASHERS
src, edge_attr, dst
588, release_year, 15374
28945, has_tags, 1672
28945, release_year, 15374
1771, release_year, 15374
1771, written_by, 31553
Question: In what context are FRAGILE, PENGUINS, and STEVE FABER connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"FRAGILE",
"PENGUINS",
"STEVE FABER"
],
"valid_edges": [
[
"FRAGILE",
"release_year",
"2005"
],
[
"MARCH OF THE PENGUINS",
"has_tags",
"PENGUINS"
],
[
"MARCH OF THE PENGUINS",
"release_year",
"2005"
],
[
"WEDDING CRASHERS",
"release_year",
"2005"
],
[
"WEDDING CRASHERS",
"written_by",
"STEVE FABER"
]
]
}
|
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
15231, BARBARA CARRERA
31783, ENGLISH
36066, FANTASY
18873, GIANTS
37407, JACK THE GIANT SLAYER
29877, THE ISLAND OF DR. MOREAU
8712, THE LORD OF THE RINGS
34128, WILLIAM SQUIRE
src, edge_attr, dst
37407, has_genre, 36066
37407, has_tags, 36066
37407, has_tags, 18873
37407, in_language, 31783
29877, in_language, 31783
29877, starred_actors, 15231
8712, has_tags, 36066
8712, in_language, 31783
8712, starred_actors, 34128
Question: In what context are BARBARA CARRERA, GIANTS, and WILLIAM SQUIRE connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"BARBARA CARRERA",
"GIANTS",
"WILLIAM SQUIRE"
],
"valid_edges": [
[
"JACK THE GIANT SLAYER",
"has_genre",
"FANTASY"
],
[
"JACK THE GIANT SLAYER",
"has_tags",
"FANTASY"
],
[
"JACK THE GIANT SLAYER",
"has_tags",
"GIANTS"
],
[
"JACK THE GIANT SLAYER",
"in_language",
"ENGLISH"
],
[
"THE ISLAND OF DR. MOREAU",
"in_language",
"ENGLISH"
],
[
"THE ISLAND OF DR. MOREAU",
"starred_actors",
"BARBARA CARRERA"
],
[
"THE LORD OF THE RINGS",
"has_tags",
"FANTASY"
],
[
"THE LORD OF THE RINGS",
"in_language",
"ENGLISH"
],
[
"THE LORD OF THE RINGS",
"starred_actors",
"WILLIAM SQUIRE"
]
]
}
|
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
1421, 2013
18644, A RESURRECTION
23682, DEVON SAWA
9641, DIRTY PRETTY THINGS
28859, EXTREME OPS
32950, GEENA DAVIS
3829, HERO
4859, HISTORY
22991, OUT OF THE BLUE
8104, PIETRO GERMI
24676, SEDUCED AND ABANDONED
15043, SLACKERS
5605, STEPHEN FREARS
1808, STUART LITTLE 2
src, edge_attr, dst
18644, release_year, 1421
18644, starred_actors, 23682
9641, directed_by, 5605
9641, has_tags, 5605
9641, release_year, 35935
28859, release_year, 35935
28859, starred_actors, 23682
3829, directed_by, 5605
3829, has_genre, 4859
3829, has_tags, 5605
3829, release_year, 35935
3829, starred_actors, 32950
22991, has_genre, 4859
22991, release_year, 35935
24676, directed_by, 8104
24676, has_tags, 8104
24676, release_year, 1421
24676, written_by, 8104
15043, release_year, 35935
15043, starred_actors, 23682
1808, release_year, 35935
1808, starred_actors, 32950
Question: For what reason are DEVON SAWA, HERO, and PIETRO GERMI associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"DEVON SAWA",
"HERO",
"PIETRO GERMI"
],
"valid_edges": [
[
"A RESURRECTION",
"release_year",
"2013"
],
[
"A RESURRECTION",
"starred_actors",
"DEVON SAWA"
],
[
"DIRTY PRETTY THINGS",
"directed_by",
"STEPHEN FREARS"
],
[
"DIRTY PRETTY THINGS",
"has_tags",
"STEPHEN FREARS"
],
[
"DIRTY PRETTY THINGS",
"release_year",
"2002"
],
[
"EXTREME OPS",
"release_year",
"2002"
],
[
"EXTREME OPS",
"starred_actors",
"DEVON SAWA"
],
[
"HERO",
"directed_by",
"STEPHEN FREARS"
],
[
"HERO",
"has_genre",
"HISTORY"
],
[
"HERO",
"has_tags",
"STEPHEN FREARS"
],
[
"HERO",
"release_year",
"2002"
],
[
"HERO",
"starred_actors",
"GEENA DAVIS"
],
[
"OUT OF THE BLUE",
"has_genre",
"HISTORY"
],
[
"OUT OF THE BLUE",
"release_year",
"2002"
],
[
"SEDUCED AND ABANDONED",
"directed_by",
"PIETRO GERMI"
],
[
"SEDUCED AND ABANDONED",
"has_tags",
"PIETRO GERMI"
],
[
"SEDUCED AND ABANDONED",
"release_year",
"2013"
],
[
"SEDUCED AND ABANDONED",
"written_by",
"PIETRO GERMI"
],
[
"SLACKERS",
"release_year",
"2002"
],
[
"SLACKERS",
"starred_actors",
"DEVON SAWA"
],
[
"STUART LITTLE 2",
"release_year",
"2002"
],
[
"STUART LITTLE 2",
"starred_actors",
"GEENA DAVIS"
]
]
}
|
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
29424, 2011
26212, 3 DAYS TO KILL
39501, 30 MINUTES OR LESS
7955, 5 DAYS OF WAR
35101, ABDUCTION
39289, ACTION
1805, AMBER HEARD
22265, AMERICA OLIVO
2960, ARENA
32931, ASSASSINATION GAMES
5973, BATTLE OF LOS ANGELES
26055, BITCH SLAP
22834, BLOOD OUT
39667, BLUBBERELLA
3122, CAT RUN
35701, CATCH .44
33726, COLOMBIANA
23112, CON AIR
4283, CONAN THE BARBARIAN
38780, DETENTION
9529, DON 2
20776, DRAGON
21021, DRIVE
39870, DRIVE ANGRY
25823, ELEPHANT WHITE
25227, FACE/OFF
36699, FAST FIVE
23451, FIRE BIRDS
26921, GREEN LANTERN
9479, HANNA
19720, HAYWIRE
16208, HOBO WITH A SHOTGUN
40147, HOUSE OF THE RISING SUN
3859, I AM NUMBER FOUR
32132, KILLER ELITE
3723, KUNG FU PANDA 2
19523, LEFT BEHIND
20300, MACHETE KILLS
23468, MACHINE GUN PREACHER
24437, MANIAC
36603, NEVER BACK DOWN
30350, NEXT
1128, NICOLAS CAGE
1740, PAUL CZINNER
13383, PRIEST
12428, RAGE
4939, REAL STEEL
4551, RECOIL
15071, RED STATE
10303, SEEKING JUSTICE
24874, SETUP
14948, SINGHAM
40067, STOLEN
33900, SUCKER PUNCH
18808, THE GREEN HORNET
26115, THE HIT LIST
8839, THE MECHANIC
29353, THE RISE OF CATHERINE THE GREAT
36327, THE ROCK
20261, THE VETERAN
34977, TICKING CLOCK
22110, TRESPASS
11059, WAR OF THE DEAD
src, edge_attr, dst
26212, has_genre, 39289
26212, starred_actors, 1805
39501, has_genre, 39289
39501, release_year, 29424
7955, has_genre, 39289
7955, release_year, 29424
35101, has_genre, 39289
35101, has_tags, 39289
35101, release_year, 29424
2960, has_genre, 39289
2960, release_year, 29424
32931, has_genre, 39289
32931, release_year, 29424
5973, has_genre, 39289
5973, release_year, 29424
26055, has_genre, 39289
26055, starred_actors, 22265
22834, has_genre, 39289
22834, release_year, 29424
39667, has_genre, 39289
39667, release_year, 29424
3122, has_genre, 39289
3122, release_year, 29424
35701, has_genre, 39289
35701, release_year, 29424
33726, has_genre, 39289
33726, has_tags, 39289
33726, release_year, 29424
23112, has_genre, 39289
23112, has_tags, 39289
23112, has_tags, 1128
4283, has_genre, 39289
4283, has_tags, 39289
4283, release_year, 29424
38780, has_genre, 39289
38780, release_year, 29424
9529, has_genre, 39289
9529, release_year, 29424
20776, has_genre, 39289
20776, release_year, 29424
21021, has_tags, 39289
21021, release_year, 29424
39870, has_genre, 39289
39870, has_tags, 1805
39870, has_tags, 1128
39870, release_year, 29424
39870, starred_actors, 1805
39870, starred_actors, 1128
25823, has_genre, 39289
25823, release_year, 29424
25227, has_genre, 39289
25227, has_tags, 39289
25227, has_tags, 1128
25227, starred_actors, 1128
36699, has_genre, 39289
36699, release_year, 29424
23451, has_genre, 39289
23451, has_tags, 1128
23451, starred_actors, 1128
26921, has_genre, 39289
26921, release_year, 29424
9479, has_genre, 39289
9479, has_tags, 39289
9479, release_year, 29424
19720, has_genre, 39289
19720, has_tags, 39289
19720, release_year, 29424
16208, has_genre, 39289
16208, release_year, 29424
40147, has_genre, 39289
40147, release_year, 29424
3859, has_genre, 39289
3859, has_tags, 39289
3859, release_year, 29424
32132, has_genre, 39289
32132, has_tags, 39289
32132, release_year, 29424
3723, has_genre, 39289
3723, release_year, 29424
19523, has_genre, 39289
19523, has_tags, 1128
19523, starred_actors, 1128
20300, has_genre, 39289
20300, starred_actors, 1805
23468, has_genre, 39289
23468, release_year, 29424
24437, release_year, 36522
24437, starred_actors, 22265
36603, has_genre, 39289
36603, starred_actors, 1805
30350, has_genre, 39289
30350, has_tags, 39289
30350, has_tags, 1128
30350, starred_actors, 1128
13383, has_genre, 39289
13383, release_year, 29424
12428, has_genre, 39289
12428, starred_actors, 1128
4939, has_genre, 39289
4939, release_year, 29424
4551, has_genre, 39289
4551, release_year, 29424
15071, has_genre, 39289
15071, release_year, 29424
10303, has_genre, 39289
10303, has_tags, 39289
10303, has_tags, 1128
10303, release_year, 29424
10303, starred_actors, 1128
24874, has_genre, 39289
24874, release_year, 29424
14948, has_genre, 39289
14948, has_tags, 39289
14948, release_year, 29424
40067, has_genre, 39289
40067, has_tags, 1128
40067, starred_actors, 1128
33900, has_genre, 39289
33900, release_year, 29424
18808, has_genre, 39289
18808, has_tags, 39289
18808, release_year, 29424
26115, has_genre, 39289
26115, release_year, 29424
8839, has_genre, 39289
8839, has_tags, 39289
8839, release_year, 29424
29353, directed_by, 1740
29353, release_year, 36522
36327, has_genre, 39289
36327, has_tags, 39289
36327, has_tags, 1128
36327, starred_actors, 1128
20261, has_genre, 39289
20261, release_year, 29424
34977, has_genre, 39289
34977, release_year, 29424
22110, has_genre, 39289
22110, has_tags, 1128
22110, release_year, 29424
22110, starred_actors, 1128
11059, has_genre, 39289
11059, release_year, 29424
Question: For what reason are AMERICA OLIVO, DRIVE ANGRY, and PAUL CZINNER associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"AMERICA OLIVO",
"DRIVE ANGRY",
"PAUL CZINNER"
],
"valid_edges": [
[
"3 DAYS TO KILL",
"has_genre",
"ACTION"
],
[
"3 DAYS TO KILL",
"starred_actors",
"AMBER HEARD"
],
[
"30 MINUTES OR LESS",
"has_genre",
"ACTION"
],
[
"30 MINUTES OR LESS",
"release_year",
"2011"
],
[
"5 DAYS OF WAR",
"has_genre",
"ACTION"
],
[
"5 DAYS OF WAR",
"release_year",
"2011"
],
[
"ABDUCTION",
"has_genre",
"ACTION"
],
[
"ABDUCTION",
"has_tags",
"ACTION"
],
[
"ABDUCTION",
"release_year",
"2011"
],
[
"ARENA",
"has_genre",
"ACTION"
],
[
"ARENA",
"release_year",
"2011"
],
[
"ASSASSINATION GAMES",
"has_genre",
"ACTION"
],
[
"ASSASSINATION GAMES",
"release_year",
"2011"
],
[
"BATTLE OF LOS ANGELES",
"has_genre",
"ACTION"
],
[
"BATTLE OF LOS ANGELES",
"release_year",
"2011"
],
[
"BITCH SLAP",
"has_genre",
"ACTION"
],
[
"BITCH SLAP",
"starred_actors",
"AMERICA OLIVO"
],
[
"BLOOD OUT",
"has_genre",
"ACTION"
],
[
"BLOOD OUT",
"release_year",
"2011"
],
[
"BLUBBERELLA",
"has_genre",
"ACTION"
],
[
"BLUBBERELLA",
"release_year",
"2011"
],
[
"CAT RUN",
"has_genre",
"ACTION"
],
[
"CAT RUN",
"release_year",
"2011"
],
[
"CATCH .44",
"has_genre",
"ACTION"
],
[
"CATCH .44",
"release_year",
"2011"
],
[
"COLOMBIANA",
"has_genre",
"ACTION"
],
[
"COLOMBIANA",
"has_tags",
"ACTION"
],
[
"COLOMBIANA",
"release_year",
"2011"
],
[
"CON AIR",
"has_genre",
"ACTION"
],
[
"CON AIR",
"has_tags",
"ACTION"
],
[
"CON AIR",
"has_tags",
"NICOLAS CAGE"
],
[
"CONAN THE BARBARIAN",
"has_genre",
"ACTION"
],
[
"CONAN THE BARBARIAN",
"has_tags",
"ACTION"
],
[
"CONAN THE BARBARIAN",
"release_year",
"2011"
],
[
"DETENTION",
"has_genre",
"ACTION"
],
[
"DETENTION",
"release_year",
"2011"
],
[
"DON 2",
"has_genre",
"ACTION"
],
[
"DON 2",
"release_year",
"2011"
],
[
"DRAGON",
"has_genre",
"ACTION"
],
[
"DRAGON",
"release_year",
"2011"
],
[
"DRIVE",
"has_tags",
"ACTION"
],
[
"DRIVE",
"release_year",
"2011"
],
[
"DRIVE ANGRY",
"has_genre",
"ACTION"
],
[
"DRIVE ANGRY",
"has_tags",
"AMBER HEARD"
],
[
"DRIVE ANGRY",
"has_tags",
"NICOLAS CAGE"
],
[
"DRIVE ANGRY",
"release_year",
"2011"
],
[
"DRIVE ANGRY",
"starred_actors",
"AMBER HEARD"
],
[
"DRIVE ANGRY",
"starred_actors",
"NICOLAS CAGE"
],
[
"ELEPHANT WHITE",
"has_genre",
"ACTION"
],
[
"ELEPHANT WHITE",
"release_year",
"2011"
],
[
"FACE/OFF",
"has_genre",
"ACTION"
],
[
"FACE/OFF",
"has_tags",
"ACTION"
],
[
"FACE/OFF",
"has_tags",
"NICOLAS CAGE"
],
[
"FACE/OFF",
"starred_actors",
"NICOLAS CAGE"
],
[
"FAST FIVE",
"has_genre",
"ACTION"
],
[
"FAST FIVE",
"release_year",
"2011"
],
[
"FIRE BIRDS",
"has_genre",
"ACTION"
],
[
"FIRE BIRDS",
"has_tags",
"NICOLAS CAGE"
],
[
"FIRE BIRDS",
"starred_actors",
"NICOLAS CAGE"
],
[
"GREEN LANTERN",
"has_genre",
"ACTION"
],
[
"GREEN LANTERN",
"release_year",
"2011"
],
[
"HANNA",
"has_genre",
"ACTION"
],
[
"HANNA",
"has_tags",
"ACTION"
],
[
"HANNA",
"release_year",
"2011"
],
[
"HAYWIRE",
"has_genre",
"ACTION"
],
[
"HAYWIRE",
"has_tags",
"ACTION"
],
[
"HAYWIRE",
"release_year",
"2011"
],
[
"HOBO WITH A SHOTGUN",
"has_genre",
"ACTION"
],
[
"HOBO WITH A SHOTGUN",
"release_year",
"2011"
],
[
"HOUSE OF THE RISING SUN",
"has_genre",
"ACTION"
],
[
"HOUSE OF THE RISING SUN",
"release_year",
"2011"
],
[
"I AM NUMBER FOUR",
"has_genre",
"ACTION"
],
[
"I AM NUMBER FOUR",
"has_tags",
"ACTION"
],
[
"I AM NUMBER FOUR",
"release_year",
"2011"
],
[
"KILLER ELITE",
"has_genre",
"ACTION"
],
[
"KILLER ELITE",
"has_tags",
"ACTION"
],
[
"KILLER ELITE",
"release_year",
"2011"
],
[
"KUNG FU PANDA 2",
"has_genre",
"ACTION"
],
[
"KUNG FU PANDA 2",
"release_year",
"2011"
],
[
"LEFT BEHIND",
"has_genre",
"ACTION"
],
[
"LEFT BEHIND",
"has_tags",
"NICOLAS CAGE"
],
[
"LEFT BEHIND",
"starred_actors",
"NICOLAS CAGE"
],
[
"MACHETE KILLS",
"has_genre",
"ACTION"
],
[
"MACHETE KILLS",
"starred_actors",
"AMBER HEARD"
],
[
"MACHINE GUN PREACHER",
"has_genre",
"ACTION"
],
[
"MACHINE GUN PREACHER",
"release_year",
"2011"
],
[
"MANIAC",
"release_year",
"1934"
],
[
"MANIAC",
"starred_actors",
"AMERICA OLIVO"
],
[
"NEVER BACK DOWN",
"has_genre",
"ACTION"
],
[
"NEVER BACK DOWN",
"starred_actors",
"AMBER HEARD"
],
[
"NEXT",
"has_genre",
"ACTION"
],
[
"NEXT",
"has_tags",
"ACTION"
],
[
"NEXT",
"has_tags",
"NICOLAS CAGE"
],
[
"NEXT",
"starred_actors",
"NICOLAS CAGE"
],
[
"PRIEST",
"has_genre",
"ACTION"
],
[
"PRIEST",
"release_year",
"2011"
],
[
"RAGE",
"has_genre",
"ACTION"
],
[
"RAGE",
"starred_actors",
"NICOLAS CAGE"
],
[
"REAL STEEL",
"has_genre",
"ACTION"
],
[
"REAL STEEL",
"release_year",
"2011"
],
[
"RECOIL",
"has_genre",
"ACTION"
],
[
"RECOIL",
"release_year",
"2011"
],
[
"RED STATE",
"has_genre",
"ACTION"
],
[
"RED STATE",
"release_year",
"2011"
],
[
"SEEKING JUSTICE",
"has_genre",
"ACTION"
],
[
"SEEKING JUSTICE",
"has_tags",
"ACTION"
],
[
"SEEKING JUSTICE",
"has_tags",
"NICOLAS CAGE"
],
[
"SEEKING JUSTICE",
"release_year",
"2011"
],
[
"SEEKING JUSTICE",
"starred_actors",
"NICOLAS CAGE"
],
[
"SETUP",
"has_genre",
"ACTION"
],
[
"SETUP",
"release_year",
"2011"
],
[
"SINGHAM",
"has_genre",
"ACTION"
],
[
"SINGHAM",
"has_tags",
"ACTION"
],
[
"SINGHAM",
"release_year",
"2011"
],
[
"STOLEN",
"has_genre",
"ACTION"
],
[
"STOLEN",
"has_tags",
"NICOLAS CAGE"
],
[
"STOLEN",
"starred_actors",
"NICOLAS CAGE"
],
[
"SUCKER PUNCH",
"has_genre",
"ACTION"
],
[
"SUCKER PUNCH",
"release_year",
"2011"
],
[
"THE GREEN HORNET",
"has_genre",
"ACTION"
],
[
"THE GREEN HORNET",
"has_tags",
"ACTION"
],
[
"THE GREEN HORNET",
"release_year",
"2011"
],
[
"THE HIT LIST",
"has_genre",
"ACTION"
],
[
"THE HIT LIST",
"release_year",
"2011"
],
[
"THE MECHANIC",
"has_genre",
"ACTION"
],
[
"THE MECHANIC",
"has_tags",
"ACTION"
],
[
"THE MECHANIC",
"release_year",
"2011"
],
[
"THE RISE OF CATHERINE THE GREAT",
"directed_by",
"PAUL CZINNER"
],
[
"THE RISE OF CATHERINE THE GREAT",
"release_year",
"1934"
],
[
"THE ROCK",
"has_genre",
"ACTION"
],
[
"THE ROCK",
"has_tags",
"ACTION"
],
[
"THE ROCK",
"has_tags",
"NICOLAS CAGE"
],
[
"THE ROCK",
"starred_actors",
"NICOLAS CAGE"
],
[
"THE VETERAN",
"has_genre",
"ACTION"
],
[
"THE VETERAN",
"release_year",
"2011"
],
[
"TICKING CLOCK",
"has_genre",
"ACTION"
],
[
"TICKING CLOCK",
"release_year",
"2011"
],
[
"TRESPASS",
"has_genre",
"ACTION"
],
[
"TRESPASS",
"has_tags",
"NICOLAS CAGE"
],
[
"TRESPASS",
"release_year",
"2011"
],
[
"TRESPASS",
"starred_actors",
"NICOLAS CAGE"
],
[
"WAR OF THE DEAD",
"has_genre",
"ACTION"
],
[
"WAR OF THE DEAD",
"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
10825, 1973
35798, 2010
6718, A FAREWELL TO ARMS
12649, A LITTLE ROMANCE
37987, A ROOM WITH A VIEW
10341, ADVENTURES OF DON JUAN
15918, ALL THAT HEAVEN ALLOWS
25395, AMERICAN GRAFFITI
10045, BD-R
16400, BILLY ROSE'S JUMBO
11547, BROKEBACK MOUNTAIN
34935, DILLINGER
27950, ENTER THE DRAGON
20693, GONE WITH THE WIND
21646, HIGH AND DIZZY
5617, HOT TUB TIME MACHINE
9381, I'M HERE
36299, IT'S THE GREAT PUMPKIN, CHARLIE BROWN
7539, IVANHOE
36621, JEREMY
33561, MEAN STREETS
36083, MIRANDA
5237, MURPHY'S ROMANCE
17576, MY BRILLIANT CAREER
5338, NINOTCHKA
18184, OKLAHOMA!
7960, QUALITY STREET
680, ROB CORDDRY
8379, ROMANCE
2738, ROMEO AND JULIET
36899, SHORT
31624, SPELLBOUND
20671, SPIDER
23429, SUMMERTIME
18902, TESS
10812, THE CONSTANT NYMPH
38676, THE CREEPING FLESH
27885, THE KILLERS
8623, THE LEGEND OF HELL HOUSE
4182, THE MAN IN THE IRON MASK
20747, THE PAPER CHASE
28879, THE PILGRIM
39278, THE STING
7816, THE THREE MUSKETEERS
32709, THE WAY WE WERE
22751, THE WICKER MAN
3594, THEATRE OF BLOOD
24789, TO HAVE AND HAVE NOT
6724, TOM SAWYER
8363, TOUKI BOUKI
14868, WESTWORLD
36233, WHERE THE BOYS ARE
15674, WHITE SHADOWS IN THE SOUTH SEAS
27708, WUTHERING HEIGHTS
src, edge_attr, dst
35798, has_tags, 10045
6718, has_genre, 8379
6718, has_tags, 10045
12649, has_genre, 8379
12649, has_tags, 10045
37987, has_genre, 8379
37987, has_tags, 10045
10341, has_genre, 8379
10341, has_tags, 10045
15918, has_genre, 8379
15918, has_tags, 10045
25395, has_tags, 10045
25395, release_year, 10825
16400, has_genre, 8379
16400, has_tags, 10045
11547, has_genre, 8379
11547, has_tags, 10045
11547, has_tags, 8379
34935, has_tags, 10045
34935, release_year, 10825
27950, has_tags, 10045
27950, release_year, 10825
20693, has_genre, 8379
20693, has_tags, 10045
20693, has_tags, 8379
21646, has_genre, 36899
21646, has_tags, 10045
5617, release_year, 35798
5617, starred_actors, 680
9381, has_genre, 8379
9381, has_genre, 36899
36299, has_tags, 10045
36299, has_tags, 36899
7539, has_genre, 8379
7539, has_tags, 10045
36621, has_genre, 8379
36621, release_year, 10825
33561, has_tags, 10045
33561, release_year, 10825
36083, has_genre, 8379
36083, has_tags, 10045
5237, has_genre, 8379
5237, has_tags, 10045
17576, has_genre, 8379
17576, has_tags, 10045
5338, has_genre, 8379
5338, has_tags, 10045
18184, has_genre, 8379
18184, has_tags, 10045
7960, has_genre, 8379
7960, has_tags, 10045
2738, has_genre, 8379
2738, has_tags, 10045
2738, has_tags, 8379
31624, has_genre, 8379
31624, has_tags, 10045
20671, has_genre, 36899
20671, has_tags, 10045
23429, has_genre, 8379
23429, has_tags, 10045
23429, has_tags, 8379
18902, has_genre, 8379
18902, has_tags, 10045
10812, has_genre, 8379
10812, has_tags, 10045
38676, has_tags, 10045
38676, release_year, 10825
27885, has_genre, 36899
27885, has_tags, 10045
8623, has_tags, 10045
8623, release_year, 10825
4182, has_genre, 8379
4182, has_tags, 10045
20747, has_tags, 10045
20747, release_year, 10825
28879, has_genre, 36899
28879, has_tags, 10045
39278, has_tags, 10045
39278, release_year, 10825
7816, has_tags, 10045
7816, release_year, 10825
32709, has_tags, 10045
32709, release_year, 10825
22751, has_tags, 10045
22751, release_year, 10825
3594, has_tags, 10045
3594, release_year, 10825
24789, has_genre, 8379
24789, has_tags, 10045
6724, has_tags, 10045
6724, release_year, 10825
8363, has_tags, 10045
8363, release_year, 10825
14868, has_tags, 10045
14868, release_year, 10825
36233, has_genre, 8379
36233, has_tags, 10045
15674, has_genre, 8379
15674, has_tags, 10045
27708, has_genre, 8379
27708, has_tags, 10045
Question: In what context are HIGH AND DIZZY, JEREMY, and ROB CORDDRY connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"HIGH AND DIZZY",
"JEREMY",
"ROB CORDDRY"
],
"valid_edges": [
[
"2010",
"has_tags",
"BD-R"
],
[
"A FAREWELL TO ARMS",
"has_genre",
"ROMANCE"
],
[
"A FAREWELL TO ARMS",
"has_tags",
"BD-R"
],
[
"A LITTLE ROMANCE",
"has_genre",
"ROMANCE"
],
[
"A LITTLE ROMANCE",
"has_tags",
"BD-R"
],
[
"A ROOM WITH A VIEW",
"has_genre",
"ROMANCE"
],
[
"A ROOM WITH A VIEW",
"has_tags",
"BD-R"
],
[
"ADVENTURES OF DON JUAN",
"has_genre",
"ROMANCE"
],
[
"ADVENTURES OF DON JUAN",
"has_tags",
"BD-R"
],
[
"ALL THAT HEAVEN ALLOWS",
"has_genre",
"ROMANCE"
],
[
"ALL THAT HEAVEN ALLOWS",
"has_tags",
"BD-R"
],
[
"AMERICAN GRAFFITI",
"has_tags",
"BD-R"
],
[
"AMERICAN GRAFFITI",
"release_year",
"1973"
],
[
"BILLY ROSE'S JUMBO",
"has_genre",
"ROMANCE"
],
[
"BILLY ROSE'S JUMBO",
"has_tags",
"BD-R"
],
[
"BROKEBACK MOUNTAIN",
"has_genre",
"ROMANCE"
],
[
"BROKEBACK MOUNTAIN",
"has_tags",
"BD-R"
],
[
"BROKEBACK MOUNTAIN",
"has_tags",
"ROMANCE"
],
[
"DILLINGER",
"has_tags",
"BD-R"
],
[
"DILLINGER",
"release_year",
"1973"
],
[
"ENTER THE DRAGON",
"has_tags",
"BD-R"
],
[
"ENTER THE DRAGON",
"release_year",
"1973"
],
[
"GONE WITH THE WIND",
"has_genre",
"ROMANCE"
],
[
"GONE WITH THE WIND",
"has_tags",
"BD-R"
],
[
"GONE WITH THE WIND",
"has_tags",
"ROMANCE"
],
[
"HIGH AND DIZZY",
"has_genre",
"SHORT"
],
[
"HIGH AND DIZZY",
"has_tags",
"BD-R"
],
[
"HOT TUB TIME MACHINE",
"release_year",
"2010"
],
[
"HOT TUB TIME MACHINE",
"starred_actors",
"ROB CORDDRY"
],
[
"I'M HERE",
"has_genre",
"ROMANCE"
],
[
"I'M HERE",
"has_genre",
"SHORT"
],
[
"IT'S THE GREAT PUMPKIN, CHARLIE BROWN",
"has_tags",
"BD-R"
],
[
"IT'S THE GREAT PUMPKIN, CHARLIE BROWN",
"has_tags",
"SHORT"
],
[
"IVANHOE",
"has_genre",
"ROMANCE"
],
[
"IVANHOE",
"has_tags",
"BD-R"
],
[
"JEREMY",
"has_genre",
"ROMANCE"
],
[
"JEREMY",
"release_year",
"1973"
],
[
"MEAN STREETS",
"has_tags",
"BD-R"
],
[
"MEAN STREETS",
"release_year",
"1973"
],
[
"MIRANDA",
"has_genre",
"ROMANCE"
],
[
"MIRANDA",
"has_tags",
"BD-R"
],
[
"MURPHY'S ROMANCE",
"has_genre",
"ROMANCE"
],
[
"MURPHY'S ROMANCE",
"has_tags",
"BD-R"
],
[
"MY BRILLIANT CAREER",
"has_genre",
"ROMANCE"
],
[
"MY BRILLIANT CAREER",
"has_tags",
"BD-R"
],
[
"NINOTCHKA",
"has_genre",
"ROMANCE"
],
[
"NINOTCHKA",
"has_tags",
"BD-R"
],
[
"OKLAHOMA!",
"has_genre",
"ROMANCE"
],
[
"OKLAHOMA!",
"has_tags",
"BD-R"
],
[
"QUALITY STREET",
"has_genre",
"ROMANCE"
],
[
"QUALITY STREET",
"has_tags",
"BD-R"
],
[
"ROMEO AND JULIET",
"has_genre",
"ROMANCE"
],
[
"ROMEO AND JULIET",
"has_tags",
"BD-R"
],
[
"ROMEO AND JULIET",
"has_tags",
"ROMANCE"
],
[
"SPELLBOUND",
"has_genre",
"ROMANCE"
],
[
"SPELLBOUND",
"has_tags",
"BD-R"
],
[
"SPIDER",
"has_genre",
"SHORT"
],
[
"SPIDER",
"has_tags",
"BD-R"
],
[
"SUMMERTIME",
"has_genre",
"ROMANCE"
],
[
"SUMMERTIME",
"has_tags",
"BD-R"
],
[
"SUMMERTIME",
"has_tags",
"ROMANCE"
],
[
"TESS",
"has_genre",
"ROMANCE"
],
[
"TESS",
"has_tags",
"BD-R"
],
[
"THE CONSTANT NYMPH",
"has_genre",
"ROMANCE"
],
[
"THE CONSTANT NYMPH",
"has_tags",
"BD-R"
],
[
"THE CREEPING FLESH",
"has_tags",
"BD-R"
],
[
"THE CREEPING FLESH",
"release_year",
"1973"
],
[
"THE KILLERS",
"has_genre",
"SHORT"
],
[
"THE KILLERS",
"has_tags",
"BD-R"
],
[
"THE LEGEND OF HELL HOUSE",
"has_tags",
"BD-R"
],
[
"THE LEGEND OF HELL HOUSE",
"release_year",
"1973"
],
[
"THE MAN IN THE IRON MASK",
"has_genre",
"ROMANCE"
],
[
"THE MAN IN THE IRON MASK",
"has_tags",
"BD-R"
],
[
"THE PAPER CHASE",
"has_tags",
"BD-R"
],
[
"THE PAPER CHASE",
"release_year",
"1973"
],
[
"THE PILGRIM",
"has_genre",
"SHORT"
],
[
"THE PILGRIM",
"has_tags",
"BD-R"
],
[
"THE STING",
"has_tags",
"BD-R"
],
[
"THE STING",
"release_year",
"1973"
],
[
"THE THREE MUSKETEERS",
"has_tags",
"BD-R"
],
[
"THE THREE MUSKETEERS",
"release_year",
"1973"
],
[
"THE WAY WE WERE",
"has_tags",
"BD-R"
],
[
"THE WAY WE WERE",
"release_year",
"1973"
],
[
"THE WICKER MAN",
"has_tags",
"BD-R"
],
[
"THE WICKER MAN",
"release_year",
"1973"
],
[
"THEATRE OF BLOOD",
"has_tags",
"BD-R"
],
[
"THEATRE OF BLOOD",
"release_year",
"1973"
],
[
"TO HAVE AND HAVE NOT",
"has_genre",
"ROMANCE"
],
[
"TO HAVE AND HAVE NOT",
"has_tags",
"BD-R"
],
[
"TOM SAWYER",
"has_tags",
"BD-R"
],
[
"TOM SAWYER",
"release_year",
"1973"
],
[
"TOUKI BOUKI",
"has_tags",
"BD-R"
],
[
"TOUKI BOUKI",
"release_year",
"1973"
],
[
"WESTWORLD",
"has_tags",
"BD-R"
],
[
"WESTWORLD",
"release_year",
"1973"
],
[
"WHERE THE BOYS ARE",
"has_genre",
"ROMANCE"
],
[
"WHERE THE BOYS ARE",
"has_tags",
"BD-R"
],
[
"WHITE SHADOWS IN THE SOUTH SEAS",
"has_genre",
"ROMANCE"
],
[
"WHITE SHADOWS IN THE SOUTH SEAS",
"has_tags",
"BD-R"
],
[
"WUTHERING HEIGHTS",
"has_genre",
"ROMANCE"
],
[
"WUTHERING HEIGHTS",
"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
11, 1940
27261, 2009
29424, 2011
39964, 247°F
39452, 96 MINUTES
35101, ABDUCTION
22786, ANONYMOUS
17883, BARRY LEVINSON
10045, BD-R
7724, BLITZ
11985, CEDRIC HARDWICKE
38751, CHRISTOPHER LEE
12226, CONTAGION
25607, CREATURE WITH THE ATOM BRAIN
6358, CURT SIODMAK
13659, DISCLOSURE
3154, DONOVAN'S BRAIN
7392, DREAM HOUSE
2232, DUSTIN HOFFMAN
3786, ENTER NOWHERE
1329, ENVY
16678, FALSE TRAIL
11565, GOOD
21763, GOOD MORNING, VIETNAM
9479, HANNA
19720, HAYWIRE
10975, HEADHUNTERS
580, HELLGATE
3595, HILARY SWANK
3436, IN TIME
13825, INSOMNIA
30511, INVISIBLE AGENT
3743, JUDAS KISS
32132, KILLER ELITE
7647, LIMITLESS
29754, MARTHA MARCY MAY MARLENE
28910, MICHAEL CRICHTON
13103, NO REST FOR THE WICKED
1309, OCCUPANT
31160, PAGE EIGHT
37623, RAIN MAN
25241, RETREAT
9216, ROSEWOOD LANE
10303, SEEKING JUSTICE
34723, SLEEPLESS NIGHT
30851, SPHERE
16127, STRAW DOGS
19102, SUPER 8
35243, TAKE SHELTER
16231, TARZAN'S MAGIC FOUNTAIN
21402, THE ADJUSTMENT BUREAU
16069, THE APE
10171, THE CALLER
7240, THE GIRL WITH THE DRAGON TATTOO
13340, THE GOOD DOCTOR
15989, THE GREY
8273, THE HIDDEN FACE
31667, THE HOLDING
23688, THE HUNTER
27604, THE INTERNECINE PROJECT
26776, THE INVISIBLE MAN RETURNS
5521, THE LEDGE
20779, THE LINCOLN LAWYER
8839, THE MECHANIC
29250, THE MONITOR
10049, THE MONK
28084, THE RESIDENT
18953, THE RITE
10053, THE RIVER MURDERS
11596, THE ROOMMATE
4957, THE SKIN I LIVE IN
21676, THE SON OF NO ONE
15340, THE SPEED OF THOUGHT
22751, THE WICKER MAN
24811, THRILLER
22110, TRESPASS
36954, TWIXT
36262, UNFAITHFULLY YOURS
10133, UNKNOWN
22214, WAR
src, edge_attr, dst
39964, has_genre, 24811
39964, release_year, 29424
39452, has_genre, 24811
39452, release_year, 29424
35101, has_genre, 24811
35101, release_year, 29424
22786, has_genre, 24811
22786, release_year, 29424
7724, has_genre, 24811
7724, release_year, 29424
12226, has_genre, 24811
12226, has_tags, 24811
12226, release_year, 29424
25607, has_tags, 10045
25607, written_by, 6358
13659, directed_by, 17883
13659, has_genre, 24811
13659, has_tags, 28910
13659, written_by, 28910
3154, has_tags, 10045
3154, written_by, 6358
7392, has_genre, 24811
7392, release_year, 29424
3786, has_genre, 24811
3786, release_year, 29424
1329, directed_by, 17883
1329, release_year, 27261
16678, has_genre, 24811
16678, release_year, 29424
21763, directed_by, 17883
21763, has_genre, 22214
21763, has_imdb_rating, 11565
21763, has_tags, 17883
21763, has_tags, 10045
21763, has_tags, 22214
9479, has_genre, 24811
9479, has_tags, 24811
9479, release_year, 29424
19720, has_genre, 24811
19720, release_year, 29424
10975, has_genre, 24811
10975, release_year, 29424
580, has_genre, 24811
580, release_year, 29424
3436, has_genre, 24811
3436, has_tags, 24811
3436, release_year, 29424
13825, has_genre, 24811
13825, has_tags, 3595
13825, starred_actors, 3595
30511, has_genre, 22214
30511, starred_actors, 11985
30511, written_by, 6358
3743, has_genre, 24811
3743, release_year, 29424
32132, has_genre, 24811
32132, release_year, 29424
7647, has_genre, 24811
7647, release_year, 29424
29754, has_genre, 24811
29754, has_tags, 24811
29754, release_year, 29424
13103, has_genre, 24811
13103, has_tags, 24811
13103, release_year, 29424
1309, has_genre, 24811
1309, release_year, 29424
31160, has_genre, 24811
31160, release_year, 29424
37623, directed_by, 17883
37623, has_imdb_rating, 11565
37623, has_tags, 17883
37623, has_tags, 2232
37623, starred_actors, 2232
25241, has_genre, 24811
25241, release_year, 29424
9216, has_genre, 24811
9216, release_year, 29424
10303, has_genre, 24811
10303, release_year, 29424
34723, has_genre, 24811
34723, release_year, 29424
30851, directed_by, 17883
30851, has_tags, 17883
30851, has_tags, 2232
30851, has_tags, 28910
30851, starred_actors, 2232
30851, written_by, 28910
16127, has_genre, 24811
16127, release_year, 29424
19102, has_genre, 24811
19102, release_year, 29424
35243, has_genre, 24811
35243, release_year, 29424
16231, has_tags, 10045
16231, written_by, 6358
21402, has_genre, 24811
21402, release_year, 29424
16069, release_year, 11
16069, release_year, 27261
16069, written_by, 6358
10171, has_genre, 24811
10171, release_year, 29424
7240, has_tags, 24811
7240, release_year, 29424
13340, has_genre, 24811
13340, release_year, 29424
15989, has_genre, 24811
15989, release_year, 29424
8273, has_genre, 24811
8273, has_tags, 24811
8273, release_year, 29424
31667, has_genre, 24811
31667, release_year, 29424
23688, has_genre, 24811
23688, release_year, 29424
27604, has_genre, 24811
27604, written_by, 17883
26776, has_imdb_rating, 11565
26776, release_year, 11
26776, starred_actors, 11985
26776, written_by, 6358
5521, has_genre, 24811
5521, release_year, 29424
20779, has_genre, 24811
20779, release_year, 29424
8839, has_genre, 24811
8839, release_year, 29424
29250, has_genre, 24811
29250, release_year, 29424
10049, has_genre, 24811
10049, release_year, 29424
28084, has_genre, 24811
28084, release_year, 29424
28084, starred_actors, 38751
28084, starred_actors, 3595
18953, has_tags, 24811
18953, release_year, 29424
10053, has_genre, 24811
10053, release_year, 29424
11596, has_genre, 24811
11596, has_tags, 24811
11596, release_year, 29424
4957, has_genre, 24811
4957, release_year, 29424
21676, has_genre, 24811
21676, has_tags, 24811
21676, release_year, 29424
15340, has_genre, 24811
15340, release_year, 29424
22751, has_genre, 24811
22751, has_tags, 38751
22751, starred_actors, 38751
22110, has_genre, 24811
22110, release_year, 29424
36954, has_genre, 24811
36954, release_year, 29424
36262, has_tags, 10045
36262, written_by, 17883
10133, has_genre, 24811
10133, release_year, 29424
Question: In what context are BARRY LEVINSON, CURT SIODMAK, and THE RESIDENT connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"BARRY LEVINSON",
"CURT SIODMAK",
"THE RESIDENT"
],
"valid_edges": [
[
"247°F",
"has_genre",
"THRILLER"
],
[
"247°F",
"release_year",
"2011"
],
[
"96 MINUTES",
"has_genre",
"THRILLER"
],
[
"96 MINUTES",
"release_year",
"2011"
],
[
"ABDUCTION",
"has_genre",
"THRILLER"
],
[
"ABDUCTION",
"release_year",
"2011"
],
[
"ANONYMOUS",
"has_genre",
"THRILLER"
],
[
"ANONYMOUS",
"release_year",
"2011"
],
[
"BLITZ",
"has_genre",
"THRILLER"
],
[
"BLITZ",
"release_year",
"2011"
],
[
"CONTAGION",
"has_genre",
"THRILLER"
],
[
"CONTAGION",
"has_tags",
"THRILLER"
],
[
"CONTAGION",
"release_year",
"2011"
],
[
"CREATURE WITH THE ATOM BRAIN",
"has_tags",
"BD-R"
],
[
"CREATURE WITH THE ATOM BRAIN",
"written_by",
"CURT SIODMAK"
],
[
"DISCLOSURE",
"directed_by",
"BARRY LEVINSON"
],
[
"DISCLOSURE",
"has_genre",
"THRILLER"
],
[
"DISCLOSURE",
"has_tags",
"MICHAEL CRICHTON"
],
[
"DISCLOSURE",
"written_by",
"MICHAEL CRICHTON"
],
[
"DONOVAN'S BRAIN",
"has_tags",
"BD-R"
],
[
"DONOVAN'S BRAIN",
"written_by",
"CURT SIODMAK"
],
[
"DREAM HOUSE",
"has_genre",
"THRILLER"
],
[
"DREAM HOUSE",
"release_year",
"2011"
],
[
"ENTER NOWHERE",
"has_genre",
"THRILLER"
],
[
"ENTER NOWHERE",
"release_year",
"2011"
],
[
"ENVY",
"directed_by",
"BARRY LEVINSON"
],
[
"ENVY",
"release_year",
"2009"
],
[
"FALSE TRAIL",
"has_genre",
"THRILLER"
],
[
"FALSE TRAIL",
"release_year",
"2011"
],
[
"GOOD MORNING, VIETNAM",
"directed_by",
"BARRY LEVINSON"
],
[
"GOOD MORNING, VIETNAM",
"has_genre",
"WAR"
],
[
"GOOD MORNING, VIETNAM",
"has_imdb_rating",
"GOOD"
],
[
"GOOD MORNING, VIETNAM",
"has_tags",
"BARRY LEVINSON"
],
[
"GOOD MORNING, VIETNAM",
"has_tags",
"BD-R"
],
[
"GOOD MORNING, VIETNAM",
"has_tags",
"WAR"
],
[
"HANNA",
"has_genre",
"THRILLER"
],
[
"HANNA",
"has_tags",
"THRILLER"
],
[
"HANNA",
"release_year",
"2011"
],
[
"HAYWIRE",
"has_genre",
"THRILLER"
],
[
"HAYWIRE",
"release_year",
"2011"
],
[
"HEADHUNTERS",
"has_genre",
"THRILLER"
],
[
"HEADHUNTERS",
"release_year",
"2011"
],
[
"HELLGATE",
"has_genre",
"THRILLER"
],
[
"HELLGATE",
"release_year",
"2011"
],
[
"IN TIME",
"has_genre",
"THRILLER"
],
[
"IN TIME",
"has_tags",
"THRILLER"
],
[
"IN TIME",
"release_year",
"2011"
],
[
"INSOMNIA",
"has_genre",
"THRILLER"
],
[
"INSOMNIA",
"has_tags",
"HILARY SWANK"
],
[
"INSOMNIA",
"starred_actors",
"HILARY SWANK"
],
[
"INVISIBLE AGENT",
"has_genre",
"WAR"
],
[
"INVISIBLE AGENT",
"starred_actors",
"CEDRIC HARDWICKE"
],
[
"INVISIBLE AGENT",
"written_by",
"CURT SIODMAK"
],
[
"JUDAS KISS",
"has_genre",
"THRILLER"
],
[
"JUDAS KISS",
"release_year",
"2011"
],
[
"KILLER ELITE",
"has_genre",
"THRILLER"
],
[
"KILLER ELITE",
"release_year",
"2011"
],
[
"LIMITLESS",
"has_genre",
"THRILLER"
],
[
"LIMITLESS",
"release_year",
"2011"
],
[
"MARTHA MARCY MAY MARLENE",
"has_genre",
"THRILLER"
],
[
"MARTHA MARCY MAY MARLENE",
"has_tags",
"THRILLER"
],
[
"MARTHA MARCY MAY MARLENE",
"release_year",
"2011"
],
[
"NO REST FOR THE WICKED",
"has_genre",
"THRILLER"
],
[
"NO REST FOR THE WICKED",
"has_tags",
"THRILLER"
],
[
"NO REST FOR THE WICKED",
"release_year",
"2011"
],
[
"OCCUPANT",
"has_genre",
"THRILLER"
],
[
"OCCUPANT",
"release_year",
"2011"
],
[
"PAGE EIGHT",
"has_genre",
"THRILLER"
],
[
"PAGE EIGHT",
"release_year",
"2011"
],
[
"RAIN MAN",
"directed_by",
"BARRY LEVINSON"
],
[
"RAIN MAN",
"has_imdb_rating",
"GOOD"
],
[
"RAIN MAN",
"has_tags",
"BARRY LEVINSON"
],
[
"RAIN MAN",
"has_tags",
"DUSTIN HOFFMAN"
],
[
"RAIN MAN",
"starred_actors",
"DUSTIN HOFFMAN"
],
[
"RETREAT",
"has_genre",
"THRILLER"
],
[
"RETREAT",
"release_year",
"2011"
],
[
"ROSEWOOD LANE",
"has_genre",
"THRILLER"
],
[
"ROSEWOOD LANE",
"release_year",
"2011"
],
[
"SEEKING JUSTICE",
"has_genre",
"THRILLER"
],
[
"SEEKING JUSTICE",
"release_year",
"2011"
],
[
"SLEEPLESS NIGHT",
"has_genre",
"THRILLER"
],
[
"SLEEPLESS NIGHT",
"release_year",
"2011"
],
[
"SPHERE",
"directed_by",
"BARRY LEVINSON"
],
[
"SPHERE",
"has_tags",
"BARRY LEVINSON"
],
[
"SPHERE",
"has_tags",
"DUSTIN HOFFMAN"
],
[
"SPHERE",
"has_tags",
"MICHAEL CRICHTON"
],
[
"SPHERE",
"starred_actors",
"DUSTIN HOFFMAN"
],
[
"SPHERE",
"written_by",
"MICHAEL CRICHTON"
],
[
"STRAW DOGS",
"has_genre",
"THRILLER"
],
[
"STRAW DOGS",
"release_year",
"2011"
],
[
"SUPER 8",
"has_genre",
"THRILLER"
],
[
"SUPER 8",
"release_year",
"2011"
],
[
"TAKE SHELTER",
"has_genre",
"THRILLER"
],
[
"TAKE SHELTER",
"release_year",
"2011"
],
[
"TARZAN'S MAGIC FOUNTAIN",
"has_tags",
"BD-R"
],
[
"TARZAN'S MAGIC FOUNTAIN",
"written_by",
"CURT SIODMAK"
],
[
"THE ADJUSTMENT BUREAU",
"has_genre",
"THRILLER"
],
[
"THE ADJUSTMENT BUREAU",
"release_year",
"2011"
],
[
"THE APE",
"release_year",
"1940"
],
[
"THE APE",
"release_year",
"2009"
],
[
"THE APE",
"written_by",
"CURT SIODMAK"
],
[
"THE CALLER",
"has_genre",
"THRILLER"
],
[
"THE CALLER",
"release_year",
"2011"
],
[
"THE GIRL WITH THE DRAGON TATTOO",
"has_tags",
"THRILLER"
],
[
"THE GIRL WITH THE DRAGON TATTOO",
"release_year",
"2011"
],
[
"THE GOOD DOCTOR",
"has_genre",
"THRILLER"
],
[
"THE GOOD DOCTOR",
"release_year",
"2011"
],
[
"THE GREY",
"has_genre",
"THRILLER"
],
[
"THE GREY",
"release_year",
"2011"
],
[
"THE HIDDEN FACE",
"has_genre",
"THRILLER"
],
[
"THE HIDDEN FACE",
"has_tags",
"THRILLER"
],
[
"THE HIDDEN FACE",
"release_year",
"2011"
],
[
"THE HOLDING",
"has_genre",
"THRILLER"
],
[
"THE HOLDING",
"release_year",
"2011"
],
[
"THE HUNTER",
"has_genre",
"THRILLER"
],
[
"THE HUNTER",
"release_year",
"2011"
],
[
"THE INTERNECINE PROJECT",
"has_genre",
"THRILLER"
],
[
"THE INTERNECINE PROJECT",
"written_by",
"BARRY LEVINSON"
],
[
"THE INVISIBLE MAN RETURNS",
"has_imdb_rating",
"GOOD"
],
[
"THE INVISIBLE MAN RETURNS",
"release_year",
"1940"
],
[
"THE INVISIBLE MAN RETURNS",
"starred_actors",
"CEDRIC HARDWICKE"
],
[
"THE INVISIBLE MAN RETURNS",
"written_by",
"CURT SIODMAK"
],
[
"THE LEDGE",
"has_genre",
"THRILLER"
],
[
"THE LEDGE",
"release_year",
"2011"
],
[
"THE LINCOLN LAWYER",
"has_genre",
"THRILLER"
],
[
"THE LINCOLN LAWYER",
"release_year",
"2011"
],
[
"THE MECHANIC",
"has_genre",
"THRILLER"
],
[
"THE MECHANIC",
"release_year",
"2011"
],
[
"THE MONITOR",
"has_genre",
"THRILLER"
],
[
"THE MONITOR",
"release_year",
"2011"
],
[
"THE MONK",
"has_genre",
"THRILLER"
],
[
"THE MONK",
"release_year",
"2011"
],
[
"THE RESIDENT",
"has_genre",
"THRILLER"
],
[
"THE RESIDENT",
"release_year",
"2011"
],
[
"THE RESIDENT",
"starred_actors",
"CHRISTOPHER LEE"
],
[
"THE RESIDENT",
"starred_actors",
"HILARY SWANK"
],
[
"THE RITE",
"has_tags",
"THRILLER"
],
[
"THE RITE",
"release_year",
"2011"
],
[
"THE RIVER MURDERS",
"has_genre",
"THRILLER"
],
[
"THE RIVER MURDERS",
"release_year",
"2011"
],
[
"THE ROOMMATE",
"has_genre",
"THRILLER"
],
[
"THE ROOMMATE",
"has_tags",
"THRILLER"
],
[
"THE ROOMMATE",
"release_year",
"2011"
],
[
"THE SKIN I LIVE IN",
"has_genre",
"THRILLER"
],
[
"THE SKIN I LIVE IN",
"release_year",
"2011"
],
[
"THE SON OF NO ONE",
"has_genre",
"THRILLER"
],
[
"THE SON OF NO ONE",
"has_tags",
"THRILLER"
],
[
"THE SON OF NO ONE",
"release_year",
"2011"
],
[
"THE SPEED OF THOUGHT",
"has_genre",
"THRILLER"
],
[
"THE SPEED OF THOUGHT",
"release_year",
"2011"
],
[
"THE WICKER MAN",
"has_genre",
"THRILLER"
],
[
"THE WICKER MAN",
"has_tags",
"CHRISTOPHER LEE"
],
[
"THE WICKER MAN",
"starred_actors",
"CHRISTOPHER LEE"
],
[
"TRESPASS",
"has_genre",
"THRILLER"
],
[
"TRESPASS",
"release_year",
"2011"
],
[
"TWIXT",
"has_genre",
"THRILLER"
],
[
"TWIXT",
"release_year",
"2011"
],
[
"UNFAITHFULLY YOURS",
"has_tags",
"BD-R"
],
[
"UNFAITHFULLY YOURS",
"written_by",
"BARRY LEVINSON"
],
[
"UNKNOWN",
"has_genre",
"THRILLER"
],
[
"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
9189, 50 CENT
3541, BRIGHT LEAVES
12841, DOCUMENTARY
18116, HOW TO MAKE MONEY SELLING DRUGS
5697, JAMES TOBACK
36869, ROSS MCELWEE
24676, SEDUCED AND ABANDONED
30043, SHERMAN'S MARCH
12757, TYSON
src, edge_attr, dst
3541, directed_by, 36869
3541, has_genre, 12841
3541, written_by, 36869
18116, has_genre, 12841
18116, has_tags, 12841
18116, starred_actors, 9189
24676, directed_by, 5697
24676, has_genre, 12841
24676, has_tags, 5697
24676, written_by, 5697
30043, directed_by, 36869
30043, has_genre, 12841
30043, starred_actors, 36869
30043, written_by, 36869
12757, directed_by, 5697
12757, has_genre, 12841
12757, has_tags, 5697
12757, written_by, 5697
Question: How are 50 CENT, ROSS MCELWEE, and SEDUCED AND ABANDONED related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"50 CENT",
"ROSS MCELWEE",
"SEDUCED AND ABANDONED"
],
"valid_edges": [
[
"BRIGHT LEAVES",
"directed_by",
"ROSS MCELWEE"
],
[
"BRIGHT LEAVES",
"has_genre",
"DOCUMENTARY"
],
[
"BRIGHT LEAVES",
"written_by",
"ROSS MCELWEE"
],
[
"HOW TO MAKE MONEY SELLING DRUGS",
"has_genre",
"DOCUMENTARY"
],
[
"HOW TO MAKE MONEY SELLING DRUGS",
"has_tags",
"DOCUMENTARY"
],
[
"HOW TO MAKE MONEY SELLING DRUGS",
"starred_actors",
"50 CENT"
],
[
"SEDUCED AND ABANDONED",
"directed_by",
"JAMES TOBACK"
],
[
"SEDUCED AND ABANDONED",
"has_genre",
"DOCUMENTARY"
],
[
"SEDUCED AND ABANDONED",
"has_tags",
"JAMES TOBACK"
],
[
"SEDUCED AND ABANDONED",
"written_by",
"JAMES TOBACK"
],
[
"SHERMAN'S MARCH",
"directed_by",
"ROSS MCELWEE"
],
[
"SHERMAN'S MARCH",
"has_genre",
"DOCUMENTARY"
],
[
"SHERMAN'S MARCH",
"starred_actors",
"ROSS MCELWEE"
],
[
"SHERMAN'S MARCH",
"written_by",
"ROSS MCELWEE"
],
[
"TYSON",
"directed_by",
"JAMES TOBACK"
],
[
"TYSON",
"has_genre",
"DOCUMENTARY"
],
[
"TYSON",
"has_tags",
"JAMES TOBACK"
],
[
"TYSON",
"written_by",
"JAMES TOBACK"
]
]
}
|
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
25221, 1981
35845, 2006
27261, 2009
2779, A PROPHET
10429, A SUNDAY IN KIGALI
21524, A TOWN CALLED PANIC
29167, AMER
24216, ASTERIX AND THE VIKINGS
2156, AVENUE MONTAIGNE
25570, BEAUTY AND THE BEAST
26602, BETTY
4197, BLUEBEARD
6283, CARGO
33914, CHÉRI
36000, CLAUDE CHABROL
25853, COCO BEFORE CHANEL
6855, COME DANCE WITH ME!
23571, COMEDY OF POWER
4513, DANS PARIS
3567, DAYS OF GLORY
36405, DON'T LOOK BACK
37874, DON'T WORRY, I'M FINE
7480, EDEN
8176, FAREWELL
22941, FATHER AND GUNS
36601, FLANDERS
1273, FLYBOYS
6012, FRENCH
36001, HADEWIJCH
38589, I DO
7569, IN THE BEGINNING
16560, INGLOURIOUS BASTERDS
15366, KORKORO
18091, L'ENFER
27429, LA CÉRÉMONIE
21884, LADY CHATTERLEY
1311, LASCARS
35149, LE BEAU SERGE
13066, LE BOUCHER
31837, LEAVING
13227, LES BICHES
39572, LES COUSINS
17372, LOL
5214, LOOKING FOR ERIC
2889, MADAME BOVARY
2533, MADEMOISELLE CHAMBON
29822, MAKING PLANS FOR LENA
19594, MAMMUTH
28455, MARIE ANTOINETTE
39644, MUTANTS
29894, OCEANS
29693, PICKPOCKET
20440, PICNIC ON THE GRASS
1103, PLEASURE PARTY
8171, PRICELESS
12223, PRIVATE FEARS IN PUBLIC PLACES
27445, PRIVATE PROPERTY
5538, QUEEN TO PLAY
12820, RAPT
18480, RENAISSANCE
16482, RICKY
3942, SALVAGE
28126, SHEITAN
27301, SPLICE
15194, STORY OF WOMEN
5467, SÉRAPHINE
37807, TELL NO ONE
18486, THE 400 BLOWS
23231, THE BRIDESMAID
1059, THE DA VINCI CODE
39211, THE FLOWER OF EVIL
33810, THE FRENCH KISSERS
36893, THE GIRL ON THE TRAIN
17555, THE HEDGEHOG
25529, THE ILLUSIONIST
37047, THE MAN OF MY LIFE
23972, THE PAGE TURNER
11383, THE SCIENCE OF SLEEP
20919, THE STRING
26678, THE SWINDLE
39999, THE THORN IN THE HEART
29199, THE UNFAITHFUL WIFE
4542, THE VALET
35283, THEM
10179, THIS MAN MUST DIE
10988, TOMORROW AT DAWN
37543, TRANSYLVANIA
19606, TWO MEN IN MANHATTAN
32772, UNFAITHFUL
10735, VENGEANCE
17001, VILLA AMALIA
22910, WEDDING IN BLOOD
34053, WELCOME
23392, WHITE MATERIAL
9876, WILD GRASS
3739, YOLANDE MOREAU
src, edge_attr, dst
25221, in_language, 6012
25221, release_year, 27261
2779, has_tags, 6012
2779, in_language, 6012
2779, release_year, 27261
10429, in_language, 6012
10429, release_year, 35845
21524, has_tags, 6012
21524, in_language, 6012
21524, release_year, 27261
29167, in_language, 6012
29167, release_year, 27261
24216, in_language, 6012
24216, release_year, 35845
2156, has_tags, 6012
2156, in_language, 6012
2156, release_year, 35845
25570, in_language, 6012
25570, release_year, 27261
26602, directed_by, 36000
26602, in_language, 6012
26602, written_by, 36000
4197, in_language, 6012
4197, release_year, 27261
6283, release_year, 35845
6283, release_year, 27261
33914, in_language, 6012
33914, release_year, 27261
25853, has_tags, 6012
25853, in_language, 6012
25853, release_year, 27261
6855, in_language, 6012
6855, release_year, 33637
23571, directed_by, 36000
23571, in_language, 6012
23571, release_year, 35845
23571, written_by, 36000
4513, in_language, 6012
4513, release_year, 35845
3567, in_language, 6012
3567, release_year, 35845
36405, in_language, 6012
36405, release_year, 27261
37874, in_language, 6012
37874, release_year, 35845
7480, in_language, 6012
7480, release_year, 35845
8176, in_language, 6012
8176, release_year, 27261
22941, in_language, 6012
22941, release_year, 27261
36601, in_language, 6012
36601, release_year, 35845
1273, in_language, 6012
1273, release_year, 35845
36001, in_language, 6012
36001, release_year, 27261
38589, has_tags, 6012
38589, in_language, 6012
38589, release_year, 35845
7569, in_language, 6012
7569, release_year, 27261
16560, has_tags, 6012
16560, in_language, 6012
16560, release_year, 27261
15366, has_tags, 6012
15366, in_language, 6012
15366, release_year, 27261
18091, directed_by, 36000
18091, has_tags, 36000
18091, in_language, 6012
18091, written_by, 36000
27429, directed_by, 36000
27429, has_tags, 36000
27429, in_language, 6012
27429, written_by, 36000
21884, in_language, 6012
21884, release_year, 35845
1311, in_language, 6012
1311, release_year, 27261
35149, directed_by, 36000
35149, has_tags, 36000
35149, in_language, 6012
35149, written_by, 36000
13066, directed_by, 36000
13066, has_tags, 36000
13066, in_language, 6012
13066, written_by, 36000
31837, in_language, 6012
31837, release_year, 27261
13227, directed_by, 36000
13227, has_tags, 36000
13227, in_language, 6012
13227, written_by, 36000
39572, directed_by, 36000
39572, has_tags, 36000
39572, in_language, 6012
39572, release_year, 33637
39572, written_by, 36000
17372, in_language, 6012
17372, release_year, 35845
5214, in_language, 6012
5214, release_year, 27261
2889, directed_by, 36000
2889, in_language, 6012
2889, written_by, 36000
2533, in_language, 6012
2533, release_year, 27261
29822, in_language, 6012
29822, release_year, 27261
19594, in_language, 6012
19594, starred_actors, 3739
28455, in_language, 6012
28455, release_year, 35845
39644, in_language, 6012
39644, release_year, 27261
29894, in_language, 6012
29894, release_year, 27261
29693, in_language, 6012
29693, release_year, 33637
20440, in_language, 6012
20440, release_year, 33637
1103, directed_by, 36000
1103, in_language, 6012
8171, has_tags, 6012
8171, in_language, 6012
8171, release_year, 35845
12223, in_language, 6012
12223, release_year, 35845
27445, in_language, 6012
27445, release_year, 35845
5538, in_language, 6012
5538, release_year, 27261
12820, in_language, 6012
12820, release_year, 27261
18480, in_language, 6012
18480, release_year, 35845
16482, in_language, 6012
16482, release_year, 27261
3942, release_year, 35845
3942, release_year, 27261
28126, in_language, 6012
28126, release_year, 35845
27301, in_language, 6012
27301, release_year, 27261
15194, directed_by, 36000
15194, has_tags, 36000
15194, in_language, 6012
15194, written_by, 36000
5467, in_language, 6012
5467, starred_actors, 3739
37807, has_tags, 6012
37807, in_language, 6012
37807, release_year, 35845
18486, in_language, 6012
18486, release_year, 33637
23231, directed_by, 36000
23231, in_language, 6012
23231, written_by, 36000
1059, in_language, 6012
1059, release_year, 35845
39211, directed_by, 36000
39211, in_language, 6012
39211, written_by, 36000
33810, in_language, 6012
33810, release_year, 27261
36893, in_language, 6012
36893, release_year, 27261
17555, has_tags, 6012
17555, in_language, 6012
17555, release_year, 27261
25529, in_language, 6012
25529, release_year, 35845
37047, in_language, 6012
37047, release_year, 35845
23972, has_tags, 6012
23972, in_language, 6012
23972, release_year, 35845
11383, in_language, 6012
11383, release_year, 35845
20919, in_language, 6012
20919, release_year, 27261
26678, directed_by, 36000
26678, in_language, 6012
26678, written_by, 36000
39999, in_language, 6012
39999, release_year, 27261
29199, directed_by, 36000
29199, has_tags, 36000
29199, in_language, 6012
29199, written_by, 36000
4542, has_tags, 6012
4542, in_language, 6012
4542, release_year, 35845
35283, in_language, 6012
35283, release_year, 35845
10179, directed_by, 36000
10179, has_tags, 36000
10179, in_language, 6012
10179, written_by, 36000
10988, in_language, 6012
10988, release_year, 27261
37543, in_language, 6012
37543, release_year, 35845
19606, in_language, 6012
19606, release_year, 33637
32772, in_language, 6012
32772, written_by, 36000
10735, in_language, 6012
10735, release_year, 27261
17001, in_language, 6012
17001, release_year, 27261
22910, directed_by, 36000
22910, has_tags, 36000
22910, in_language, 6012
22910, written_by, 36000
34053, in_language, 6012
34053, release_year, 27261
23392, in_language, 6012
23392, release_year, 27261
9876, has_tags, 6012
9876, in_language, 6012
9876, release_year, 27261
Question: In what context are CARGO, LES COUSINS, and YOLANDE MOREAU connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"CARGO",
"LES COUSINS",
"YOLANDE MOREAU"
],
"valid_edges": [
[
"1981",
"in_language",
"FRENCH"
],
[
"1981",
"release_year",
"2009"
],
[
"A PROPHET",
"has_tags",
"FRENCH"
],
[
"A PROPHET",
"in_language",
"FRENCH"
],
[
"A PROPHET",
"release_year",
"2009"
],
[
"A SUNDAY IN KIGALI",
"in_language",
"FRENCH"
],
[
"A SUNDAY IN KIGALI",
"release_year",
"2006"
],
[
"A TOWN CALLED PANIC",
"has_tags",
"FRENCH"
],
[
"A TOWN CALLED PANIC",
"in_language",
"FRENCH"
],
[
"A TOWN CALLED PANIC",
"release_year",
"2009"
],
[
"AMER",
"in_language",
"FRENCH"
],
[
"AMER",
"release_year",
"2009"
],
[
"ASTERIX AND THE VIKINGS",
"in_language",
"FRENCH"
],
[
"ASTERIX AND THE VIKINGS",
"release_year",
"2006"
],
[
"AVENUE MONTAIGNE",
"has_tags",
"FRENCH"
],
[
"AVENUE MONTAIGNE",
"in_language",
"FRENCH"
],
[
"AVENUE MONTAIGNE",
"release_year",
"2006"
],
[
"BEAUTY AND THE BEAST",
"in_language",
"FRENCH"
],
[
"BEAUTY AND THE BEAST",
"release_year",
"2009"
],
[
"BETTY",
"directed_by",
"CLAUDE CHABROL"
],
[
"BETTY",
"in_language",
"FRENCH"
],
[
"BETTY",
"written_by",
"CLAUDE CHABROL"
],
[
"BLUEBEARD",
"in_language",
"FRENCH"
],
[
"BLUEBEARD",
"release_year",
"2009"
],
[
"CARGO",
"release_year",
"2006"
],
[
"CARGO",
"release_year",
"2009"
],
[
"CHÉRI",
"in_language",
"FRENCH"
],
[
"CHÉRI",
"release_year",
"2009"
],
[
"COCO BEFORE CHANEL",
"has_tags",
"FRENCH"
],
[
"COCO BEFORE CHANEL",
"in_language",
"FRENCH"
],
[
"COCO BEFORE CHANEL",
"release_year",
"2009"
],
[
"COME DANCE WITH ME!",
"in_language",
"FRENCH"
],
[
"COME DANCE WITH ME!",
"release_year",
"1959"
],
[
"COMEDY OF POWER",
"directed_by",
"CLAUDE CHABROL"
],
[
"COMEDY OF POWER",
"in_language",
"FRENCH"
],
[
"COMEDY OF POWER",
"release_year",
"2006"
],
[
"COMEDY OF POWER",
"written_by",
"CLAUDE CHABROL"
],
[
"DANS PARIS",
"in_language",
"FRENCH"
],
[
"DANS PARIS",
"release_year",
"2006"
],
[
"DAYS OF GLORY",
"in_language",
"FRENCH"
],
[
"DAYS OF GLORY",
"release_year",
"2006"
],
[
"DON'T LOOK BACK",
"in_language",
"FRENCH"
],
[
"DON'T LOOK BACK",
"release_year",
"2009"
],
[
"DON'T WORRY, I'M FINE",
"in_language",
"FRENCH"
],
[
"DON'T WORRY, I'M FINE",
"release_year",
"2006"
],
[
"EDEN",
"in_language",
"FRENCH"
],
[
"EDEN",
"release_year",
"2006"
],
[
"FAREWELL",
"in_language",
"FRENCH"
],
[
"FAREWELL",
"release_year",
"2009"
],
[
"FATHER AND GUNS",
"in_language",
"FRENCH"
],
[
"FATHER AND GUNS",
"release_year",
"2009"
],
[
"FLANDERS",
"in_language",
"FRENCH"
],
[
"FLANDERS",
"release_year",
"2006"
],
[
"FLYBOYS",
"in_language",
"FRENCH"
],
[
"FLYBOYS",
"release_year",
"2006"
],
[
"HADEWIJCH",
"in_language",
"FRENCH"
],
[
"HADEWIJCH",
"release_year",
"2009"
],
[
"I DO",
"has_tags",
"FRENCH"
],
[
"I DO",
"in_language",
"FRENCH"
],
[
"I DO",
"release_year",
"2006"
],
[
"IN THE BEGINNING",
"in_language",
"FRENCH"
],
[
"IN THE BEGINNING",
"release_year",
"2009"
],
[
"INGLOURIOUS BASTERDS",
"has_tags",
"FRENCH"
],
[
"INGLOURIOUS BASTERDS",
"in_language",
"FRENCH"
],
[
"INGLOURIOUS BASTERDS",
"release_year",
"2009"
],
[
"KORKORO",
"has_tags",
"FRENCH"
],
[
"KORKORO",
"in_language",
"FRENCH"
],
[
"KORKORO",
"release_year",
"2009"
],
[
"L'ENFER",
"directed_by",
"CLAUDE CHABROL"
],
[
"L'ENFER",
"has_tags",
"CLAUDE CHABROL"
],
[
"L'ENFER",
"in_language",
"FRENCH"
],
[
"L'ENFER",
"written_by",
"CLAUDE CHABROL"
],
[
"LA CÉRÉMONIE",
"directed_by",
"CLAUDE CHABROL"
],
[
"LA CÉRÉMONIE",
"has_tags",
"CLAUDE CHABROL"
],
[
"LA CÉRÉMONIE",
"in_language",
"FRENCH"
],
[
"LA CÉRÉMONIE",
"written_by",
"CLAUDE CHABROL"
],
[
"LADY CHATTERLEY",
"in_language",
"FRENCH"
],
[
"LADY CHATTERLEY",
"release_year",
"2006"
],
[
"LASCARS",
"in_language",
"FRENCH"
],
[
"LASCARS",
"release_year",
"2009"
],
[
"LE BEAU SERGE",
"directed_by",
"CLAUDE CHABROL"
],
[
"LE BEAU SERGE",
"has_tags",
"CLAUDE CHABROL"
],
[
"LE BEAU SERGE",
"in_language",
"FRENCH"
],
[
"LE BEAU SERGE",
"written_by",
"CLAUDE CHABROL"
],
[
"LE BOUCHER",
"directed_by",
"CLAUDE CHABROL"
],
[
"LE BOUCHER",
"has_tags",
"CLAUDE CHABROL"
],
[
"LE BOUCHER",
"in_language",
"FRENCH"
],
[
"LE BOUCHER",
"written_by",
"CLAUDE CHABROL"
],
[
"LEAVING",
"in_language",
"FRENCH"
],
[
"LEAVING",
"release_year",
"2009"
],
[
"LES BICHES",
"directed_by",
"CLAUDE CHABROL"
],
[
"LES BICHES",
"has_tags",
"CLAUDE CHABROL"
],
[
"LES BICHES",
"in_language",
"FRENCH"
],
[
"LES BICHES",
"written_by",
"CLAUDE CHABROL"
],
[
"LES COUSINS",
"directed_by",
"CLAUDE CHABROL"
],
[
"LES COUSINS",
"has_tags",
"CLAUDE CHABROL"
],
[
"LES COUSINS",
"in_language",
"FRENCH"
],
[
"LES COUSINS",
"release_year",
"1959"
],
[
"LES COUSINS",
"written_by",
"CLAUDE CHABROL"
],
[
"LOL",
"in_language",
"FRENCH"
],
[
"LOL",
"release_year",
"2006"
],
[
"LOOKING FOR ERIC",
"in_language",
"FRENCH"
],
[
"LOOKING FOR ERIC",
"release_year",
"2009"
],
[
"MADAME BOVARY",
"directed_by",
"CLAUDE CHABROL"
],
[
"MADAME BOVARY",
"in_language",
"FRENCH"
],
[
"MADAME BOVARY",
"written_by",
"CLAUDE CHABROL"
],
[
"MADEMOISELLE CHAMBON",
"in_language",
"FRENCH"
],
[
"MADEMOISELLE CHAMBON",
"release_year",
"2009"
],
[
"MAKING PLANS FOR LENA",
"in_language",
"FRENCH"
],
[
"MAKING PLANS FOR LENA",
"release_year",
"2009"
],
[
"MAMMUTH",
"in_language",
"FRENCH"
],
[
"MAMMUTH",
"starred_actors",
"YOLANDE MOREAU"
],
[
"MARIE ANTOINETTE",
"in_language",
"FRENCH"
],
[
"MARIE ANTOINETTE",
"release_year",
"2006"
],
[
"MUTANTS",
"in_language",
"FRENCH"
],
[
"MUTANTS",
"release_year",
"2009"
],
[
"OCEANS",
"in_language",
"FRENCH"
],
[
"OCEANS",
"release_year",
"2009"
],
[
"PICKPOCKET",
"in_language",
"FRENCH"
],
[
"PICKPOCKET",
"release_year",
"1959"
],
[
"PICNIC ON THE GRASS",
"in_language",
"FRENCH"
],
[
"PICNIC ON THE GRASS",
"release_year",
"1959"
],
[
"PLEASURE PARTY",
"directed_by",
"CLAUDE CHABROL"
],
[
"PLEASURE PARTY",
"in_language",
"FRENCH"
],
[
"PRICELESS",
"has_tags",
"FRENCH"
],
[
"PRICELESS",
"in_language",
"FRENCH"
],
[
"PRICELESS",
"release_year",
"2006"
],
[
"PRIVATE FEARS IN PUBLIC PLACES",
"in_language",
"FRENCH"
],
[
"PRIVATE FEARS IN PUBLIC PLACES",
"release_year",
"2006"
],
[
"PRIVATE PROPERTY",
"in_language",
"FRENCH"
],
[
"PRIVATE PROPERTY",
"release_year",
"2006"
],
[
"QUEEN TO PLAY",
"in_language",
"FRENCH"
],
[
"QUEEN TO PLAY",
"release_year",
"2009"
],
[
"RAPT",
"in_language",
"FRENCH"
],
[
"RAPT",
"release_year",
"2009"
],
[
"RENAISSANCE",
"in_language",
"FRENCH"
],
[
"RENAISSANCE",
"release_year",
"2006"
],
[
"RICKY",
"in_language",
"FRENCH"
],
[
"RICKY",
"release_year",
"2009"
],
[
"SALVAGE",
"release_year",
"2006"
],
[
"SALVAGE",
"release_year",
"2009"
],
[
"SHEITAN",
"in_language",
"FRENCH"
],
[
"SHEITAN",
"release_year",
"2006"
],
[
"SPLICE",
"in_language",
"FRENCH"
],
[
"SPLICE",
"release_year",
"2009"
],
[
"STORY OF WOMEN",
"directed_by",
"CLAUDE CHABROL"
],
[
"STORY OF WOMEN",
"has_tags",
"CLAUDE CHABROL"
],
[
"STORY OF WOMEN",
"in_language",
"FRENCH"
],
[
"STORY OF WOMEN",
"written_by",
"CLAUDE CHABROL"
],
[
"SÉRAPHINE",
"in_language",
"FRENCH"
],
[
"SÉRAPHINE",
"starred_actors",
"YOLANDE MOREAU"
],
[
"TELL NO ONE",
"has_tags",
"FRENCH"
],
[
"TELL NO ONE",
"in_language",
"FRENCH"
],
[
"TELL NO ONE",
"release_year",
"2006"
],
[
"THE 400 BLOWS",
"in_language",
"FRENCH"
],
[
"THE 400 BLOWS",
"release_year",
"1959"
],
[
"THE BRIDESMAID",
"directed_by",
"CLAUDE CHABROL"
],
[
"THE BRIDESMAID",
"in_language",
"FRENCH"
],
[
"THE BRIDESMAID",
"written_by",
"CLAUDE CHABROL"
],
[
"THE DA VINCI CODE",
"in_language",
"FRENCH"
],
[
"THE DA VINCI CODE",
"release_year",
"2006"
],
[
"THE FLOWER OF EVIL",
"directed_by",
"CLAUDE CHABROL"
],
[
"THE FLOWER OF EVIL",
"in_language",
"FRENCH"
],
[
"THE FLOWER OF EVIL",
"written_by",
"CLAUDE CHABROL"
],
[
"THE FRENCH KISSERS",
"in_language",
"FRENCH"
],
[
"THE FRENCH KISSERS",
"release_year",
"2009"
],
[
"THE GIRL ON THE TRAIN",
"in_language",
"FRENCH"
],
[
"THE GIRL ON THE TRAIN",
"release_year",
"2009"
],
[
"THE HEDGEHOG",
"has_tags",
"FRENCH"
],
[
"THE HEDGEHOG",
"in_language",
"FRENCH"
],
[
"THE HEDGEHOG",
"release_year",
"2009"
],
[
"THE ILLUSIONIST",
"in_language",
"FRENCH"
],
[
"THE ILLUSIONIST",
"release_year",
"2006"
],
[
"THE MAN OF MY LIFE",
"in_language",
"FRENCH"
],
[
"THE MAN OF MY LIFE",
"release_year",
"2006"
],
[
"THE PAGE TURNER",
"has_tags",
"FRENCH"
],
[
"THE PAGE TURNER",
"in_language",
"FRENCH"
],
[
"THE PAGE TURNER",
"release_year",
"2006"
],
[
"THE SCIENCE OF SLEEP",
"in_language",
"FRENCH"
],
[
"THE SCIENCE OF SLEEP",
"release_year",
"2006"
],
[
"THE STRING",
"in_language",
"FRENCH"
],
[
"THE STRING",
"release_year",
"2009"
],
[
"THE SWINDLE",
"directed_by",
"CLAUDE CHABROL"
],
[
"THE SWINDLE",
"in_language",
"FRENCH"
],
[
"THE SWINDLE",
"written_by",
"CLAUDE CHABROL"
],
[
"THE THORN IN THE HEART",
"in_language",
"FRENCH"
],
[
"THE THORN IN THE HEART",
"release_year",
"2009"
],
[
"THE UNFAITHFUL WIFE",
"directed_by",
"CLAUDE CHABROL"
],
[
"THE UNFAITHFUL WIFE",
"has_tags",
"CLAUDE CHABROL"
],
[
"THE UNFAITHFUL WIFE",
"in_language",
"FRENCH"
],
[
"THE UNFAITHFUL WIFE",
"written_by",
"CLAUDE CHABROL"
],
[
"THE VALET",
"has_tags",
"FRENCH"
],
[
"THE VALET",
"in_language",
"FRENCH"
],
[
"THE VALET",
"release_year",
"2006"
],
[
"THEM",
"in_language",
"FRENCH"
],
[
"THEM",
"release_year",
"2006"
],
[
"THIS MAN MUST DIE",
"directed_by",
"CLAUDE CHABROL"
],
[
"THIS MAN MUST DIE",
"has_tags",
"CLAUDE CHABROL"
],
[
"THIS MAN MUST DIE",
"in_language",
"FRENCH"
],
[
"THIS MAN MUST DIE",
"written_by",
"CLAUDE CHABROL"
],
[
"TOMORROW AT DAWN",
"in_language",
"FRENCH"
],
[
"TOMORROW AT DAWN",
"release_year",
"2009"
],
[
"TRANSYLVANIA",
"in_language",
"FRENCH"
],
[
"TRANSYLVANIA",
"release_year",
"2006"
],
[
"TWO MEN IN MANHATTAN",
"in_language",
"FRENCH"
],
[
"TWO MEN IN MANHATTAN",
"release_year",
"1959"
],
[
"UNFAITHFUL",
"in_language",
"FRENCH"
],
[
"UNFAITHFUL",
"written_by",
"CLAUDE CHABROL"
],
[
"VENGEANCE",
"in_language",
"FRENCH"
],
[
"VENGEANCE",
"release_year",
"2009"
],
[
"VILLA AMALIA",
"in_language",
"FRENCH"
],
[
"VILLA AMALIA",
"release_year",
"2009"
],
[
"WEDDING IN BLOOD",
"directed_by",
"CLAUDE CHABROL"
],
[
"WEDDING IN BLOOD",
"has_tags",
"CLAUDE CHABROL"
],
[
"WEDDING IN BLOOD",
"in_language",
"FRENCH"
],
[
"WEDDING IN BLOOD",
"written_by",
"CLAUDE CHABROL"
],
[
"WELCOME",
"in_language",
"FRENCH"
],
[
"WELCOME",
"release_year",
"2009"
],
[
"WHITE MATERIAL",
"in_language",
"FRENCH"
],
[
"WHITE MATERIAL",
"release_year",
"2009"
],
[
"WILD GRASS",
"has_tags",
"FRENCH"
],
[
"WILD GRASS",
"in_language",
"FRENCH"
],
[
"WILD GRASS",
"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
39435, 1975
8539, 1982
35205, DARK AND STORMY NIGHT
14492, DEAD MEN DON'T WEAR PLAID
29266, FITZCARRALDO
15145, MYSTERY
6446, NIGHT MOVES
27115, PICNIC AT HANGING ROCK
9875, THE DRAUGHTSMAN'S CONTRACT
476, THE NIGHT THAT PANICKED AMERICA
25255, THREE DAYS OF THE CONDOR
src, edge_attr, dst
35205, has_genre, 15145
14492, has_genre, 15145
14492, has_tags, 15145
14492, release_year, 8539
29266, release_year, 8539
6446, has_genre, 15145
6446, release_year, 39435
27115, has_genre, 15145
27115, release_year, 39435
9875, has_genre, 15145
9875, release_year, 8539
476, release_year, 39435
25255, has_genre, 15145
25255, release_year, 39435
Question: For what reason are DARK AND STORMY NIGHT, FITZCARRALDO, and THE NIGHT THAT PANICKED AMERICA associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"DARK AND STORMY NIGHT",
"FITZCARRALDO",
"THE NIGHT THAT PANICKED AMERICA"
],
"valid_edges": [
[
"DARK AND STORMY NIGHT",
"has_genre",
"MYSTERY"
],
[
"DEAD MEN DON'T WEAR PLAID",
"has_genre",
"MYSTERY"
],
[
"DEAD MEN DON'T WEAR PLAID",
"has_tags",
"MYSTERY"
],
[
"DEAD MEN DON'T WEAR PLAID",
"release_year",
"1982"
],
[
"FITZCARRALDO",
"release_year",
"1982"
],
[
"NIGHT MOVES",
"has_genre",
"MYSTERY"
],
[
"NIGHT MOVES",
"release_year",
"1975"
],
[
"PICNIC AT HANGING ROCK",
"has_genre",
"MYSTERY"
],
[
"PICNIC AT HANGING ROCK",
"release_year",
"1975"
],
[
"THE DRAUGHTSMAN'S CONTRACT",
"has_genre",
"MYSTERY"
],
[
"THE DRAUGHTSMAN'S CONTRACT",
"release_year",
"1982"
],
[
"THE NIGHT THAT PANICKED AMERICA",
"release_year",
"1975"
],
[
"THREE DAYS OF THE CONDOR",
"has_genre",
"MYSTERY"
],
[
"THREE DAYS OF THE CONDOR",
"release_year",
"1975"
]
]
}
|
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
23897, 1942
34322, AMERICAN HARDCORE
30870, BEAUTIFUL CREATURES
30019, CROSSROADS
35259, GLENN MILLER
29418, JEREMY IRONS
22845, MUSIC
37682, ORCHESTRA WIVES
24383, PAUL RACHMAN
39227, SUN VALLEY SERENADE
14478, THE LION KING
src, edge_attr, dst
34322, directed_by, 24383
34322, has_genre, 22845
30870, starred_actors, 29418
30019, has_genre, 22845
30019, release_year, 23897
37682, has_genre, 22845
37682, release_year, 23897
37682, starred_actors, 35259
39227, has_genre, 22845
39227, starred_actors, 35259
14478, has_tags, 29418
14478, has_tags, 22845
14478, starred_actors, 29418
Question: In what context are BEAUTIFUL CREATURES, ORCHESTRA WIVES, and PAUL RACHMAN connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"BEAUTIFUL CREATURES",
"ORCHESTRA WIVES",
"PAUL RACHMAN"
],
"valid_edges": [
[
"AMERICAN HARDCORE",
"directed_by",
"PAUL RACHMAN"
],
[
"AMERICAN HARDCORE",
"has_genre",
"MUSIC"
],
[
"BEAUTIFUL CREATURES",
"starred_actors",
"JEREMY IRONS"
],
[
"CROSSROADS",
"has_genre",
"MUSIC"
],
[
"CROSSROADS",
"release_year",
"1942"
],
[
"ORCHESTRA WIVES",
"has_genre",
"MUSIC"
],
[
"ORCHESTRA WIVES",
"release_year",
"1942"
],
[
"ORCHESTRA WIVES",
"starred_actors",
"GLENN MILLER"
],
[
"SUN VALLEY SERENADE",
"has_genre",
"MUSIC"
],
[
"SUN VALLEY SERENADE",
"starred_actors",
"GLENN MILLER"
],
[
"THE LION KING",
"has_tags",
"JEREMY IRONS"
],
[
"THE LION KING",
"has_tags",
"MUSIC"
],
[
"THE LION KING",
"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
16089, 13 GOING ON 30
37484, 2004
31079, 50 FIRST DATES
27455, A CINDERELLA STORY
31327, A DIRTY SHAME
4028, AALTRA
39289, ACTION
33087, AFTER THE SUNSET
16602, AGATA AND THE STORM
1698, ALFIE
32427, ALL THE QUEEN'S MEN
36361, ALONG CAME POLLY
18310, AROUND THE WORLD IN 80 DAYS
39895, BLAST
7318, BLOOD, GUTS, BULLETS AND OCTANE
21490, BOOK OF LOVE
13790, BREAKIN' ALL THE RULES
17453, CATCH THAT KID
6261, CELLULAR
19950, CHASING LIBERTY
24598, CHRISTMAS WITH THE KRANKS
1551, CLUB DREAD
30463, COMEDY
10272, CONFESSIONS OF A TEENAGE DRAMA QUEEN
24750, CONNIE AND CARLA
22220, D.E.B.S.
15779, DORIAN BLUES
1200, DUPLICATE
14645, ELLA ENCHANTED
22658, EMPLOYEE OF THE MONTH
1329, ENVY
5449, EULOGY
2449, EUROTRIP
19305, FAT ALBERT
25625, FIRST DAUGHTER
20743, FOUR SHADES OF BROWN
38061, G.O.R.A.
21640, GARDEN STATE
24815, GOING THE DISTANCE
24145, HAIR SHOW
21992, HOME ON THE RANGE
26968, HOT FUZZ
12857, HUM TUM
141, I HEART HUCKABEES
38304, IN GOOD COMPANY
26189, IT'S ALL GONE PETE TONG
26372, JERRY SPRINGER
21861, JERSEY GIRL
29431, JIMINY GLICK IN LALAWOOD
32303, JOHNSON FAMILY VACATION
9821, KUNG FU HUSTLE
31997, LAWS OF ATTRACTION
35898, LEMONY SNICKET'S A SERIES OF UNFORTUNATE EVENTS
1555, LITTLE BLACK BOOK
21412, LOST EMBRACE
17043, LOVE IS ETERNAL WHILE IT LASTS
26370, MADHOUSE
27174, MAIN HOON NA
29853, MASH
28590, MASTI
19791, MEAN GIRLS
39051, MEET THE FOCKERS
831, MELINDA AND MELINDA
13143, MILLIONS
14649, MUJHSE SHAADI KAROGI
27224, MY BABY'S DADDY
9951, NAPOLEON DYNAMITE
10574, NEW YORK MINUTE
13268, OYSTER FARMER
28047, PALINDROMES
33224, POSTAL
5693, RAISING HELEN
39339, RICHARD HOOKER
24415, RINGMASTER
32607, RUSH HOUR
18478, RUSH HOUR 3
35586, SAHARA
34022, SATAN'S LITTLE HELPER
11313, SAVED!
2135, SAVING FACE
136, SEE THIS MOVIE
2186, SEED OF CHUCKY
39218, SEX LIVES OF THE POTATO MEN
31340, SHARK TALE
29855, SHAUN OF THE DEAD
12902, SHE HATE ME
21512, SHERLOCK HOLMES
11357, SHOOT 'EM UP
16264, SHREK 2
36797, SIDEWAYS
32387, SIMON
32807, SIX-STRING SAMURAI
36556, SMALL SOLDIERS
17493, SOUL PLANE
7717, SPANGLISH
24987, SUMMER STORM
29095, SURVIVING CHRISTMAS
10732, TAXI
5285, THE BIG BOUNCE
36412, THE BIG HIT
29403, THE BOURNE SUPREMACY
2556, THE CALCIUM KID
2127, THE COOKOUT
30857, THE DEFENDER
4068, THE GENERAL
14807, THE GOODBYE GIRL
7447, THE INCREDIBLES
4223, THE INTERVIEW
30690, THE LADYKILLERS
11214, THE LAST SHOT
32925, THE LIFE AND DEATH OF PETER SELLERS
28217, THE LIFE AQUATIC WITH STEVE ZISSOU
36024, THE LIZARD
21149, THE NINE LIVES OF TOMAS KATZ
1619, THE PRINCE AND ME
15608, THE SPONGEBOB SQUAREPANTS MOVIE
23847, THE STEPFORD WIVES
15768, THE TERMINAL
18065, THE WHOLE TEN YARDS
32881, TOUCH OF PINK
5729, TROY
32741, UNDERDOG
22214, WAR
17375, WELCOME TO MOOSEPORT
12842, WHISKY
11366, WHITE CHICKS
11800, WIMBLEDON
2062, WIN A DATE WITH TAD HAMILTON!
src, edge_attr, dst
16089, has_genre, 30463
16089, has_tags, 30463
16089, release_year, 37484
31079, has_genre, 30463
31079, has_tags, 30463
31079, release_year, 37484
27455, has_genre, 30463
27455, release_year, 37484
31327, has_genre, 30463
31327, release_year, 37484
4028, has_genre, 30463
4028, release_year, 37484
33087, has_genre, 39289
33087, has_genre, 30463
33087, release_year, 37484
16602, has_genre, 30463
16602, release_year, 37484
1698, has_genre, 30463
1698, release_year, 37484
32427, has_genre, 39289
32427, has_genre, 30463
36361, has_genre, 30463
36361, has_tags, 30463
36361, release_year, 37484
18310, has_genre, 30463
18310, release_year, 37484
39895, has_genre, 39289
39895, has_genre, 30463
39895, release_year, 37484
7318, has_genre, 39289
7318, has_genre, 30463
21490, has_genre, 30463
21490, release_year, 37484
13790, has_genre, 30463
13790, release_year, 37484
17453, has_genre, 30463
17453, release_year, 37484
6261, has_tags, 39289
6261, release_year, 37484
19950, has_genre, 30463
19950, release_year, 37484
24598, has_genre, 30463
24598, release_year, 37484
1551, has_genre, 30463
1551, release_year, 37484
10272, has_genre, 30463
10272, has_tags, 30463
10272, release_year, 37484
24750, has_genre, 30463
24750, release_year, 37484
22220, has_genre, 39289
22220, has_genre, 30463
22220, release_year, 37484
15779, has_genre, 30463
15779, release_year, 37484
1200, has_genre, 39289
1200, has_genre, 30463
14645, has_genre, 30463
14645, release_year, 37484
22658, has_genre, 30463
22658, has_tags, 30463
22658, release_year, 37484
1329, has_genre, 30463
1329, release_year, 37484
5449, has_genre, 30463
5449, release_year, 37484
2449, has_genre, 30463
2449, has_tags, 30463
2449, release_year, 37484
19305, has_genre, 30463
19305, release_year, 37484
25625, has_genre, 30463
25625, release_year, 37484
20743, has_genre, 30463
20743, release_year, 37484
38061, has_genre, 30463
38061, release_year, 37484
21640, has_genre, 30463
21640, release_year, 37484
24815, has_genre, 30463
24815, has_tags, 30463
24815, release_year, 37484
24145, has_genre, 30463
24145, release_year, 37484
21992, has_genre, 30463
21992, release_year, 37484
26968, has_genre, 30463
26968, has_tags, 39289
26968, has_tags, 30463
12857, has_genre, 30463
12857, has_tags, 30463
12857, release_year, 37484
141, has_genre, 30463
141, has_tags, 30463
141, release_year, 37484
38304, has_genre, 30463
38304, release_year, 37484
26189, has_genre, 30463
26189, release_year, 37484
21861, has_genre, 30463
21861, has_tags, 30463
21861, release_year, 37484
29431, has_genre, 30463
29431, release_year, 37484
32303, has_genre, 30463
32303, release_year, 37484
9821, has_genre, 39289
9821, has_genre, 30463
9821, has_tags, 39289
9821, has_tags, 30463
9821, release_year, 37484
31997, has_genre, 30463
31997, has_tags, 30463
31997, release_year, 37484
35898, has_genre, 30463
35898, release_year, 37484
1555, has_genre, 30463
1555, release_year, 37484
21412, has_genre, 30463
21412, release_year, 37484
17043, has_genre, 30463
17043, release_year, 37484
26370, has_genre, 30463
26370, release_year, 37484
27174, has_genre, 39289
27174, has_genre, 30463
27174, release_year, 37484
29853, has_genre, 30463
29853, has_genre, 22214
29853, written_by, 39339
28590, has_genre, 30463
28590, release_year, 37484
19791, has_genre, 30463
19791, has_tags, 30463
19791, release_year, 37484
39051, has_genre, 30463
39051, release_year, 37484
831, has_genre, 30463
831, release_year, 37484
13143, has_genre, 30463
13143, release_year, 37484
14649, has_genre, 30463
14649, release_year, 37484
27224, has_genre, 30463
27224, release_year, 37484
9951, has_genre, 30463
9951, has_tags, 30463
9951, release_year, 37484
10574, has_genre, 30463
10574, release_year, 37484
13268, has_genre, 30463
13268, release_year, 37484
28047, has_genre, 30463
28047, release_year, 37484
33224, has_genre, 39289
33224, has_genre, 30463
5693, has_genre, 30463
5693, release_year, 37484
24415, has_genre, 30463
24415, starred_actors, 26372
32607, has_genre, 39289
32607, has_genre, 30463
32607, has_tags, 39289
32607, has_tags, 30463
18478, has_genre, 39289
18478, has_genre, 30463
18478, has_tags, 30463
35586, has_genre, 39289
35586, has_genre, 30463
35586, has_tags, 39289
34022, has_genre, 30463
34022, release_year, 37484
11313, has_genre, 30463
11313, release_year, 37484
2135, has_genre, 30463
2135, release_year, 37484
136, has_genre, 30463
136, release_year, 37484
2186, has_genre, 30463
2186, release_year, 37484
39218, has_genre, 30463
39218, release_year, 37484
31340, has_genre, 30463
31340, release_year, 37484
29855, has_genre, 30463
29855, has_tags, 30463
29855, release_year, 37484
12902, has_genre, 30463
12902, release_year, 37484
21512, has_genre, 39289
21512, has_tags, 39289
21512, has_tags, 30463
11357, has_genre, 39289
11357, has_genre, 30463
16264, has_genre, 30463
16264, has_tags, 30463
16264, release_year, 37484
36797, has_genre, 30463
36797, release_year, 37484
32387, has_genre, 30463
32387, release_year, 37484
32807, has_genre, 39289
32807, has_genre, 30463
36556, has_genre, 39289
36556, has_genre, 30463
17493, has_genre, 30463
17493, release_year, 37484
7717, has_genre, 30463
7717, release_year, 37484
24987, has_genre, 30463
24987, release_year, 37484
29095, has_genre, 30463
29095, release_year, 37484
10732, has_genre, 39289
10732, has_genre, 30463
10732, has_tags, 30463
10732, release_year, 37484
5285, has_genre, 30463
5285, release_year, 37484
36412, has_genre, 39289
36412, has_genre, 30463
36412, has_tags, 39289
36412, has_tags, 30463
29403, has_genre, 39289
29403, has_tags, 39289
29403, release_year, 37484
2556, has_genre, 30463
2556, release_year, 37484
2127, has_genre, 30463
2127, release_year, 37484
30857, has_genre, 39289
30857, release_year, 37484
30857, starred_actors, 26372
4068, has_genre, 39289
4068, has_genre, 30463
4068, has_tags, 30463
14807, has_genre, 30463
14807, release_year, 37484
7447, has_tags, 30463
7447, release_year, 37484
4223, has_genre, 39289
4223, has_genre, 30463
4223, has_tags, 30463
30690, has_genre, 30463
30690, has_tags, 30463
30690, release_year, 37484
11214, has_genre, 30463
11214, release_year, 37484
32925, has_genre, 30463
32925, release_year, 37484
28217, has_genre, 30463
28217, has_tags, 30463
28217, release_year, 37484
36024, has_genre, 30463
36024, has_tags, 30463
36024, release_year, 37484
21149, has_genre, 30463
1619, has_genre, 30463
1619, release_year, 37484
15608, has_genre, 30463
15608, release_year, 37484
23847, has_genre, 30463
23847, release_year, 37484
15768, has_genre, 30463
15768, has_tags, 30463
15768, release_year, 37484
18065, has_genre, 30463
18065, release_year, 37484
32881, has_genre, 30463
32881, has_tags, 30463
32881, release_year, 37484
5729, has_tags, 39289
5729, release_year, 37484
32741, has_genre, 39289
32741, has_genre, 30463
22214, has_genre, 39289
17375, has_genre, 30463
17375, release_year, 37484
12842, has_genre, 30463
12842, release_year, 37484
11366, has_genre, 30463
11366, has_tags, 30463
11366, release_year, 37484
11800, has_genre, 30463
11800, release_year, 37484
2062, has_genre, 30463
2062, has_tags, 30463
2062, release_year, 37484
Question: In what context are RICHARD HOOKER, THE DEFENDER, and THE NINE LIVES OF TOMAS KATZ connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"RICHARD HOOKER",
"THE DEFENDER",
"THE NINE LIVES OF TOMAS KATZ"
],
"valid_edges": [
[
"13 GOING ON 30",
"has_genre",
"COMEDY"
],
[
"13 GOING ON 30",
"has_tags",
"COMEDY"
],
[
"13 GOING ON 30",
"release_year",
"2004"
],
[
"50 FIRST DATES",
"has_genre",
"COMEDY"
],
[
"50 FIRST DATES",
"has_tags",
"COMEDY"
],
[
"50 FIRST DATES",
"release_year",
"2004"
],
[
"A CINDERELLA STORY",
"has_genre",
"COMEDY"
],
[
"A CINDERELLA STORY",
"release_year",
"2004"
],
[
"A DIRTY SHAME",
"has_genre",
"COMEDY"
],
[
"A DIRTY SHAME",
"release_year",
"2004"
],
[
"AALTRA",
"has_genre",
"COMEDY"
],
[
"AALTRA",
"release_year",
"2004"
],
[
"AFTER THE SUNSET",
"has_genre",
"ACTION"
],
[
"AFTER THE SUNSET",
"has_genre",
"COMEDY"
],
[
"AFTER THE SUNSET",
"release_year",
"2004"
],
[
"AGATA AND THE STORM",
"has_genre",
"COMEDY"
],
[
"AGATA AND THE STORM",
"release_year",
"2004"
],
[
"ALFIE",
"has_genre",
"COMEDY"
],
[
"ALFIE",
"release_year",
"2004"
],
[
"ALL THE QUEEN'S MEN",
"has_genre",
"ACTION"
],
[
"ALL THE QUEEN'S MEN",
"has_genre",
"COMEDY"
],
[
"ALONG CAME POLLY",
"has_genre",
"COMEDY"
],
[
"ALONG CAME POLLY",
"has_tags",
"COMEDY"
],
[
"ALONG CAME POLLY",
"release_year",
"2004"
],
[
"AROUND THE WORLD IN 80 DAYS",
"has_genre",
"COMEDY"
],
[
"AROUND THE WORLD IN 80 DAYS",
"release_year",
"2004"
],
[
"BLAST",
"has_genre",
"ACTION"
],
[
"BLAST",
"has_genre",
"COMEDY"
],
[
"BLAST",
"release_year",
"2004"
],
[
"BLOOD, GUTS, BULLETS AND OCTANE",
"has_genre",
"ACTION"
],
[
"BLOOD, GUTS, BULLETS AND OCTANE",
"has_genre",
"COMEDY"
],
[
"BOOK OF LOVE",
"has_genre",
"COMEDY"
],
[
"BOOK OF LOVE",
"release_year",
"2004"
],
[
"BREAKIN' ALL THE RULES",
"has_genre",
"COMEDY"
],
[
"BREAKIN' ALL THE RULES",
"release_year",
"2004"
],
[
"CATCH THAT KID",
"has_genre",
"COMEDY"
],
[
"CATCH THAT KID",
"release_year",
"2004"
],
[
"CELLULAR",
"has_tags",
"ACTION"
],
[
"CELLULAR",
"release_year",
"2004"
],
[
"CHASING LIBERTY",
"has_genre",
"COMEDY"
],
[
"CHASING LIBERTY",
"release_year",
"2004"
],
[
"CHRISTMAS WITH THE KRANKS",
"has_genre",
"COMEDY"
],
[
"CHRISTMAS WITH THE KRANKS",
"release_year",
"2004"
],
[
"CLUB DREAD",
"has_genre",
"COMEDY"
],
[
"CLUB DREAD",
"release_year",
"2004"
],
[
"CONFESSIONS OF A TEENAGE DRAMA QUEEN",
"has_genre",
"COMEDY"
],
[
"CONFESSIONS OF A TEENAGE DRAMA QUEEN",
"has_tags",
"COMEDY"
],
[
"CONFESSIONS OF A TEENAGE DRAMA QUEEN",
"release_year",
"2004"
],
[
"CONNIE AND CARLA",
"has_genre",
"COMEDY"
],
[
"CONNIE AND CARLA",
"release_year",
"2004"
],
[
"D.E.B.S.",
"has_genre",
"ACTION"
],
[
"D.E.B.S.",
"has_genre",
"COMEDY"
],
[
"D.E.B.S.",
"release_year",
"2004"
],
[
"DORIAN BLUES",
"has_genre",
"COMEDY"
],
[
"DORIAN BLUES",
"release_year",
"2004"
],
[
"DUPLICATE",
"has_genre",
"ACTION"
],
[
"DUPLICATE",
"has_genre",
"COMEDY"
],
[
"ELLA ENCHANTED",
"has_genre",
"COMEDY"
],
[
"ELLA ENCHANTED",
"release_year",
"2004"
],
[
"EMPLOYEE OF THE MONTH",
"has_genre",
"COMEDY"
],
[
"EMPLOYEE OF THE MONTH",
"has_tags",
"COMEDY"
],
[
"EMPLOYEE OF THE MONTH",
"release_year",
"2004"
],
[
"ENVY",
"has_genre",
"COMEDY"
],
[
"ENVY",
"release_year",
"2004"
],
[
"EULOGY",
"has_genre",
"COMEDY"
],
[
"EULOGY",
"release_year",
"2004"
],
[
"EUROTRIP",
"has_genre",
"COMEDY"
],
[
"EUROTRIP",
"has_tags",
"COMEDY"
],
[
"EUROTRIP",
"release_year",
"2004"
],
[
"FAT ALBERT",
"has_genre",
"COMEDY"
],
[
"FAT ALBERT",
"release_year",
"2004"
],
[
"FIRST DAUGHTER",
"has_genre",
"COMEDY"
],
[
"FIRST DAUGHTER",
"release_year",
"2004"
],
[
"FOUR SHADES OF BROWN",
"has_genre",
"COMEDY"
],
[
"FOUR SHADES OF BROWN",
"release_year",
"2004"
],
[
"G.O.R.A.",
"has_genre",
"COMEDY"
],
[
"G.O.R.A.",
"release_year",
"2004"
],
[
"GARDEN STATE",
"has_genre",
"COMEDY"
],
[
"GARDEN STATE",
"release_year",
"2004"
],
[
"GOING THE DISTANCE",
"has_genre",
"COMEDY"
],
[
"GOING THE DISTANCE",
"has_tags",
"COMEDY"
],
[
"GOING THE DISTANCE",
"release_year",
"2004"
],
[
"HAIR SHOW",
"has_genre",
"COMEDY"
],
[
"HAIR SHOW",
"release_year",
"2004"
],
[
"HOME ON THE RANGE",
"has_genre",
"COMEDY"
],
[
"HOME ON THE RANGE",
"release_year",
"2004"
],
[
"HOT FUZZ",
"has_genre",
"COMEDY"
],
[
"HOT FUZZ",
"has_tags",
"ACTION"
],
[
"HOT FUZZ",
"has_tags",
"COMEDY"
],
[
"HUM TUM",
"has_genre",
"COMEDY"
],
[
"HUM TUM",
"has_tags",
"COMEDY"
],
[
"HUM TUM",
"release_year",
"2004"
],
[
"I HEART HUCKABEES",
"has_genre",
"COMEDY"
],
[
"I HEART HUCKABEES",
"has_tags",
"COMEDY"
],
[
"I HEART HUCKABEES",
"release_year",
"2004"
],
[
"IN GOOD COMPANY",
"has_genre",
"COMEDY"
],
[
"IN GOOD COMPANY",
"release_year",
"2004"
],
[
"IT'S ALL GONE PETE TONG",
"has_genre",
"COMEDY"
],
[
"IT'S ALL GONE PETE TONG",
"release_year",
"2004"
],
[
"JERSEY GIRL",
"has_genre",
"COMEDY"
],
[
"JERSEY GIRL",
"has_tags",
"COMEDY"
],
[
"JERSEY GIRL",
"release_year",
"2004"
],
[
"JIMINY GLICK IN LALAWOOD",
"has_genre",
"COMEDY"
],
[
"JIMINY GLICK IN LALAWOOD",
"release_year",
"2004"
],
[
"JOHNSON FAMILY VACATION",
"has_genre",
"COMEDY"
],
[
"JOHNSON FAMILY VACATION",
"release_year",
"2004"
],
[
"KUNG FU HUSTLE",
"has_genre",
"ACTION"
],
[
"KUNG FU HUSTLE",
"has_genre",
"COMEDY"
],
[
"KUNG FU HUSTLE",
"has_tags",
"ACTION"
],
[
"KUNG FU HUSTLE",
"has_tags",
"COMEDY"
],
[
"KUNG FU HUSTLE",
"release_year",
"2004"
],
[
"LAWS OF ATTRACTION",
"has_genre",
"COMEDY"
],
[
"LAWS OF ATTRACTION",
"has_tags",
"COMEDY"
],
[
"LAWS OF ATTRACTION",
"release_year",
"2004"
],
[
"LEMONY SNICKET'S A SERIES OF UNFORTUNATE EVENTS",
"has_genre",
"COMEDY"
],
[
"LEMONY SNICKET'S A SERIES OF UNFORTUNATE EVENTS",
"release_year",
"2004"
],
[
"LITTLE BLACK BOOK",
"has_genre",
"COMEDY"
],
[
"LITTLE BLACK BOOK",
"release_year",
"2004"
],
[
"LOST EMBRACE",
"has_genre",
"COMEDY"
],
[
"LOST EMBRACE",
"release_year",
"2004"
],
[
"LOVE IS ETERNAL WHILE IT LASTS",
"has_genre",
"COMEDY"
],
[
"LOVE IS ETERNAL WHILE IT LASTS",
"release_year",
"2004"
],
[
"MADHOUSE",
"has_genre",
"COMEDY"
],
[
"MADHOUSE",
"release_year",
"2004"
],
[
"MAIN HOON NA",
"has_genre",
"ACTION"
],
[
"MAIN HOON NA",
"has_genre",
"COMEDY"
],
[
"MAIN HOON NA",
"release_year",
"2004"
],
[
"MASH",
"has_genre",
"COMEDY"
],
[
"MASH",
"has_genre",
"WAR"
],
[
"MASH",
"written_by",
"RICHARD HOOKER"
],
[
"MASTI",
"has_genre",
"COMEDY"
],
[
"MASTI",
"release_year",
"2004"
],
[
"MEAN GIRLS",
"has_genre",
"COMEDY"
],
[
"MEAN GIRLS",
"has_tags",
"COMEDY"
],
[
"MEAN GIRLS",
"release_year",
"2004"
],
[
"MEET THE FOCKERS",
"has_genre",
"COMEDY"
],
[
"MEET THE FOCKERS",
"release_year",
"2004"
],
[
"MELINDA AND MELINDA",
"has_genre",
"COMEDY"
],
[
"MELINDA AND MELINDA",
"release_year",
"2004"
],
[
"MILLIONS",
"has_genre",
"COMEDY"
],
[
"MILLIONS",
"release_year",
"2004"
],
[
"MUJHSE SHAADI KAROGI",
"has_genre",
"COMEDY"
],
[
"MUJHSE SHAADI KAROGI",
"release_year",
"2004"
],
[
"MY BABY'S DADDY",
"has_genre",
"COMEDY"
],
[
"MY BABY'S DADDY",
"release_year",
"2004"
],
[
"NAPOLEON DYNAMITE",
"has_genre",
"COMEDY"
],
[
"NAPOLEON DYNAMITE",
"has_tags",
"COMEDY"
],
[
"NAPOLEON DYNAMITE",
"release_year",
"2004"
],
[
"NEW YORK MINUTE",
"has_genre",
"COMEDY"
],
[
"NEW YORK MINUTE",
"release_year",
"2004"
],
[
"OYSTER FARMER",
"has_genre",
"COMEDY"
],
[
"OYSTER FARMER",
"release_year",
"2004"
],
[
"PALINDROMES",
"has_genre",
"COMEDY"
],
[
"PALINDROMES",
"release_year",
"2004"
],
[
"POSTAL",
"has_genre",
"ACTION"
],
[
"POSTAL",
"has_genre",
"COMEDY"
],
[
"RAISING HELEN",
"has_genre",
"COMEDY"
],
[
"RAISING HELEN",
"release_year",
"2004"
],
[
"RINGMASTER",
"has_genre",
"COMEDY"
],
[
"RINGMASTER",
"starred_actors",
"JERRY SPRINGER"
],
[
"RUSH HOUR",
"has_genre",
"ACTION"
],
[
"RUSH HOUR",
"has_genre",
"COMEDY"
],
[
"RUSH HOUR",
"has_tags",
"ACTION"
],
[
"RUSH HOUR",
"has_tags",
"COMEDY"
],
[
"RUSH HOUR 3",
"has_genre",
"ACTION"
],
[
"RUSH HOUR 3",
"has_genre",
"COMEDY"
],
[
"RUSH HOUR 3",
"has_tags",
"COMEDY"
],
[
"SAHARA",
"has_genre",
"ACTION"
],
[
"SAHARA",
"has_genre",
"COMEDY"
],
[
"SAHARA",
"has_tags",
"ACTION"
],
[
"SATAN'S LITTLE HELPER",
"has_genre",
"COMEDY"
],
[
"SATAN'S LITTLE HELPER",
"release_year",
"2004"
],
[
"SAVED!",
"has_genre",
"COMEDY"
],
[
"SAVED!",
"release_year",
"2004"
],
[
"SAVING FACE",
"has_genre",
"COMEDY"
],
[
"SAVING FACE",
"release_year",
"2004"
],
[
"SEE THIS MOVIE",
"has_genre",
"COMEDY"
],
[
"SEE THIS MOVIE",
"release_year",
"2004"
],
[
"SEED OF CHUCKY",
"has_genre",
"COMEDY"
],
[
"SEED OF CHUCKY",
"release_year",
"2004"
],
[
"SEX LIVES OF THE POTATO MEN",
"has_genre",
"COMEDY"
],
[
"SEX LIVES OF THE POTATO MEN",
"release_year",
"2004"
],
[
"SHARK TALE",
"has_genre",
"COMEDY"
],
[
"SHARK TALE",
"release_year",
"2004"
],
[
"SHAUN OF THE DEAD",
"has_genre",
"COMEDY"
],
[
"SHAUN OF THE DEAD",
"has_tags",
"COMEDY"
],
[
"SHAUN OF THE DEAD",
"release_year",
"2004"
],
[
"SHE HATE ME",
"has_genre",
"COMEDY"
],
[
"SHE HATE ME",
"release_year",
"2004"
],
[
"SHERLOCK HOLMES",
"has_genre",
"ACTION"
],
[
"SHERLOCK HOLMES",
"has_tags",
"ACTION"
],
[
"SHERLOCK HOLMES",
"has_tags",
"COMEDY"
],
[
"SHOOT 'EM UP",
"has_genre",
"ACTION"
],
[
"SHOOT 'EM UP",
"has_genre",
"COMEDY"
],
[
"SHREK 2",
"has_genre",
"COMEDY"
],
[
"SHREK 2",
"has_tags",
"COMEDY"
],
[
"SHREK 2",
"release_year",
"2004"
],
[
"SIDEWAYS",
"has_genre",
"COMEDY"
],
[
"SIDEWAYS",
"release_year",
"2004"
],
[
"SIMON",
"has_genre",
"COMEDY"
],
[
"SIMON",
"release_year",
"2004"
],
[
"SIX-STRING SAMURAI",
"has_genre",
"ACTION"
],
[
"SIX-STRING SAMURAI",
"has_genre",
"COMEDY"
],
[
"SMALL SOLDIERS",
"has_genre",
"ACTION"
],
[
"SMALL SOLDIERS",
"has_genre",
"COMEDY"
],
[
"SOUL PLANE",
"has_genre",
"COMEDY"
],
[
"SOUL PLANE",
"release_year",
"2004"
],
[
"SPANGLISH",
"has_genre",
"COMEDY"
],
[
"SPANGLISH",
"release_year",
"2004"
],
[
"SUMMER STORM",
"has_genre",
"COMEDY"
],
[
"SUMMER STORM",
"release_year",
"2004"
],
[
"SURVIVING CHRISTMAS",
"has_genre",
"COMEDY"
],
[
"SURVIVING CHRISTMAS",
"release_year",
"2004"
],
[
"TAXI",
"has_genre",
"ACTION"
],
[
"TAXI",
"has_genre",
"COMEDY"
],
[
"TAXI",
"has_tags",
"COMEDY"
],
[
"TAXI",
"release_year",
"2004"
],
[
"THE BIG BOUNCE",
"has_genre",
"COMEDY"
],
[
"THE BIG BOUNCE",
"release_year",
"2004"
],
[
"THE BIG HIT",
"has_genre",
"ACTION"
],
[
"THE BIG HIT",
"has_genre",
"COMEDY"
],
[
"THE BIG HIT",
"has_tags",
"ACTION"
],
[
"THE BIG HIT",
"has_tags",
"COMEDY"
],
[
"THE BOURNE SUPREMACY",
"has_genre",
"ACTION"
],
[
"THE BOURNE SUPREMACY",
"has_tags",
"ACTION"
],
[
"THE BOURNE SUPREMACY",
"release_year",
"2004"
],
[
"THE CALCIUM KID",
"has_genre",
"COMEDY"
],
[
"THE CALCIUM KID",
"release_year",
"2004"
],
[
"THE COOKOUT",
"has_genre",
"COMEDY"
],
[
"THE COOKOUT",
"release_year",
"2004"
],
[
"THE DEFENDER",
"has_genre",
"ACTION"
],
[
"THE DEFENDER",
"release_year",
"2004"
],
[
"THE DEFENDER",
"starred_actors",
"JERRY SPRINGER"
],
[
"THE GENERAL",
"has_genre",
"ACTION"
],
[
"THE GENERAL",
"has_genre",
"COMEDY"
],
[
"THE GENERAL",
"has_tags",
"COMEDY"
],
[
"THE GOODBYE GIRL",
"has_genre",
"COMEDY"
],
[
"THE GOODBYE GIRL",
"release_year",
"2004"
],
[
"THE INCREDIBLES",
"has_tags",
"COMEDY"
],
[
"THE INCREDIBLES",
"release_year",
"2004"
],
[
"THE INTERVIEW",
"has_genre",
"ACTION"
],
[
"THE INTERVIEW",
"has_genre",
"COMEDY"
],
[
"THE INTERVIEW",
"has_tags",
"COMEDY"
],
[
"THE LADYKILLERS",
"has_genre",
"COMEDY"
],
[
"THE LADYKILLERS",
"has_tags",
"COMEDY"
],
[
"THE LADYKILLERS",
"release_year",
"2004"
],
[
"THE LAST SHOT",
"has_genre",
"COMEDY"
],
[
"THE LAST SHOT",
"release_year",
"2004"
],
[
"THE LIFE AND DEATH OF PETER SELLERS",
"has_genre",
"COMEDY"
],
[
"THE LIFE AND DEATH OF PETER SELLERS",
"release_year",
"2004"
],
[
"THE LIFE AQUATIC WITH STEVE ZISSOU",
"has_genre",
"COMEDY"
],
[
"THE LIFE AQUATIC WITH STEVE ZISSOU",
"has_tags",
"COMEDY"
],
[
"THE LIFE AQUATIC WITH STEVE ZISSOU",
"release_year",
"2004"
],
[
"THE LIZARD",
"has_genre",
"COMEDY"
],
[
"THE LIZARD",
"has_tags",
"COMEDY"
],
[
"THE LIZARD",
"release_year",
"2004"
],
[
"THE NINE LIVES OF TOMAS KATZ",
"has_genre",
"COMEDY"
],
[
"THE PRINCE AND ME",
"has_genre",
"COMEDY"
],
[
"THE PRINCE AND ME",
"release_year",
"2004"
],
[
"THE SPONGEBOB SQUAREPANTS MOVIE",
"has_genre",
"COMEDY"
],
[
"THE SPONGEBOB SQUAREPANTS MOVIE",
"release_year",
"2004"
],
[
"THE STEPFORD WIVES",
"has_genre",
"COMEDY"
],
[
"THE STEPFORD WIVES",
"release_year",
"2004"
],
[
"THE TERMINAL",
"has_genre",
"COMEDY"
],
[
"THE TERMINAL",
"has_tags",
"COMEDY"
],
[
"THE TERMINAL",
"release_year",
"2004"
],
[
"THE WHOLE TEN YARDS",
"has_genre",
"COMEDY"
],
[
"THE WHOLE TEN YARDS",
"release_year",
"2004"
],
[
"TOUCH OF PINK",
"has_genre",
"COMEDY"
],
[
"TOUCH OF PINK",
"has_tags",
"COMEDY"
],
[
"TOUCH OF PINK",
"release_year",
"2004"
],
[
"TROY",
"has_tags",
"ACTION"
],
[
"TROY",
"release_year",
"2004"
],
[
"UNDERDOG",
"has_genre",
"ACTION"
],
[
"UNDERDOG",
"has_genre",
"COMEDY"
],
[
"WAR",
"has_genre",
"ACTION"
],
[
"WELCOME TO MOOSEPORT",
"has_genre",
"COMEDY"
],
[
"WELCOME TO MOOSEPORT",
"release_year",
"2004"
],
[
"WHISKY",
"has_genre",
"COMEDY"
],
[
"WHISKY",
"release_year",
"2004"
],
[
"WHITE CHICKS",
"has_genre",
"COMEDY"
],
[
"WHITE CHICKS",
"has_tags",
"COMEDY"
],
[
"WHITE CHICKS",
"release_year",
"2004"
],
[
"WIMBLEDON",
"has_genre",
"COMEDY"
],
[
"WIMBLEDON",
"release_year",
"2004"
],
[
"WIN A DATE WITH TAD HAMILTON!",
"has_genre",
"COMEDY"
],
[
"WIN A DATE WITH TAD HAMILTON!",
"has_tags",
"COMEDY"
],
[
"WIN A DATE WITH TAD HAMILTON!",
"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
36434, BLIND WOMAN
23134, EILEEN HECKART
17360, JOSÉ CORONADO
13103, NO REST FOR THE WICKED
15262, NO WAY TO TREAT A LADY
24811, THRILLER
499, WAIT UNTIL DARK
src, edge_attr, dst
13103, has_genre, 24811
13103, has_tags, 24811
13103, starred_actors, 17360
15262, has_genre, 24811
15262, starred_actors, 23134
499, has_genre, 24811
499, has_tags, 36434
499, has_tags, 24811
Question: For what reason are BLIND WOMAN, EILEEN HECKART, and JOSÉ CORONADO associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"BLIND WOMAN",
"EILEEN HECKART",
"JOSÉ CORONADO"
],
"valid_edges": [
[
"NO REST FOR THE WICKED",
"has_genre",
"THRILLER"
],
[
"NO REST FOR THE WICKED",
"has_tags",
"THRILLER"
],
[
"NO REST FOR THE WICKED",
"starred_actors",
"JOSÉ CORONADO"
],
[
"NO WAY TO TREAT A LADY",
"has_genre",
"THRILLER"
],
[
"NO WAY TO TREAT A LADY",
"starred_actors",
"EILEEN HECKART"
],
[
"WAIT UNTIL DARK",
"has_genre",
"THRILLER"
],
[
"WAIT UNTIL DARK",
"has_tags",
"BLIND WOMAN"
],
[
"WAIT UNTIL DARK",
"has_tags",
"THRILLER"
]
]
}
|
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
11, 1940
1097, 2003
24715, CAMP
36504, ERIKA CHRISTENSEN
23553, OUR TOWN
37536, SWIMFAN
36649, TORRID ZONE
27708, WUTHERING HEIGHTS
src, edge_attr, dst
24715, release_year, 1097
23553, release_year, 11
23553, release_year, 1097
37536, starred_actors, 36504
36649, release_year, 11
27708, release_year, 1097
27708, starred_actors, 36504
Question: How are CAMP, SWIMFAN, and TORRID ZONE related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"CAMP",
"SWIMFAN",
"TORRID ZONE"
],
"valid_edges": [
[
"CAMP",
"release_year",
"2003"
],
[
"OUR TOWN",
"release_year",
"1940"
],
[
"OUR TOWN",
"release_year",
"2003"
],
[
"SWIMFAN",
"starred_actors",
"ERIKA CHRISTENSEN"
],
[
"TORRID ZONE",
"release_year",
"1940"
],
[
"WUTHERING HEIGHTS",
"release_year",
"2003"
],
[
"WUTHERING HEIGHTS",
"starred_actors",
"ERIKA CHRISTENSEN"
]
]
}
|
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
22088, A BRIDGE TOO FAR
34734, BATTLE OF THE BULGE
25285, COME AND SEE
18972, DAS BOOT
37240, DAVID NIVEN
11363, DEFIANCE
19194, ENIGMA
30030, EUROPA
6480, GERMAN
8287, GREGORY PECK
15765, HAMSUN
15343, IN DARKNESS
38574, IT HAPPENED HERE
22600, JUDGMENT AT NUREMBERG
30157, LOLA
5127, MOTHER NIGHT
38294, MRS. MINIVER
9036, PAISAN
1009, ROBERT STADLOBER
24027, SOLO SUNNY
21196, STALAG 17
11124, STALINGRAD
24987, SUMMER STORM
29788, THE BRIDGE AT REMAGEN
39700, THE DAWN PATROL
10001, THE EAGLE HAS LANDED
6424, THE GREAT ESCAPE
9166, THE GUNS OF NAVARONE
9406, THE IMITATION GAME
27237, THE LONGEST DAY
12614, THE PIANIST
2813, THE SEA WOLVES
4962, THE SORROW AND THE PITY
37831, TOWN WITHOUT PITY
37253, U-571
39558, UNDERGROUND
33011, VALKYRIE
2175, VON RYAN'S EXPRESS
15308, WOLFGANG KOHLHAASE
24155, WORLD WAR II
src, edge_attr, dst
22088, has_tags, 24155
22088, in_language, 6480
34734, has_tags, 24155
34734, in_language, 6480
25285, has_tags, 24155
25285, in_language, 6480
18972, has_tags, 6480
18972, has_tags, 24155
18972, in_language, 6480
11363, has_tags, 24155
11363, in_language, 6480
19194, has_tags, 24155
19194, in_language, 6480
30030, has_tags, 24155
30030, in_language, 6480
15765, has_tags, 24155
15765, in_language, 6480
15343, has_tags, 24155
15343, in_language, 6480
38574, has_tags, 24155
38574, in_language, 6480
22600, in_language, 6480
22600, release_year, 22772
30157, in_language, 6480
30157, release_year, 22772
5127, has_tags, 24155
5127, in_language, 6480
38294, has_tags, 24155
38294, in_language, 6480
9036, has_tags, 24155
9036, in_language, 6480
24027, directed_by, 15308
24027, in_language, 6480
24027, written_by, 15308
21196, has_tags, 24155
21196, in_language, 6480
11124, has_tags, 6480
11124, has_tags, 24155
11124, in_language, 6480
24987, has_tags, 1009
24987, in_language, 6480
24987, starred_actors, 1009
29788, has_tags, 24155
29788, in_language, 6480
39700, in_language, 6480
39700, starred_actors, 37240
10001, has_tags, 6480
10001, has_tags, 24155
10001, in_language, 6480
6424, has_tags, 24155
6424, in_language, 6480
9166, has_tags, 24155
9166, in_language, 6480
9166, release_year, 22772
9166, starred_actors, 37240
9166, starred_actors, 8287
9406, has_tags, 24155
9406, in_language, 6480
27237, has_tags, 24155
27237, in_language, 6480
12614, has_tags, 24155
12614, in_language, 6480
2813, in_language, 6480
2813, starred_actors, 37240
2813, starred_actors, 8287
4962, has_tags, 24155
4962, in_language, 6480
37831, in_language, 6480
37831, release_year, 22772
37253, has_tags, 24155
37253, in_language, 6480
39558, has_tags, 24155
39558, in_language, 6480
33011, has_tags, 24155
33011, in_language, 6480
2175, has_tags, 24155
2175, in_language, 6480
Question: How are ROBERT STADLOBER, THE GUNS OF NAVARONE, and WOLFGANG KOHLHAASE related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"ROBERT STADLOBER",
"THE GUNS OF NAVARONE",
"WOLFGANG KOHLHAASE"
],
"valid_edges": [
[
"A BRIDGE TOO FAR",
"has_tags",
"WORLD WAR II"
],
[
"A BRIDGE TOO FAR",
"in_language",
"GERMAN"
],
[
"BATTLE OF THE BULGE",
"has_tags",
"WORLD WAR II"
],
[
"BATTLE OF THE BULGE",
"in_language",
"GERMAN"
],
[
"COME AND SEE",
"has_tags",
"WORLD WAR II"
],
[
"COME AND SEE",
"in_language",
"GERMAN"
],
[
"DAS BOOT",
"has_tags",
"GERMAN"
],
[
"DAS BOOT",
"has_tags",
"WORLD WAR II"
],
[
"DAS BOOT",
"in_language",
"GERMAN"
],
[
"DEFIANCE",
"has_tags",
"WORLD WAR II"
],
[
"DEFIANCE",
"in_language",
"GERMAN"
],
[
"ENIGMA",
"has_tags",
"WORLD WAR II"
],
[
"ENIGMA",
"in_language",
"GERMAN"
],
[
"EUROPA",
"has_tags",
"WORLD WAR II"
],
[
"EUROPA",
"in_language",
"GERMAN"
],
[
"HAMSUN",
"has_tags",
"WORLD WAR II"
],
[
"HAMSUN",
"in_language",
"GERMAN"
],
[
"IN DARKNESS",
"has_tags",
"WORLD WAR II"
],
[
"IN DARKNESS",
"in_language",
"GERMAN"
],
[
"IT HAPPENED HERE",
"has_tags",
"WORLD WAR II"
],
[
"IT HAPPENED HERE",
"in_language",
"GERMAN"
],
[
"JUDGMENT AT NUREMBERG",
"in_language",
"GERMAN"
],
[
"JUDGMENT AT NUREMBERG",
"release_year",
"1961"
],
[
"LOLA",
"in_language",
"GERMAN"
],
[
"LOLA",
"release_year",
"1961"
],
[
"MOTHER NIGHT",
"has_tags",
"WORLD WAR II"
],
[
"MOTHER NIGHT",
"in_language",
"GERMAN"
],
[
"MRS. MINIVER",
"has_tags",
"WORLD WAR II"
],
[
"MRS. MINIVER",
"in_language",
"GERMAN"
],
[
"PAISAN",
"has_tags",
"WORLD WAR II"
],
[
"PAISAN",
"in_language",
"GERMAN"
],
[
"SOLO SUNNY",
"directed_by",
"WOLFGANG KOHLHAASE"
],
[
"SOLO SUNNY",
"in_language",
"GERMAN"
],
[
"SOLO SUNNY",
"written_by",
"WOLFGANG KOHLHAASE"
],
[
"STALAG 17",
"has_tags",
"WORLD WAR II"
],
[
"STALAG 17",
"in_language",
"GERMAN"
],
[
"STALINGRAD",
"has_tags",
"GERMAN"
],
[
"STALINGRAD",
"has_tags",
"WORLD WAR II"
],
[
"STALINGRAD",
"in_language",
"GERMAN"
],
[
"SUMMER STORM",
"has_tags",
"ROBERT STADLOBER"
],
[
"SUMMER STORM",
"in_language",
"GERMAN"
],
[
"SUMMER STORM",
"starred_actors",
"ROBERT STADLOBER"
],
[
"THE BRIDGE AT REMAGEN",
"has_tags",
"WORLD WAR II"
],
[
"THE BRIDGE AT REMAGEN",
"in_language",
"GERMAN"
],
[
"THE DAWN PATROL",
"in_language",
"GERMAN"
],
[
"THE DAWN PATROL",
"starred_actors",
"DAVID NIVEN"
],
[
"THE EAGLE HAS LANDED",
"has_tags",
"GERMAN"
],
[
"THE EAGLE HAS LANDED",
"has_tags",
"WORLD WAR II"
],
[
"THE EAGLE HAS LANDED",
"in_language",
"GERMAN"
],
[
"THE GREAT ESCAPE",
"has_tags",
"WORLD WAR II"
],
[
"THE GREAT ESCAPE",
"in_language",
"GERMAN"
],
[
"THE GUNS OF NAVARONE",
"has_tags",
"WORLD WAR II"
],
[
"THE GUNS OF NAVARONE",
"in_language",
"GERMAN"
],
[
"THE GUNS OF NAVARONE",
"release_year",
"1961"
],
[
"THE GUNS OF NAVARONE",
"starred_actors",
"DAVID NIVEN"
],
[
"THE GUNS OF NAVARONE",
"starred_actors",
"GREGORY PECK"
],
[
"THE IMITATION GAME",
"has_tags",
"WORLD WAR II"
],
[
"THE IMITATION GAME",
"in_language",
"GERMAN"
],
[
"THE LONGEST DAY",
"has_tags",
"WORLD WAR II"
],
[
"THE LONGEST DAY",
"in_language",
"GERMAN"
],
[
"THE PIANIST",
"has_tags",
"WORLD WAR II"
],
[
"THE PIANIST",
"in_language",
"GERMAN"
],
[
"THE SEA WOLVES",
"in_language",
"GERMAN"
],
[
"THE SEA WOLVES",
"starred_actors",
"DAVID NIVEN"
],
[
"THE SEA WOLVES",
"starred_actors",
"GREGORY PECK"
],
[
"THE SORROW AND THE PITY",
"has_tags",
"WORLD WAR II"
],
[
"THE SORROW AND THE PITY",
"in_language",
"GERMAN"
],
[
"TOWN WITHOUT PITY",
"in_language",
"GERMAN"
],
[
"TOWN WITHOUT PITY",
"release_year",
"1961"
],
[
"U-571",
"has_tags",
"WORLD WAR II"
],
[
"U-571",
"in_language",
"GERMAN"
],
[
"UNDERGROUND",
"has_tags",
"WORLD WAR II"
],
[
"UNDERGROUND",
"in_language",
"GERMAN"
],
[
"VALKYRIE",
"has_tags",
"WORLD WAR II"
],
[
"VALKYRIE",
"in_language",
"GERMAN"
],
[
"VON RYAN'S EXPRESS",
"has_tags",
"WORLD WAR II"
],
[
"VON RYAN'S EXPRESS",
"in_language",
"GERMAN"
]
]
}
|
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
23897, 1942
9152, A STAR IS BORN
20257, ADOLPHE MENJOU
30019, CROSSROADS
22845, MUSIC
37682, ORCHESTRA WIVES
22107, ROCK 'N' ROLL HIGH SCHOOL
20954, ROXIE HART
30160, THE EDDY DUCHIN STORY
19677, YOU WERE NEVER LOVELIER
src, edge_attr, dst
9152, has_genre, 22845
9152, starred_actors, 20257
30019, has_genre, 22845
30019, release_year, 23897
37682, has_genre, 22845
37682, release_year, 23897
22107, has_genre, 22845
20954, release_year, 23897
20954, starred_actors, 20257
30160, has_genre, 22845
19677, release_year, 23897
19677, starred_actors, 20257
Question: In what context are ROCK 'N' ROLL HIGH SCHOOL, THE EDDY DUCHIN STORY, and YOU WERE NEVER LOVELIER connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"ROCK 'N' ROLL HIGH SCHOOL",
"THE EDDY DUCHIN STORY",
"YOU WERE NEVER LOVELIER"
],
"valid_edges": [
[
"A STAR IS BORN",
"has_genre",
"MUSIC"
],
[
"A STAR IS BORN",
"starred_actors",
"ADOLPHE MENJOU"
],
[
"CROSSROADS",
"has_genre",
"MUSIC"
],
[
"CROSSROADS",
"release_year",
"1942"
],
[
"ORCHESTRA WIVES",
"has_genre",
"MUSIC"
],
[
"ORCHESTRA WIVES",
"release_year",
"1942"
],
[
"ROCK 'N' ROLL HIGH SCHOOL",
"has_genre",
"MUSIC"
],
[
"ROXIE HART",
"release_year",
"1942"
],
[
"ROXIE HART",
"starred_actors",
"ADOLPHE MENJOU"
],
[
"THE EDDY DUCHIN STORY",
"has_genre",
"MUSIC"
],
[
"YOU WERE NEVER LOVELIER",
"release_year",
"1942"
],
[
"YOU WERE NEVER LOVELIER",
"starred_actors",
"ADOLPHE MENJOU"
]
]
}
|
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
36279, 10 YEARS
25221, 1981
29424, 2011
23250, 50/50
5158, A BAG OF HAMMERS
35775, A BURNING HOT SUMMER
33013, A LETTER TO MOMO
10158, A PRINCESS FOR CHRISTMAS
29800, ACE ATTORNEY
29816, AIR DOLL
29881, AMERICANO
188, ANOTHER HAPPY DAY
23286, CARNAGE
8520, CHICKEN WITH PLUMS
28503, CLOUDBURST
29904, CONDORMAN
23452, DARK HORSE
6375, DELICACY
24410, DEMONLOVER
14132, DESI BOYZ
36212, DRAMA
1612, FROM UP ON POPPY HILL
17854, GOING DOWN IN LA-LA LAND
6941, GUILTY
22180, HIMIZU
13198, HOLY FLYING CIRCUS
4209, HOUSE OF TOLERANCE
25499, I WISH
21922, JANE EYRE
36874, JAPANESE
37830, JEFF, WHO LIVES AT HOME
39091, KARATE GIRL
4526, KARATE-ROBO ZABORGAR
13594, LA OTRA FAMILIA
15175, LE HAVRE
3800, LOSERS' CLUB
4234, MADEA'S BIG HAPPY FAMILY
19916, MONSIEUR LAZHAR
21686, MOONLIGHT SERENADE
33300, NATURAL SELECTION
20537, NEWLYWEDS
10021, OUR IDIOT BROTHER
8017, PATRIOTISM
5493, POLISSE
39594, REBELLION
674, ROBERT SHECKLEY
12301, SALMON FISHING IN THE YEMEN
18005, TAKE THIS WALTZ
26586, THAT'S WHAT I AM
39795, THE ARTIST
5838, THE CLOWN
11393, THE DESCENDANTS
32295, THE DILEMMA
16031, THE FAIRY
34462, THE FLOWERS OF WAR
24493, THE FUNERAL
7240, THE GIRL WITH THE DRAGON TATTOO
6289, THE INTOUCHABLES
15562, THE ROAD
16308, THE SNOWS OF KILIMANJARO
7816, THE THREE MUSKETEERS
13003, THE WELL-DIGGER'S DAUGHTER
8555, THE WOMAN IN THE FIFTH
5529, THIN ICE
23781, TOMBOY
8957, WE BOUGHT A ZOO
35511, WE HAVE A POPE
33483, WEEKEND
36565, WIN WIN
21449, YOU WILL BE MY SON
11924, YOUNG ADULT
16822, YOUR SISTER'S SISTER
28489, ZINDAGI NA MILEGI DOBARA
src, edge_attr, dst
36279, has_genre, 36212
36279, release_year, 29424
25221, has_genre, 36212
23250, has_genre, 36212
23250, release_year, 29424
5158, has_genre, 36212
5158, release_year, 29424
35775, has_genre, 36212
35775, release_year, 29424
33013, has_genre, 36212
33013, in_language, 36874
33013, release_year, 29424
10158, has_genre, 36212
10158, release_year, 29424
29800, has_genre, 36212
29800, in_language, 36874
29816, has_genre, 36212
29816, in_language, 36874
29881, has_genre, 36212
29881, release_year, 29424
188, has_genre, 36212
188, release_year, 29424
23286, has_genre, 36212
23286, release_year, 29424
8520, has_genre, 36212
8520, release_year, 29424
28503, has_genre, 36212
28503, release_year, 29424
29904, release_year, 25221
29904, written_by, 674
23452, has_genre, 36212
23452, release_year, 29424
6375, has_genre, 36212
6375, release_year, 29424
24410, has_genre, 36212
24410, in_language, 36874
14132, has_genre, 36212
14132, release_year, 29424
1612, has_genre, 36212
1612, in_language, 36874
1612, release_year, 29424
17854, has_genre, 36212
17854, release_year, 29424
6941, has_genre, 36212
6941, has_tags, 36212
6941, release_year, 29424
22180, has_genre, 36212
22180, in_language, 36874
22180, release_year, 29424
13198, has_genre, 36212
13198, release_year, 29424
4209, has_genre, 36212
4209, release_year, 29424
25499, in_language, 36874
25499, release_year, 29424
21922, has_genre, 36212
21922, release_year, 29424
37830, has_genre, 36212
37830, release_year, 29424
39091, in_language, 36874
39091, release_year, 29424
4526, in_language, 36874
4526, release_year, 29424
13594, has_genre, 36212
13594, release_year, 29424
15175, has_genre, 36212
15175, release_year, 29424
3800, has_genre, 36212
3800, release_year, 29424
4234, has_genre, 36212
4234, release_year, 29424
19916, has_genre, 36212
19916, release_year, 29424
21686, has_genre, 36212
21686, in_language, 36874
33300, has_genre, 36212
33300, release_year, 29424
20537, has_genre, 36212
20537, release_year, 29424
10021, has_genre, 36212
10021, release_year, 29424
8017, in_language, 36874
5493, has_genre, 36212
5493, release_year, 29424
39594, has_genre, 36212
39594, release_year, 29424
12301, has_genre, 36212
12301, release_year, 29424
18005, has_genre, 36212
18005, release_year, 29424
26586, has_genre, 36212
26586, release_year, 29424
39795, has_genre, 36212
39795, has_tags, 36212
39795, release_year, 29424
5838, has_genre, 36212
5838, release_year, 29424
11393, has_genre, 36212
11393, has_tags, 36212
11393, release_year, 29424
32295, has_genre, 36212
32295, release_year, 29424
16031, has_genre, 36212
16031, release_year, 29424
34462, has_genre, 36212
34462, in_language, 36874
34462, release_year, 29424
24493, has_genre, 36212
24493, in_language, 36874
7240, has_genre, 36212
7240, release_year, 29424
6289, has_genre, 36212
6289, release_year, 29424
15562, has_genre, 36212
15562, release_year, 29424
16308, has_genre, 36212
16308, release_year, 29424
7816, has_genre, 36212
7816, release_year, 29424
13003, has_genre, 36212
13003, release_year, 29424
8555, has_genre, 36212
8555, release_year, 29424
5529, has_genre, 36212
5529, release_year, 29424
23781, has_genre, 36212
23781, release_year, 29424
8957, has_genre, 36212
8957, release_year, 29424
35511, has_genre, 36212
35511, release_year, 29424
33483, has_genre, 36212
33483, release_year, 29424
36565, has_genre, 36212
36565, release_year, 29424
21449, has_genre, 36212
21449, release_year, 29424
11924, has_genre, 36212
11924, has_tags, 36212
11924, release_year, 29424
16822, has_genre, 36212
16822, release_year, 29424
28489, has_genre, 36212
28489, release_year, 29424
Question: How are LA OTRA FAMILIA, PATRIOTISM, and ROBERT SHECKLEY related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"LA OTRA FAMILIA",
"PATRIOTISM",
"ROBERT SHECKLEY"
],
"valid_edges": [
[
"10 YEARS",
"has_genre",
"DRAMA"
],
[
"10 YEARS",
"release_year",
"2011"
],
[
"1981",
"has_genre",
"DRAMA"
],
[
"50/50",
"has_genre",
"DRAMA"
],
[
"50/50",
"release_year",
"2011"
],
[
"A BAG OF HAMMERS",
"has_genre",
"DRAMA"
],
[
"A BAG OF HAMMERS",
"release_year",
"2011"
],
[
"A BURNING HOT SUMMER",
"has_genre",
"DRAMA"
],
[
"A BURNING HOT SUMMER",
"release_year",
"2011"
],
[
"A LETTER TO MOMO",
"has_genre",
"DRAMA"
],
[
"A LETTER TO MOMO",
"in_language",
"JAPANESE"
],
[
"A LETTER TO MOMO",
"release_year",
"2011"
],
[
"A PRINCESS FOR CHRISTMAS",
"has_genre",
"DRAMA"
],
[
"A PRINCESS FOR CHRISTMAS",
"release_year",
"2011"
],
[
"ACE ATTORNEY",
"has_genre",
"DRAMA"
],
[
"ACE ATTORNEY",
"in_language",
"JAPANESE"
],
[
"AIR DOLL",
"has_genre",
"DRAMA"
],
[
"AIR DOLL",
"in_language",
"JAPANESE"
],
[
"AMERICANO",
"has_genre",
"DRAMA"
],
[
"AMERICANO",
"release_year",
"2011"
],
[
"ANOTHER HAPPY DAY",
"has_genre",
"DRAMA"
],
[
"ANOTHER HAPPY DAY",
"release_year",
"2011"
],
[
"CARNAGE",
"has_genre",
"DRAMA"
],
[
"CARNAGE",
"release_year",
"2011"
],
[
"CHICKEN WITH PLUMS",
"has_genre",
"DRAMA"
],
[
"CHICKEN WITH PLUMS",
"release_year",
"2011"
],
[
"CLOUDBURST",
"has_genre",
"DRAMA"
],
[
"CLOUDBURST",
"release_year",
"2011"
],
[
"CONDORMAN",
"release_year",
"1981"
],
[
"CONDORMAN",
"written_by",
"ROBERT SHECKLEY"
],
[
"DARK HORSE",
"has_genre",
"DRAMA"
],
[
"DARK HORSE",
"release_year",
"2011"
],
[
"DELICACY",
"has_genre",
"DRAMA"
],
[
"DELICACY",
"release_year",
"2011"
],
[
"DEMONLOVER",
"has_genre",
"DRAMA"
],
[
"DEMONLOVER",
"in_language",
"JAPANESE"
],
[
"DESI BOYZ",
"has_genre",
"DRAMA"
],
[
"DESI BOYZ",
"release_year",
"2011"
],
[
"FROM UP ON POPPY HILL",
"has_genre",
"DRAMA"
],
[
"FROM UP ON POPPY HILL",
"in_language",
"JAPANESE"
],
[
"FROM UP ON POPPY HILL",
"release_year",
"2011"
],
[
"GOING DOWN IN LA-LA LAND",
"has_genre",
"DRAMA"
],
[
"GOING DOWN IN LA-LA LAND",
"release_year",
"2011"
],
[
"GUILTY",
"has_genre",
"DRAMA"
],
[
"GUILTY",
"has_tags",
"DRAMA"
],
[
"GUILTY",
"release_year",
"2011"
],
[
"HIMIZU",
"has_genre",
"DRAMA"
],
[
"HIMIZU",
"in_language",
"JAPANESE"
],
[
"HIMIZU",
"release_year",
"2011"
],
[
"HOLY FLYING CIRCUS",
"has_genre",
"DRAMA"
],
[
"HOLY FLYING CIRCUS",
"release_year",
"2011"
],
[
"HOUSE OF TOLERANCE",
"has_genre",
"DRAMA"
],
[
"HOUSE OF TOLERANCE",
"release_year",
"2011"
],
[
"I WISH",
"in_language",
"JAPANESE"
],
[
"I WISH",
"release_year",
"2011"
],
[
"JANE EYRE",
"has_genre",
"DRAMA"
],
[
"JANE EYRE",
"release_year",
"2011"
],
[
"JEFF, WHO LIVES AT HOME",
"has_genre",
"DRAMA"
],
[
"JEFF, WHO LIVES AT HOME",
"release_year",
"2011"
],
[
"KARATE GIRL",
"in_language",
"JAPANESE"
],
[
"KARATE GIRL",
"release_year",
"2011"
],
[
"KARATE-ROBO ZABORGAR",
"in_language",
"JAPANESE"
],
[
"KARATE-ROBO ZABORGAR",
"release_year",
"2011"
],
[
"LA OTRA FAMILIA",
"has_genre",
"DRAMA"
],
[
"LA OTRA FAMILIA",
"release_year",
"2011"
],
[
"LE HAVRE",
"has_genre",
"DRAMA"
],
[
"LE HAVRE",
"release_year",
"2011"
],
[
"LOSERS' CLUB",
"has_genre",
"DRAMA"
],
[
"LOSERS' CLUB",
"release_year",
"2011"
],
[
"MADEA'S BIG HAPPY FAMILY",
"has_genre",
"DRAMA"
],
[
"MADEA'S BIG HAPPY FAMILY",
"release_year",
"2011"
],
[
"MONSIEUR LAZHAR",
"has_genre",
"DRAMA"
],
[
"MONSIEUR LAZHAR",
"release_year",
"2011"
],
[
"MOONLIGHT SERENADE",
"has_genre",
"DRAMA"
],
[
"MOONLIGHT SERENADE",
"in_language",
"JAPANESE"
],
[
"NATURAL SELECTION",
"has_genre",
"DRAMA"
],
[
"NATURAL SELECTION",
"release_year",
"2011"
],
[
"NEWLYWEDS",
"has_genre",
"DRAMA"
],
[
"NEWLYWEDS",
"release_year",
"2011"
],
[
"OUR IDIOT BROTHER",
"has_genre",
"DRAMA"
],
[
"OUR IDIOT BROTHER",
"release_year",
"2011"
],
[
"PATRIOTISM",
"in_language",
"JAPANESE"
],
[
"POLISSE",
"has_genre",
"DRAMA"
],
[
"POLISSE",
"release_year",
"2011"
],
[
"REBELLION",
"has_genre",
"DRAMA"
],
[
"REBELLION",
"release_year",
"2011"
],
[
"SALMON FISHING IN THE YEMEN",
"has_genre",
"DRAMA"
],
[
"SALMON FISHING IN THE YEMEN",
"release_year",
"2011"
],
[
"TAKE THIS WALTZ",
"has_genre",
"DRAMA"
],
[
"TAKE THIS WALTZ",
"release_year",
"2011"
],
[
"THAT'S WHAT I AM",
"has_genre",
"DRAMA"
],
[
"THAT'S WHAT I AM",
"release_year",
"2011"
],
[
"THE ARTIST",
"has_genre",
"DRAMA"
],
[
"THE ARTIST",
"has_tags",
"DRAMA"
],
[
"THE ARTIST",
"release_year",
"2011"
],
[
"THE CLOWN",
"has_genre",
"DRAMA"
],
[
"THE CLOWN",
"release_year",
"2011"
],
[
"THE DESCENDANTS",
"has_genre",
"DRAMA"
],
[
"THE DESCENDANTS",
"has_tags",
"DRAMA"
],
[
"THE DESCENDANTS",
"release_year",
"2011"
],
[
"THE DILEMMA",
"has_genre",
"DRAMA"
],
[
"THE DILEMMA",
"release_year",
"2011"
],
[
"THE FAIRY",
"has_genre",
"DRAMA"
],
[
"THE FAIRY",
"release_year",
"2011"
],
[
"THE FLOWERS OF WAR",
"has_genre",
"DRAMA"
],
[
"THE FLOWERS OF WAR",
"in_language",
"JAPANESE"
],
[
"THE FLOWERS OF WAR",
"release_year",
"2011"
],
[
"THE FUNERAL",
"has_genre",
"DRAMA"
],
[
"THE FUNERAL",
"in_language",
"JAPANESE"
],
[
"THE GIRL WITH THE DRAGON TATTOO",
"has_genre",
"DRAMA"
],
[
"THE GIRL WITH THE DRAGON TATTOO",
"release_year",
"2011"
],
[
"THE INTOUCHABLES",
"has_genre",
"DRAMA"
],
[
"THE INTOUCHABLES",
"release_year",
"2011"
],
[
"THE ROAD",
"has_genre",
"DRAMA"
],
[
"THE ROAD",
"release_year",
"2011"
],
[
"THE SNOWS OF KILIMANJARO",
"has_genre",
"DRAMA"
],
[
"THE SNOWS OF KILIMANJARO",
"release_year",
"2011"
],
[
"THE THREE MUSKETEERS",
"has_genre",
"DRAMA"
],
[
"THE THREE MUSKETEERS",
"release_year",
"2011"
],
[
"THE WELL-DIGGER'S DAUGHTER",
"has_genre",
"DRAMA"
],
[
"THE WELL-DIGGER'S DAUGHTER",
"release_year",
"2011"
],
[
"THE WOMAN IN THE FIFTH",
"has_genre",
"DRAMA"
],
[
"THE WOMAN IN THE FIFTH",
"release_year",
"2011"
],
[
"THIN ICE",
"has_genre",
"DRAMA"
],
[
"THIN ICE",
"release_year",
"2011"
],
[
"TOMBOY",
"has_genre",
"DRAMA"
],
[
"TOMBOY",
"release_year",
"2011"
],
[
"WE BOUGHT A ZOO",
"has_genre",
"DRAMA"
],
[
"WE BOUGHT A ZOO",
"release_year",
"2011"
],
[
"WE HAVE A POPE",
"has_genre",
"DRAMA"
],
[
"WE HAVE A POPE",
"release_year",
"2011"
],
[
"WEEKEND",
"has_genre",
"DRAMA"
],
[
"WEEKEND",
"release_year",
"2011"
],
[
"WIN WIN",
"has_genre",
"DRAMA"
],
[
"WIN WIN",
"release_year",
"2011"
],
[
"YOU WILL BE MY SON",
"has_genre",
"DRAMA"
],
[
"YOU WILL BE MY SON",
"release_year",
"2011"
],
[
"YOUNG ADULT",
"has_genre",
"DRAMA"
],
[
"YOUNG ADULT",
"has_tags",
"DRAMA"
],
[
"YOUNG ADULT",
"release_year",
"2011"
],
[
"YOUR SISTER'S SISTER",
"has_genre",
"DRAMA"
],
[
"YOUR SISTER'S SISTER",
"release_year",
"2011"
],
[
"ZINDAGI NA MILEGI DOBARA",
"has_genre",
"DRAMA"
],
[
"ZINDAGI NA MILEGI DOBARA",
"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
30172, 1964
30261, A CAROL FOR ANOTHER CHRISTMAS
4269, A HARD DAY'S NIGHT
21572, ACCATTONE
28463, AFTER THE FOX
8848, ALL THE LIGHT IN THE SKY
17157, ARABIAN NIGHTS
10045, BD-R
38657, BEAT THE DEVIL
22030, BEFORE THE REVOLUTION
8139, BICYCLE THIEVES
19992, BIG DEAL ON MADONNA STREET
39539, BLOOD AND BLACK LACE
32075, BURN!
12227, CASTLE OF BLOOD
7432, CHEYENNE AUTUMN
34792, CONTEMPT
29300, DEAD RINGER
34004, FAIL SAFE
7157, FIRST MEN IN THE MOON
19696, GIRL WITH GREEN EYES
20941, HAMLET
17344, I VITELLONI
16200, ITALIAN
30236, JOE SWANBERG
4285, KISS ME, STUPID
38326, L'ECLISSE
20913, LA STRADA
27312, MAIL ORDER BRIDE
13074, MARRIAGE ITALIAN STYLE
31661, MY FAIR LADY
24745, PURPLE NOON
23686, RED DESERT
24744, ROCCO AND HIS BROTHERS
29931, ROME, OPEN CITY
35586, SAHARA
14486, SANTA CLAUS CONQUERS THE MARTIANS
24232, SEND ME NO FLOWERS
9936, SEVEN DAYS IN MAY
6119, SLEUTH
8436, SPIRITS OF THE DEAD
24045, STRAIT-JACKET
4157, THE BEST MAN
17385, THE CAT O' NINE TAILS
13352, THE FLOWERS OF ST. FRANCIS
21435, THE GOOD, THE BAD AND THE UGLY
14382, THE GORGON
11668, THE GOSPEL ACCORDING TO ST. MATTHEW
25818, THE INCREDIBLE MR. LIMPET
1443, THE ITALIAN JOB
27885, THE KILLERS
11243, THE MASQUE OF THE RED DEATH
34829, THE NIGHT OF THE IGUANA
25850, THE PAWNBROKER
18274, THE ROSE TATTOO
17143, THE STRANGER
593, THE THIEF OF BAGDAD
38808, THE TRAIN
29678, THE UMBRELLAS OF CHERBOURG
35956, THE UNSINKABLE MOLLY BROWN
39026, TWO WOMEN
31252, V/H/S
16996, ZORBA THE GREEK
src, edge_attr, dst
30261, has_tags, 10045
30261, release_year, 30172
4269, has_tags, 10045
4269, release_year, 30172
21572, has_tags, 10045
21572, in_language, 16200
28463, has_tags, 10045
28463, in_language, 16200
8848, directed_by, 30236
8848, written_by, 30236
17157, has_tags, 10045
17157, in_language, 16200
38657, has_tags, 10045
38657, in_language, 16200
22030, in_language, 16200
22030, release_year, 30172
8139, has_tags, 10045
8139, has_tags, 16200
8139, in_language, 16200
19992, has_tags, 10045
19992, in_language, 16200
39539, in_language, 16200
39539, release_year, 30172
32075, has_tags, 10045
32075, in_language, 16200
12227, in_language, 16200
12227, release_year, 30172
7432, has_tags, 10045
7432, release_year, 30172
34792, has_tags, 10045
34792, in_language, 16200
29300, has_tags, 10045
29300, release_year, 30172
34004, has_tags, 10045
34004, release_year, 30172
7157, has_tags, 10045
7157, release_year, 30172
19696, has_tags, 10045
19696, release_year, 30172
20941, has_tags, 10045
20941, release_year, 30172
17344, has_tags, 10045
17344, has_tags, 16200
17344, in_language, 16200
4285, has_tags, 10045
4285, release_year, 30172
38326, has_tags, 10045
38326, in_language, 16200
20913, has_tags, 10045
20913, has_tags, 16200
20913, in_language, 16200
27312, has_tags, 10045
27312, release_year, 30172
13074, in_language, 16200
13074, release_year, 30172
31661, has_tags, 10045
31661, release_year, 30172
24745, has_tags, 10045
24745, in_language, 16200
23686, in_language, 16200
23686, release_year, 30172
24744, has_tags, 10045
24744, in_language, 16200
29931, has_tags, 10045
29931, in_language, 16200
35586, has_tags, 10045
35586, in_language, 16200
14486, has_tags, 10045
14486, release_year, 30172
24232, has_tags, 10045
24232, release_year, 30172
9936, has_tags, 10045
9936, release_year, 30172
6119, has_tags, 10045
6119, in_language, 16200
8436, has_tags, 10045
8436, in_language, 16200
24045, has_tags, 10045
24045, release_year, 30172
4157, in_language, 16200
4157, release_year, 30172
17385, has_tags, 10045
17385, in_language, 16200
13352, has_tags, 10045
13352, in_language, 16200
21435, has_tags, 10045
21435, has_tags, 16200
21435, in_language, 16200
14382, has_tags, 10045
14382, release_year, 30172
11668, in_language, 16200
11668, release_year, 30172
25818, has_tags, 10045
25818, release_year, 30172
1443, has_tags, 10045
1443, has_tags, 16200
1443, in_language, 16200
27885, has_tags, 10045
27885, release_year, 30172
11243, has_tags, 10045
11243, release_year, 30172
34829, has_tags, 10045
34829, release_year, 30172
25850, has_tags, 10045
25850, release_year, 30172
18274, has_tags, 10045
18274, in_language, 16200
17143, has_tags, 10045
17143, in_language, 16200
593, has_tags, 10045
38808, has_tags, 10045
38808, release_year, 30172
29678, has_tags, 10045
29678, release_year, 30172
35956, has_tags, 10045
35956, release_year, 30172
39026, has_tags, 10045
39026, has_tags, 16200
39026, in_language, 16200
31252, directed_by, 30236
31252, has_tags, 10045
31252, has_tags, 30236
16996, has_tags, 10045
16996, release_year, 30172
Question: For what reason are ALL THE LIGHT IN THE SKY, MARRIAGE ITALIAN STYLE, and THE THIEF OF BAGDAD associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"ALL THE LIGHT IN THE SKY",
"MARRIAGE ITALIAN STYLE",
"THE THIEF OF BAGDAD"
],
"valid_edges": [
[
"A CAROL FOR ANOTHER CHRISTMAS",
"has_tags",
"BD-R"
],
[
"A CAROL FOR ANOTHER CHRISTMAS",
"release_year",
"1964"
],
[
"A HARD DAY'S NIGHT",
"has_tags",
"BD-R"
],
[
"A HARD DAY'S NIGHT",
"release_year",
"1964"
],
[
"ACCATTONE",
"has_tags",
"BD-R"
],
[
"ACCATTONE",
"in_language",
"ITALIAN"
],
[
"AFTER THE FOX",
"has_tags",
"BD-R"
],
[
"AFTER THE FOX",
"in_language",
"ITALIAN"
],
[
"ALL THE LIGHT IN THE SKY",
"directed_by",
"JOE SWANBERG"
],
[
"ALL THE LIGHT IN THE SKY",
"written_by",
"JOE SWANBERG"
],
[
"ARABIAN NIGHTS",
"has_tags",
"BD-R"
],
[
"ARABIAN NIGHTS",
"in_language",
"ITALIAN"
],
[
"BEAT THE DEVIL",
"has_tags",
"BD-R"
],
[
"BEAT THE DEVIL",
"in_language",
"ITALIAN"
],
[
"BEFORE THE REVOLUTION",
"in_language",
"ITALIAN"
],
[
"BEFORE THE REVOLUTION",
"release_year",
"1964"
],
[
"BICYCLE THIEVES",
"has_tags",
"BD-R"
],
[
"BICYCLE THIEVES",
"has_tags",
"ITALIAN"
],
[
"BICYCLE THIEVES",
"in_language",
"ITALIAN"
],
[
"BIG DEAL ON MADONNA STREET",
"has_tags",
"BD-R"
],
[
"BIG DEAL ON MADONNA STREET",
"in_language",
"ITALIAN"
],
[
"BLOOD AND BLACK LACE",
"in_language",
"ITALIAN"
],
[
"BLOOD AND BLACK LACE",
"release_year",
"1964"
],
[
"BURN!",
"has_tags",
"BD-R"
],
[
"BURN!",
"in_language",
"ITALIAN"
],
[
"CASTLE OF BLOOD",
"in_language",
"ITALIAN"
],
[
"CASTLE OF BLOOD",
"release_year",
"1964"
],
[
"CHEYENNE AUTUMN",
"has_tags",
"BD-R"
],
[
"CHEYENNE AUTUMN",
"release_year",
"1964"
],
[
"CONTEMPT",
"has_tags",
"BD-R"
],
[
"CONTEMPT",
"in_language",
"ITALIAN"
],
[
"DEAD RINGER",
"has_tags",
"BD-R"
],
[
"DEAD RINGER",
"release_year",
"1964"
],
[
"FAIL SAFE",
"has_tags",
"BD-R"
],
[
"FAIL SAFE",
"release_year",
"1964"
],
[
"FIRST MEN IN THE MOON",
"has_tags",
"BD-R"
],
[
"FIRST MEN IN THE MOON",
"release_year",
"1964"
],
[
"GIRL WITH GREEN EYES",
"has_tags",
"BD-R"
],
[
"GIRL WITH GREEN EYES",
"release_year",
"1964"
],
[
"HAMLET",
"has_tags",
"BD-R"
],
[
"HAMLET",
"release_year",
"1964"
],
[
"I VITELLONI",
"has_tags",
"BD-R"
],
[
"I VITELLONI",
"has_tags",
"ITALIAN"
],
[
"I VITELLONI",
"in_language",
"ITALIAN"
],
[
"KISS ME, STUPID",
"has_tags",
"BD-R"
],
[
"KISS ME, STUPID",
"release_year",
"1964"
],
[
"L'ECLISSE",
"has_tags",
"BD-R"
],
[
"L'ECLISSE",
"in_language",
"ITALIAN"
],
[
"LA STRADA",
"has_tags",
"BD-R"
],
[
"LA STRADA",
"has_tags",
"ITALIAN"
],
[
"LA STRADA",
"in_language",
"ITALIAN"
],
[
"MAIL ORDER BRIDE",
"has_tags",
"BD-R"
],
[
"MAIL ORDER BRIDE",
"release_year",
"1964"
],
[
"MARRIAGE ITALIAN STYLE",
"in_language",
"ITALIAN"
],
[
"MARRIAGE ITALIAN STYLE",
"release_year",
"1964"
],
[
"MY FAIR LADY",
"has_tags",
"BD-R"
],
[
"MY FAIR LADY",
"release_year",
"1964"
],
[
"PURPLE NOON",
"has_tags",
"BD-R"
],
[
"PURPLE NOON",
"in_language",
"ITALIAN"
],
[
"RED DESERT",
"in_language",
"ITALIAN"
],
[
"RED DESERT",
"release_year",
"1964"
],
[
"ROCCO AND HIS BROTHERS",
"has_tags",
"BD-R"
],
[
"ROCCO AND HIS BROTHERS",
"in_language",
"ITALIAN"
],
[
"ROME, OPEN CITY",
"has_tags",
"BD-R"
],
[
"ROME, OPEN CITY",
"in_language",
"ITALIAN"
],
[
"SAHARA",
"has_tags",
"BD-R"
],
[
"SAHARA",
"in_language",
"ITALIAN"
],
[
"SANTA CLAUS CONQUERS THE MARTIANS",
"has_tags",
"BD-R"
],
[
"SANTA CLAUS CONQUERS THE MARTIANS",
"release_year",
"1964"
],
[
"SEND ME NO FLOWERS",
"has_tags",
"BD-R"
],
[
"SEND ME NO FLOWERS",
"release_year",
"1964"
],
[
"SEVEN DAYS IN MAY",
"has_tags",
"BD-R"
],
[
"SEVEN DAYS IN MAY",
"release_year",
"1964"
],
[
"SLEUTH",
"has_tags",
"BD-R"
],
[
"SLEUTH",
"in_language",
"ITALIAN"
],
[
"SPIRITS OF THE DEAD",
"has_tags",
"BD-R"
],
[
"SPIRITS OF THE DEAD",
"in_language",
"ITALIAN"
],
[
"STRAIT-JACKET",
"has_tags",
"BD-R"
],
[
"STRAIT-JACKET",
"release_year",
"1964"
],
[
"THE BEST MAN",
"in_language",
"ITALIAN"
],
[
"THE BEST MAN",
"release_year",
"1964"
],
[
"THE CAT O' NINE TAILS",
"has_tags",
"BD-R"
],
[
"THE CAT O' NINE TAILS",
"in_language",
"ITALIAN"
],
[
"THE FLOWERS OF ST. FRANCIS",
"has_tags",
"BD-R"
],
[
"THE FLOWERS OF ST. FRANCIS",
"in_language",
"ITALIAN"
],
[
"THE GOOD, THE BAD AND THE UGLY",
"has_tags",
"BD-R"
],
[
"THE GOOD, THE BAD AND THE UGLY",
"has_tags",
"ITALIAN"
],
[
"THE GOOD, THE BAD AND THE UGLY",
"in_language",
"ITALIAN"
],
[
"THE GORGON",
"has_tags",
"BD-R"
],
[
"THE GORGON",
"release_year",
"1964"
],
[
"THE GOSPEL ACCORDING TO ST. MATTHEW",
"in_language",
"ITALIAN"
],
[
"THE GOSPEL ACCORDING TO ST. MATTHEW",
"release_year",
"1964"
],
[
"THE INCREDIBLE MR. LIMPET",
"has_tags",
"BD-R"
],
[
"THE INCREDIBLE MR. LIMPET",
"release_year",
"1964"
],
[
"THE ITALIAN JOB",
"has_tags",
"BD-R"
],
[
"THE ITALIAN JOB",
"has_tags",
"ITALIAN"
],
[
"THE ITALIAN JOB",
"in_language",
"ITALIAN"
],
[
"THE KILLERS",
"has_tags",
"BD-R"
],
[
"THE KILLERS",
"release_year",
"1964"
],
[
"THE MASQUE OF THE RED DEATH",
"has_tags",
"BD-R"
],
[
"THE MASQUE OF THE RED DEATH",
"release_year",
"1964"
],
[
"THE NIGHT OF THE IGUANA",
"has_tags",
"BD-R"
],
[
"THE NIGHT OF THE IGUANA",
"release_year",
"1964"
],
[
"THE PAWNBROKER",
"has_tags",
"BD-R"
],
[
"THE PAWNBROKER",
"release_year",
"1964"
],
[
"THE ROSE TATTOO",
"has_tags",
"BD-R"
],
[
"THE ROSE TATTOO",
"in_language",
"ITALIAN"
],
[
"THE STRANGER",
"has_tags",
"BD-R"
],
[
"THE STRANGER",
"in_language",
"ITALIAN"
],
[
"THE THIEF OF BAGDAD",
"has_tags",
"BD-R"
],
[
"THE TRAIN",
"has_tags",
"BD-R"
],
[
"THE TRAIN",
"release_year",
"1964"
],
[
"THE UMBRELLAS OF CHERBOURG",
"has_tags",
"BD-R"
],
[
"THE UMBRELLAS OF CHERBOURG",
"release_year",
"1964"
],
[
"THE UNSINKABLE MOLLY BROWN",
"has_tags",
"BD-R"
],
[
"THE UNSINKABLE MOLLY BROWN",
"release_year",
"1964"
],
[
"TWO WOMEN",
"has_tags",
"BD-R"
],
[
"TWO WOMEN",
"has_tags",
"ITALIAN"
],
[
"TWO WOMEN",
"in_language",
"ITALIAN"
],
[
"V/H/S",
"directed_by",
"JOE SWANBERG"
],
[
"V/H/S",
"has_tags",
"BD-R"
],
[
"V/H/S",
"has_tags",
"JOE SWANBERG"
],
[
"ZORBA THE GREEK",
"has_tags",
"BD-R"
],
[
"ZORBA THE GREEK",
"release_year",
"1964"
]
]
}
|
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
9790, BLAKE EDWARDS
15662, EARL MILLS
35347, HIGH TIME
38552, INTRODUCING DOROTHY DANDRIDGE
30183, JOHN BROPHY
22845, MUSIC
28600, THE DAY THEY ROBBED THE BANK OF ENGLAND
32562, VICTOR VICTORIA
src, edge_attr, dst
35347, directed_by, 9790
35347, release_year, 18366
38552, has_genre, 22845
38552, written_by, 15662
28600, release_year, 18366
28600, written_by, 30183
32562, directed_by, 9790
32562, has_genre, 22845
32562, has_tags, 9790
32562, written_by, 9790
Question: How are BLAKE EDWARDS, EARL MILLS, and JOHN BROPHY related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"BLAKE EDWARDS",
"EARL MILLS",
"JOHN BROPHY"
],
"valid_edges": [
[
"HIGH TIME",
"directed_by",
"BLAKE EDWARDS"
],
[
"HIGH TIME",
"release_year",
"1960"
],
[
"INTRODUCING DOROTHY DANDRIDGE",
"has_genre",
"MUSIC"
],
[
"INTRODUCING DOROTHY DANDRIDGE",
"written_by",
"EARL MILLS"
],
[
"THE DAY THEY ROBBED THE BANK OF ENGLAND",
"release_year",
"1960"
],
[
"THE DAY THEY ROBBED THE BANK OF ENGLAND",
"written_by",
"JOHN BROPHY"
],
[
"VICTOR VICTORIA",
"directed_by",
"BLAKE EDWARDS"
],
[
"VICTOR VICTORIA",
"has_genre",
"MUSIC"
],
[
"VICTOR VICTORIA",
"has_tags",
"BLAKE EDWARDS"
],
[
"VICTOR VICTORIA",
"written_by",
"BLAKE EDWARDS"
]
]
}
|
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
17737, 12 ANGRY MEN
26399, 12 STOREYS
14259, 1997
2566, A BETTER PLACE
30146, A CHRISTMAS CAROL
20629, A SINGLE SHOT
14986, A THOUSAND ACRES
15136, AFFLICTION
9313, ALL OVER ME
7983, AMERICAN PERFEKT
20480, AMISTAD
21856, ANASTASIA
36963, ANNA KARENINA
23952, BANDITS
15240, BENT
25930, BETTER LIVING THROUGH CHEMISTRY
2217, BOOGIE NIGHTS
22919, BROADWAY DAMAGE
314, BUUD YAM
33121, CAREER GIRLS
31459, CHILDREN OF HEAVEN
2869, CLOCKWATCHERS
7142, COMANCHE TERRITORY
22452, COMMANDMENTS
2859, CONTACT
18235, CONVICTION
6871, COP LAND
5726, DEFYING GRAVITY
38834, DESTINY
15892, DONNIE BRASCO
36212, DRAMA
30833, DÉJÀ VU
26106, END OF WATCH
16328, EVE'S BAYOU
23387, EVERYBODY'S FINE
20378, FACE
18446, FEVER PITCH
5829, FIRE DOWN BELOW
21606, FLIRTING
35150, FRIED GREEN TOMATOES
34449, FRIENDSHIP
31224, G.I. JANE
22311, GANG RELATED
12664, GHOST WORLD
26708, GOOD WILL HUNTING
30479, GRIDLOCK'D
37982, GUMMO
7879, HALF NELSON
4840, HEAD IN THE CLOUDS
4464, HOODLUM
16164, HURRICANE STREETS
31481, ISHQ
19868, JACK FROST
19939, JACKIE BROWN
26410, JEFFREY CAINE
17974, JOHN DUIGAN
31226, JULIE JOHNSON
4447, LAWN DOGS
24419, LIFE IS BEAUTIFUL
233, LIVE FLESH
15322, LOLITA
22386, LOST AND DELIRIOUS
31294, LOVE JONES
21344, LOVE WALKED IN
18198, MATCHSTICK MEN
14102, MEN WITH GUNS
31515, METROLAND
995, MIDNIGHT IN THE GARDEN OF GOOD AND EVIL
12246, MISCHA BARTON
19598, MOLLY
32149, MOON
21686, MOONLIGHT SERENADE
22938, MOTHER AND SON
693, MRS DALLOWAY
6767, MY SON THE FANATIC
2624, NIL BY MOUTH
34420, NOWHERE
17528, ONCE UPON A TIME IN AMERICA
24682, ONE EIGHT SEVEN
30412, ONE NIGHT STAND
33979, OSCAR AND LUCINDA
22965, PATRICIA HEATON
34639, POSTMAN BLUES
18584, PRINCESS MONONOKE
10039, PUPS
30377, SAM ROCKWELL
5171, SELENA
3896, SLAVES TO THE UNDERGROUND
3826, SNOW ANGELS
38386, SOUL FOOD
28494, TELLING LIES IN AMERICA
24335, TENTAÇÃO
22564, THE APOSTLE
23009, THE BLACKOUT
15029, THE BUTCHER BOY
31161, THE CHAMBERMAID ON THE TITANIC
18142, THE CONSTANT GARDENER
26567, THE EDGE
13675, THE FULL MONTY
26569, THE GAMBLER
14807, THE GOODBYE GIRL
15840, THE ICE STORM
15006, THE JOURNEY OF AUGUST KING
34252, THE LAST TIME I COMMITTED SUICIDE
26819, THE LEADING MAN
31848, THE MYTH OF FINGERPRINTS
16072, THE RAINMAKER
15718, THE TANGO LESSON
32458, THE THIEF
34916, THE WAY WAY BACK
3201, THE WINGS OF THE DOVE
2986, THE YEAR MY VOICE BROKE
5612, TITANIC
29271, TOUCH
28819, UNDER THE SKIN
29810, VOLCANO
30676, VOYAGE TO THE BEGINNING OF THE WORLD
24288, WASHINGTON SQUARE
35647, WRINKLES
src, edge_attr, dst
17737, has_genre, 36212
17737, has_tags, 36212
17737, release_year, 14259
26399, has_genre, 36212
26399, release_year, 14259
2566, has_genre, 36212
2566, release_year, 14259
30146, has_genre, 36212
30146, release_year, 14259
20629, has_genre, 36212
20629, starred_actors, 30377
14986, has_genre, 36212
14986, release_year, 14259
15136, has_genre, 36212
15136, release_year, 14259
9313, has_genre, 36212
9313, release_year, 14259
7983, has_genre, 36212
7983, release_year, 14259
20480, has_genre, 36212
20480, release_year, 14259
21856, has_genre, 36212
21856, release_year, 14259
36963, has_genre, 36212
36963, has_tags, 36212
36963, release_year, 14259
23952, has_genre, 36212
23952, release_year, 14259
15240, has_genre, 36212
15240, release_year, 14259
25930, has_genre, 36212
25930, has_tags, 30377
25930, starred_actors, 30377
2217, has_genre, 36212
2217, has_tags, 36212
2217, release_year, 14259
22919, has_genre, 36212
22919, release_year, 14259
314, has_genre, 36212
314, release_year, 14259
33121, has_genre, 36212
33121, release_year, 14259
31459, has_genre, 36212
31459, release_year, 14259
2869, has_genre, 36212
2869, release_year, 14259
7142, has_genre, 36212
7142, release_year, 14259
22452, has_genre, 36212
22452, release_year, 14259
2859, has_genre, 36212
2859, release_year, 14259
18235, has_genre, 36212
18235, starred_actors, 30377
6871, has_genre, 36212
6871, has_tags, 36212
6871, release_year, 14259
5726, has_genre, 36212
5726, release_year, 14259
38834, has_genre, 36212
38834, release_year, 14259
15892, has_genre, 36212
15892, release_year, 14259
30833, has_genre, 36212
30833, release_year, 14259
26106, has_genre, 36212
26106, has_tags, 34449
16328, has_genre, 36212
16328, release_year, 14259
23387, has_genre, 36212
23387, starred_actors, 30377
20378, has_genre, 36212
20378, release_year, 14259
18446, has_genre, 36212
18446, release_year, 14259
5829, has_genre, 36212
5829, release_year, 14259
21606, directed_by, 17974
21606, has_genre, 36212
21606, has_tags, 17974
21606, written_by, 17974
35150, has_genre, 36212
35150, has_tags, 36212
35150, has_tags, 34449
31224, has_genre, 36212
31224, release_year, 14259
22311, has_genre, 36212
22311, release_year, 14259
12664, has_genre, 36212
12664, has_tags, 34449
26708, has_genre, 36212
26708, release_year, 14259
30479, has_genre, 36212
30479, release_year, 14259
37982, has_genre, 36212
37982, release_year, 14259
7879, has_genre, 36212
7879, has_tags, 34449
4840, directed_by, 17974
4840, has_genre, 36212
4840, written_by, 17974
4464, has_genre, 36212
4464, release_year, 14259
16164, has_genre, 36212
16164, release_year, 14259
31481, has_genre, 36212
31481, release_year, 14259
19868, has_genre, 36212
19868, release_year, 14259
19939, has_genre, 36212
19939, release_year, 14259
31226, has_genre, 36212
31226, starred_actors, 12246
4447, directed_by, 17974
4447, has_genre, 36212
4447, has_tags, 34449
4447, has_tags, 17974
4447, has_tags, 30377
4447, release_year, 14259
4447, starred_actors, 12246
4447, starred_actors, 30377
24419, has_genre, 36212
24419, release_year, 14259
233, has_genre, 36212
233, release_year, 14259
15322, has_genre, 36212
15322, has_tags, 36212
15322, release_year, 14259
22386, has_genre, 36212
22386, has_tags, 12246
22386, starred_actors, 12246
31294, has_genre, 36212
31294, release_year, 14259
21344, has_genre, 36212
21344, release_year, 14259
18198, has_genre, 36212
18198, has_tags, 36212
18198, has_tags, 30377
18198, starred_actors, 30377
14102, has_genre, 36212
14102, release_year, 14259
31515, has_genre, 36212
31515, release_year, 14259
995, has_genre, 36212
995, release_year, 14259
19598, directed_by, 17974
19598, has_genre, 36212
32149, has_genre, 36212
32149, has_tags, 36212
32149, has_tags, 30377
32149, starred_actors, 30377
21686, has_genre, 36212
21686, release_year, 14259
22938, has_genre, 36212
22938, release_year, 14259
693, has_genre, 36212
693, release_year, 14259
6767, has_genre, 36212
6767, release_year, 14259
2624, has_genre, 36212
2624, release_year, 14259
34420, has_genre, 36212
34420, release_year, 14259
17528, has_genre, 36212
17528, has_tags, 34449
24682, has_genre, 36212
24682, release_year, 14259
30412, has_genre, 36212
30412, release_year, 14259
33979, has_genre, 36212
33979, release_year, 14259
34639, has_genre, 36212
34639, release_year, 14259
18584, has_tags, 36212
18584, release_year, 14259
10039, has_genre, 36212
10039, starred_actors, 12246
5171, has_genre, 36212
5171, release_year, 14259
3896, has_genre, 36212
3896, release_year, 14259
3826, has_genre, 36212
3826, has_tags, 30377
3826, starred_actors, 30377
38386, has_genre, 36212
38386, release_year, 14259
28494, has_genre, 36212
28494, release_year, 14259
24335, has_genre, 36212
24335, release_year, 14259
22564, has_genre, 36212
22564, has_tags, 36212
22564, release_year, 14259
23009, has_genre, 36212
23009, release_year, 14259
15029, has_genre, 36212
15029, release_year, 14259
31161, has_genre, 36212
31161, release_year, 14259
18142, has_genre, 36212
18142, has_tags, 36212
18142, written_by, 26410
26567, has_genre, 36212
26567, release_year, 14259
13675, has_genre, 36212
13675, release_year, 14259
26569, has_genre, 36212
26569, release_year, 14259
14807, has_genre, 36212
14807, starred_actors, 22965
15840, has_genre, 36212
15840, has_tags, 36212
15840, release_year, 14259
15006, directed_by, 17974
15006, has_genre, 36212
34252, has_genre, 36212
34252, release_year, 14259
26819, directed_by, 17974
26819, has_genre, 36212
31848, has_genre, 36212
31848, release_year, 14259
16072, has_genre, 36212
16072, release_year, 14259
15718, has_genre, 36212
15718, release_year, 14259
32458, has_genre, 36212
32458, release_year, 14259
34916, has_genre, 36212
34916, has_tags, 36212
34916, has_tags, 30377
3201, has_genre, 36212
3201, release_year, 14259
2986, directed_by, 17974
2986, has_genre, 36212
2986, has_tags, 17974
2986, written_by, 17974
5612, has_genre, 36212
5612, release_year, 14259
29271, has_genre, 36212
29271, release_year, 14259
28819, has_genre, 36212
28819, release_year, 14259
29810, has_genre, 36212
29810, release_year, 14259
30676, has_genre, 36212
30676, release_year, 14259
24288, has_genre, 36212
24288, release_year, 14259
35647, has_genre, 36212
35647, has_tags, 34449
Question: For what reason are JEFFREY CAINE, LAWN DOGS, and PATRICIA HEATON associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"JEFFREY CAINE",
"LAWN DOGS",
"PATRICIA HEATON"
],
"valid_edges": [
[
"12 ANGRY MEN",
"has_genre",
"DRAMA"
],
[
"12 ANGRY MEN",
"has_tags",
"DRAMA"
],
[
"12 ANGRY MEN",
"release_year",
"1997"
],
[
"12 STOREYS",
"has_genre",
"DRAMA"
],
[
"12 STOREYS",
"release_year",
"1997"
],
[
"A BETTER PLACE",
"has_genre",
"DRAMA"
],
[
"A BETTER PLACE",
"release_year",
"1997"
],
[
"A CHRISTMAS CAROL",
"has_genre",
"DRAMA"
],
[
"A CHRISTMAS CAROL",
"release_year",
"1997"
],
[
"A SINGLE SHOT",
"has_genre",
"DRAMA"
],
[
"A SINGLE SHOT",
"starred_actors",
"SAM ROCKWELL"
],
[
"A THOUSAND ACRES",
"has_genre",
"DRAMA"
],
[
"A THOUSAND ACRES",
"release_year",
"1997"
],
[
"AFFLICTION",
"has_genre",
"DRAMA"
],
[
"AFFLICTION",
"release_year",
"1997"
],
[
"ALL OVER ME",
"has_genre",
"DRAMA"
],
[
"ALL OVER ME",
"release_year",
"1997"
],
[
"AMERICAN PERFEKT",
"has_genre",
"DRAMA"
],
[
"AMERICAN PERFEKT",
"release_year",
"1997"
],
[
"AMISTAD",
"has_genre",
"DRAMA"
],
[
"AMISTAD",
"release_year",
"1997"
],
[
"ANASTASIA",
"has_genre",
"DRAMA"
],
[
"ANASTASIA",
"release_year",
"1997"
],
[
"ANNA KARENINA",
"has_genre",
"DRAMA"
],
[
"ANNA KARENINA",
"has_tags",
"DRAMA"
],
[
"ANNA KARENINA",
"release_year",
"1997"
],
[
"BANDITS",
"has_genre",
"DRAMA"
],
[
"BANDITS",
"release_year",
"1997"
],
[
"BENT",
"has_genre",
"DRAMA"
],
[
"BENT",
"release_year",
"1997"
],
[
"BETTER LIVING THROUGH CHEMISTRY",
"has_genre",
"DRAMA"
],
[
"BETTER LIVING THROUGH CHEMISTRY",
"has_tags",
"SAM ROCKWELL"
],
[
"BETTER LIVING THROUGH CHEMISTRY",
"starred_actors",
"SAM ROCKWELL"
],
[
"BOOGIE NIGHTS",
"has_genre",
"DRAMA"
],
[
"BOOGIE NIGHTS",
"has_tags",
"DRAMA"
],
[
"BOOGIE NIGHTS",
"release_year",
"1997"
],
[
"BROADWAY DAMAGE",
"has_genre",
"DRAMA"
],
[
"BROADWAY DAMAGE",
"release_year",
"1997"
],
[
"BUUD YAM",
"has_genre",
"DRAMA"
],
[
"BUUD YAM",
"release_year",
"1997"
],
[
"CAREER GIRLS",
"has_genre",
"DRAMA"
],
[
"CAREER GIRLS",
"release_year",
"1997"
],
[
"CHILDREN OF HEAVEN",
"has_genre",
"DRAMA"
],
[
"CHILDREN OF HEAVEN",
"release_year",
"1997"
],
[
"CLOCKWATCHERS",
"has_genre",
"DRAMA"
],
[
"CLOCKWATCHERS",
"release_year",
"1997"
],
[
"COMANCHE TERRITORY",
"has_genre",
"DRAMA"
],
[
"COMANCHE TERRITORY",
"release_year",
"1997"
],
[
"COMMANDMENTS",
"has_genre",
"DRAMA"
],
[
"COMMANDMENTS",
"release_year",
"1997"
],
[
"CONTACT",
"has_genre",
"DRAMA"
],
[
"CONTACT",
"release_year",
"1997"
],
[
"CONVICTION",
"has_genre",
"DRAMA"
],
[
"CONVICTION",
"starred_actors",
"SAM ROCKWELL"
],
[
"COP LAND",
"has_genre",
"DRAMA"
],
[
"COP LAND",
"has_tags",
"DRAMA"
],
[
"COP LAND",
"release_year",
"1997"
],
[
"DEFYING GRAVITY",
"has_genre",
"DRAMA"
],
[
"DEFYING GRAVITY",
"release_year",
"1997"
],
[
"DESTINY",
"has_genre",
"DRAMA"
],
[
"DESTINY",
"release_year",
"1997"
],
[
"DONNIE BRASCO",
"has_genre",
"DRAMA"
],
[
"DONNIE BRASCO",
"release_year",
"1997"
],
[
"DÉJÀ VU",
"has_genre",
"DRAMA"
],
[
"DÉJÀ VU",
"release_year",
"1997"
],
[
"END OF WATCH",
"has_genre",
"DRAMA"
],
[
"END OF WATCH",
"has_tags",
"FRIENDSHIP"
],
[
"EVE'S BAYOU",
"has_genre",
"DRAMA"
],
[
"EVE'S BAYOU",
"release_year",
"1997"
],
[
"EVERYBODY'S FINE",
"has_genre",
"DRAMA"
],
[
"EVERYBODY'S FINE",
"starred_actors",
"SAM ROCKWELL"
],
[
"FACE",
"has_genre",
"DRAMA"
],
[
"FACE",
"release_year",
"1997"
],
[
"FEVER PITCH",
"has_genre",
"DRAMA"
],
[
"FEVER PITCH",
"release_year",
"1997"
],
[
"FIRE DOWN BELOW",
"has_genre",
"DRAMA"
],
[
"FIRE DOWN BELOW",
"release_year",
"1997"
],
[
"FLIRTING",
"directed_by",
"JOHN DUIGAN"
],
[
"FLIRTING",
"has_genre",
"DRAMA"
],
[
"FLIRTING",
"has_tags",
"JOHN DUIGAN"
],
[
"FLIRTING",
"written_by",
"JOHN DUIGAN"
],
[
"FRIED GREEN TOMATOES",
"has_genre",
"DRAMA"
],
[
"FRIED GREEN TOMATOES",
"has_tags",
"DRAMA"
],
[
"FRIED GREEN TOMATOES",
"has_tags",
"FRIENDSHIP"
],
[
"G.I. JANE",
"has_genre",
"DRAMA"
],
[
"G.I. JANE",
"release_year",
"1997"
],
[
"GANG RELATED",
"has_genre",
"DRAMA"
],
[
"GANG RELATED",
"release_year",
"1997"
],
[
"GHOST WORLD",
"has_genre",
"DRAMA"
],
[
"GHOST WORLD",
"has_tags",
"FRIENDSHIP"
],
[
"GOOD WILL HUNTING",
"has_genre",
"DRAMA"
],
[
"GOOD WILL HUNTING",
"release_year",
"1997"
],
[
"GRIDLOCK'D",
"has_genre",
"DRAMA"
],
[
"GRIDLOCK'D",
"release_year",
"1997"
],
[
"GUMMO",
"has_genre",
"DRAMA"
],
[
"GUMMO",
"release_year",
"1997"
],
[
"HALF NELSON",
"has_genre",
"DRAMA"
],
[
"HALF NELSON",
"has_tags",
"FRIENDSHIP"
],
[
"HEAD IN THE CLOUDS",
"directed_by",
"JOHN DUIGAN"
],
[
"HEAD IN THE CLOUDS",
"has_genre",
"DRAMA"
],
[
"HEAD IN THE CLOUDS",
"written_by",
"JOHN DUIGAN"
],
[
"HOODLUM",
"has_genre",
"DRAMA"
],
[
"HOODLUM",
"release_year",
"1997"
],
[
"HURRICANE STREETS",
"has_genre",
"DRAMA"
],
[
"HURRICANE STREETS",
"release_year",
"1997"
],
[
"ISHQ",
"has_genre",
"DRAMA"
],
[
"ISHQ",
"release_year",
"1997"
],
[
"JACK FROST",
"has_genre",
"DRAMA"
],
[
"JACK FROST",
"release_year",
"1997"
],
[
"JACKIE BROWN",
"has_genre",
"DRAMA"
],
[
"JACKIE BROWN",
"release_year",
"1997"
],
[
"JULIE JOHNSON",
"has_genre",
"DRAMA"
],
[
"JULIE JOHNSON",
"starred_actors",
"MISCHA BARTON"
],
[
"LAWN DOGS",
"directed_by",
"JOHN DUIGAN"
],
[
"LAWN DOGS",
"has_genre",
"DRAMA"
],
[
"LAWN DOGS",
"has_tags",
"FRIENDSHIP"
],
[
"LAWN DOGS",
"has_tags",
"JOHN DUIGAN"
],
[
"LAWN DOGS",
"has_tags",
"SAM ROCKWELL"
],
[
"LAWN DOGS",
"release_year",
"1997"
],
[
"LAWN DOGS",
"starred_actors",
"MISCHA BARTON"
],
[
"LAWN DOGS",
"starred_actors",
"SAM ROCKWELL"
],
[
"LIFE IS BEAUTIFUL",
"has_genre",
"DRAMA"
],
[
"LIFE IS BEAUTIFUL",
"release_year",
"1997"
],
[
"LIVE FLESH",
"has_genre",
"DRAMA"
],
[
"LIVE FLESH",
"release_year",
"1997"
],
[
"LOLITA",
"has_genre",
"DRAMA"
],
[
"LOLITA",
"has_tags",
"DRAMA"
],
[
"LOLITA",
"release_year",
"1997"
],
[
"LOST AND DELIRIOUS",
"has_genre",
"DRAMA"
],
[
"LOST AND DELIRIOUS",
"has_tags",
"MISCHA BARTON"
],
[
"LOST AND DELIRIOUS",
"starred_actors",
"MISCHA BARTON"
],
[
"LOVE JONES",
"has_genre",
"DRAMA"
],
[
"LOVE JONES",
"release_year",
"1997"
],
[
"LOVE WALKED IN",
"has_genre",
"DRAMA"
],
[
"LOVE WALKED IN",
"release_year",
"1997"
],
[
"MATCHSTICK MEN",
"has_genre",
"DRAMA"
],
[
"MATCHSTICK MEN",
"has_tags",
"DRAMA"
],
[
"MATCHSTICK MEN",
"has_tags",
"SAM ROCKWELL"
],
[
"MATCHSTICK MEN",
"starred_actors",
"SAM ROCKWELL"
],
[
"MEN WITH GUNS",
"has_genre",
"DRAMA"
],
[
"MEN WITH GUNS",
"release_year",
"1997"
],
[
"METROLAND",
"has_genre",
"DRAMA"
],
[
"METROLAND",
"release_year",
"1997"
],
[
"MIDNIGHT IN THE GARDEN OF GOOD AND EVIL",
"has_genre",
"DRAMA"
],
[
"MIDNIGHT IN THE GARDEN OF GOOD AND EVIL",
"release_year",
"1997"
],
[
"MOLLY",
"directed_by",
"JOHN DUIGAN"
],
[
"MOLLY",
"has_genre",
"DRAMA"
],
[
"MOON",
"has_genre",
"DRAMA"
],
[
"MOON",
"has_tags",
"DRAMA"
],
[
"MOON",
"has_tags",
"SAM ROCKWELL"
],
[
"MOON",
"starred_actors",
"SAM ROCKWELL"
],
[
"MOONLIGHT SERENADE",
"has_genre",
"DRAMA"
],
[
"MOONLIGHT SERENADE",
"release_year",
"1997"
],
[
"MOTHER AND SON",
"has_genre",
"DRAMA"
],
[
"MOTHER AND SON",
"release_year",
"1997"
],
[
"MRS DALLOWAY",
"has_genre",
"DRAMA"
],
[
"MRS DALLOWAY",
"release_year",
"1997"
],
[
"MY SON THE FANATIC",
"has_genre",
"DRAMA"
],
[
"MY SON THE FANATIC",
"release_year",
"1997"
],
[
"NIL BY MOUTH",
"has_genre",
"DRAMA"
],
[
"NIL BY MOUTH",
"release_year",
"1997"
],
[
"NOWHERE",
"has_genre",
"DRAMA"
],
[
"NOWHERE",
"release_year",
"1997"
],
[
"ONCE UPON A TIME IN AMERICA",
"has_genre",
"DRAMA"
],
[
"ONCE UPON A TIME IN AMERICA",
"has_tags",
"FRIENDSHIP"
],
[
"ONE EIGHT SEVEN",
"has_genre",
"DRAMA"
],
[
"ONE EIGHT SEVEN",
"release_year",
"1997"
],
[
"ONE NIGHT STAND",
"has_genre",
"DRAMA"
],
[
"ONE NIGHT STAND",
"release_year",
"1997"
],
[
"OSCAR AND LUCINDA",
"has_genre",
"DRAMA"
],
[
"OSCAR AND LUCINDA",
"release_year",
"1997"
],
[
"POSTMAN BLUES",
"has_genre",
"DRAMA"
],
[
"POSTMAN BLUES",
"release_year",
"1997"
],
[
"PRINCESS MONONOKE",
"has_tags",
"DRAMA"
],
[
"PRINCESS MONONOKE",
"release_year",
"1997"
],
[
"PUPS",
"has_genre",
"DRAMA"
],
[
"PUPS",
"starred_actors",
"MISCHA BARTON"
],
[
"SELENA",
"has_genre",
"DRAMA"
],
[
"SELENA",
"release_year",
"1997"
],
[
"SLAVES TO THE UNDERGROUND",
"has_genre",
"DRAMA"
],
[
"SLAVES TO THE UNDERGROUND",
"release_year",
"1997"
],
[
"SNOW ANGELS",
"has_genre",
"DRAMA"
],
[
"SNOW ANGELS",
"has_tags",
"SAM ROCKWELL"
],
[
"SNOW ANGELS",
"starred_actors",
"SAM ROCKWELL"
],
[
"SOUL FOOD",
"has_genre",
"DRAMA"
],
[
"SOUL FOOD",
"release_year",
"1997"
],
[
"TELLING LIES IN AMERICA",
"has_genre",
"DRAMA"
],
[
"TELLING LIES IN AMERICA",
"release_year",
"1997"
],
[
"TENTAÇÃO",
"has_genre",
"DRAMA"
],
[
"TENTAÇÃO",
"release_year",
"1997"
],
[
"THE APOSTLE",
"has_genre",
"DRAMA"
],
[
"THE APOSTLE",
"has_tags",
"DRAMA"
],
[
"THE APOSTLE",
"release_year",
"1997"
],
[
"THE BLACKOUT",
"has_genre",
"DRAMA"
],
[
"THE BLACKOUT",
"release_year",
"1997"
],
[
"THE BUTCHER BOY",
"has_genre",
"DRAMA"
],
[
"THE BUTCHER BOY",
"release_year",
"1997"
],
[
"THE CHAMBERMAID ON THE TITANIC",
"has_genre",
"DRAMA"
],
[
"THE CHAMBERMAID ON THE TITANIC",
"release_year",
"1997"
],
[
"THE CONSTANT GARDENER",
"has_genre",
"DRAMA"
],
[
"THE CONSTANT GARDENER",
"has_tags",
"DRAMA"
],
[
"THE CONSTANT GARDENER",
"written_by",
"JEFFREY CAINE"
],
[
"THE EDGE",
"has_genre",
"DRAMA"
],
[
"THE EDGE",
"release_year",
"1997"
],
[
"THE FULL MONTY",
"has_genre",
"DRAMA"
],
[
"THE FULL MONTY",
"release_year",
"1997"
],
[
"THE GAMBLER",
"has_genre",
"DRAMA"
],
[
"THE GAMBLER",
"release_year",
"1997"
],
[
"THE GOODBYE GIRL",
"has_genre",
"DRAMA"
],
[
"THE GOODBYE GIRL",
"starred_actors",
"PATRICIA HEATON"
],
[
"THE ICE STORM",
"has_genre",
"DRAMA"
],
[
"THE ICE STORM",
"has_tags",
"DRAMA"
],
[
"THE ICE STORM",
"release_year",
"1997"
],
[
"THE JOURNEY OF AUGUST KING",
"directed_by",
"JOHN DUIGAN"
],
[
"THE JOURNEY OF AUGUST KING",
"has_genre",
"DRAMA"
],
[
"THE LAST TIME I COMMITTED SUICIDE",
"has_genre",
"DRAMA"
],
[
"THE LAST TIME I COMMITTED SUICIDE",
"release_year",
"1997"
],
[
"THE LEADING MAN",
"directed_by",
"JOHN DUIGAN"
],
[
"THE LEADING MAN",
"has_genre",
"DRAMA"
],
[
"THE MYTH OF FINGERPRINTS",
"has_genre",
"DRAMA"
],
[
"THE MYTH OF FINGERPRINTS",
"release_year",
"1997"
],
[
"THE RAINMAKER",
"has_genre",
"DRAMA"
],
[
"THE RAINMAKER",
"release_year",
"1997"
],
[
"THE TANGO LESSON",
"has_genre",
"DRAMA"
],
[
"THE TANGO LESSON",
"release_year",
"1997"
],
[
"THE THIEF",
"has_genre",
"DRAMA"
],
[
"THE THIEF",
"release_year",
"1997"
],
[
"THE WAY WAY BACK",
"has_genre",
"DRAMA"
],
[
"THE WAY WAY BACK",
"has_tags",
"DRAMA"
],
[
"THE WAY WAY BACK",
"has_tags",
"SAM ROCKWELL"
],
[
"THE WINGS OF THE DOVE",
"has_genre",
"DRAMA"
],
[
"THE WINGS OF THE DOVE",
"release_year",
"1997"
],
[
"THE YEAR MY VOICE BROKE",
"directed_by",
"JOHN DUIGAN"
],
[
"THE YEAR MY VOICE BROKE",
"has_genre",
"DRAMA"
],
[
"THE YEAR MY VOICE BROKE",
"has_tags",
"JOHN DUIGAN"
],
[
"THE YEAR MY VOICE BROKE",
"written_by",
"JOHN DUIGAN"
],
[
"TITANIC",
"has_genre",
"DRAMA"
],
[
"TITANIC",
"release_year",
"1997"
],
[
"TOUCH",
"has_genre",
"DRAMA"
],
[
"TOUCH",
"release_year",
"1997"
],
[
"UNDER THE SKIN",
"has_genre",
"DRAMA"
],
[
"UNDER THE SKIN",
"release_year",
"1997"
],
[
"VOLCANO",
"has_genre",
"DRAMA"
],
[
"VOLCANO",
"release_year",
"1997"
],
[
"VOYAGE TO THE BEGINNING OF THE WORLD",
"has_genre",
"DRAMA"
],
[
"VOYAGE TO THE BEGINNING OF THE WORLD",
"release_year",
"1997"
],
[
"WASHINGTON SQUARE",
"has_genre",
"DRAMA"
],
[
"WASHINGTON SQUARE",
"release_year",
"1997"
],
[
"WRINKLES",
"has_genre",
"DRAMA"
],
[
"WRINKLES",
"has_tags",
"FRIENDSHIP"
]
]
}
|
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
2452, 13 ASSASSINS
25221, 1981
7596, 4
3830, 47 RONIN
30045, AKIRA KUROSAWA
9855, AMSTERDAMNED
36212, DRAMA
31008, DUTCH
8248, JAPAN
36874, JAPANESE
27034, KUROSAWA
24299, MONIQUE VAN DE VEN
4807, PASSION FLOWER
39594, REBELLION
35944, SAMURAI
25217, SAMURAI REBELLION
29960, SAMURAI REINCARNATION
25538, SANJURO
20932, SEVEN SAMURAI
22852, THE ASSAULT
21468, THE LAST SAMURAI
8873, THE TALE OF ZATOICHI
29888, THREE OUTLAW SAMURAI
36569, TURKISH DELIGHT
src, edge_attr, dst
2452, has_genre, 36212
2452, has_tags, 8248
2452, has_tags, 35944
2452, in_language, 36874
25221, has_genre, 36212
7596, has_genre, 36212
3830, has_tags, 35944
3830, in_language, 36874
9855, in_language, 31008
9855, starred_actors, 24299
31008, has_genre, 36212
4807, has_genre, 36212
39594, has_genre, 36212
25217, has_tags, 8248
25217, has_tags, 35944
25217, in_language, 36874
29960, has_tags, 35944
29960, in_language, 36874
29960, release_year, 25221
25538, directed_by, 30045
25538, has_tags, 30045
25538, has_tags, 8248
25538, has_tags, 36874
25538, has_tags, 27034
25538, has_tags, 35944
25538, in_language, 36874
25538, written_by, 30045
20932, directed_by, 30045
20932, has_genre, 36212
20932, has_tags, 7596
20932, has_tags, 30045
20932, has_tags, 36212
20932, has_tags, 8248
20932, has_tags, 27034
20932, has_tags, 35944
20932, in_language, 36874
20932, written_by, 30045
22852, in_language, 31008
22852, starred_actors, 24299
21468, has_tags, 8248
21468, has_tags, 39594
21468, has_tags, 35944
8873, has_genre, 36212
8873, has_tags, 35944
8873, in_language, 36874
29888, has_tags, 35944
29888, in_language, 36874
36569, in_language, 31008
36569, starred_actors, 24299
Question: In what context are MONIQUE VAN DE VEN, PASSION FLOWER, and SAMURAI connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"MONIQUE VAN DE VEN",
"PASSION FLOWER",
"SAMURAI"
],
"valid_edges": [
[
"13 ASSASSINS",
"has_genre",
"DRAMA"
],
[
"13 ASSASSINS",
"has_tags",
"JAPAN"
],
[
"13 ASSASSINS",
"has_tags",
"SAMURAI"
],
[
"13 ASSASSINS",
"in_language",
"JAPANESE"
],
[
"1981",
"has_genre",
"DRAMA"
],
[
"4",
"has_genre",
"DRAMA"
],
[
"47 RONIN",
"has_tags",
"SAMURAI"
],
[
"47 RONIN",
"in_language",
"JAPANESE"
],
[
"AMSTERDAMNED",
"in_language",
"DUTCH"
],
[
"AMSTERDAMNED",
"starred_actors",
"MONIQUE VAN DE VEN"
],
[
"DUTCH",
"has_genre",
"DRAMA"
],
[
"PASSION FLOWER",
"has_genre",
"DRAMA"
],
[
"REBELLION",
"has_genre",
"DRAMA"
],
[
"SAMURAI REBELLION",
"has_tags",
"JAPAN"
],
[
"SAMURAI REBELLION",
"has_tags",
"SAMURAI"
],
[
"SAMURAI REBELLION",
"in_language",
"JAPANESE"
],
[
"SAMURAI REINCARNATION",
"has_tags",
"SAMURAI"
],
[
"SAMURAI REINCARNATION",
"in_language",
"JAPANESE"
],
[
"SAMURAI REINCARNATION",
"release_year",
"1981"
],
[
"SANJURO",
"directed_by",
"AKIRA KUROSAWA"
],
[
"SANJURO",
"has_tags",
"AKIRA KUROSAWA"
],
[
"SANJURO",
"has_tags",
"JAPAN"
],
[
"SANJURO",
"has_tags",
"JAPANESE"
],
[
"SANJURO",
"has_tags",
"KUROSAWA"
],
[
"SANJURO",
"has_tags",
"SAMURAI"
],
[
"SANJURO",
"in_language",
"JAPANESE"
],
[
"SANJURO",
"written_by",
"AKIRA KUROSAWA"
],
[
"SEVEN SAMURAI",
"directed_by",
"AKIRA KUROSAWA"
],
[
"SEVEN SAMURAI",
"has_genre",
"DRAMA"
],
[
"SEVEN SAMURAI",
"has_tags",
"4"
],
[
"SEVEN SAMURAI",
"has_tags",
"AKIRA KUROSAWA"
],
[
"SEVEN SAMURAI",
"has_tags",
"DRAMA"
],
[
"SEVEN SAMURAI",
"has_tags",
"JAPAN"
],
[
"SEVEN SAMURAI",
"has_tags",
"KUROSAWA"
],
[
"SEVEN SAMURAI",
"has_tags",
"SAMURAI"
],
[
"SEVEN SAMURAI",
"in_language",
"JAPANESE"
],
[
"SEVEN SAMURAI",
"written_by",
"AKIRA KUROSAWA"
],
[
"THE ASSAULT",
"in_language",
"DUTCH"
],
[
"THE ASSAULT",
"starred_actors",
"MONIQUE VAN DE VEN"
],
[
"THE LAST SAMURAI",
"has_tags",
"JAPAN"
],
[
"THE LAST SAMURAI",
"has_tags",
"REBELLION"
],
[
"THE LAST SAMURAI",
"has_tags",
"SAMURAI"
],
[
"THE TALE OF ZATOICHI",
"has_genre",
"DRAMA"
],
[
"THE TALE OF ZATOICHI",
"has_tags",
"SAMURAI"
],
[
"THE TALE OF ZATOICHI",
"in_language",
"JAPANESE"
],
[
"THREE OUTLAW SAMURAI",
"has_tags",
"SAMURAI"
],
[
"THREE OUTLAW SAMURAI",
"in_language",
"JAPANESE"
],
[
"TURKISH DELIGHT",
"in_language",
"DUTCH"
],
[
"TURKISH DELIGHT",
"starred_actors",
"MONIQUE VAN DE VEN"
]
]
}
|
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
12401, 1937
11112, 1939
11, 1940
29561, 1943
35187, 1948
3863, 1962
6925, 1966
27810, 1968
25221, 1981
15374, 2005
18561, A BIG HAND FOR THE LITTLE LADY
29881, AMERICANO
27981, ANGEL-A
8284, ANTHONY QUINN
21815, ANTHONY ZIMMER
10511, BACKSTAGE
34734, BATTLE OF THE BULGE
35487, C.R.A.Z.Y.
38311, CHAOS
6176, COLD SHOWERS
2394, DICK RICKARD
11172, DRUMS ALONG THE MOHAWK
33955, EMPIRE OF THE WOLVES
27441, ENTRE SES MAINS
8406, FIRECREEK
38886, FORT APACHE
6012, FRENCH
10387, FRITZ LANG
7770, GABRIELLE
6480, GERMAN
29188, HEADING SOUTH
34073, HELL
34149, HENRY FONDA
4429, HOW MUCH DO YOU LOVE ME?
7515, HOW THE WEST WAS WON
617, IMMORTAL SERGEANT
16200, ITALIAN
7736, JAMES STEWART
17968, JASON ROBARDS
13255, JOHN FORD
12435, JOHN WAYNE
3215, KEN ANNAKIN
12898, KING VIDOR
28945, MARCH OF THE PENGUINS
31701, MISTER ROBERTS
22845, MUSIC
15797, MY DARLING CLEMENTINE
37497, NATIONAL FILM REGISTRY
24488, NOT HERE TO BE LOVED
7450, ON GOLDEN POND
9638, ON OUR MERRY WAY
147, ONCE UPON A TIME IN THE WEST
5730, RUSSIAN DOLLS
31632, SAM HELLMAN
6054, SKY FIGHTERS
4717, SNOW WHITE AND THE SEVEN DWARFS
27831, THE BEAT THAT MY HEART SKIPPED
3354, THE BROTHERS GRIMM
7763, THE CHEYENNE SOCIAL CLUB
1748, THE GRAPES OF WRATH
1806, THE LADY EVE
27237, THE LONGEST DAY
4624, THE OX-BOW INCIDENT
14824, THE RETURN OF FRANK JAMES
34185, THE TIN STAR
11918, TIME TO LEAVE
20251, TO PAINT OR MAKE LOVE
22680, TRANSPORTER 2
22214, WAR
26367, WAR AND PEACE
10352, WARLOCK
36026, WESTERN
24155, WORLD WAR II
1088, YOU ONLY LIVE ONCE
6277, YOUNG MR. LINCOLN
src, edge_attr, dst
25221, in_language, 6012
18561, has_genre, 36026
18561, release_year, 6925
18561, starred_actors, 34149
18561, starred_actors, 17968
29881, in_language, 6012
29881, release_year, 15374
27981, has_tags, 6012
27981, in_language, 6012
27981, release_year, 15374
21815, in_language, 6012
21815, release_year, 15374
10511, in_language, 6012
10511, release_year, 15374
34734, directed_by, 3215
34734, has_genre, 22214
34734, has_tags, 34149
34734, has_tags, 24155
34734, in_language, 6480
34734, starred_actors, 34149
35487, in_language, 6012
35487, release_year, 15374
38311, in_language, 6012
38311, release_year, 15374
6176, in_language, 6012
6176, release_year, 15374
11172, directed_by, 13255
11172, has_genre, 22214
11172, has_tags, 13255
11172, release_year, 11112
11172, starred_actors, 34149
33955, has_tags, 6012
33955, in_language, 6012
33955, release_year, 15374
27441, in_language, 6012
27441, release_year, 15374
8406, has_genre, 36026
8406, release_year, 27810
8406, starred_actors, 34149
8406, starred_actors, 7736
38886, directed_by, 13255
38886, has_genre, 36026
38886, has_tags, 13255
38886, has_tags, 12435
38886, release_year, 35187
38886, starred_actors, 34149
38886, starred_actors, 12435
7770, in_language, 6012
7770, release_year, 15374
29188, in_language, 6012
29188, release_year, 15374
34073, in_language, 6012
34073, release_year, 15374
4429, in_language, 6012
4429, release_year, 15374
7515, directed_by, 13255
7515, has_genre, 36026
7515, has_tags, 13255
7515, has_tags, 37497
7515, has_tags, 36026
7515, release_year, 3863
7515, starred_actors, 34149
617, has_genre, 22214
617, release_year, 29561
617, starred_actors, 34149
28945, has_tags, 6012
28945, in_language, 6012
28945, release_year, 15374
31701, directed_by, 13255
31701, has_genre, 22214
31701, has_tags, 34149
31701, has_tags, 13255
31701, starred_actors, 34149
15797, directed_by, 13255
15797, has_genre, 36026
15797, has_tags, 13255
15797, starred_actors, 34149
15797, written_by, 31632
24488, in_language, 6012
24488, release_year, 15374
7450, has_tags, 34149
7450, release_year, 25221
7450, starred_actors, 34149
9638, directed_by, 12898
9638, has_genre, 22845
9638, release_year, 35187
9638, starred_actors, 34149
9638, starred_actors, 7736
147, has_genre, 36026
147, has_tags, 34149
147, has_tags, 17968
147, has_tags, 36026
147, in_language, 16200
147, release_year, 27810
147, starred_actors, 34149
147, starred_actors, 17968
5730, in_language, 6012
5730, release_year, 15374
6054, in_language, 6012
6054, release_year, 15374
4717, has_tags, 22845
4717, has_tags, 37497
4717, release_year, 12401
4717, written_by, 2394
27831, has_tags, 6012
27831, in_language, 6012
27831, release_year, 15374
3354, in_language, 6012
3354, release_year, 15374
7763, has_genre, 36026
7763, starred_actors, 34149
7763, starred_actors, 7736
1748, directed_by, 13255
1748, has_tags, 34149
1748, has_tags, 13255
1748, has_tags, 37497
1748, release_year, 11
1748, starred_actors, 34149
1806, has_tags, 34149
1806, has_tags, 37497
1806, starred_actors, 34149
27237, directed_by, 3215
27237, has_tags, 34149
27237, has_tags, 12435
27237, has_tags, 3215
27237, has_tags, 22214
27237, has_tags, 24155
27237, in_language, 6012
27237, in_language, 6480
27237, release_year, 3863
4624, has_genre, 36026
4624, has_tags, 8284
4624, has_tags, 34149
4624, has_tags, 37497
4624, has_tags, 36026
4624, release_year, 29561
4624, starred_actors, 8284
4624, starred_actors, 34149
14824, directed_by, 10387
14824, has_genre, 36026
14824, release_year, 11
14824, starred_actors, 34149
14824, written_by, 31632
34185, has_genre, 36026
34185, starred_actors, 34149
11918, in_language, 6012
11918, release_year, 15374
20251, in_language, 6012
20251, release_year, 15374
22680, in_language, 6012
22680, release_year, 15374
26367, directed_by, 12898
26367, has_genre, 22214
26367, in_language, 16200
26367, release_year, 6925
26367, starred_actors, 34149
26367, written_by, 12898
10352, has_genre, 36026
10352, starred_actors, 8284
10352, starred_actors, 34149
36026, in_language, 6012
1088, directed_by, 10387
1088, has_tags, 10387
1088, release_year, 12401
1088, starred_actors, 34149
6277, directed_by, 13255
6277, has_tags, 13255
6277, has_tags, 37497
6277, release_year, 11112
6277, starred_actors, 34149
Question: How are COLD SHOWERS, DICK RICKARD, and HENRY FONDA related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"COLD SHOWERS",
"DICK RICKARD",
"HENRY FONDA"
],
"valid_edges": [
[
"1981",
"in_language",
"FRENCH"
],
[
"A BIG HAND FOR THE LITTLE LADY",
"has_genre",
"WESTERN"
],
[
"A BIG HAND FOR THE LITTLE LADY",
"release_year",
"1966"
],
[
"A BIG HAND FOR THE LITTLE LADY",
"starred_actors",
"HENRY FONDA"
],
[
"A BIG HAND FOR THE LITTLE LADY",
"starred_actors",
"JASON ROBARDS"
],
[
"AMERICANO",
"in_language",
"FRENCH"
],
[
"AMERICANO",
"release_year",
"2005"
],
[
"ANGEL-A",
"has_tags",
"FRENCH"
],
[
"ANGEL-A",
"in_language",
"FRENCH"
],
[
"ANGEL-A",
"release_year",
"2005"
],
[
"ANTHONY ZIMMER",
"in_language",
"FRENCH"
],
[
"ANTHONY ZIMMER",
"release_year",
"2005"
],
[
"BACKSTAGE",
"in_language",
"FRENCH"
],
[
"BACKSTAGE",
"release_year",
"2005"
],
[
"BATTLE OF THE BULGE",
"directed_by",
"KEN ANNAKIN"
],
[
"BATTLE OF THE BULGE",
"has_genre",
"WAR"
],
[
"BATTLE OF THE BULGE",
"has_tags",
"HENRY FONDA"
],
[
"BATTLE OF THE BULGE",
"has_tags",
"WORLD WAR II"
],
[
"BATTLE OF THE BULGE",
"in_language",
"GERMAN"
],
[
"BATTLE OF THE BULGE",
"starred_actors",
"HENRY FONDA"
],
[
"C.R.A.Z.Y.",
"in_language",
"FRENCH"
],
[
"C.R.A.Z.Y.",
"release_year",
"2005"
],
[
"CHAOS",
"in_language",
"FRENCH"
],
[
"CHAOS",
"release_year",
"2005"
],
[
"COLD SHOWERS",
"in_language",
"FRENCH"
],
[
"COLD SHOWERS",
"release_year",
"2005"
],
[
"DRUMS ALONG THE MOHAWK",
"directed_by",
"JOHN FORD"
],
[
"DRUMS ALONG THE MOHAWK",
"has_genre",
"WAR"
],
[
"DRUMS ALONG THE MOHAWK",
"has_tags",
"JOHN FORD"
],
[
"DRUMS ALONG THE MOHAWK",
"release_year",
"1939"
],
[
"DRUMS ALONG THE MOHAWK",
"starred_actors",
"HENRY FONDA"
],
[
"EMPIRE OF THE WOLVES",
"has_tags",
"FRENCH"
],
[
"EMPIRE OF THE WOLVES",
"in_language",
"FRENCH"
],
[
"EMPIRE OF THE WOLVES",
"release_year",
"2005"
],
[
"ENTRE SES MAINS",
"in_language",
"FRENCH"
],
[
"ENTRE SES MAINS",
"release_year",
"2005"
],
[
"FIRECREEK",
"has_genre",
"WESTERN"
],
[
"FIRECREEK",
"release_year",
"1968"
],
[
"FIRECREEK",
"starred_actors",
"HENRY FONDA"
],
[
"FIRECREEK",
"starred_actors",
"JAMES STEWART"
],
[
"FORT APACHE",
"directed_by",
"JOHN FORD"
],
[
"FORT APACHE",
"has_genre",
"WESTERN"
],
[
"FORT APACHE",
"has_tags",
"JOHN FORD"
],
[
"FORT APACHE",
"has_tags",
"JOHN WAYNE"
],
[
"FORT APACHE",
"release_year",
"1948"
],
[
"FORT APACHE",
"starred_actors",
"HENRY FONDA"
],
[
"FORT APACHE",
"starred_actors",
"JOHN WAYNE"
],
[
"GABRIELLE",
"in_language",
"FRENCH"
],
[
"GABRIELLE",
"release_year",
"2005"
],
[
"HEADING SOUTH",
"in_language",
"FRENCH"
],
[
"HEADING SOUTH",
"release_year",
"2005"
],
[
"HELL",
"in_language",
"FRENCH"
],
[
"HELL",
"release_year",
"2005"
],
[
"HOW MUCH DO YOU LOVE ME?",
"in_language",
"FRENCH"
],
[
"HOW MUCH DO YOU LOVE ME?",
"release_year",
"2005"
],
[
"HOW THE WEST WAS WON",
"directed_by",
"JOHN FORD"
],
[
"HOW THE WEST WAS WON",
"has_genre",
"WESTERN"
],
[
"HOW THE WEST WAS WON",
"has_tags",
"JOHN FORD"
],
[
"HOW THE WEST WAS WON",
"has_tags",
"NATIONAL FILM REGISTRY"
],
[
"HOW THE WEST WAS WON",
"has_tags",
"WESTERN"
],
[
"HOW THE WEST WAS WON",
"release_year",
"1962"
],
[
"HOW THE WEST WAS WON",
"starred_actors",
"HENRY FONDA"
],
[
"IMMORTAL SERGEANT",
"has_genre",
"WAR"
],
[
"IMMORTAL SERGEANT",
"release_year",
"1943"
],
[
"IMMORTAL SERGEANT",
"starred_actors",
"HENRY FONDA"
],
[
"MARCH OF THE PENGUINS",
"has_tags",
"FRENCH"
],
[
"MARCH OF THE PENGUINS",
"in_language",
"FRENCH"
],
[
"MARCH OF THE PENGUINS",
"release_year",
"2005"
],
[
"MISTER ROBERTS",
"directed_by",
"JOHN FORD"
],
[
"MISTER ROBERTS",
"has_genre",
"WAR"
],
[
"MISTER ROBERTS",
"has_tags",
"HENRY FONDA"
],
[
"MISTER ROBERTS",
"has_tags",
"JOHN FORD"
],
[
"MISTER ROBERTS",
"starred_actors",
"HENRY FONDA"
],
[
"MY DARLING CLEMENTINE",
"directed_by",
"JOHN FORD"
],
[
"MY DARLING CLEMENTINE",
"has_genre",
"WESTERN"
],
[
"MY DARLING CLEMENTINE",
"has_tags",
"JOHN FORD"
],
[
"MY DARLING CLEMENTINE",
"starred_actors",
"HENRY FONDA"
],
[
"MY DARLING CLEMENTINE",
"written_by",
"SAM HELLMAN"
],
[
"NOT HERE TO BE LOVED",
"in_language",
"FRENCH"
],
[
"NOT HERE TO BE LOVED",
"release_year",
"2005"
],
[
"ON GOLDEN POND",
"has_tags",
"HENRY FONDA"
],
[
"ON GOLDEN POND",
"release_year",
"1981"
],
[
"ON GOLDEN POND",
"starred_actors",
"HENRY FONDA"
],
[
"ON OUR MERRY WAY",
"directed_by",
"KING VIDOR"
],
[
"ON OUR MERRY WAY",
"has_genre",
"MUSIC"
],
[
"ON OUR MERRY WAY",
"release_year",
"1948"
],
[
"ON OUR MERRY WAY",
"starred_actors",
"HENRY FONDA"
],
[
"ON OUR MERRY WAY",
"starred_actors",
"JAMES STEWART"
],
[
"ONCE UPON A TIME IN THE WEST",
"has_genre",
"WESTERN"
],
[
"ONCE UPON A TIME IN THE WEST",
"has_tags",
"HENRY FONDA"
],
[
"ONCE UPON A TIME IN THE WEST",
"has_tags",
"JASON ROBARDS"
],
[
"ONCE UPON A TIME IN THE WEST",
"has_tags",
"WESTERN"
],
[
"ONCE UPON A TIME IN THE WEST",
"in_language",
"ITALIAN"
],
[
"ONCE UPON A TIME IN THE WEST",
"release_year",
"1968"
],
[
"ONCE UPON A TIME IN THE WEST",
"starred_actors",
"HENRY FONDA"
],
[
"ONCE UPON A TIME IN THE WEST",
"starred_actors",
"JASON ROBARDS"
],
[
"RUSSIAN DOLLS",
"in_language",
"FRENCH"
],
[
"RUSSIAN DOLLS",
"release_year",
"2005"
],
[
"SKY FIGHTERS",
"in_language",
"FRENCH"
],
[
"SKY FIGHTERS",
"release_year",
"2005"
],
[
"SNOW WHITE AND THE SEVEN DWARFS",
"has_tags",
"MUSIC"
],
[
"SNOW WHITE AND THE SEVEN DWARFS",
"has_tags",
"NATIONAL FILM REGISTRY"
],
[
"SNOW WHITE AND THE SEVEN DWARFS",
"release_year",
"1937"
],
[
"SNOW WHITE AND THE SEVEN DWARFS",
"written_by",
"DICK RICKARD"
],
[
"THE BEAT THAT MY HEART SKIPPED",
"has_tags",
"FRENCH"
],
[
"THE BEAT THAT MY HEART SKIPPED",
"in_language",
"FRENCH"
],
[
"THE BEAT THAT MY HEART SKIPPED",
"release_year",
"2005"
],
[
"THE BROTHERS GRIMM",
"in_language",
"FRENCH"
],
[
"THE BROTHERS GRIMM",
"release_year",
"2005"
],
[
"THE CHEYENNE SOCIAL CLUB",
"has_genre",
"WESTERN"
],
[
"THE CHEYENNE SOCIAL CLUB",
"starred_actors",
"HENRY FONDA"
],
[
"THE CHEYENNE SOCIAL CLUB",
"starred_actors",
"JAMES STEWART"
],
[
"THE GRAPES OF WRATH",
"directed_by",
"JOHN FORD"
],
[
"THE GRAPES OF WRATH",
"has_tags",
"HENRY FONDA"
],
[
"THE GRAPES OF WRATH",
"has_tags",
"JOHN FORD"
],
[
"THE GRAPES OF WRATH",
"has_tags",
"NATIONAL FILM REGISTRY"
],
[
"THE GRAPES OF WRATH",
"release_year",
"1940"
],
[
"THE GRAPES OF WRATH",
"starred_actors",
"HENRY FONDA"
],
[
"THE LADY EVE",
"has_tags",
"HENRY FONDA"
],
[
"THE LADY EVE",
"has_tags",
"NATIONAL FILM REGISTRY"
],
[
"THE LADY EVE",
"starred_actors",
"HENRY FONDA"
],
[
"THE LONGEST DAY",
"directed_by",
"KEN ANNAKIN"
],
[
"THE LONGEST DAY",
"has_tags",
"HENRY FONDA"
],
[
"THE LONGEST DAY",
"has_tags",
"JOHN WAYNE"
],
[
"THE LONGEST DAY",
"has_tags",
"KEN ANNAKIN"
],
[
"THE LONGEST DAY",
"has_tags",
"WAR"
],
[
"THE LONGEST DAY",
"has_tags",
"WORLD WAR II"
],
[
"THE LONGEST DAY",
"in_language",
"FRENCH"
],
[
"THE LONGEST DAY",
"in_language",
"GERMAN"
],
[
"THE LONGEST DAY",
"release_year",
"1962"
],
[
"THE OX-BOW INCIDENT",
"has_genre",
"WESTERN"
],
[
"THE OX-BOW INCIDENT",
"has_tags",
"ANTHONY QUINN"
],
[
"THE OX-BOW INCIDENT",
"has_tags",
"HENRY FONDA"
],
[
"THE OX-BOW INCIDENT",
"has_tags",
"NATIONAL FILM REGISTRY"
],
[
"THE OX-BOW INCIDENT",
"has_tags",
"WESTERN"
],
[
"THE OX-BOW INCIDENT",
"release_year",
"1943"
],
[
"THE OX-BOW INCIDENT",
"starred_actors",
"ANTHONY QUINN"
],
[
"THE OX-BOW INCIDENT",
"starred_actors",
"HENRY FONDA"
],
[
"THE RETURN OF FRANK JAMES",
"directed_by",
"FRITZ LANG"
],
[
"THE RETURN OF FRANK JAMES",
"has_genre",
"WESTERN"
],
[
"THE RETURN OF FRANK JAMES",
"release_year",
"1940"
],
[
"THE RETURN OF FRANK JAMES",
"starred_actors",
"HENRY FONDA"
],
[
"THE RETURN OF FRANK JAMES",
"written_by",
"SAM HELLMAN"
],
[
"THE TIN STAR",
"has_genre",
"WESTERN"
],
[
"THE TIN STAR",
"starred_actors",
"HENRY FONDA"
],
[
"TIME TO LEAVE",
"in_language",
"FRENCH"
],
[
"TIME TO LEAVE",
"release_year",
"2005"
],
[
"TO PAINT OR MAKE LOVE",
"in_language",
"FRENCH"
],
[
"TO PAINT OR MAKE LOVE",
"release_year",
"2005"
],
[
"TRANSPORTER 2",
"in_language",
"FRENCH"
],
[
"TRANSPORTER 2",
"release_year",
"2005"
],
[
"WAR AND PEACE",
"directed_by",
"KING VIDOR"
],
[
"WAR AND PEACE",
"has_genre",
"WAR"
],
[
"WAR AND PEACE",
"in_language",
"ITALIAN"
],
[
"WAR AND PEACE",
"release_year",
"1966"
],
[
"WAR AND PEACE",
"starred_actors",
"HENRY FONDA"
],
[
"WAR AND PEACE",
"written_by",
"KING VIDOR"
],
[
"WARLOCK",
"has_genre",
"WESTERN"
],
[
"WARLOCK",
"starred_actors",
"ANTHONY QUINN"
],
[
"WARLOCK",
"starred_actors",
"HENRY FONDA"
],
[
"WESTERN",
"in_language",
"FRENCH"
],
[
"YOU ONLY LIVE ONCE",
"directed_by",
"FRITZ LANG"
],
[
"YOU ONLY LIVE ONCE",
"has_tags",
"FRITZ LANG"
],
[
"YOU ONLY LIVE ONCE",
"release_year",
"1937"
],
[
"YOU ONLY LIVE ONCE",
"starred_actors",
"HENRY FONDA"
],
[
"YOUNG MR. LINCOLN",
"directed_by",
"JOHN FORD"
],
[
"YOUNG MR. LINCOLN",
"has_tags",
"JOHN FORD"
],
[
"YOUNG MR. LINCOLN",
"has_tags",
"NATIONAL FILM REGISTRY"
],
[
"YOUNG MR. LINCOLN",
"release_year",
"1939"
],
[
"YOUNG MR. LINCOLN",
"starred_actors",
"HENRY FONDA"
]
]
}
|
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
3702, 1995
1097, 2003
12144, BAD BOYS
26812, CRUISING
29606, FRISK
9198, MALIBU'S MOST WANTED
24437, MANIAC
27827, MONSTER
10981, SERIAL KILLER
16151, THE FIENDISH PLOT OF DR. FU MANCHU
3579, THE HUNTED
src, edge_attr, dst
12144, release_year, 3702
12144, release_year, 1097
26812, has_tags, 10981
26812, release_year, 36268
29606, has_tags, 10981
29606, release_year, 3702
9198, release_year, 1097
24437, has_tags, 10981
24437, release_year, 36268
27827, has_tags, 10981
27827, release_year, 1097
16151, release_year, 36268
3579, release_year, 3702
3579, release_year, 1097
Question: For what reason are FRISK, MALIBU'S MOST WANTED, and THE FIENDISH PLOT OF DR. FU MANCHU associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"FRISK",
"MALIBU'S MOST WANTED",
"THE FIENDISH PLOT OF DR. FU MANCHU"
],
"valid_edges": [
[
"BAD BOYS",
"release_year",
"1995"
],
[
"BAD BOYS",
"release_year",
"2003"
],
[
"CRUISING",
"has_tags",
"SERIAL KILLER"
],
[
"CRUISING",
"release_year",
"1980"
],
[
"FRISK",
"has_tags",
"SERIAL KILLER"
],
[
"FRISK",
"release_year",
"1995"
],
[
"MALIBU'S MOST WANTED",
"release_year",
"2003"
],
[
"MANIAC",
"has_tags",
"SERIAL KILLER"
],
[
"MANIAC",
"release_year",
"1980"
],
[
"MONSTER",
"has_tags",
"SERIAL KILLER"
],
[
"MONSTER",
"release_year",
"2003"
],
[
"THE FIENDISH PLOT OF DR. FU MANCHU",
"release_year",
"1980"
],
[
"THE HUNTED",
"release_year",
"1995"
],
[
"THE HUNTED",
"release_year",
"2003"
]
]
}
|
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
35845, 2006
14242, A FRIEND OF MINE
24039, A GOOD YEAR
19790, A GUIDE TO RECOGNIZING YOUR SAINTS
8198, A PRAIRIE HOME COMPANION
23754, AFTER THE WEDDING
11183, AKEELAH AND THE BEE
6181, ALL THE KING'S MEN
6938, ALPHA DOG
29918, AMAZING GRACE
7806, ANDREA RISEBOROUGH
29422, ANNA AND THE KING
9846, ANNAPOLIS
21852, APICHATPONG WEERASETHAKUL
24301, ART SCHOOL CONFIDENTIAL
24366, BABEL
38436, BAMBI II
34728, BEAUTIFUL OHIO
5791, BLACK SNAKE MOAN
10531, BOBBY
26553, BONNEVILLE
11079, BORDERTOWN
867, BREAKING AND ENTERING
7918, BROKEDOWN PALACE
34030, BROKEN BRIDGES
13657, BROKEN FLOWERS
12724, BROKEN SKY
33360, CANDY
24510, CANVAS
31906, CATCH A FIRE
29065, CHOKING MAN
18016, CLICK
30012, CLIMATES
23571, COMEDY OF POWER
12407, COPYING BEETHOVEN
15115, CURSE OF THE GOLDEN FLOWER
36298, DAY NIGHT DAY NIGHT
26244, DESTRICTED
37874, DON'T WORRY, I'M FINE
36212, DRAMA
37267, DREAMGIRLS
7480, EDEN
25844, EIGHT BELOW
20591, EYE OF THE DOLPHIN
37952, FACING THE GIANTS
8262, FAMILY LAW
13766, FAST FOOD NATION
36222, FEARLESS
8294, FIVE FINGERS
29786, FLOWERS
1273, FLYBOYS
13308, FREEDOMLAND
14023, GLORY ROAD
27044, GRIDIRON GANG
33097, HALF LIGHT
7879, HALF NELSON
15613, HOLLY
26170, HOLLYWOODLAND
38589, I DO
2924, I DON'T WANT TO SLEEP ALONE
17120, INFAMOUS
23380, INVINCIBLE
880, IRRESISTIBLE
9264, JAM
35835, JINDABYNE
16337, JOURNEY FROM THE FALL
35012, KABUL EXPRESS
22547, KIDULTHOOD
37319, KILL YOUR DARLINGS
2289, LAND OF THE BLIND
35863, LIGHTS IN THE DUSK
11277, LITTLE CHILDREN
24376, LITTLE MISS SUNSHINE
17372, LOL
36308, LONGFORD
7221, LOVE SICK
13713, MADE IN DAGENHAM
39979, MADEA'S FAMILY REUNION
10502, MAN ABOUT TOWN
27801, MAN OF THE YEAR
28455, MARIE ANTOINETTE
6059, MENTOR
3519, MY NAME IS JUANI
25264, NOTES ON A SCANDAL
16171, OFF THE BLACK
36508, ONE NIGHT WITH THE KING
869, ONLY GOD KNOWS
22991, OUT OF THE BLUE
39852, PAN'S LABYRINTH
2753, PEACEFUL WARRIOR
685, PLOY
24369, QUINCEAÑERA
24793, RANG DE BASANTI
36352, REQUIEM
39310, RESCUE DAWN
8379, ROMANCE
5766, RUNNING WITH SCISSORS
31315, SCENES OF A SEXUAL NATURE
17383, SHERRYBABY
3237, SIXTY SIX
35449, SNOW CAKE
27398, SOMETHING NEW
28005, SOUTHLAND TALES
21048, SPECIAL
26020, STARTER FOR 10
947, STEP UP
39786, STICK IT
15851, SWEET MUD
35075, SYNDROMES AND A CENTURY
25661, TAKE THE LEAD
38498, TAXIDERMIA
13090, THAI
6958, THE ASTRONAUT FARMER
35559, THE BANQUET
30285, THE BEACH
12982, THE BUBBLE
36932, THE CAIMAN
19883, THE CHATTERLEY AFFAIR
1096, THE CONRAD BOYS
18997, THE DEPARTED
22346, THE DEVIL WEARS PRADA
31676, THE FLYING SCOTSMAN
33027, THE FOUNTAIN
21650, THE FREE WILL
3655, THE FRONT LINE
15616, THE GUARDIAN
15420, THE HISTORY BOYS
31309, THE HOAX
37551, THE HOTTEST STATE
25529, THE ILLUSIONIST
16834, THE KILLING OF JOHN LENNON
36917, THE LAKE HOUSE
2467, THE LAST KING OF SCOTLAND
28107, THE LAST KISS
14315, THE LIVES OF OTHERS
7800, THE LIVING AND THE DEAD
6207, THE LOVE OF SIAM
19600, THE MISSING STAR
23084, THE PAINTED VEIL
471, THE PURSUIT OF HAPPYNESS
5289, THE QUEEN
28919, THE RETURN
31265, THE SECOND CHANCE
20293, THE WEDDING DIRECTOR
2783, THE WIND THAT SHAKES THE BARLEY
35021, THE YEAR MY PARENTS WENT ON VACATION
18052, THIS IS ENGLAND
13051, TIMES AND WINDS
37543, TRANSYLVANIA
16413, TROPICAL MALADY
25806, UNITED 93
36753, VENUS
20531, VITUS
35728, VOLVER
6338, W.E.
33239, WAIST DEEP
28493, WE ARE MARSHALL
13698, WORLD TRADE CENTER
src, edge_attr, dst
29145, has_genre, 36212
29145, release_year, 35845
14242, has_genre, 36212
14242, release_year, 35845
24039, has_genre, 36212
24039, release_year, 35845
19790, has_genre, 36212
19790, release_year, 35845
8198, has_genre, 36212
8198, release_year, 35845
23754, has_genre, 36212
23754, has_tags, 36212
23754, release_year, 35845
11183, has_genre, 36212
11183, release_year, 35845
6181, has_genre, 36212
6181, release_year, 35845
6938, has_genre, 36212
6938, release_year, 35845
29918, has_genre, 36212
29918, release_year, 35845
29422, has_genre, 36212
29422, in_language, 13090
9846, has_genre, 36212
9846, release_year, 35845
24301, has_genre, 36212
24301, release_year, 35845
24366, has_genre, 36212
24366, has_tags, 36212
24366, release_year, 35845
38436, has_genre, 36212
38436, release_year, 35845
34728, has_genre, 36212
34728, release_year, 35845
5791, has_genre, 36212
5791, release_year, 35845
10531, has_genre, 36212
10531, release_year, 35845
26553, has_genre, 36212
26553, release_year, 35845
11079, has_genre, 36212
11079, release_year, 35845
867, has_genre, 36212
867, release_year, 35845
7918, has_genre, 36212
7918, in_language, 13090
34030, has_genre, 36212
34030, release_year, 35845
13657, has_genre, 36212
13657, has_tags, 36212
13657, has_tags, 29786
12724, has_genre, 36212
12724, release_year, 35845
33360, has_genre, 36212
33360, release_year, 35845
24510, has_genre, 36212
24510, release_year, 35845
31906, has_genre, 36212
31906, release_year, 35845
29065, has_genre, 36212
29065, release_year, 35845
18016, has_genre, 36212
18016, release_year, 35845
30012, has_genre, 36212
30012, release_year, 35845
23571, has_genre, 36212
23571, release_year, 35845
12407, has_genre, 36212
12407, release_year, 35845
15115, has_genre, 36212
15115, release_year, 35845
36298, has_genre, 36212
36298, release_year, 35845
26244, has_genre, 36212
26244, release_year, 35845
37874, has_genre, 36212
37874, release_year, 35845
37267, has_genre, 36212
37267, release_year, 35845
7480, has_genre, 36212
7480, release_year, 35845
25844, has_genre, 36212
25844, release_year, 35845
20591, has_genre, 36212
20591, release_year, 35845
37952, has_genre, 36212
37952, release_year, 35845
8262, has_genre, 36212
8262, release_year, 35845
13766, has_genre, 36212
13766, release_year, 35845
36222, has_genre, 36212
36222, release_year, 35845
8294, has_genre, 36212
8294, release_year, 35845
1273, has_genre, 36212
1273, release_year, 35845
13308, has_genre, 36212
13308, release_year, 35845
14023, has_genre, 36212
14023, release_year, 35845
27044, has_genre, 36212
27044, release_year, 35845
33097, has_genre, 36212
33097, release_year, 35845
7879, has_genre, 36212
7879, release_year, 35845
15613, has_genre, 36212
15613, release_year, 35845
26170, has_genre, 36212
26170, release_year, 35845
38589, has_genre, 36212
38589, release_year, 35845
2924, has_genre, 36212
2924, has_tags, 36212
2924, release_year, 35845
17120, has_genre, 36212
17120, release_year, 35845
23380, has_genre, 36212
23380, release_year, 35845
880, has_genre, 36212
880, release_year, 35845
9264, has_genre, 36212
9264, release_year, 35845
35835, has_genre, 36212
35835, release_year, 35845
16337, has_genre, 36212
16337, release_year, 35845
35012, has_genre, 36212
35012, release_year, 35845
22547, has_genre, 36212
22547, release_year, 35845
37319, has_genre, 36212
37319, release_year, 35845
2289, has_genre, 36212
2289, release_year, 35845
35863, has_genre, 36212
35863, release_year, 35845
11277, has_genre, 36212
11277, has_tags, 36212
11277, release_year, 35845
24376, has_genre, 36212
24376, release_year, 35845
17372, has_genre, 36212
17372, release_year, 35845
36308, has_genre, 36212
36308, release_year, 35845
7221, has_genre, 36212
7221, release_year, 35845
13713, has_genre, 36212
13713, starred_actors, 7806
39979, has_genre, 36212
39979, release_year, 35845
10502, has_genre, 36212
10502, release_year, 35845
27801, has_genre, 36212
27801, release_year, 35845
28455, has_genre, 36212
28455, release_year, 35845
6059, has_genre, 36212
6059, release_year, 35845
3519, has_genre, 36212
3519, release_year, 35845
25264, has_genre, 36212
25264, release_year, 35845
16171, has_genre, 36212
16171, release_year, 35845
36508, has_genre, 36212
36508, release_year, 35845
869, has_genre, 36212
869, release_year, 35845
22991, has_genre, 36212
22991, release_year, 35845
39852, has_genre, 36212
39852, has_tags, 36212
39852, release_year, 35845
2753, has_genre, 36212
2753, release_year, 35845
685, has_genre, 36212
685, in_language, 13090
24369, has_genre, 36212
24369, release_year, 35845
24793, has_genre, 36212
24793, release_year, 35845
36352, has_genre, 36212
36352, release_year, 35845
39310, has_genre, 36212
39310, release_year, 35845
8379, has_genre, 36212
5766, has_genre, 36212
5766, release_year, 35845
31315, has_genre, 36212
31315, release_year, 35845
17383, has_genre, 36212
17383, release_year, 35845
3237, has_genre, 36212
3237, release_year, 35845
35449, has_genre, 36212
35449, release_year, 35845
27398, has_genre, 36212
27398, release_year, 35845
28005, has_genre, 36212
28005, release_year, 35845
21048, has_genre, 36212
21048, release_year, 35845
26020, has_genre, 36212
26020, release_year, 35845
947, has_genre, 36212
947, release_year, 35845
39786, has_genre, 36212
39786, release_year, 35845
15851, has_genre, 36212
15851, release_year, 35845
35075, directed_by, 21852
35075, has_genre, 36212
35075, in_language, 13090
35075, release_year, 35845
35075, written_by, 21852
25661, has_genre, 36212
25661, release_year, 35845
38498, has_genre, 36212
38498, release_year, 35845
6958, has_genre, 36212
6958, release_year, 35845
35559, has_genre, 36212
35559, release_year, 35845
30285, has_genre, 36212
30285, in_language, 13090
12982, has_genre, 36212
12982, release_year, 35845
36932, has_genre, 36212
36932, release_year, 35845
19883, has_genre, 36212
19883, release_year, 35845
1096, has_genre, 36212
1096, release_year, 35845
18997, has_genre, 36212
18997, release_year, 35845
22346, has_genre, 36212
22346, release_year, 35845
31676, has_genre, 36212
31676, release_year, 35845
33027, has_genre, 36212
33027, release_year, 35845
21650, has_genre, 36212
21650, release_year, 35845
3655, has_genre, 36212
3655, release_year, 35845
15616, has_genre, 36212
15616, release_year, 35845
15420, has_genre, 36212
15420, release_year, 35845
31309, has_genre, 36212
31309, release_year, 35845
37551, has_genre, 36212
37551, release_year, 35845
25529, has_genre, 36212
25529, release_year, 35845
16834, has_genre, 36212
16834, release_year, 35845
36917, has_genre, 36212
36917, release_year, 35845
2467, has_genre, 36212
2467, has_tags, 36212
2467, release_year, 35845
28107, has_genre, 36212
28107, release_year, 35845
14315, has_genre, 36212
14315, has_tags, 36212
14315, release_year, 35845
7800, has_genre, 36212
7800, release_year, 35845
6207, has_genre, 36212
6207, in_language, 13090
19600, has_genre, 36212
19600, release_year, 35845
23084, has_genre, 36212
23084, release_year, 35845
471, has_genre, 36212
471, release_year, 35845
5289, has_genre, 36212
5289, release_year, 35845
28919, has_genre, 36212
28919, release_year, 35845
31265, has_genre, 36212
31265, release_year, 35845
20293, has_genre, 36212
20293, release_year, 35845
2783, has_genre, 36212
2783, has_tags, 36212
2783, release_year, 35845
35021, has_genre, 36212
35021, release_year, 35845
18052, has_genre, 36212
18052, release_year, 35845
13051, has_genre, 36212
13051, release_year, 35845
37543, has_genre, 36212
37543, release_year, 35845
16413, directed_by, 21852
16413, has_genre, 36212
16413, in_language, 13090
16413, written_by, 21852
25806, has_genre, 36212
25806, release_year, 35845
36753, has_genre, 36212
36753, release_year, 35845
20531, has_genre, 36212
20531, release_year, 35845
35728, has_genre, 36212
35728, release_year, 35845
6338, has_genre, 36212
6338, has_genre, 8379
6338, starred_actors, 7806
33239, has_genre, 36212
33239, release_year, 35845
28493, has_genre, 36212
28493, release_year, 35845
13698, has_genre, 36212
13698, release_year, 35845
Question: How are ANDREA RISEBOROUGH, FLOWERS, and SYNDROMES AND A CENTURY related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"ANDREA RISEBOROUGH",
"FLOWERS",
"SYNDROMES AND A CENTURY"
],
"valid_edges": [
[
"10 ITEMS OR LESS",
"has_genre",
"DRAMA"
],
[
"10 ITEMS OR LESS",
"release_year",
"2006"
],
[
"A FRIEND OF MINE",
"has_genre",
"DRAMA"
],
[
"A FRIEND OF MINE",
"release_year",
"2006"
],
[
"A GOOD YEAR",
"has_genre",
"DRAMA"
],
[
"A GOOD YEAR",
"release_year",
"2006"
],
[
"A GUIDE TO RECOGNIZING YOUR SAINTS",
"has_genre",
"DRAMA"
],
[
"A GUIDE TO RECOGNIZING YOUR SAINTS",
"release_year",
"2006"
],
[
"A PRAIRIE HOME COMPANION",
"has_genre",
"DRAMA"
],
[
"A PRAIRIE HOME COMPANION",
"release_year",
"2006"
],
[
"AFTER THE WEDDING",
"has_genre",
"DRAMA"
],
[
"AFTER THE WEDDING",
"has_tags",
"DRAMA"
],
[
"AFTER THE WEDDING",
"release_year",
"2006"
],
[
"AKEELAH AND THE BEE",
"has_genre",
"DRAMA"
],
[
"AKEELAH AND THE BEE",
"release_year",
"2006"
],
[
"ALL THE KING'S MEN",
"has_genre",
"DRAMA"
],
[
"ALL THE KING'S MEN",
"release_year",
"2006"
],
[
"ALPHA DOG",
"has_genre",
"DRAMA"
],
[
"ALPHA DOG",
"release_year",
"2006"
],
[
"AMAZING GRACE",
"has_genre",
"DRAMA"
],
[
"AMAZING GRACE",
"release_year",
"2006"
],
[
"ANNA AND THE KING",
"has_genre",
"DRAMA"
],
[
"ANNA AND THE KING",
"in_language",
"THAI"
],
[
"ANNAPOLIS",
"has_genre",
"DRAMA"
],
[
"ANNAPOLIS",
"release_year",
"2006"
],
[
"ART SCHOOL CONFIDENTIAL",
"has_genre",
"DRAMA"
],
[
"ART SCHOOL CONFIDENTIAL",
"release_year",
"2006"
],
[
"BABEL",
"has_genre",
"DRAMA"
],
[
"BABEL",
"has_tags",
"DRAMA"
],
[
"BABEL",
"release_year",
"2006"
],
[
"BAMBI II",
"has_genre",
"DRAMA"
],
[
"BAMBI II",
"release_year",
"2006"
],
[
"BEAUTIFUL OHIO",
"has_genre",
"DRAMA"
],
[
"BEAUTIFUL OHIO",
"release_year",
"2006"
],
[
"BLACK SNAKE MOAN",
"has_genre",
"DRAMA"
],
[
"BLACK SNAKE MOAN",
"release_year",
"2006"
],
[
"BOBBY",
"has_genre",
"DRAMA"
],
[
"BOBBY",
"release_year",
"2006"
],
[
"BONNEVILLE",
"has_genre",
"DRAMA"
],
[
"BONNEVILLE",
"release_year",
"2006"
],
[
"BORDERTOWN",
"has_genre",
"DRAMA"
],
[
"BORDERTOWN",
"release_year",
"2006"
],
[
"BREAKING AND ENTERING",
"has_genre",
"DRAMA"
],
[
"BREAKING AND ENTERING",
"release_year",
"2006"
],
[
"BROKEDOWN PALACE",
"has_genre",
"DRAMA"
],
[
"BROKEDOWN PALACE",
"in_language",
"THAI"
],
[
"BROKEN BRIDGES",
"has_genre",
"DRAMA"
],
[
"BROKEN BRIDGES",
"release_year",
"2006"
],
[
"BROKEN FLOWERS",
"has_genre",
"DRAMA"
],
[
"BROKEN FLOWERS",
"has_tags",
"DRAMA"
],
[
"BROKEN FLOWERS",
"has_tags",
"FLOWERS"
],
[
"BROKEN SKY",
"has_genre",
"DRAMA"
],
[
"BROKEN SKY",
"release_year",
"2006"
],
[
"CANDY",
"has_genre",
"DRAMA"
],
[
"CANDY",
"release_year",
"2006"
],
[
"CANVAS",
"has_genre",
"DRAMA"
],
[
"CANVAS",
"release_year",
"2006"
],
[
"CATCH A FIRE",
"has_genre",
"DRAMA"
],
[
"CATCH A FIRE",
"release_year",
"2006"
],
[
"CHOKING MAN",
"has_genre",
"DRAMA"
],
[
"CHOKING MAN",
"release_year",
"2006"
],
[
"CLICK",
"has_genre",
"DRAMA"
],
[
"CLICK",
"release_year",
"2006"
],
[
"CLIMATES",
"has_genre",
"DRAMA"
],
[
"CLIMATES",
"release_year",
"2006"
],
[
"COMEDY OF POWER",
"has_genre",
"DRAMA"
],
[
"COMEDY OF POWER",
"release_year",
"2006"
],
[
"COPYING BEETHOVEN",
"has_genre",
"DRAMA"
],
[
"COPYING BEETHOVEN",
"release_year",
"2006"
],
[
"CURSE OF THE GOLDEN FLOWER",
"has_genre",
"DRAMA"
],
[
"CURSE OF THE GOLDEN FLOWER",
"release_year",
"2006"
],
[
"DAY NIGHT DAY NIGHT",
"has_genre",
"DRAMA"
],
[
"DAY NIGHT DAY NIGHT",
"release_year",
"2006"
],
[
"DESTRICTED",
"has_genre",
"DRAMA"
],
[
"DESTRICTED",
"release_year",
"2006"
],
[
"DON'T WORRY, I'M FINE",
"has_genre",
"DRAMA"
],
[
"DON'T WORRY, I'M FINE",
"release_year",
"2006"
],
[
"DREAMGIRLS",
"has_genre",
"DRAMA"
],
[
"DREAMGIRLS",
"release_year",
"2006"
],
[
"EDEN",
"has_genre",
"DRAMA"
],
[
"EDEN",
"release_year",
"2006"
],
[
"EIGHT BELOW",
"has_genre",
"DRAMA"
],
[
"EIGHT BELOW",
"release_year",
"2006"
],
[
"EYE OF THE DOLPHIN",
"has_genre",
"DRAMA"
],
[
"EYE OF THE DOLPHIN",
"release_year",
"2006"
],
[
"FACING THE GIANTS",
"has_genre",
"DRAMA"
],
[
"FACING THE GIANTS",
"release_year",
"2006"
],
[
"FAMILY LAW",
"has_genre",
"DRAMA"
],
[
"FAMILY LAW",
"release_year",
"2006"
],
[
"FAST FOOD NATION",
"has_genre",
"DRAMA"
],
[
"FAST FOOD NATION",
"release_year",
"2006"
],
[
"FEARLESS",
"has_genre",
"DRAMA"
],
[
"FEARLESS",
"release_year",
"2006"
],
[
"FIVE FINGERS",
"has_genre",
"DRAMA"
],
[
"FIVE FINGERS",
"release_year",
"2006"
],
[
"FLYBOYS",
"has_genre",
"DRAMA"
],
[
"FLYBOYS",
"release_year",
"2006"
],
[
"FREEDOMLAND",
"has_genre",
"DRAMA"
],
[
"FREEDOMLAND",
"release_year",
"2006"
],
[
"GLORY ROAD",
"has_genre",
"DRAMA"
],
[
"GLORY ROAD",
"release_year",
"2006"
],
[
"GRIDIRON GANG",
"has_genre",
"DRAMA"
],
[
"GRIDIRON GANG",
"release_year",
"2006"
],
[
"HALF LIGHT",
"has_genre",
"DRAMA"
],
[
"HALF LIGHT",
"release_year",
"2006"
],
[
"HALF NELSON",
"has_genre",
"DRAMA"
],
[
"HALF NELSON",
"release_year",
"2006"
],
[
"HOLLY",
"has_genre",
"DRAMA"
],
[
"HOLLY",
"release_year",
"2006"
],
[
"HOLLYWOODLAND",
"has_genre",
"DRAMA"
],
[
"HOLLYWOODLAND",
"release_year",
"2006"
],
[
"I DO",
"has_genre",
"DRAMA"
],
[
"I DO",
"release_year",
"2006"
],
[
"I DON'T WANT TO SLEEP ALONE",
"has_genre",
"DRAMA"
],
[
"I DON'T WANT TO SLEEP ALONE",
"has_tags",
"DRAMA"
],
[
"I DON'T WANT TO SLEEP ALONE",
"release_year",
"2006"
],
[
"INFAMOUS",
"has_genre",
"DRAMA"
],
[
"INFAMOUS",
"release_year",
"2006"
],
[
"INVINCIBLE",
"has_genre",
"DRAMA"
],
[
"INVINCIBLE",
"release_year",
"2006"
],
[
"IRRESISTIBLE",
"has_genre",
"DRAMA"
],
[
"IRRESISTIBLE",
"release_year",
"2006"
],
[
"JAM",
"has_genre",
"DRAMA"
],
[
"JAM",
"release_year",
"2006"
],
[
"JINDABYNE",
"has_genre",
"DRAMA"
],
[
"JINDABYNE",
"release_year",
"2006"
],
[
"JOURNEY FROM THE FALL",
"has_genre",
"DRAMA"
],
[
"JOURNEY FROM THE FALL",
"release_year",
"2006"
],
[
"KABUL EXPRESS",
"has_genre",
"DRAMA"
],
[
"KABUL EXPRESS",
"release_year",
"2006"
],
[
"KIDULTHOOD",
"has_genre",
"DRAMA"
],
[
"KIDULTHOOD",
"release_year",
"2006"
],
[
"KILL YOUR DARLINGS",
"has_genre",
"DRAMA"
],
[
"KILL YOUR DARLINGS",
"release_year",
"2006"
],
[
"LAND OF THE BLIND",
"has_genre",
"DRAMA"
],
[
"LAND OF THE BLIND",
"release_year",
"2006"
],
[
"LIGHTS IN THE DUSK",
"has_genre",
"DRAMA"
],
[
"LIGHTS IN THE DUSK",
"release_year",
"2006"
],
[
"LITTLE CHILDREN",
"has_genre",
"DRAMA"
],
[
"LITTLE CHILDREN",
"has_tags",
"DRAMA"
],
[
"LITTLE CHILDREN",
"release_year",
"2006"
],
[
"LITTLE MISS SUNSHINE",
"has_genre",
"DRAMA"
],
[
"LITTLE MISS SUNSHINE",
"release_year",
"2006"
],
[
"LOL",
"has_genre",
"DRAMA"
],
[
"LOL",
"release_year",
"2006"
],
[
"LONGFORD",
"has_genre",
"DRAMA"
],
[
"LONGFORD",
"release_year",
"2006"
],
[
"LOVE SICK",
"has_genre",
"DRAMA"
],
[
"LOVE SICK",
"release_year",
"2006"
],
[
"MADE IN DAGENHAM",
"has_genre",
"DRAMA"
],
[
"MADE IN DAGENHAM",
"starred_actors",
"ANDREA RISEBOROUGH"
],
[
"MADEA'S FAMILY REUNION",
"has_genre",
"DRAMA"
],
[
"MADEA'S FAMILY REUNION",
"release_year",
"2006"
],
[
"MAN ABOUT TOWN",
"has_genre",
"DRAMA"
],
[
"MAN ABOUT TOWN",
"release_year",
"2006"
],
[
"MAN OF THE YEAR",
"has_genre",
"DRAMA"
],
[
"MAN OF THE YEAR",
"release_year",
"2006"
],
[
"MARIE ANTOINETTE",
"has_genre",
"DRAMA"
],
[
"MARIE ANTOINETTE",
"release_year",
"2006"
],
[
"MENTOR",
"has_genre",
"DRAMA"
],
[
"MENTOR",
"release_year",
"2006"
],
[
"MY NAME IS JUANI",
"has_genre",
"DRAMA"
],
[
"MY NAME IS JUANI",
"release_year",
"2006"
],
[
"NOTES ON A SCANDAL",
"has_genre",
"DRAMA"
],
[
"NOTES ON A SCANDAL",
"release_year",
"2006"
],
[
"OFF THE BLACK",
"has_genre",
"DRAMA"
],
[
"OFF THE BLACK",
"release_year",
"2006"
],
[
"ONE NIGHT WITH THE KING",
"has_genre",
"DRAMA"
],
[
"ONE NIGHT WITH THE KING",
"release_year",
"2006"
],
[
"ONLY GOD KNOWS",
"has_genre",
"DRAMA"
],
[
"ONLY GOD KNOWS",
"release_year",
"2006"
],
[
"OUT OF THE BLUE",
"has_genre",
"DRAMA"
],
[
"OUT OF THE BLUE",
"release_year",
"2006"
],
[
"PAN'S LABYRINTH",
"has_genre",
"DRAMA"
],
[
"PAN'S LABYRINTH",
"has_tags",
"DRAMA"
],
[
"PAN'S LABYRINTH",
"release_year",
"2006"
],
[
"PEACEFUL WARRIOR",
"has_genre",
"DRAMA"
],
[
"PEACEFUL WARRIOR",
"release_year",
"2006"
],
[
"PLOY",
"has_genre",
"DRAMA"
],
[
"PLOY",
"in_language",
"THAI"
],
[
"QUINCEAÑERA",
"has_genre",
"DRAMA"
],
[
"QUINCEAÑERA",
"release_year",
"2006"
],
[
"RANG DE BASANTI",
"has_genre",
"DRAMA"
],
[
"RANG DE BASANTI",
"release_year",
"2006"
],
[
"REQUIEM",
"has_genre",
"DRAMA"
],
[
"REQUIEM",
"release_year",
"2006"
],
[
"RESCUE DAWN",
"has_genre",
"DRAMA"
],
[
"RESCUE DAWN",
"release_year",
"2006"
],
[
"ROMANCE",
"has_genre",
"DRAMA"
],
[
"RUNNING WITH SCISSORS",
"has_genre",
"DRAMA"
],
[
"RUNNING WITH SCISSORS",
"release_year",
"2006"
],
[
"SCENES OF A SEXUAL NATURE",
"has_genre",
"DRAMA"
],
[
"SCENES OF A SEXUAL NATURE",
"release_year",
"2006"
],
[
"SHERRYBABY",
"has_genre",
"DRAMA"
],
[
"SHERRYBABY",
"release_year",
"2006"
],
[
"SIXTY SIX",
"has_genre",
"DRAMA"
],
[
"SIXTY SIX",
"release_year",
"2006"
],
[
"SNOW CAKE",
"has_genre",
"DRAMA"
],
[
"SNOW CAKE",
"release_year",
"2006"
],
[
"SOMETHING NEW",
"has_genre",
"DRAMA"
],
[
"SOMETHING NEW",
"release_year",
"2006"
],
[
"SOUTHLAND TALES",
"has_genre",
"DRAMA"
],
[
"SOUTHLAND TALES",
"release_year",
"2006"
],
[
"SPECIAL",
"has_genre",
"DRAMA"
],
[
"SPECIAL",
"release_year",
"2006"
],
[
"STARTER FOR 10",
"has_genre",
"DRAMA"
],
[
"STARTER FOR 10",
"release_year",
"2006"
],
[
"STEP UP",
"has_genre",
"DRAMA"
],
[
"STEP UP",
"release_year",
"2006"
],
[
"STICK IT",
"has_genre",
"DRAMA"
],
[
"STICK IT",
"release_year",
"2006"
],
[
"SWEET MUD",
"has_genre",
"DRAMA"
],
[
"SWEET MUD",
"release_year",
"2006"
],
[
"SYNDROMES AND A CENTURY",
"directed_by",
"APICHATPONG WEERASETHAKUL"
],
[
"SYNDROMES AND A CENTURY",
"has_genre",
"DRAMA"
],
[
"SYNDROMES AND A CENTURY",
"in_language",
"THAI"
],
[
"SYNDROMES AND A CENTURY",
"release_year",
"2006"
],
[
"SYNDROMES AND A CENTURY",
"written_by",
"APICHATPONG WEERASETHAKUL"
],
[
"TAKE THE LEAD",
"has_genre",
"DRAMA"
],
[
"TAKE THE LEAD",
"release_year",
"2006"
],
[
"TAXIDERMIA",
"has_genre",
"DRAMA"
],
[
"TAXIDERMIA",
"release_year",
"2006"
],
[
"THE ASTRONAUT FARMER",
"has_genre",
"DRAMA"
],
[
"THE ASTRONAUT FARMER",
"release_year",
"2006"
],
[
"THE BANQUET",
"has_genre",
"DRAMA"
],
[
"THE BANQUET",
"release_year",
"2006"
],
[
"THE BEACH",
"has_genre",
"DRAMA"
],
[
"THE BEACH",
"in_language",
"THAI"
],
[
"THE BUBBLE",
"has_genre",
"DRAMA"
],
[
"THE BUBBLE",
"release_year",
"2006"
],
[
"THE CAIMAN",
"has_genre",
"DRAMA"
],
[
"THE CAIMAN",
"release_year",
"2006"
],
[
"THE CHATTERLEY AFFAIR",
"has_genre",
"DRAMA"
],
[
"THE CHATTERLEY AFFAIR",
"release_year",
"2006"
],
[
"THE CONRAD BOYS",
"has_genre",
"DRAMA"
],
[
"THE CONRAD BOYS",
"release_year",
"2006"
],
[
"THE DEPARTED",
"has_genre",
"DRAMA"
],
[
"THE DEPARTED",
"release_year",
"2006"
],
[
"THE DEVIL WEARS PRADA",
"has_genre",
"DRAMA"
],
[
"THE DEVIL WEARS PRADA",
"release_year",
"2006"
],
[
"THE FLYING SCOTSMAN",
"has_genre",
"DRAMA"
],
[
"THE FLYING SCOTSMAN",
"release_year",
"2006"
],
[
"THE FOUNTAIN",
"has_genre",
"DRAMA"
],
[
"THE FOUNTAIN",
"release_year",
"2006"
],
[
"THE FREE WILL",
"has_genre",
"DRAMA"
],
[
"THE FREE WILL",
"release_year",
"2006"
],
[
"THE FRONT LINE",
"has_genre",
"DRAMA"
],
[
"THE FRONT LINE",
"release_year",
"2006"
],
[
"THE GUARDIAN",
"has_genre",
"DRAMA"
],
[
"THE GUARDIAN",
"release_year",
"2006"
],
[
"THE HISTORY BOYS",
"has_genre",
"DRAMA"
],
[
"THE HISTORY BOYS",
"release_year",
"2006"
],
[
"THE HOAX",
"has_genre",
"DRAMA"
],
[
"THE HOAX",
"release_year",
"2006"
],
[
"THE HOTTEST STATE",
"has_genre",
"DRAMA"
],
[
"THE HOTTEST STATE",
"release_year",
"2006"
],
[
"THE ILLUSIONIST",
"has_genre",
"DRAMA"
],
[
"THE ILLUSIONIST",
"release_year",
"2006"
],
[
"THE KILLING OF JOHN LENNON",
"has_genre",
"DRAMA"
],
[
"THE KILLING OF JOHN LENNON",
"release_year",
"2006"
],
[
"THE LAKE HOUSE",
"has_genre",
"DRAMA"
],
[
"THE LAKE HOUSE",
"release_year",
"2006"
],
[
"THE LAST KING OF SCOTLAND",
"has_genre",
"DRAMA"
],
[
"THE LAST KING OF SCOTLAND",
"has_tags",
"DRAMA"
],
[
"THE LAST KING OF SCOTLAND",
"release_year",
"2006"
],
[
"THE LAST KISS",
"has_genre",
"DRAMA"
],
[
"THE LAST KISS",
"release_year",
"2006"
],
[
"THE LIVES OF OTHERS",
"has_genre",
"DRAMA"
],
[
"THE LIVES OF OTHERS",
"has_tags",
"DRAMA"
],
[
"THE LIVES OF OTHERS",
"release_year",
"2006"
],
[
"THE LIVING AND THE DEAD",
"has_genre",
"DRAMA"
],
[
"THE LIVING AND THE DEAD",
"release_year",
"2006"
],
[
"THE LOVE OF SIAM",
"has_genre",
"DRAMA"
],
[
"THE LOVE OF SIAM",
"in_language",
"THAI"
],
[
"THE MISSING STAR",
"has_genre",
"DRAMA"
],
[
"THE MISSING STAR",
"release_year",
"2006"
],
[
"THE PAINTED VEIL",
"has_genre",
"DRAMA"
],
[
"THE PAINTED VEIL",
"release_year",
"2006"
],
[
"THE PURSUIT OF HAPPYNESS",
"has_genre",
"DRAMA"
],
[
"THE PURSUIT OF HAPPYNESS",
"release_year",
"2006"
],
[
"THE QUEEN",
"has_genre",
"DRAMA"
],
[
"THE QUEEN",
"release_year",
"2006"
],
[
"THE RETURN",
"has_genre",
"DRAMA"
],
[
"THE RETURN",
"release_year",
"2006"
],
[
"THE SECOND CHANCE",
"has_genre",
"DRAMA"
],
[
"THE SECOND CHANCE",
"release_year",
"2006"
],
[
"THE WEDDING DIRECTOR",
"has_genre",
"DRAMA"
],
[
"THE WEDDING DIRECTOR",
"release_year",
"2006"
],
[
"THE WIND THAT SHAKES THE BARLEY",
"has_genre",
"DRAMA"
],
[
"THE WIND THAT SHAKES THE BARLEY",
"has_tags",
"DRAMA"
],
[
"THE WIND THAT SHAKES THE BARLEY",
"release_year",
"2006"
],
[
"THE YEAR MY PARENTS WENT ON VACATION",
"has_genre",
"DRAMA"
],
[
"THE YEAR MY PARENTS WENT ON VACATION",
"release_year",
"2006"
],
[
"THIS IS ENGLAND",
"has_genre",
"DRAMA"
],
[
"THIS IS ENGLAND",
"release_year",
"2006"
],
[
"TIMES AND WINDS",
"has_genre",
"DRAMA"
],
[
"TIMES AND WINDS",
"release_year",
"2006"
],
[
"TRANSYLVANIA",
"has_genre",
"DRAMA"
],
[
"TRANSYLVANIA",
"release_year",
"2006"
],
[
"TROPICAL MALADY",
"directed_by",
"APICHATPONG WEERASETHAKUL"
],
[
"TROPICAL MALADY",
"has_genre",
"DRAMA"
],
[
"TROPICAL MALADY",
"in_language",
"THAI"
],
[
"TROPICAL MALADY",
"written_by",
"APICHATPONG WEERASETHAKUL"
],
[
"UNITED 93",
"has_genre",
"DRAMA"
],
[
"UNITED 93",
"release_year",
"2006"
],
[
"VENUS",
"has_genre",
"DRAMA"
],
[
"VENUS",
"release_year",
"2006"
],
[
"VITUS",
"has_genre",
"DRAMA"
],
[
"VITUS",
"release_year",
"2006"
],
[
"VOLVER",
"has_genre",
"DRAMA"
],
[
"VOLVER",
"release_year",
"2006"
],
[
"W.E.",
"has_genre",
"DRAMA"
],
[
"W.E.",
"has_genre",
"ROMANCE"
],
[
"W.E.",
"starred_actors",
"ANDREA RISEBOROUGH"
],
[
"WAIST DEEP",
"has_genre",
"DRAMA"
],
[
"WAIST DEEP",
"release_year",
"2006"
],
[
"WE ARE MARSHALL",
"has_genre",
"DRAMA"
],
[
"WE ARE MARSHALL",
"release_year",
"2006"
],
[
"WORLD TRADE CENTER",
"has_genre",
"DRAMA"
],
[
"WORLD TRADE CENTER",
"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
24438, 1993
12342, 54
19407, 8½
37315, A BRONX TALE
30146, A CHRISTMAS CAROL
26698, A FAR OFF PLACE
9302, A HOME OF OUR OWN
458, A PERFECT WORLD
18239, A RAISIN IN THE SUN
28624, A SHINE OF RAINBOWS
30135, ABRAHAM'S VALLEY
35253, ACE OF HEARTS
25900, ALMOST FAMOUS
9677, ANATOMY OF A MURDER
28792, AND THE BAND PLAYED ON
3952, ANGELS SING
36963, ANNA KARENINA
6309, BABY TAKE A BOW
14561, BEETHOVEN'S 2ND
16426, BELLE DE JOUR
2313, BEN-HUR
3256, BHAJI ON THE BEACH
20511, BOPHA!
17565, BORN ON THE FOURTH OF JULY
37616, BORN YESTERDAY
4847, BOXING HELENA
12541, BRASSED OFF
7461, BROTHERHOOD OF THE WOLF
37190, CALENDAR
16076, CALIGULA
33362, CARLITO'S WAY
3034, CAT ON A HOT TIN ROOF
31459, CHILDREN OF HEAVEN
18016, CLICK
30463, COMEDY
10272, CONFESSIONS OF A TEENAGE DRAMA QUEEN
31694, DEADFALL
13280, DENNIS THE MENACE
25805, DOCTOR ZHIVAGO
3032, DOLPHIN TALE
8573, DR. DOLITTLE 3
36212, DRAMA
7543, EDWARD SCISSORHANDS
8413, ETHAN FROME
10648, EVEN COWGIRLS GET THE BLUES
36165, FALLING DOWN
10509, FAMILY
22958, FAMOUS
26935, FAREWELL MY CONCUBINE
19305, FAT ALBERT
36222, FEARLESS
28574, FIDDLER ON THE ROOF
26507, FIORILE
25869, FIRE IN THE SKY
255, FLASHDANCE
18521, FLY AWAY HOME
20125, FREE WILLY
28119, GRAND HOTEL
18687, GUILTY AS SIN
19871, GYPSY
1937, HANNAH AND HER SISTERS
17345, HERE WITHOUT ME
1044, HOTEL RWANDA
34869, HOTEL TRANSYLVANIA
19380, HOUSE OF CARDS
390, HOW GREEN WAS MY VALLEY
12466, I DON'T WANT TO TALK ABOUT IT
11757, IF....
10400, INDECENT PROPOSAL
18026, INDIAN SUMMER
17120, INFAMOUS
39987, IT RUNS IN THE FAMILY
1331, IT'S A WONDERFUL LIFE
14188, JACK THE BEAR
7228, JOSH AND S.A.M.
6713, KAMCHATKA
21224, KIKUJIRO
38467, KIND HEARTS AND CORONETS
634, KYLA PRATT
27812, LA ESTRATEGIA DEL CARACOL
14601, LES MISÉRABLES
39471, LETTERS TO JULIET
36763, LITTLE BUDDHA
2352, LITTLE LORD FAUNTLEROY
26784, LITTLE WOMEN
35491, LOOK WHO'S TALKING NOW
35537, LORDS OF DOGTOWN
36539, M. BUTTERFLY
14587, MAD DOG AND GLORY
37867, MAN ON THE MOON
18216, MENACE II SOCIETY
995, MIDNIGHT IN THE GARDEN OF GOOD AND EVIL
25936, MONA LISA SMILE
21188, MR. JONES
12358, MY FAVORITE SEASON
3159, NAKED
20367, NICHOLAS MONSARRAT
16827, NOWHERE TO RUN
15644, OLIVER TWIST
3656, ORDINARY PEOPLE
5023, PARENTHOOD
27284, PARIS, FRANCE
23801, PARTY MONSTER
11222, PATHER PANCHALI
3389, PHILADELPHIA
4343, POETIC JUSTICE
40032, PUBLIC ACCESS
2738, ROMEO AND JULIET
14507, SAVANNAH
34329, SCHINDLER'S LIST
15974, SEARCHING FOR BOBBY FISCHER
6577, SHILOH
26699, SHORT CUTS
31824, SIX DEGREES OF SEPARATION
37133, SOMEWHERE
5873, SOMMERSBY
11124, STALINGRAD
13467, STRAPPED
14474, SULLIVAN'S TRAVELS
32587, SUMMER HOURS
33839, SWING KIDS
27310, THE AGE OF INNOCENCE
4789, THE BROTHERS MCMULLEN
9399, THE CEMENT GARDEN
6882, THE COLOR PURPLE
30812, THE DARK CRYSTAL
18997, THE DEPARTED
26726, THE DIARY OF ANNE FRANK
32295, THE DILEMMA
28948, THE FAMILY STONE
10363, THE FUGITIVE
34001, THE HOUSE OF THE SPIRITS
39978, THE HUMAN COMEDY
40066, THE JUNGLE BOOK
22224, THE LITTLEST REBEL
36676, THE MAN WITHOUT A FACE
30868, THE MUSIC OF CHANCE
19496, THE PIANO
6296, THE RED SQUIRREL
13761, THE ROOKIE
26278, THE SECRET GARDEN
2702, THE SILVER BRUMBY
24562, THE SLINGSHOT
11064, THE SNAPPER
12455, THE STORY OF ESTHER COSTELLO
39883, THE STORY OF THE WEEPING CAMEL
25489, THE THING CALLED LOVE
7816, THE THREE MUSKETEERS
14983, THE WINSLOW BOY
34407, THE WRONG MAN
11863, THE YEAR OF LIVING DANGEROUSLY
27519, THE YEARLING
37639, THE YOUNG AMERICANS
25299, UNTAMED HEART
8957, WE BOUGHT A ZOO
9837, WHAT'S EATING GILBERT GRAPE
34987, WHAT'S LOVE GOT TO DO WITH IT
19679, WIDE AWAKE
3585, WIDE-EYED AND LEGLESS
22756, WINDOW TO PARIS
22077, WRESTLING ERNEST HEMINGWAY
12162, YOU CAN COUNT ON ME
src, edge_attr, dst
12342, has_genre, 36212
12342, has_imdb_votes, 22958
19407, has_genre, 36212
19407, has_imdb_votes, 22958
37315, has_genre, 36212
37315, release_year, 24438
30146, has_genre, 36212
30146, has_genre, 10509
30146, has_imdb_votes, 22958
26698, has_genre, 36212
26698, has_genre, 10509
26698, release_year, 24438
9302, has_genre, 36212
9302, release_year, 24438
458, has_genre, 36212
458, release_year, 24438
18239, has_genre, 36212
18239, has_tags, 10509
28624, has_genre, 36212
28624, has_genre, 10509
30135, has_genre, 36212
30135, release_year, 24438
35253, has_genre, 36212
35253, has_genre, 10509
25900, has_genre, 36212
25900, has_imdb_votes, 22958
25900, has_tags, 36212
9677, has_genre, 36212
9677, has_imdb_votes, 22958
28792, has_genre, 36212
28792, release_year, 24438
3952, has_genre, 36212
3952, has_genre, 10509
36963, has_genre, 36212
36963, has_imdb_votes, 22958
36963, has_tags, 36212
6309, has_genre, 36212
6309, has_genre, 10509
14561, has_genre, 10509
14561, release_year, 24438
16426, has_genre, 36212
16426, has_imdb_votes, 22958
16426, has_tags, 36212
2313, has_genre, 36212
2313, has_imdb_votes, 22958
3256, has_genre, 36212
3256, release_year, 24438
20511, has_genre, 36212
20511, release_year, 24438
17565, has_genre, 36212
17565, has_imdb_votes, 22958
17565, has_tags, 36212
37616, has_genre, 36212
37616, release_year, 24438
4847, has_genre, 36212
4847, release_year, 24438
12541, has_genre, 36212
12541, has_imdb_votes, 22958
7461, has_genre, 36212
7461, has_imdb_votes, 22958
37190, has_genre, 36212
37190, release_year, 24438
16076, has_genre, 36212
16076, has_imdb_votes, 22958
33362, has_genre, 36212
33362, release_year, 24438
3034, has_genre, 36212
3034, has_tags, 10509
31459, has_genre, 36212
31459, has_genre, 10509
18016, has_genre, 36212
18016, has_tags, 10509
10272, has_genre, 10509
10272, has_tags, 36212
31694, has_genre, 36212
31694, release_year, 24438
13280, has_genre, 10509
13280, release_year, 24438
25805, has_genre, 36212
25805, has_imdb_votes, 22958
3032, has_genre, 36212
3032, has_genre, 10509
3032, has_tags, 10509
8573, has_genre, 30463
8573, has_genre, 10509
8573, starred_actors, 634
7543, has_genre, 36212
7543, has_tags, 10509
8413, has_genre, 36212
8413, release_year, 24438
10648, has_genre, 36212
10648, release_year, 24438
36165, has_genre, 36212
36165, release_year, 24438
26935, has_genre, 36212
26935, release_year, 24438
19305, has_genre, 30463
19305, starred_actors, 634
36222, has_genre, 36212
36222, release_year, 24438
28574, has_genre, 36212
28574, has_genre, 10509
28574, has_imdb_votes, 22958
26507, has_genre, 36212
26507, release_year, 24438
25869, has_genre, 36212
25869, release_year, 24438
255, has_genre, 36212
255, has_imdb_votes, 22958
18521, has_genre, 36212
18521, has_genre, 10509
20125, has_genre, 36212
20125, has_genre, 10509
20125, has_imdb_votes, 22958
20125, has_tags, 10509
20125, release_year, 24438
28119, has_genre, 36212
28119, has_imdb_votes, 22958
18687, has_genre, 36212
18687, release_year, 24438
19871, has_genre, 36212
19871, release_year, 24438
1937, has_genre, 36212
1937, has_tags, 10509
17345, has_genre, 36212
17345, has_genre, 10509
1044, has_genre, 36212
1044, has_tags, 36212
1044, has_tags, 10509
34869, has_genre, 10509
34869, has_imdb_votes, 22958
19380, has_genre, 36212
19380, release_year, 24438
390, has_genre, 36212
390, has_genre, 10509
12466, has_genre, 36212
12466, release_year, 24438
11757, has_genre, 36212
11757, has_imdb_votes, 22958
10400, has_genre, 36212
10400, release_year, 24438
18026, has_genre, 36212
18026, release_year, 24438
17120, has_genre, 36212
17120, has_imdb_votes, 22958
39987, has_genre, 36212
39987, has_genre, 10509
1331, has_genre, 36212
1331, has_genre, 10509
1331, has_tags, 36212
1331, has_tags, 10509
14188, has_genre, 36212
14188, release_year, 24438
7228, has_genre, 36212
7228, release_year, 24438
6713, has_genre, 36212
6713, has_tags, 10509
21224, has_genre, 36212
21224, has_imdb_votes, 22958
38467, has_imdb_votes, 22958
38467, has_tags, 10509
27812, has_genre, 36212
27812, release_year, 24438
14601, has_genre, 36212
14601, has_imdb_votes, 22958
39471, has_genre, 36212
39471, has_imdb_votes, 22958
36763, has_genre, 36212
36763, release_year, 24438
2352, has_genre, 36212
2352, has_genre, 10509
26784, has_genre, 36212
26784, has_genre, 10509
26784, has_tags, 36212
35491, has_genre, 10509
35491, has_tags, 10509
35491, release_year, 24438
35537, has_genre, 36212
35537, has_imdb_votes, 22958
36539, has_genre, 36212
36539, release_year, 24438
14587, has_genre, 36212
14587, release_year, 24438
37867, has_genre, 36212
37867, has_imdb_votes, 22958
18216, has_genre, 36212
18216, release_year, 24438
995, has_genre, 36212
995, has_imdb_votes, 22958
25936, has_genre, 36212
25936, has_imdb_votes, 22958
21188, has_genre, 36212
21188, release_year, 24438
12358, has_genre, 36212
12358, release_year, 24438
3159, has_genre, 36212
3159, release_year, 24438
16827, has_genre, 36212
16827, release_year, 24438
15644, has_genre, 36212
15644, has_imdb_votes, 22958
3656, has_genre, 36212
3656, has_tags, 10509
5023, has_genre, 36212
5023, has_tags, 10509
27284, has_genre, 36212
27284, release_year, 24438
23801, has_genre, 36212
23801, has_imdb_votes, 22958
11222, has_genre, 36212
11222, has_tags, 10509
3389, has_genre, 36212
3389, release_year, 24438
4343, has_genre, 36212
4343, release_year, 24438
40032, has_genre, 36212
40032, release_year, 24438
2738, has_genre, 36212
2738, has_imdb_votes, 22958
14507, has_genre, 36212
14507, has_genre, 10509
34329, has_genre, 36212
34329, has_tags, 36212
34329, release_year, 24438
15974, has_genre, 36212
15974, release_year, 24438
6577, has_genre, 36212
6577, has_genre, 10509
26699, has_genre, 36212
26699, release_year, 24438
31824, has_genre, 36212
31824, release_year, 24438
37133, has_genre, 36212
37133, has_imdb_votes, 22958
5873, has_genre, 36212
5873, release_year, 24438
11124, has_genre, 36212
11124, release_year, 24438
13467, has_genre, 36212
13467, release_year, 24438
14474, has_genre, 36212
14474, has_imdb_votes, 22958
32587, has_genre, 36212
32587, has_genre, 10509
33839, has_genre, 36212
33839, release_year, 24438
27310, has_genre, 36212
27310, release_year, 24438
4789, has_genre, 36212
4789, has_tags, 10509
9399, has_genre, 36212
9399, release_year, 24438
6882, has_genre, 36212
6882, has_imdb_votes, 22958
30812, has_genre, 10509
30812, has_imdb_votes, 22958
18997, has_genre, 36212
18997, has_imdb_votes, 22958
26726, has_genre, 36212
26726, has_genre, 10509
32295, has_genre, 36212
32295, has_imdb_votes, 22958
28948, has_genre, 36212
28948, has_tags, 36212
28948, has_tags, 10509
10363, has_genre, 36212
10363, release_year, 24438
34001, has_genre, 36212
34001, release_year, 24438
39978, has_genre, 36212
39978, has_genre, 10509
40066, has_genre, 10509
40066, has_imdb_votes, 22958
22224, has_genre, 36212
22224, has_genre, 10509
36676, has_genre, 36212
36676, has_tags, 36212
36676, release_year, 24438
30868, has_genre, 36212
30868, release_year, 24438
19496, has_genre, 36212
19496, release_year, 24438
6296, has_genre, 36212
6296, release_year, 24438
13761, has_genre, 36212
13761, has_imdb_votes, 22958
26278, has_genre, 36212
26278, release_year, 24438
2702, has_genre, 36212
2702, has_genre, 10509
2702, release_year, 24438
24562, has_genre, 36212
24562, release_year, 24438
11064, has_tags, 10509
11064, release_year, 24438
12455, has_genre, 36212
12455, written_by, 20367
39883, has_genre, 36212
39883, has_genre, 10509
39883, has_tags, 10509
25489, has_genre, 36212
25489, release_year, 24438
7816, has_genre, 36212
7816, release_year, 24438
14983, has_genre, 36212
14983, has_tags, 10509
34407, has_genre, 36212
34407, release_year, 24438
11863, has_genre, 36212
11863, has_imdb_votes, 22958
27519, has_genre, 36212
27519, has_genre, 10509
37639, has_genre, 36212
37639, release_year, 24438
25299, has_genre, 36212
25299, release_year, 24438
8957, has_genre, 36212
8957, has_genre, 10509
8957, has_tags, 10509
9837, has_genre, 36212
9837, release_year, 24438
34987, has_genre, 36212
34987, release_year, 24438
19679, has_genre, 36212
19679, has_genre, 10509
3585, has_genre, 36212
3585, release_year, 24438
22756, has_genre, 36212
22756, release_year, 24438
22077, has_genre, 36212
22077, release_year, 24438
12162, has_genre, 36212
12162, has_tags, 10509
Question: In what context are FREE WILLY, KYLA PRATT, and NICHOLAS MONSARRAT connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"FREE WILLY",
"KYLA PRATT",
"NICHOLAS MONSARRAT"
],
"valid_edges": [
[
"54",
"has_genre",
"DRAMA"
],
[
"54",
"has_imdb_votes",
"FAMOUS"
],
[
"8½",
"has_genre",
"DRAMA"
],
[
"8½",
"has_imdb_votes",
"FAMOUS"
],
[
"A BRONX TALE",
"has_genre",
"DRAMA"
],
[
"A BRONX TALE",
"release_year",
"1993"
],
[
"A CHRISTMAS CAROL",
"has_genre",
"DRAMA"
],
[
"A CHRISTMAS CAROL",
"has_genre",
"FAMILY"
],
[
"A CHRISTMAS CAROL",
"has_imdb_votes",
"FAMOUS"
],
[
"A FAR OFF PLACE",
"has_genre",
"DRAMA"
],
[
"A FAR OFF PLACE",
"has_genre",
"FAMILY"
],
[
"A FAR OFF PLACE",
"release_year",
"1993"
],
[
"A HOME OF OUR OWN",
"has_genre",
"DRAMA"
],
[
"A HOME OF OUR OWN",
"release_year",
"1993"
],
[
"A PERFECT WORLD",
"has_genre",
"DRAMA"
],
[
"A PERFECT WORLD",
"release_year",
"1993"
],
[
"A RAISIN IN THE SUN",
"has_genre",
"DRAMA"
],
[
"A RAISIN IN THE SUN",
"has_tags",
"FAMILY"
],
[
"A SHINE OF RAINBOWS",
"has_genre",
"DRAMA"
],
[
"A SHINE OF RAINBOWS",
"has_genre",
"FAMILY"
],
[
"ABRAHAM'S VALLEY",
"has_genre",
"DRAMA"
],
[
"ABRAHAM'S VALLEY",
"release_year",
"1993"
],
[
"ACE OF HEARTS",
"has_genre",
"DRAMA"
],
[
"ACE OF HEARTS",
"has_genre",
"FAMILY"
],
[
"ALMOST FAMOUS",
"has_genre",
"DRAMA"
],
[
"ALMOST FAMOUS",
"has_imdb_votes",
"FAMOUS"
],
[
"ALMOST FAMOUS",
"has_tags",
"DRAMA"
],
[
"ANATOMY OF A MURDER",
"has_genre",
"DRAMA"
],
[
"ANATOMY OF A MURDER",
"has_imdb_votes",
"FAMOUS"
],
[
"AND THE BAND PLAYED ON",
"has_genre",
"DRAMA"
],
[
"AND THE BAND PLAYED ON",
"release_year",
"1993"
],
[
"ANGELS SING",
"has_genre",
"DRAMA"
],
[
"ANGELS SING",
"has_genre",
"FAMILY"
],
[
"ANNA KARENINA",
"has_genre",
"DRAMA"
],
[
"ANNA KARENINA",
"has_imdb_votes",
"FAMOUS"
],
[
"ANNA KARENINA",
"has_tags",
"DRAMA"
],
[
"BABY TAKE A BOW",
"has_genre",
"DRAMA"
],
[
"BABY TAKE A BOW",
"has_genre",
"FAMILY"
],
[
"BEETHOVEN'S 2ND",
"has_genre",
"FAMILY"
],
[
"BEETHOVEN'S 2ND",
"release_year",
"1993"
],
[
"BELLE DE JOUR",
"has_genre",
"DRAMA"
],
[
"BELLE DE JOUR",
"has_imdb_votes",
"FAMOUS"
],
[
"BELLE DE JOUR",
"has_tags",
"DRAMA"
],
[
"BEN-HUR",
"has_genre",
"DRAMA"
],
[
"BEN-HUR",
"has_imdb_votes",
"FAMOUS"
],
[
"BHAJI ON THE BEACH",
"has_genre",
"DRAMA"
],
[
"BHAJI ON THE BEACH",
"release_year",
"1993"
],
[
"BOPHA!",
"has_genre",
"DRAMA"
],
[
"BOPHA!",
"release_year",
"1993"
],
[
"BORN ON THE FOURTH OF JULY",
"has_genre",
"DRAMA"
],
[
"BORN ON THE FOURTH OF JULY",
"has_imdb_votes",
"FAMOUS"
],
[
"BORN ON THE FOURTH OF JULY",
"has_tags",
"DRAMA"
],
[
"BORN YESTERDAY",
"has_genre",
"DRAMA"
],
[
"BORN YESTERDAY",
"release_year",
"1993"
],
[
"BOXING HELENA",
"has_genre",
"DRAMA"
],
[
"BOXING HELENA",
"release_year",
"1993"
],
[
"BRASSED OFF",
"has_genre",
"DRAMA"
],
[
"BRASSED OFF",
"has_imdb_votes",
"FAMOUS"
],
[
"BROTHERHOOD OF THE WOLF",
"has_genre",
"DRAMA"
],
[
"BROTHERHOOD OF THE WOLF",
"has_imdb_votes",
"FAMOUS"
],
[
"CALENDAR",
"has_genre",
"DRAMA"
],
[
"CALENDAR",
"release_year",
"1993"
],
[
"CALIGULA",
"has_genre",
"DRAMA"
],
[
"CALIGULA",
"has_imdb_votes",
"FAMOUS"
],
[
"CARLITO'S WAY",
"has_genre",
"DRAMA"
],
[
"CARLITO'S WAY",
"release_year",
"1993"
],
[
"CAT ON A HOT TIN ROOF",
"has_genre",
"DRAMA"
],
[
"CAT ON A HOT TIN ROOF",
"has_tags",
"FAMILY"
],
[
"CHILDREN OF HEAVEN",
"has_genre",
"DRAMA"
],
[
"CHILDREN OF HEAVEN",
"has_genre",
"FAMILY"
],
[
"CLICK",
"has_genre",
"DRAMA"
],
[
"CLICK",
"has_tags",
"FAMILY"
],
[
"CONFESSIONS OF A TEENAGE DRAMA QUEEN",
"has_genre",
"FAMILY"
],
[
"CONFESSIONS OF A TEENAGE DRAMA QUEEN",
"has_tags",
"DRAMA"
],
[
"DEADFALL",
"has_genre",
"DRAMA"
],
[
"DEADFALL",
"release_year",
"1993"
],
[
"DENNIS THE MENACE",
"has_genre",
"FAMILY"
],
[
"DENNIS THE MENACE",
"release_year",
"1993"
],
[
"DOCTOR ZHIVAGO",
"has_genre",
"DRAMA"
],
[
"DOCTOR ZHIVAGO",
"has_imdb_votes",
"FAMOUS"
],
[
"DOLPHIN TALE",
"has_genre",
"DRAMA"
],
[
"DOLPHIN TALE",
"has_genre",
"FAMILY"
],
[
"DOLPHIN TALE",
"has_tags",
"FAMILY"
],
[
"DR. DOLITTLE 3",
"has_genre",
"COMEDY"
],
[
"DR. DOLITTLE 3",
"has_genre",
"FAMILY"
],
[
"DR. DOLITTLE 3",
"starred_actors",
"KYLA PRATT"
],
[
"EDWARD SCISSORHANDS",
"has_genre",
"DRAMA"
],
[
"EDWARD SCISSORHANDS",
"has_tags",
"FAMILY"
],
[
"ETHAN FROME",
"has_genre",
"DRAMA"
],
[
"ETHAN FROME",
"release_year",
"1993"
],
[
"EVEN COWGIRLS GET THE BLUES",
"has_genre",
"DRAMA"
],
[
"EVEN COWGIRLS GET THE BLUES",
"release_year",
"1993"
],
[
"FALLING DOWN",
"has_genre",
"DRAMA"
],
[
"FALLING DOWN",
"release_year",
"1993"
],
[
"FAREWELL MY CONCUBINE",
"has_genre",
"DRAMA"
],
[
"FAREWELL MY CONCUBINE",
"release_year",
"1993"
],
[
"FAT ALBERT",
"has_genre",
"COMEDY"
],
[
"FAT ALBERT",
"starred_actors",
"KYLA PRATT"
],
[
"FEARLESS",
"has_genre",
"DRAMA"
],
[
"FEARLESS",
"release_year",
"1993"
],
[
"FIDDLER ON THE ROOF",
"has_genre",
"DRAMA"
],
[
"FIDDLER ON THE ROOF",
"has_genre",
"FAMILY"
],
[
"FIDDLER ON THE ROOF",
"has_imdb_votes",
"FAMOUS"
],
[
"FIORILE",
"has_genre",
"DRAMA"
],
[
"FIORILE",
"release_year",
"1993"
],
[
"FIRE IN THE SKY",
"has_genre",
"DRAMA"
],
[
"FIRE IN THE SKY",
"release_year",
"1993"
],
[
"FLASHDANCE",
"has_genre",
"DRAMA"
],
[
"FLASHDANCE",
"has_imdb_votes",
"FAMOUS"
],
[
"FLY AWAY HOME",
"has_genre",
"DRAMA"
],
[
"FLY AWAY HOME",
"has_genre",
"FAMILY"
],
[
"FREE WILLY",
"has_genre",
"DRAMA"
],
[
"FREE WILLY",
"has_genre",
"FAMILY"
],
[
"FREE WILLY",
"has_imdb_votes",
"FAMOUS"
],
[
"FREE WILLY",
"has_tags",
"FAMILY"
],
[
"FREE WILLY",
"release_year",
"1993"
],
[
"GRAND HOTEL",
"has_genre",
"DRAMA"
],
[
"GRAND HOTEL",
"has_imdb_votes",
"FAMOUS"
],
[
"GUILTY AS SIN",
"has_genre",
"DRAMA"
],
[
"GUILTY AS SIN",
"release_year",
"1993"
],
[
"GYPSY",
"has_genre",
"DRAMA"
],
[
"GYPSY",
"release_year",
"1993"
],
[
"HANNAH AND HER SISTERS",
"has_genre",
"DRAMA"
],
[
"HANNAH AND HER SISTERS",
"has_tags",
"FAMILY"
],
[
"HERE WITHOUT ME",
"has_genre",
"DRAMA"
],
[
"HERE WITHOUT ME",
"has_genre",
"FAMILY"
],
[
"HOTEL RWANDA",
"has_genre",
"DRAMA"
],
[
"HOTEL RWANDA",
"has_tags",
"DRAMA"
],
[
"HOTEL RWANDA",
"has_tags",
"FAMILY"
],
[
"HOTEL TRANSYLVANIA",
"has_genre",
"FAMILY"
],
[
"HOTEL TRANSYLVANIA",
"has_imdb_votes",
"FAMOUS"
],
[
"HOUSE OF CARDS",
"has_genre",
"DRAMA"
],
[
"HOUSE OF CARDS",
"release_year",
"1993"
],
[
"HOW GREEN WAS MY VALLEY",
"has_genre",
"DRAMA"
],
[
"HOW GREEN WAS MY VALLEY",
"has_genre",
"FAMILY"
],
[
"I DON'T WANT TO TALK ABOUT IT",
"has_genre",
"DRAMA"
],
[
"I DON'T WANT TO TALK ABOUT IT",
"release_year",
"1993"
],
[
"IF....",
"has_genre",
"DRAMA"
],
[
"IF....",
"has_imdb_votes",
"FAMOUS"
],
[
"INDECENT PROPOSAL",
"has_genre",
"DRAMA"
],
[
"INDECENT PROPOSAL",
"release_year",
"1993"
],
[
"INDIAN SUMMER",
"has_genre",
"DRAMA"
],
[
"INDIAN SUMMER",
"release_year",
"1993"
],
[
"INFAMOUS",
"has_genre",
"DRAMA"
],
[
"INFAMOUS",
"has_imdb_votes",
"FAMOUS"
],
[
"IT RUNS IN THE FAMILY",
"has_genre",
"DRAMA"
],
[
"IT RUNS IN THE FAMILY",
"has_genre",
"FAMILY"
],
[
"IT'S A WONDERFUL LIFE",
"has_genre",
"DRAMA"
],
[
"IT'S A WONDERFUL LIFE",
"has_genre",
"FAMILY"
],
[
"IT'S A WONDERFUL LIFE",
"has_tags",
"DRAMA"
],
[
"IT'S A WONDERFUL LIFE",
"has_tags",
"FAMILY"
],
[
"JACK THE BEAR",
"has_genre",
"DRAMA"
],
[
"JACK THE BEAR",
"release_year",
"1993"
],
[
"JOSH AND S.A.M.",
"has_genre",
"DRAMA"
],
[
"JOSH AND S.A.M.",
"release_year",
"1993"
],
[
"KAMCHATKA",
"has_genre",
"DRAMA"
],
[
"KAMCHATKA",
"has_tags",
"FAMILY"
],
[
"KIKUJIRO",
"has_genre",
"DRAMA"
],
[
"KIKUJIRO",
"has_imdb_votes",
"FAMOUS"
],
[
"KIND HEARTS AND CORONETS",
"has_imdb_votes",
"FAMOUS"
],
[
"KIND HEARTS AND CORONETS",
"has_tags",
"FAMILY"
],
[
"LA ESTRATEGIA DEL CARACOL",
"has_genre",
"DRAMA"
],
[
"LA ESTRATEGIA DEL CARACOL",
"release_year",
"1993"
],
[
"LES MISÉRABLES",
"has_genre",
"DRAMA"
],
[
"LES MISÉRABLES",
"has_imdb_votes",
"FAMOUS"
],
[
"LETTERS TO JULIET",
"has_genre",
"DRAMA"
],
[
"LETTERS TO JULIET",
"has_imdb_votes",
"FAMOUS"
],
[
"LITTLE BUDDHA",
"has_genre",
"DRAMA"
],
[
"LITTLE BUDDHA",
"release_year",
"1993"
],
[
"LITTLE LORD FAUNTLEROY",
"has_genre",
"DRAMA"
],
[
"LITTLE LORD FAUNTLEROY",
"has_genre",
"FAMILY"
],
[
"LITTLE WOMEN",
"has_genre",
"DRAMA"
],
[
"LITTLE WOMEN",
"has_genre",
"FAMILY"
],
[
"LITTLE WOMEN",
"has_tags",
"DRAMA"
],
[
"LOOK WHO'S TALKING NOW",
"has_genre",
"FAMILY"
],
[
"LOOK WHO'S TALKING NOW",
"has_tags",
"FAMILY"
],
[
"LOOK WHO'S TALKING NOW",
"release_year",
"1993"
],
[
"LORDS OF DOGTOWN",
"has_genre",
"DRAMA"
],
[
"LORDS OF DOGTOWN",
"has_imdb_votes",
"FAMOUS"
],
[
"M. BUTTERFLY",
"has_genre",
"DRAMA"
],
[
"M. BUTTERFLY",
"release_year",
"1993"
],
[
"MAD DOG AND GLORY",
"has_genre",
"DRAMA"
],
[
"MAD DOG AND GLORY",
"release_year",
"1993"
],
[
"MAN ON THE MOON",
"has_genre",
"DRAMA"
],
[
"MAN ON THE MOON",
"has_imdb_votes",
"FAMOUS"
],
[
"MENACE II SOCIETY",
"has_genre",
"DRAMA"
],
[
"MENACE II SOCIETY",
"release_year",
"1993"
],
[
"MIDNIGHT IN THE GARDEN OF GOOD AND EVIL",
"has_genre",
"DRAMA"
],
[
"MIDNIGHT IN THE GARDEN OF GOOD AND EVIL",
"has_imdb_votes",
"FAMOUS"
],
[
"MONA LISA SMILE",
"has_genre",
"DRAMA"
],
[
"MONA LISA SMILE",
"has_imdb_votes",
"FAMOUS"
],
[
"MR. JONES",
"has_genre",
"DRAMA"
],
[
"MR. JONES",
"release_year",
"1993"
],
[
"MY FAVORITE SEASON",
"has_genre",
"DRAMA"
],
[
"MY FAVORITE SEASON",
"release_year",
"1993"
],
[
"NAKED",
"has_genre",
"DRAMA"
],
[
"NAKED",
"release_year",
"1993"
],
[
"NOWHERE TO RUN",
"has_genre",
"DRAMA"
],
[
"NOWHERE TO RUN",
"release_year",
"1993"
],
[
"OLIVER TWIST",
"has_genre",
"DRAMA"
],
[
"OLIVER TWIST",
"has_imdb_votes",
"FAMOUS"
],
[
"ORDINARY PEOPLE",
"has_genre",
"DRAMA"
],
[
"ORDINARY PEOPLE",
"has_tags",
"FAMILY"
],
[
"PARENTHOOD",
"has_genre",
"DRAMA"
],
[
"PARENTHOOD",
"has_tags",
"FAMILY"
],
[
"PARIS, FRANCE",
"has_genre",
"DRAMA"
],
[
"PARIS, FRANCE",
"release_year",
"1993"
],
[
"PARTY MONSTER",
"has_genre",
"DRAMA"
],
[
"PARTY MONSTER",
"has_imdb_votes",
"FAMOUS"
],
[
"PATHER PANCHALI",
"has_genre",
"DRAMA"
],
[
"PATHER PANCHALI",
"has_tags",
"FAMILY"
],
[
"PHILADELPHIA",
"has_genre",
"DRAMA"
],
[
"PHILADELPHIA",
"release_year",
"1993"
],
[
"POETIC JUSTICE",
"has_genre",
"DRAMA"
],
[
"POETIC JUSTICE",
"release_year",
"1993"
],
[
"PUBLIC ACCESS",
"has_genre",
"DRAMA"
],
[
"PUBLIC ACCESS",
"release_year",
"1993"
],
[
"ROMEO AND JULIET",
"has_genre",
"DRAMA"
],
[
"ROMEO AND JULIET",
"has_imdb_votes",
"FAMOUS"
],
[
"SAVANNAH",
"has_genre",
"DRAMA"
],
[
"SAVANNAH",
"has_genre",
"FAMILY"
],
[
"SCHINDLER'S LIST",
"has_genre",
"DRAMA"
],
[
"SCHINDLER'S LIST",
"has_tags",
"DRAMA"
],
[
"SCHINDLER'S LIST",
"release_year",
"1993"
],
[
"SEARCHING FOR BOBBY FISCHER",
"has_genre",
"DRAMA"
],
[
"SEARCHING FOR BOBBY FISCHER",
"release_year",
"1993"
],
[
"SHILOH",
"has_genre",
"DRAMA"
],
[
"SHILOH",
"has_genre",
"FAMILY"
],
[
"SHORT CUTS",
"has_genre",
"DRAMA"
],
[
"SHORT CUTS",
"release_year",
"1993"
],
[
"SIX DEGREES OF SEPARATION",
"has_genre",
"DRAMA"
],
[
"SIX DEGREES OF SEPARATION",
"release_year",
"1993"
],
[
"SOMEWHERE",
"has_genre",
"DRAMA"
],
[
"SOMEWHERE",
"has_imdb_votes",
"FAMOUS"
],
[
"SOMMERSBY",
"has_genre",
"DRAMA"
],
[
"SOMMERSBY",
"release_year",
"1993"
],
[
"STALINGRAD",
"has_genre",
"DRAMA"
],
[
"STALINGRAD",
"release_year",
"1993"
],
[
"STRAPPED",
"has_genre",
"DRAMA"
],
[
"STRAPPED",
"release_year",
"1993"
],
[
"SULLIVAN'S TRAVELS",
"has_genre",
"DRAMA"
],
[
"SULLIVAN'S TRAVELS",
"has_imdb_votes",
"FAMOUS"
],
[
"SUMMER HOURS",
"has_genre",
"DRAMA"
],
[
"SUMMER HOURS",
"has_genre",
"FAMILY"
],
[
"SWING KIDS",
"has_genre",
"DRAMA"
],
[
"SWING KIDS",
"release_year",
"1993"
],
[
"THE AGE OF INNOCENCE",
"has_genre",
"DRAMA"
],
[
"THE AGE OF INNOCENCE",
"release_year",
"1993"
],
[
"THE BROTHERS MCMULLEN",
"has_genre",
"DRAMA"
],
[
"THE BROTHERS MCMULLEN",
"has_tags",
"FAMILY"
],
[
"THE CEMENT GARDEN",
"has_genre",
"DRAMA"
],
[
"THE CEMENT GARDEN",
"release_year",
"1993"
],
[
"THE COLOR PURPLE",
"has_genre",
"DRAMA"
],
[
"THE COLOR PURPLE",
"has_imdb_votes",
"FAMOUS"
],
[
"THE DARK CRYSTAL",
"has_genre",
"FAMILY"
],
[
"THE DARK CRYSTAL",
"has_imdb_votes",
"FAMOUS"
],
[
"THE DEPARTED",
"has_genre",
"DRAMA"
],
[
"THE DEPARTED",
"has_imdb_votes",
"FAMOUS"
],
[
"THE DIARY OF ANNE FRANK",
"has_genre",
"DRAMA"
],
[
"THE DIARY OF ANNE FRANK",
"has_genre",
"FAMILY"
],
[
"THE DILEMMA",
"has_genre",
"DRAMA"
],
[
"THE DILEMMA",
"has_imdb_votes",
"FAMOUS"
],
[
"THE FAMILY STONE",
"has_genre",
"DRAMA"
],
[
"THE FAMILY STONE",
"has_tags",
"DRAMA"
],
[
"THE FAMILY STONE",
"has_tags",
"FAMILY"
],
[
"THE FUGITIVE",
"has_genre",
"DRAMA"
],
[
"THE FUGITIVE",
"release_year",
"1993"
],
[
"THE HOUSE OF THE SPIRITS",
"has_genre",
"DRAMA"
],
[
"THE HOUSE OF THE SPIRITS",
"release_year",
"1993"
],
[
"THE HUMAN COMEDY",
"has_genre",
"DRAMA"
],
[
"THE HUMAN COMEDY",
"has_genre",
"FAMILY"
],
[
"THE JUNGLE BOOK",
"has_genre",
"FAMILY"
],
[
"THE JUNGLE BOOK",
"has_imdb_votes",
"FAMOUS"
],
[
"THE LITTLEST REBEL",
"has_genre",
"DRAMA"
],
[
"THE LITTLEST REBEL",
"has_genre",
"FAMILY"
],
[
"THE MAN WITHOUT A FACE",
"has_genre",
"DRAMA"
],
[
"THE MAN WITHOUT A FACE",
"has_tags",
"DRAMA"
],
[
"THE MAN WITHOUT A FACE",
"release_year",
"1993"
],
[
"THE MUSIC OF CHANCE",
"has_genre",
"DRAMA"
],
[
"THE MUSIC OF CHANCE",
"release_year",
"1993"
],
[
"THE PIANO",
"has_genre",
"DRAMA"
],
[
"THE PIANO",
"release_year",
"1993"
],
[
"THE RED SQUIRREL",
"has_genre",
"DRAMA"
],
[
"THE RED SQUIRREL",
"release_year",
"1993"
],
[
"THE ROOKIE",
"has_genre",
"DRAMA"
],
[
"THE ROOKIE",
"has_imdb_votes",
"FAMOUS"
],
[
"THE SECRET GARDEN",
"has_genre",
"DRAMA"
],
[
"THE SECRET GARDEN",
"release_year",
"1993"
],
[
"THE SILVER BRUMBY",
"has_genre",
"DRAMA"
],
[
"THE SILVER BRUMBY",
"has_genre",
"FAMILY"
],
[
"THE SILVER BRUMBY",
"release_year",
"1993"
],
[
"THE SLINGSHOT",
"has_genre",
"DRAMA"
],
[
"THE SLINGSHOT",
"release_year",
"1993"
],
[
"THE SNAPPER",
"has_tags",
"FAMILY"
],
[
"THE SNAPPER",
"release_year",
"1993"
],
[
"THE STORY OF ESTHER COSTELLO",
"has_genre",
"DRAMA"
],
[
"THE STORY OF ESTHER COSTELLO",
"written_by",
"NICHOLAS MONSARRAT"
],
[
"THE STORY OF THE WEEPING CAMEL",
"has_genre",
"DRAMA"
],
[
"THE STORY OF THE WEEPING CAMEL",
"has_genre",
"FAMILY"
],
[
"THE STORY OF THE WEEPING CAMEL",
"has_tags",
"FAMILY"
],
[
"THE THING CALLED LOVE",
"has_genre",
"DRAMA"
],
[
"THE THING CALLED LOVE",
"release_year",
"1993"
],
[
"THE THREE MUSKETEERS",
"has_genre",
"DRAMA"
],
[
"THE THREE MUSKETEERS",
"release_year",
"1993"
],
[
"THE WINSLOW BOY",
"has_genre",
"DRAMA"
],
[
"THE WINSLOW BOY",
"has_tags",
"FAMILY"
],
[
"THE WRONG MAN",
"has_genre",
"DRAMA"
],
[
"THE WRONG MAN",
"release_year",
"1993"
],
[
"THE YEAR OF LIVING DANGEROUSLY",
"has_genre",
"DRAMA"
],
[
"THE YEAR OF LIVING DANGEROUSLY",
"has_imdb_votes",
"FAMOUS"
],
[
"THE YEARLING",
"has_genre",
"DRAMA"
],
[
"THE YEARLING",
"has_genre",
"FAMILY"
],
[
"THE YOUNG AMERICANS",
"has_genre",
"DRAMA"
],
[
"THE YOUNG AMERICANS",
"release_year",
"1993"
],
[
"UNTAMED HEART",
"has_genre",
"DRAMA"
],
[
"UNTAMED HEART",
"release_year",
"1993"
],
[
"WE BOUGHT A ZOO",
"has_genre",
"DRAMA"
],
[
"WE BOUGHT A ZOO",
"has_genre",
"FAMILY"
],
[
"WE BOUGHT A ZOO",
"has_tags",
"FAMILY"
],
[
"WHAT'S EATING GILBERT GRAPE",
"has_genre",
"DRAMA"
],
[
"WHAT'S EATING GILBERT GRAPE",
"release_year",
"1993"
],
[
"WHAT'S LOVE GOT TO DO WITH IT",
"has_genre",
"DRAMA"
],
[
"WHAT'S LOVE GOT TO DO WITH IT",
"release_year",
"1993"
],
[
"WIDE AWAKE",
"has_genre",
"DRAMA"
],
[
"WIDE AWAKE",
"has_genre",
"FAMILY"
],
[
"WIDE-EYED AND LEGLESS",
"has_genre",
"DRAMA"
],
[
"WIDE-EYED AND LEGLESS",
"release_year",
"1993"
],
[
"WINDOW TO PARIS",
"has_genre",
"DRAMA"
],
[
"WINDOW TO PARIS",
"release_year",
"1993"
],
[
"WRESTLING ERNEST HEMINGWAY",
"has_genre",
"DRAMA"
],
[
"WRESTLING ERNEST HEMINGWAY",
"release_year",
"1993"
],
[
"YOU CAN COUNT ON ME",
"has_genre",
"DRAMA"
],
[
"YOU CAN COUNT ON ME",
"has_tags",
"FAMILY"
]
]
}
|
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
13634, ARTHUR PENN
9243, CHARLES GRODIN
9387, CLIFFORD
13176, DEAD OF WINTER
6012, FRENCH
7569, IN THE BEGINNING
24208, INSIDE
39987, IT RUNS IN THE FAMILY
21474, MARLON BRANDO
16619, MARY STEENBURGEN
13876, PONTIAC MOON
13685, THE CHASE
26879, THE MISSOURI BREAKS
4632, XAVIER GIANNOLI
src, edge_attr, dst
9387, release_year, 26257
9387, starred_actors, 9243
9387, starred_actors, 16619
13176, directed_by, 13634
13176, starred_actors, 16619
7569, directed_by, 4632
7569, in_language, 6012
7569, written_by, 4632
24208, directed_by, 13634
24208, has_tags, 6012
24208, in_language, 6012
39987, release_year, 26257
39987, starred_actors, 9243
39987, starred_actors, 16619
13876, release_year, 26257
13876, starred_actors, 16619
13685, directed_by, 13634
13685, has_tags, 13634
13685, has_tags, 21474
13685, release_year, 26257
13685, starred_actors, 21474
26879, directed_by, 13634
26879, has_tags, 21474
26879, starred_actors, 21474
Question: In what context are ARTHUR PENN, CLIFFORD, and XAVIER GIANNOLI connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"ARTHUR PENN",
"CLIFFORD",
"XAVIER GIANNOLI"
],
"valid_edges": [
[
"CLIFFORD",
"release_year",
"1994"
],
[
"CLIFFORD",
"starred_actors",
"CHARLES GRODIN"
],
[
"CLIFFORD",
"starred_actors",
"MARY STEENBURGEN"
],
[
"DEAD OF WINTER",
"directed_by",
"ARTHUR PENN"
],
[
"DEAD OF WINTER",
"starred_actors",
"MARY STEENBURGEN"
],
[
"IN THE BEGINNING",
"directed_by",
"XAVIER GIANNOLI"
],
[
"IN THE BEGINNING",
"in_language",
"FRENCH"
],
[
"IN THE BEGINNING",
"written_by",
"XAVIER GIANNOLI"
],
[
"INSIDE",
"directed_by",
"ARTHUR PENN"
],
[
"INSIDE",
"has_tags",
"FRENCH"
],
[
"INSIDE",
"in_language",
"FRENCH"
],
[
"IT RUNS IN THE FAMILY",
"release_year",
"1994"
],
[
"IT RUNS IN THE FAMILY",
"starred_actors",
"CHARLES GRODIN"
],
[
"IT RUNS IN THE FAMILY",
"starred_actors",
"MARY STEENBURGEN"
],
[
"PONTIAC MOON",
"release_year",
"1994"
],
[
"PONTIAC MOON",
"starred_actors",
"MARY STEENBURGEN"
],
[
"THE CHASE",
"directed_by",
"ARTHUR PENN"
],
[
"THE CHASE",
"has_tags",
"ARTHUR PENN"
],
[
"THE CHASE",
"has_tags",
"MARLON BRANDO"
],
[
"THE CHASE",
"release_year",
"1994"
],
[
"THE CHASE",
"starred_actors",
"MARLON BRANDO"
],
[
"THE MISSOURI BREAKS",
"directed_by",
"ARTHUR PENN"
],
[
"THE MISSOURI BREAKS",
"has_tags",
"MARLON BRANDO"
],
[
"THE MISSOURI BREAKS",
"starred_actors",
"MARLON BRANDO"
]
]
}
|
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
4763, ADVENTURE
4152, COMIN' AT YA!
14616, OUTLAND
36591, SEAN CONNERY
4635, SERENITY
12165, SHALAKO
28395, SPACE
32435, SPACE WESTERN
18657, SPIES LIKE US
37179, STEVE FORREST
17426, THE LAND UNKNOWN
15027, THE LEGEND OF THE LONE RANGER
22340, THE SECOND TIME AROUND
36026, WESTERN
14905, WILLIAM REYNOLDS
src, edge_attr, dst
4152, has_genre, 36026
4152, release_year, 25221
14616, has_tags, 36591
14616, has_tags, 28395
14616, has_tags, 32435
14616, has_tags, 36026
14616, release_year, 25221
14616, starred_actors, 36591
4635, has_tags, 28395
4635, has_tags, 32435
4635, has_tags, 36026
12165, has_genre, 36026
12165, starred_actors, 36591
18657, has_genre, 4763
18657, starred_actors, 37179
17426, has_genre, 4763
17426, starred_actors, 14905
15027, has_genre, 36026
15027, release_year, 25221
22340, has_genre, 36026
22340, starred_actors, 37179
Question: How are OUTLAND, STEVE FORREST, and WILLIAM REYNOLDS related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"OUTLAND",
"STEVE FORREST",
"WILLIAM REYNOLDS"
],
"valid_edges": [
[
"COMIN' AT YA!",
"has_genre",
"WESTERN"
],
[
"COMIN' AT YA!",
"release_year",
"1981"
],
[
"OUTLAND",
"has_tags",
"SEAN CONNERY"
],
[
"OUTLAND",
"has_tags",
"SPACE"
],
[
"OUTLAND",
"has_tags",
"SPACE WESTERN"
],
[
"OUTLAND",
"has_tags",
"WESTERN"
],
[
"OUTLAND",
"release_year",
"1981"
],
[
"OUTLAND",
"starred_actors",
"SEAN CONNERY"
],
[
"SERENITY",
"has_tags",
"SPACE"
],
[
"SERENITY",
"has_tags",
"SPACE WESTERN"
],
[
"SERENITY",
"has_tags",
"WESTERN"
],
[
"SHALAKO",
"has_genre",
"WESTERN"
],
[
"SHALAKO",
"starred_actors",
"SEAN CONNERY"
],
[
"SPIES LIKE US",
"has_genre",
"ADVENTURE"
],
[
"SPIES LIKE US",
"starred_actors",
"STEVE FORREST"
],
[
"THE LAND UNKNOWN",
"has_genre",
"ADVENTURE"
],
[
"THE LAND UNKNOWN",
"starred_actors",
"WILLIAM REYNOLDS"
],
[
"THE LEGEND OF THE LONE RANGER",
"has_genre",
"WESTERN"
],
[
"THE LEGEND OF THE LONE RANGER",
"release_year",
"1981"
],
[
"THE SECOND TIME AROUND",
"has_genre",
"WESTERN"
],
[
"THE SECOND TIME AROUND",
"starred_actors",
"STEVE FORREST"
]
]
}
|
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
37493, 102 DALMATIANS
23986, 18 AGAIN!
17480, 1988
24818, 1992
13578, 22 JUMP STREET
9005, 3 NINJAS
9351, A FISH CALLED WANDA
31650, A HAUNTED HOUSE 2
31344, A LEAGUE OF THEIR OWN
12929, A VERY BRADY SEQUEL
22412, ALLAN QUATERMAIN AND THE LOST CITY OF GOLD
34371, ALOHA SUMMER
34899, AMERICAN PIE 2
368, AMERICAN WEDDING
27571, AN AMERICAN WEREWOLF IN PARIS
26858, ARMY OF DARKNESS
31229, BANDSLAM
20940, BEACHES
14271, BEETHOVEN
39695, BEETLEJUICE
24579, BEVERLY HILLS COP II
15905, BIG
35901, BIG BUSINESS
9127, BIG GIRLS DON'T CRY... THEY GET EVEN
11779, BIG TOP PEE-WEE
18599, BILOXI BLUES
32193, BLAME IT ON THE BELLBOY
16023, BLUES BROTHERS 2000
19829, BOOMERANG
9190, BRAIN DAMAGE
8606, BRAIN DONORS
23128, BRIDGET JONES'S DIARY
23319, BUFFY THE VAMPIRE SLAYER
16714, BULL DURHAM
38286, BUSTER
33773, BÉBÉ'S KIDS
31116, CADDYSHACK II
24715, CAMP
10877, CAPTAIN RON
39255, CARS 2
27136, CASUAL SEX?
15721, CIAO, PROFESSORE!
12356, CLASS ACT
21625, CLERKS II
29046, CLOUDY WITH A CHANCE OF MEATBALLS 2
30463, COMEDY
9144, COMING TO AMERICA
26689, COMPAGNI DI SCUOLA
11807, CRITTERS 4
11441, CROSSING DELANCEY
27380, DEATH BECOMES HER
1463, DIRTY ROTTEN SCOUNDRELS
22341, DRAGONS FOREVER
18349, EARTH GIRLS ARE EASY
9457, ENCINO MAN
29258, ERNEST SAVES CHRISTMAS
31630, EVIL TOONS
21243, FATHER OF THE BRIDE PART II
4880, FEDS
5636, FOLKS!
32553, FROZEN ASSETS
17144, GRUMPIER OLD MEN
9798, HAIRSPRAY
10658, HEARTBREAK HOTEL
949, HEATHERS
3829, HERO
10555, HIGH HOPES
37827, HIGH SCHOOL
35566, HIGH SPIRITS
18546, HONEYMOON IN VEGAS
5068, HOT SHOTS! PART DEUX
30435, HOT TO TROT
25277, HUSBANDS AND WIVES
4419, IN THE SOUP
17556, JAWBREAKER
29896, JOHNNY BE GOOD
8923, JOHNNY ENGLISH REBORN
16510, JOYFUL NOISE
7729, JULIE BENZ
25894, KICK-ASS 2
11048, KILLER KLOWNS FROM OUTER SPACE
25510, KING OF BEGGARS
13704, KUFFS
18950, LADYBUGS
191, LEAVING NORMAL
25390, LIFE IS A LONG QUIET RIVER
24500, LITTLE SISTER
19450, LOOK WHO'S TALKING TOO
8268, MALEDETTO IL GIORNO CHE T'HO INCONTRATO
10560, MAN BITES DOG
24068, MAN TROUBLE
28521, MARRIED TO THE MOB
30022, MEAN GIRLS 2
4561, MEMOIRS OF AN INVISIBLE MAN
35049, MIDNIGHT RUN
34536, MISTRESS
39399, MO' MONEY
17135, MOM AND DAD SAVE THE WORLD
27936, MONSTERS UNIVERSITY
32033, MOVING
815, MR. BASEBALL
3855, MR. NORTH
21919, MY COUSIN VINNY
2581, MY NEW GUN
25950, MY STEPMOTHER IS AN ALIEN
5229, OLLIE HOPNOODLE'S HAVEN OF BLISS
14917, OUT ON A LIMB
16910, PARENTI SERPENTI
25678, PETER'S FRIENDS
8526, PUNCHLINE
9555, RED HEAT
28034, SCREAM 2
4187, SCROOGED
18762, SEQUEL
32127, SHE'S HAVING A BABY
701, SHORT CIRCUIT 2
36159, SHREK
16264, SHREK 2
3358, SINGLES
8652, SISTER ACT
29298, SON OF THE MASK
38010, STARS AND BARS
17370, STAY TUNED
2033, STOP! OR MY MOM WILL SHOOT
22993, STRAIGHT TALK
1432, STRICTLY BALLROOM
40018, SUNSET
40054, SWITCHING CHANNELS
20121, TAPEHEADS
2584, THE ADVENTURES OF BARON MUNCHAUSEN
1876, THE APPOINTMENTS OF DENNIS JENNINGS
36928, THE BIKINI CARWASH COMPANY
12710, THE COUCH TRIP
13869, THE DISTINGUISHED GENTLEMAN
7087, THE GREAT OUTDOORS
21831, THE GUN IN BETTY LOU'S HANDBAG
18150, THE JEWEL OF THE NILE
24724, THE MIGHTY DUCKS
26128, THE MUPPET CHRISTMAS CAROL
24035, THE NORTHERNERS
29027, THE TELEPHONE
12922, THE WRONG GUYS
21375, THINGS CHANGE
939, THIS IS 40
13520, TODD GRAFF
11574, TORCH SONG TRILOGY
14499, TOY STORY 2
2281, TOYS
7279, TWIN DRAGONS
31301, TWINS
10376, USED PEOPLE
38723, VIBES
21967, VICE VERSA
10177, WAXWORK
38839, WAYNE'S WORLD
20751, WHITE MEN CAN'T JUMP
3912, WHO FRAMED ROGER RABBIT
13847, WITHOUT A CLUE
29650, WOMEN ON THE VERGE OF A NERVOUS BREAKDOWN
33275, WORKING GIRL
32182, YOUNG EINSTEIN
src, edge_attr, dst
37493, has_genre, 30463
37493, has_tags, 18762
23986, has_genre, 30463
23986, release_year, 17480
13578, has_genre, 30463
13578, has_tags, 18762
9005, has_genre, 30463
9005, release_year, 24818
9351, has_genre, 30463
9351, release_year, 17480
31650, has_genre, 30463
31650, has_tags, 18762
31344, has_genre, 30463
31344, release_year, 24818
12929, has_genre, 30463
12929, has_tags, 18762
22412, has_genre, 30463
22412, has_tags, 18762
34371, has_genre, 30463
34371, release_year, 17480
34899, has_genre, 30463
34899, has_tags, 30463
34899, has_tags, 18762
368, has_genre, 30463
368, has_tags, 30463
368, has_tags, 18762
27571, has_genre, 30463
27571, has_tags, 18762
26858, has_genre, 30463
26858, has_tags, 30463
26858, release_year, 24818
31229, directed_by, 13520
31229, has_genre, 30463
31229, written_by, 13520
20940, has_genre, 30463
20940, release_year, 17480
14271, has_genre, 30463
14271, has_tags, 30463
14271, release_year, 24818
39695, has_genre, 30463
39695, has_tags, 30463
39695, release_year, 17480
24579, has_genre, 30463
24579, has_tags, 18762
15905, has_genre, 30463
15905, has_tags, 30463
15905, release_year, 17480
35901, has_genre, 30463
35901, release_year, 17480
9127, has_genre, 30463
9127, release_year, 24818
11779, has_genre, 30463
11779, release_year, 17480
18599, has_genre, 30463
18599, release_year, 17480
32193, has_genre, 30463
32193, release_year, 24818
16023, has_genre, 30463
16023, has_tags, 18762
19829, has_genre, 30463
19829, release_year, 24818
9190, has_genre, 30463
9190, release_year, 17480
8606, has_genre, 30463
8606, release_year, 24818
23128, has_genre, 30463
23128, has_tags, 30463
23128, has_tags, 18762
23319, has_genre, 30463
23319, has_tags, 30463
23319, release_year, 24818
16714, has_genre, 30463
16714, release_year, 17480
38286, has_genre, 30463
38286, release_year, 17480
33773, has_genre, 30463
33773, release_year, 24818
31116, has_genre, 30463
31116, release_year, 17480
24715, directed_by, 13520
24715, has_genre, 30463
24715, written_by, 13520
10877, has_genre, 30463
10877, has_tags, 30463
10877, release_year, 24818
39255, has_genre, 30463
39255, has_tags, 18762
27136, has_genre, 30463
27136, release_year, 17480
15721, has_genre, 30463
15721, release_year, 24818
12356, has_genre, 30463
12356, release_year, 24818
21625, has_genre, 30463
21625, has_tags, 30463
21625, has_tags, 18762
29046, has_genre, 30463
29046, has_tags, 18762
9144, has_genre, 30463
9144, has_tags, 30463
9144, release_year, 17480
26689, has_genre, 30463
26689, release_year, 17480
11807, has_genre, 30463
11807, release_year, 24818
11441, has_genre, 30463
11441, release_year, 17480
27380, has_genre, 30463
27380, release_year, 24818
1463, has_genre, 30463
1463, release_year, 17480
22341, has_genre, 30463
22341, release_year, 17480
18349, has_genre, 30463
18349, release_year, 17480
9457, has_genre, 30463
9457, release_year, 24818
29258, has_genre, 30463
29258, release_year, 17480
31630, has_genre, 30463
31630, release_year, 24818
21243, has_genre, 30463
21243, has_tags, 30463
21243, has_tags, 18762
4880, has_genre, 30463
4880, release_year, 17480
5636, has_genre, 30463
5636, release_year, 24818
32553, has_genre, 30463
32553, release_year, 24818
17144, has_genre, 30463
17144, has_tags, 30463
17144, has_tags, 18762
9798, has_genre, 30463
9798, has_tags, 30463
9798, release_year, 17480
10658, has_genre, 30463
10658, release_year, 17480
949, has_genre, 30463
949, release_year, 17480
3829, has_genre, 30463
3829, release_year, 24818
10555, has_genre, 30463
10555, release_year, 17480
37827, has_genre, 30463
35566, has_genre, 30463
35566, release_year, 17480
18546, has_genre, 30463
18546, release_year, 24818
5068, has_genre, 30463
5068, has_tags, 30463
5068, has_tags, 18762
30435, has_genre, 30463
30435, release_year, 17480
25277, has_genre, 30463
25277, release_year, 24818
4419, has_genre, 30463
4419, release_year, 24818
17556, has_genre, 30463
17556, has_tags, 37827
17556, has_tags, 7729
17556, starred_actors, 7729
29896, has_genre, 30463
29896, release_year, 17480
8923, has_genre, 30463
8923, has_tags, 30463
8923, has_tags, 18762
16510, directed_by, 13520
16510, has_genre, 30463
16510, written_by, 13520
25894, has_genre, 30463
25894, has_tags, 18762
11048, has_genre, 30463
11048, release_year, 17480
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
25390, has_genre, 30463
25390, release_year, 17480
24500, has_genre, 30463
24500, release_year, 24818
19450, has_genre, 30463
19450, has_tags, 18762
8268, has_genre, 30463
8268, release_year, 24818
10560, has_genre, 30463
10560, release_year, 24818
24068, has_genre, 30463
24068, release_year, 24818
28521, has_genre, 30463
28521, release_year, 17480
30022, has_genre, 30463
30022, has_tags, 18762
4561, has_genre, 30463
4561, release_year, 24818
35049, has_genre, 30463
35049, has_tags, 30463
35049, release_year, 17480
34536, has_genre, 30463
34536, release_year, 24818
39399, has_genre, 30463
39399, release_year, 24818
17135, has_genre, 30463
17135, release_year, 24818
27936, has_genre, 30463
27936, has_tags, 30463
27936, has_tags, 18762
32033, has_genre, 30463
32033, release_year, 17480
815, has_genre, 30463
815, release_year, 24818
3855, has_genre, 30463
3855, release_year, 17480
21919, has_genre, 30463
21919, has_tags, 30463
21919, release_year, 24818
2581, has_genre, 30463
2581, release_year, 24818
25950, has_genre, 30463
25950, release_year, 17480
5229, has_genre, 30463
5229, release_year, 17480
14917, has_genre, 30463
14917, release_year, 24818
16910, has_genre, 30463
16910, release_year, 24818
25678, has_genre, 30463
25678, release_year, 24818
8526, has_genre, 30463
8526, release_year, 17480
9555, has_genre, 30463
9555, release_year, 17480
28034, has_tags, 30463
28034, has_tags, 18762
4187, has_genre, 30463
4187, has_tags, 30463
4187, release_year, 17480
32127, has_genre, 30463
32127, release_year, 17480
701, has_tags, 18762
701, release_year, 17480
36159, has_genre, 30463
36159, has_tags, 30463
36159, has_tags, 18762
16264, has_genre, 30463
16264, has_tags, 30463
16264, has_tags, 18762
3358, has_genre, 30463
3358, release_year, 24818
8652, has_genre, 30463
8652, release_year, 24818
29298, has_genre, 30463
29298, has_tags, 18762
38010, has_genre, 30463
38010, release_year, 17480
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
40018, has_genre, 30463
40018, release_year, 17480
40054, has_genre, 30463
40054, release_year, 17480
20121, has_genre, 30463
20121, release_year, 17480
2584, has_genre, 30463
2584, release_year, 17480
1876, has_genre, 30463
1876, release_year, 17480
36928, has_genre, 30463
36928, release_year, 24818
12710, has_genre, 30463
12710, release_year, 17480
13869, has_genre, 30463
13869, release_year, 24818
7087, has_genre, 30463
7087, release_year, 17480
21831, has_genre, 30463
21831, release_year, 24818
18150, has_genre, 30463
18150, has_tags, 30463
18150, has_tags, 18762
24724, has_genre, 30463
24724, release_year, 24818
26128, has_genre, 30463
26128, release_year, 24818
24035, has_genre, 30463
24035, release_year, 24818
29027, has_genre, 30463
29027, release_year, 17480
12922, has_genre, 30463
12922, release_year, 17480
21375, has_genre, 30463
21375, release_year, 17480
939, has_genre, 30463
939, has_tags, 18762
11574, has_genre, 30463
11574, release_year, 17480
14499, has_genre, 30463
14499, has_tags, 18762
2281, has_genre, 30463
2281, release_year, 24818
7279, has_genre, 30463
7279, release_year, 24818
31301, has_genre, 30463
31301, has_tags, 30463
31301, release_year, 17480
10376, has_genre, 30463
10376, release_year, 24818
10376, written_by, 13520
38723, has_genre, 30463
38723, release_year, 17480
21967, has_genre, 30463
21967, release_year, 17480
10177, has_genre, 30463
10177, release_year, 17480
38839, has_genre, 30463
38839, has_tags, 30463
38839, release_year, 24818
20751, has_genre, 30463
20751, has_tags, 30463
20751, release_year, 24818
3912, has_genre, 30463
3912, has_tags, 30463
3912, release_year, 17480
13847, has_genre, 30463
13847, release_year, 17480
29650, has_genre, 30463
29650, release_year, 17480
33275, has_genre, 30463
33275, release_year, 17480
32182, has_genre, 30463
32182, release_year, 17480
Question: For what reason are JULIE BENZ, SHORT CIRCUIT 2, and USED PEOPLE associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"JULIE BENZ",
"SHORT CIRCUIT 2",
"USED PEOPLE"
],
"valid_edges": [
[
"102 DALMATIANS",
"has_genre",
"COMEDY"
],
[
"102 DALMATIANS",
"has_tags",
"SEQUEL"
],
[
"18 AGAIN!",
"has_genre",
"COMEDY"
],
[
"18 AGAIN!",
"release_year",
"1988"
],
[
"22 JUMP STREET",
"has_genre",
"COMEDY"
],
[
"22 JUMP STREET",
"has_tags",
"SEQUEL"
],
[
"3 NINJAS",
"has_genre",
"COMEDY"
],
[
"3 NINJAS",
"release_year",
"1992"
],
[
"A FISH CALLED WANDA",
"has_genre",
"COMEDY"
],
[
"A FISH CALLED WANDA",
"release_year",
"1988"
],
[
"A HAUNTED HOUSE 2",
"has_genre",
"COMEDY"
],
[
"A HAUNTED HOUSE 2",
"has_tags",
"SEQUEL"
],
[
"A LEAGUE OF THEIR OWN",
"has_genre",
"COMEDY"
],
[
"A LEAGUE OF THEIR OWN",
"release_year",
"1992"
],
[
"A VERY BRADY SEQUEL",
"has_genre",
"COMEDY"
],
[
"A VERY BRADY SEQUEL",
"has_tags",
"SEQUEL"
],
[
"ALLAN QUATERMAIN AND THE LOST CITY OF GOLD",
"has_genre",
"COMEDY"
],
[
"ALLAN QUATERMAIN AND THE LOST CITY OF GOLD",
"has_tags",
"SEQUEL"
],
[
"ALOHA SUMMER",
"has_genre",
"COMEDY"
],
[
"ALOHA SUMMER",
"release_year",
"1988"
],
[
"AMERICAN PIE 2",
"has_genre",
"COMEDY"
],
[
"AMERICAN PIE 2",
"has_tags",
"COMEDY"
],
[
"AMERICAN PIE 2",
"has_tags",
"SEQUEL"
],
[
"AMERICAN WEDDING",
"has_genre",
"COMEDY"
],
[
"AMERICAN WEDDING",
"has_tags",
"COMEDY"
],
[
"AMERICAN WEDDING",
"has_tags",
"SEQUEL"
],
[
"AN AMERICAN WEREWOLF IN PARIS",
"has_genre",
"COMEDY"
],
[
"AN AMERICAN WEREWOLF IN PARIS",
"has_tags",
"SEQUEL"
],
[
"ARMY OF DARKNESS",
"has_genre",
"COMEDY"
],
[
"ARMY OF DARKNESS",
"has_tags",
"COMEDY"
],
[
"ARMY OF DARKNESS",
"release_year",
"1992"
],
[
"BANDSLAM",
"directed_by",
"TODD GRAFF"
],
[
"BANDSLAM",
"has_genre",
"COMEDY"
],
[
"BANDSLAM",
"written_by",
"TODD GRAFF"
],
[
"BEACHES",
"has_genre",
"COMEDY"
],
[
"BEACHES",
"release_year",
"1988"
],
[
"BEETHOVEN",
"has_genre",
"COMEDY"
],
[
"BEETHOVEN",
"has_tags",
"COMEDY"
],
[
"BEETHOVEN",
"release_year",
"1992"
],
[
"BEETLEJUICE",
"has_genre",
"COMEDY"
],
[
"BEETLEJUICE",
"has_tags",
"COMEDY"
],
[
"BEETLEJUICE",
"release_year",
"1988"
],
[
"BEVERLY HILLS COP II",
"has_genre",
"COMEDY"
],
[
"BEVERLY HILLS COP II",
"has_tags",
"SEQUEL"
],
[
"BIG",
"has_genre",
"COMEDY"
],
[
"BIG",
"has_tags",
"COMEDY"
],
[
"BIG",
"release_year",
"1988"
],
[
"BIG BUSINESS",
"has_genre",
"COMEDY"
],
[
"BIG BUSINESS",
"release_year",
"1988"
],
[
"BIG GIRLS DON'T CRY... THEY GET EVEN",
"has_genre",
"COMEDY"
],
[
"BIG GIRLS DON'T CRY... THEY GET EVEN",
"release_year",
"1992"
],
[
"BIG TOP PEE-WEE",
"has_genre",
"COMEDY"
],
[
"BIG TOP PEE-WEE",
"release_year",
"1988"
],
[
"BILOXI BLUES",
"has_genre",
"COMEDY"
],
[
"BILOXI BLUES",
"release_year",
"1988"
],
[
"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",
"SEQUEL"
],
[
"BOOMERANG",
"has_genre",
"COMEDY"
],
[
"BOOMERANG",
"release_year",
"1992"
],
[
"BRAIN DAMAGE",
"has_genre",
"COMEDY"
],
[
"BRAIN DAMAGE",
"release_year",
"1988"
],
[
"BRAIN DONORS",
"has_genre",
"COMEDY"
],
[
"BRAIN DONORS",
"release_year",
"1992"
],
[
"BRIDGET JONES'S DIARY",
"has_genre",
"COMEDY"
],
[
"BRIDGET JONES'S DIARY",
"has_tags",
"COMEDY"
],
[
"BRIDGET JONES'S DIARY",
"has_tags",
"SEQUEL"
],
[
"BUFFY THE VAMPIRE SLAYER",
"has_genre",
"COMEDY"
],
[
"BUFFY THE VAMPIRE SLAYER",
"has_tags",
"COMEDY"
],
[
"BUFFY THE VAMPIRE SLAYER",
"release_year",
"1992"
],
[
"BULL DURHAM",
"has_genre",
"COMEDY"
],
[
"BULL DURHAM",
"release_year",
"1988"
],
[
"BUSTER",
"has_genre",
"COMEDY"
],
[
"BUSTER",
"release_year",
"1988"
],
[
"BÉBÉ'S KIDS",
"has_genre",
"COMEDY"
],
[
"BÉBÉ'S KIDS",
"release_year",
"1992"
],
[
"CADDYSHACK II",
"has_genre",
"COMEDY"
],
[
"CADDYSHACK II",
"release_year",
"1988"
],
[
"CAMP",
"directed_by",
"TODD GRAFF"
],
[
"CAMP",
"has_genre",
"COMEDY"
],
[
"CAMP",
"written_by",
"TODD GRAFF"
],
[
"CAPTAIN RON",
"has_genre",
"COMEDY"
],
[
"CAPTAIN RON",
"has_tags",
"COMEDY"
],
[
"CAPTAIN RON",
"release_year",
"1992"
],
[
"CARS 2",
"has_genre",
"COMEDY"
],
[
"CARS 2",
"has_tags",
"SEQUEL"
],
[
"CASUAL SEX?",
"has_genre",
"COMEDY"
],
[
"CASUAL SEX?",
"release_year",
"1988"
],
[
"CIAO, PROFESSORE!",
"has_genre",
"COMEDY"
],
[
"CIAO, PROFESSORE!",
"release_year",
"1992"
],
[
"CLASS ACT",
"has_genre",
"COMEDY"
],
[
"CLASS ACT",
"release_year",
"1992"
],
[
"CLERKS II",
"has_genre",
"COMEDY"
],
[
"CLERKS II",
"has_tags",
"COMEDY"
],
[
"CLERKS II",
"has_tags",
"SEQUEL"
],
[
"CLOUDY WITH A CHANCE OF MEATBALLS 2",
"has_genre",
"COMEDY"
],
[
"CLOUDY WITH A CHANCE OF MEATBALLS 2",
"has_tags",
"SEQUEL"
],
[
"COMING TO AMERICA",
"has_genre",
"COMEDY"
],
[
"COMING TO AMERICA",
"has_tags",
"COMEDY"
],
[
"COMING TO AMERICA",
"release_year",
"1988"
],
[
"COMPAGNI DI SCUOLA",
"has_genre",
"COMEDY"
],
[
"COMPAGNI DI SCUOLA",
"release_year",
"1988"
],
[
"CRITTERS 4",
"has_genre",
"COMEDY"
],
[
"CRITTERS 4",
"release_year",
"1992"
],
[
"CROSSING DELANCEY",
"has_genre",
"COMEDY"
],
[
"CROSSING DELANCEY",
"release_year",
"1988"
],
[
"DEATH BECOMES HER",
"has_genre",
"COMEDY"
],
[
"DEATH BECOMES HER",
"release_year",
"1992"
],
[
"DIRTY ROTTEN SCOUNDRELS",
"has_genre",
"COMEDY"
],
[
"DIRTY ROTTEN SCOUNDRELS",
"release_year",
"1988"
],
[
"DRAGONS FOREVER",
"has_genre",
"COMEDY"
],
[
"DRAGONS FOREVER",
"release_year",
"1988"
],
[
"EARTH GIRLS ARE EASY",
"has_genre",
"COMEDY"
],
[
"EARTH GIRLS ARE EASY",
"release_year",
"1988"
],
[
"ENCINO MAN",
"has_genre",
"COMEDY"
],
[
"ENCINO MAN",
"release_year",
"1992"
],
[
"ERNEST SAVES CHRISTMAS",
"has_genre",
"COMEDY"
],
[
"ERNEST SAVES CHRISTMAS",
"release_year",
"1988"
],
[
"EVIL TOONS",
"has_genre",
"COMEDY"
],
[
"EVIL TOONS",
"release_year",
"1992"
],
[
"FATHER OF THE BRIDE PART II",
"has_genre",
"COMEDY"
],
[
"FATHER OF THE BRIDE PART II",
"has_tags",
"COMEDY"
],
[
"FATHER OF THE BRIDE PART II",
"has_tags",
"SEQUEL"
],
[
"FEDS",
"has_genre",
"COMEDY"
],
[
"FEDS",
"release_year",
"1988"
],
[
"FOLKS!",
"has_genre",
"COMEDY"
],
[
"FOLKS!",
"release_year",
"1992"
],
[
"FROZEN ASSETS",
"has_genre",
"COMEDY"
],
[
"FROZEN ASSETS",
"release_year",
"1992"
],
[
"GRUMPIER OLD MEN",
"has_genre",
"COMEDY"
],
[
"GRUMPIER OLD MEN",
"has_tags",
"COMEDY"
],
[
"GRUMPIER OLD MEN",
"has_tags",
"SEQUEL"
],
[
"HAIRSPRAY",
"has_genre",
"COMEDY"
],
[
"HAIRSPRAY",
"has_tags",
"COMEDY"
],
[
"HAIRSPRAY",
"release_year",
"1988"
],
[
"HEARTBREAK HOTEL",
"has_genre",
"COMEDY"
],
[
"HEARTBREAK HOTEL",
"release_year",
"1988"
],
[
"HEATHERS",
"has_genre",
"COMEDY"
],
[
"HEATHERS",
"release_year",
"1988"
],
[
"HERO",
"has_genre",
"COMEDY"
],
[
"HERO",
"release_year",
"1992"
],
[
"HIGH HOPES",
"has_genre",
"COMEDY"
],
[
"HIGH HOPES",
"release_year",
"1988"
],
[
"HIGH SCHOOL",
"has_genre",
"COMEDY"
],
[
"HIGH SPIRITS",
"has_genre",
"COMEDY"
],
[
"HIGH SPIRITS",
"release_year",
"1988"
],
[
"HONEYMOON IN VEGAS",
"has_genre",
"COMEDY"
],
[
"HONEYMOON IN VEGAS",
"release_year",
"1992"
],
[
"HOT SHOTS! PART DEUX",
"has_genre",
"COMEDY"
],
[
"HOT SHOTS! PART DEUX",
"has_tags",
"COMEDY"
],
[
"HOT SHOTS! PART DEUX",
"has_tags",
"SEQUEL"
],
[
"HOT TO TROT",
"has_genre",
"COMEDY"
],
[
"HOT TO TROT",
"release_year",
"1988"
],
[
"HUSBANDS AND WIVES",
"has_genre",
"COMEDY"
],
[
"HUSBANDS AND WIVES",
"release_year",
"1992"
],
[
"IN THE SOUP",
"has_genre",
"COMEDY"
],
[
"IN THE SOUP",
"release_year",
"1992"
],
[
"JAWBREAKER",
"has_genre",
"COMEDY"
],
[
"JAWBREAKER",
"has_tags",
"HIGH SCHOOL"
],
[
"JAWBREAKER",
"has_tags",
"JULIE BENZ"
],
[
"JAWBREAKER",
"starred_actors",
"JULIE BENZ"
],
[
"JOHNNY BE GOOD",
"has_genre",
"COMEDY"
],
[
"JOHNNY BE GOOD",
"release_year",
"1988"
],
[
"JOHNNY ENGLISH REBORN",
"has_genre",
"COMEDY"
],
[
"JOHNNY ENGLISH REBORN",
"has_tags",
"COMEDY"
],
[
"JOHNNY ENGLISH REBORN",
"has_tags",
"SEQUEL"
],
[
"JOYFUL NOISE",
"directed_by",
"TODD GRAFF"
],
[
"JOYFUL NOISE",
"has_genre",
"COMEDY"
],
[
"JOYFUL NOISE",
"written_by",
"TODD GRAFF"
],
[
"KICK-ASS 2",
"has_genre",
"COMEDY"
],
[
"KICK-ASS 2",
"has_tags",
"SEQUEL"
],
[
"KILLER KLOWNS FROM OUTER SPACE",
"has_genre",
"COMEDY"
],
[
"KILLER KLOWNS FROM OUTER SPACE",
"release_year",
"1988"
],
[
"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"
],
[
"LIFE IS A LONG QUIET RIVER",
"has_genre",
"COMEDY"
],
[
"LIFE IS A LONG QUIET RIVER",
"release_year",
"1988"
],
[
"LITTLE SISTER",
"has_genre",
"COMEDY"
],
[
"LITTLE SISTER",
"release_year",
"1992"
],
[
"LOOK WHO'S TALKING TOO",
"has_genre",
"COMEDY"
],
[
"LOOK WHO'S TALKING TOO",
"has_tags",
"SEQUEL"
],
[
"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"
],
[
"MARRIED TO THE MOB",
"has_genre",
"COMEDY"
],
[
"MARRIED TO THE MOB",
"release_year",
"1988"
],
[
"MEAN GIRLS 2",
"has_genre",
"COMEDY"
],
[
"MEAN GIRLS 2",
"has_tags",
"SEQUEL"
],
[
"MEMOIRS OF AN INVISIBLE MAN",
"has_genre",
"COMEDY"
],
[
"MEMOIRS OF AN INVISIBLE MAN",
"release_year",
"1992"
],
[
"MIDNIGHT RUN",
"has_genre",
"COMEDY"
],
[
"MIDNIGHT RUN",
"has_tags",
"COMEDY"
],
[
"MIDNIGHT RUN",
"release_year",
"1988"
],
[
"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 UNIVERSITY",
"has_genre",
"COMEDY"
],
[
"MONSTERS UNIVERSITY",
"has_tags",
"COMEDY"
],
[
"MONSTERS UNIVERSITY",
"has_tags",
"SEQUEL"
],
[
"MOVING",
"has_genre",
"COMEDY"
],
[
"MOVING",
"release_year",
"1988"
],
[
"MR. BASEBALL",
"has_genre",
"COMEDY"
],
[
"MR. BASEBALL",
"release_year",
"1992"
],
[
"MR. NORTH",
"has_genre",
"COMEDY"
],
[
"MR. NORTH",
"release_year",
"1988"
],
[
"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 STEPMOTHER IS AN ALIEN",
"has_genre",
"COMEDY"
],
[
"MY STEPMOTHER IS AN ALIEN",
"release_year",
"1988"
],
[
"OLLIE HOPNOODLE'S HAVEN OF BLISS",
"has_genre",
"COMEDY"
],
[
"OLLIE HOPNOODLE'S HAVEN OF BLISS",
"release_year",
"1988"
],
[
"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"
],
[
"PUNCHLINE",
"has_genre",
"COMEDY"
],
[
"PUNCHLINE",
"release_year",
"1988"
],
[
"RED HEAT",
"has_genre",
"COMEDY"
],
[
"RED HEAT",
"release_year",
"1988"
],
[
"SCREAM 2",
"has_tags",
"COMEDY"
],
[
"SCREAM 2",
"has_tags",
"SEQUEL"
],
[
"SCROOGED",
"has_genre",
"COMEDY"
],
[
"SCROOGED",
"has_tags",
"COMEDY"
],
[
"SCROOGED",
"release_year",
"1988"
],
[
"SHE'S HAVING A BABY",
"has_genre",
"COMEDY"
],
[
"SHE'S HAVING A BABY",
"release_year",
"1988"
],
[
"SHORT CIRCUIT 2",
"has_tags",
"SEQUEL"
],
[
"SHORT CIRCUIT 2",
"release_year",
"1988"
],
[
"SHREK",
"has_genre",
"COMEDY"
],
[
"SHREK",
"has_tags",
"COMEDY"
],
[
"SHREK",
"has_tags",
"SEQUEL"
],
[
"SHREK 2",
"has_genre",
"COMEDY"
],
[
"SHREK 2",
"has_tags",
"COMEDY"
],
[
"SHREK 2",
"has_tags",
"SEQUEL"
],
[
"SINGLES",
"has_genre",
"COMEDY"
],
[
"SINGLES",
"release_year",
"1992"
],
[
"SISTER ACT",
"has_genre",
"COMEDY"
],
[
"SISTER ACT",
"release_year",
"1992"
],
[
"SON OF THE MASK",
"has_genre",
"COMEDY"
],
[
"SON OF THE MASK",
"has_tags",
"SEQUEL"
],
[
"STARS AND BARS",
"has_genre",
"COMEDY"
],
[
"STARS AND BARS",
"release_year",
"1988"
],
[
"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"
],
[
"SUNSET",
"has_genre",
"COMEDY"
],
[
"SUNSET",
"release_year",
"1988"
],
[
"SWITCHING CHANNELS",
"has_genre",
"COMEDY"
],
[
"SWITCHING CHANNELS",
"release_year",
"1988"
],
[
"TAPEHEADS",
"has_genre",
"COMEDY"
],
[
"TAPEHEADS",
"release_year",
"1988"
],
[
"THE ADVENTURES OF BARON MUNCHAUSEN",
"has_genre",
"COMEDY"
],
[
"THE ADVENTURES OF BARON MUNCHAUSEN",
"release_year",
"1988"
],
[
"THE APPOINTMENTS OF DENNIS JENNINGS",
"has_genre",
"COMEDY"
],
[
"THE APPOINTMENTS OF DENNIS JENNINGS",
"release_year",
"1988"
],
[
"THE BIKINI CARWASH COMPANY",
"has_genre",
"COMEDY"
],
[
"THE BIKINI CARWASH COMPANY",
"release_year",
"1992"
],
[
"THE COUCH TRIP",
"has_genre",
"COMEDY"
],
[
"THE COUCH TRIP",
"release_year",
"1988"
],
[
"THE DISTINGUISHED GENTLEMAN",
"has_genre",
"COMEDY"
],
[
"THE DISTINGUISHED GENTLEMAN",
"release_year",
"1992"
],
[
"THE GREAT OUTDOORS",
"has_genre",
"COMEDY"
],
[
"THE GREAT OUTDOORS",
"release_year",
"1988"
],
[
"THE GUN IN BETTY LOU'S HANDBAG",
"has_genre",
"COMEDY"
],
[
"THE GUN IN BETTY LOU'S HANDBAG",
"release_year",
"1992"
],
[
"THE JEWEL OF THE NILE",
"has_genre",
"COMEDY"
],
[
"THE JEWEL OF THE NILE",
"has_tags",
"COMEDY"
],
[
"THE JEWEL OF THE NILE",
"has_tags",
"SEQUEL"
],
[
"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 NORTHERNERS",
"has_genre",
"COMEDY"
],
[
"THE NORTHERNERS",
"release_year",
"1992"
],
[
"THE TELEPHONE",
"has_genre",
"COMEDY"
],
[
"THE TELEPHONE",
"release_year",
"1988"
],
[
"THE WRONG GUYS",
"has_genre",
"COMEDY"
],
[
"THE WRONG GUYS",
"release_year",
"1988"
],
[
"THINGS CHANGE",
"has_genre",
"COMEDY"
],
[
"THINGS CHANGE",
"release_year",
"1988"
],
[
"THIS IS 40",
"has_genre",
"COMEDY"
],
[
"THIS IS 40",
"has_tags",
"SEQUEL"
],
[
"TORCH SONG TRILOGY",
"has_genre",
"COMEDY"
],
[
"TORCH SONG TRILOGY",
"release_year",
"1988"
],
[
"TOY STORY 2",
"has_genre",
"COMEDY"
],
[
"TOY STORY 2",
"has_tags",
"SEQUEL"
],
[
"TOYS",
"has_genre",
"COMEDY"
],
[
"TOYS",
"release_year",
"1992"
],
[
"TWIN DRAGONS",
"has_genre",
"COMEDY"
],
[
"TWIN DRAGONS",
"release_year",
"1992"
],
[
"TWINS",
"has_genre",
"COMEDY"
],
[
"TWINS",
"has_tags",
"COMEDY"
],
[
"TWINS",
"release_year",
"1988"
],
[
"USED PEOPLE",
"has_genre",
"COMEDY"
],
[
"USED PEOPLE",
"release_year",
"1992"
],
[
"USED PEOPLE",
"written_by",
"TODD GRAFF"
],
[
"VIBES",
"has_genre",
"COMEDY"
],
[
"VIBES",
"release_year",
"1988"
],
[
"VICE VERSA",
"has_genre",
"COMEDY"
],
[
"VICE VERSA",
"release_year",
"1988"
],
[
"WAXWORK",
"has_genre",
"COMEDY"
],
[
"WAXWORK",
"release_year",
"1988"
],
[
"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"
],
[
"WHO FRAMED ROGER RABBIT",
"has_genre",
"COMEDY"
],
[
"WHO FRAMED ROGER RABBIT",
"has_tags",
"COMEDY"
],
[
"WHO FRAMED ROGER RABBIT",
"release_year",
"1988"
],
[
"WITHOUT A CLUE",
"has_genre",
"COMEDY"
],
[
"WITHOUT A CLUE",
"release_year",
"1988"
],
[
"WOMEN ON THE VERGE OF A NERVOUS BREAKDOWN",
"has_genre",
"COMEDY"
],
[
"WOMEN ON THE VERGE OF A NERVOUS BREAKDOWN",
"release_year",
"1988"
],
[
"WORKING GIRL",
"has_genre",
"COMEDY"
],
[
"WORKING GIRL",
"release_year",
"1988"
],
[
"YOUNG EINSTEIN",
"has_genre",
"COMEDY"
],
[
"YOUNG EINSTEIN",
"release_year",
"1988"
]
]
}
|
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
10264, .45
39813, 1971
35845, 2006
27495, AFTER...
19293, ALL THE PRESIDENT'S MEN
30269, AMITYVILLE 3-D
694, ASSAULT ON PRECINCT 13
36430, BASIC INSTINCT 2
10045, BD-R
40074, BLACK BOOK
7635, BLACKMAIL
16664, BLOOD DIAMOND
34404, BREAKDOWN
21584, BUNNY LAKE IS MISSING
6283, CARGO
10377, CIVIC DUTY
38680, COMPULSION
31923, DARK RIDE
29300, DEAD RINGER
28094, DELIVERANCE
27143, DEMENTIA 13
8381, DETOUR
23396, DIAL M FOR MURDER
15961, DON
771, DRESSED TO KILL
33960, DUEL
8131, EMILY MORTIMER
1690, EYES OF LAURA MARS
14623, FADE TO BLACK
1831, FIREWALL
19500, FIRST SNOW
8294, FIVE FINGERS
15351, FOREIGN CORRESPONDENT
39565, FRIGHT
9003, FUNNY GAMES
19221, GASLIGHT
23299, GET CARTER
16365, GOOD NEIGHBORS
34771, GREEN FOR DANGER
39298, HARD LUCK
39972, HOLLOW MAN
7264, INSIDE MAN
10707, KATHLEEN QUINLAN
7415, KISS OF DEATH
21302, KLUTE
7743, LADY IN THE WATER
33950, LUCKY NUMBER SLEVIN
40127, MACABRE
22260, MEMORY
36083, MIRANDA
16462, MYSTERY OF THE WAX MUSEUM
25264, NOTES ON A SCANDAL
37989, OBSESSION
19017, PEEPING TOM
39493, PLAY MISTY FOR ME
6297, REBECCA
7368, RICHARD FLEISCHER
15605, RIGHT AT YOUR DOOR
30059, SEE NO EVIL
9936, SEVEN DAYS IN MAY
7060, SEVEN DAYS TO NOON
16921, SHADOW MAN
29005, SIN CITY
6119, SLEUTH
13, SNAKES ON A PLANE
24045, STRAIT-JACKET
40046, STRANGERS ON A TRAIN
16127, STRAW DOGS
35380, SUSPICION
37807, TELL NO ONE
35864, THE ABANDONED
32227, THE ANDROMEDA STRAIN
24057, THE BACKWOODS
1070, THE BUTTERFLY EFFECT 2
29799, THE CANYONS
12339, THE CHINA SYNDROME
1059, THE DA VINCI CODE
16732, THE END
24006, THE FIFTH CORD
35937, THE FIFTH ESTATE
22869, THE GHOST SHIP
11168, THE HUMAN FACTOR
4091, THE LADY VANISHES
30690, THE LADYKILLERS
20165, THE LAST WINTER
33948, THE LETTER
30903, THE MAN BETWEEN
29773, THE MANCHURIAN CANDIDATE
27599, THE NIGHT OF THE HUNTER
15196, THE NIGHT VISITOR
13933, THE PARALLAX VIEW
27098, THE PRESTIGE
18162, THE RAVEN
28919, THE RETURN
4300, THE SENTINEL
18785, THE SILENCE
23847, THE STEPFORD WIVES
25030, THE UNKNOWN WOMAN
17568, THE VANISHING
22751, THE WICKER MAN
34407, THE WRONG MAN
24811, THRILLER
8334, TRANSSIBERIAN
10133, UNKNOWN
35164, VANISHING ON 7TH STREET
499, WAIT UNTIL DARK
6190, WAKE IN FRIGHT
14868, WESTWORLD
28071, WHAT EVER HAPPENED TO BABY JANE?
31083, WRONG IS RIGHT
38760, Z
src, edge_attr, dst
10264, has_genre, 24811
10264, release_year, 35845
27495, has_genre, 24811
27495, release_year, 35845
19293, has_genre, 24811
19293, has_tags, 10045
19293, has_tags, 24811
30269, directed_by, 7368
30269, has_genre, 24811
694, has_genre, 24811
694, has_tags, 10045
36430, has_genre, 24811
36430, release_year, 35845
40074, has_genre, 24811
40074, release_year, 35845
7635, has_genre, 24811
7635, has_tags, 10045
16664, has_genre, 24811
16664, release_year, 35845
34404, has_tags, 24811
34404, starred_actors, 10707
21584, has_genre, 24811
21584, has_tags, 10045
6283, has_genre, 24811
6283, release_year, 35845
10377, has_genre, 24811
10377, release_year, 35845
38680, directed_by, 7368
38680, has_genre, 24811
38680, has_tags, 10045
38680, has_tags, 7368
31923, has_genre, 24811
31923, release_year, 35845
29300, has_genre, 24811
29300, has_tags, 10045
28094, has_genre, 24811
28094, has_tags, 10045
28094, has_tags, 24811
27143, has_genre, 24811
27143, has_tags, 10045
8381, has_genre, 24811
8381, has_tags, 10045
23396, has_genre, 24811
23396, has_tags, 10045
15961, has_genre, 24811
15961, release_year, 35845
771, has_genre, 24811
771, has_tags, 10045
33960, has_genre, 24811
33960, has_tags, 24811
33960, release_year, 39813
1690, has_genre, 24811
1690, has_tags, 10045
14623, has_genre, 24811
14623, release_year, 35845
1831, has_genre, 24811
1831, release_year, 35845
19500, has_genre, 24811
19500, release_year, 35845
8294, has_genre, 24811
8294, release_year, 35845
15351, has_genre, 24811
15351, has_tags, 10045
39565, has_genre, 24811
39565, has_tags, 10045
39565, release_year, 39813
9003, has_genre, 24811
9003, has_tags, 10045
9003, has_tags, 24811
19221, has_genre, 24811
19221, has_tags, 10045
23299, has_genre, 24811
23299, has_tags, 10045
23299, release_year, 39813
16365, has_genre, 24811
16365, has_tags, 10045
34771, has_genre, 24811
34771, has_tags, 10045
39298, has_genre, 24811
39298, release_year, 35845
39972, has_genre, 24811
39972, has_tags, 10045
7264, has_genre, 24811
7264, release_year, 35845
7415, has_genre, 24811
7415, has_tags, 10045
21302, has_genre, 24811
21302, has_tags, 24811
21302, release_year, 39813
7743, has_genre, 24811
7743, release_year, 35845
33950, has_tags, 24811
33950, release_year, 35845
40127, has_genre, 24811
40127, has_tags, 10045
22260, has_genre, 24811
22260, release_year, 35845
36083, has_genre, 24811
36083, has_tags, 10045
16462, has_genre, 24811
16462, has_tags, 10045
25264, has_genre, 24811
25264, release_year, 35845
37989, has_genre, 24811
37989, has_tags, 10045
19017, has_genre, 24811
19017, has_tags, 10045
39493, has_genre, 24811
39493, release_year, 39813
6297, has_genre, 24811
6297, has_tags, 10045
15605, has_genre, 24811
15605, has_tags, 24811
15605, release_year, 35845
30059, directed_by, 7368
30059, has_genre, 24811
30059, has_tags, 10045
30059, release_year, 39813
30059, release_year, 35845
9936, has_genre, 24811
9936, has_tags, 10045
9936, has_tags, 24811
7060, has_genre, 24811
7060, has_tags, 10045
16921, has_genre, 24811
16921, release_year, 35845
29005, has_genre, 24811
29005, has_tags, 10045
6119, has_genre, 24811
6119, has_tags, 10045
13, has_genre, 24811
13, release_year, 35845
24045, has_genre, 24811
24045, has_tags, 10045
40046, has_genre, 24811
40046, has_tags, 10045
16127, has_genre, 24811
16127, release_year, 39813
35380, has_genre, 24811
35380, has_tags, 10045
37807, has_tags, 24811
37807, release_year, 35845
35864, has_genre, 24811
35864, release_year, 35845
32227, has_genre, 24811
32227, release_year, 39813
24057, has_genre, 24811
24057, release_year, 35845
1070, has_genre, 24811
1070, release_year, 35845
29799, has_genre, 24811
29799, has_tags, 10045
12339, has_genre, 24811
12339, has_tags, 10045
1059, has_genre, 24811
1059, release_year, 35845
16732, has_genre, 24811
16732, has_tags, 10045
24006, has_genre, 24811
24006, release_year, 39813
35937, has_genre, 24811
35937, has_tags, 10045
22869, has_genre, 24811
22869, has_tags, 10045
11168, has_genre, 24811
11168, has_tags, 10045
4091, has_genre, 24811
4091, has_tags, 10045
30690, has_genre, 24811
30690, has_tags, 10045
20165, has_genre, 24811
20165, release_year, 35845
33948, has_genre, 24811
33948, has_tags, 10045
30903, has_genre, 24811
30903, has_tags, 10045
29773, has_genre, 24811
29773, has_tags, 10045
29773, has_tags, 24811
27599, has_tags, 10045
27599, has_tags, 24811
15196, has_genre, 24811
15196, release_year, 39813
13933, has_genre, 24811
13933, has_tags, 10045
27098, has_genre, 24811
27098, has_tags, 24811
27098, release_year, 35845
18162, has_genre, 24811
18162, has_tags, 10045
18162, release_year, 35845
28919, has_genre, 24811
28919, release_year, 35845
4300, has_genre, 24811
4300, has_tags, 24811
4300, release_year, 35845
18785, has_genre, 24811
18785, has_tags, 10045
23847, has_genre, 24811
23847, has_tags, 10045
23847, has_tags, 24811
25030, has_genre, 24811
25030, release_year, 35845
17568, has_genre, 24811
17568, has_tags, 10045
22751, has_genre, 24811
22751, has_tags, 10045
22751, release_year, 35845
34407, has_genre, 24811
34407, has_tags, 10045
8334, has_tags, 8131
8334, has_tags, 24811
8334, starred_actors, 8131
10133, has_genre, 24811
10133, release_year, 35845
35164, has_genre, 24811
35164, has_tags, 10045
499, has_genre, 24811
499, has_tags, 10045
499, has_tags, 24811
6190, has_genre, 24811
6190, release_year, 39813
14868, has_genre, 24811
14868, has_tags, 10045
28071, has_genre, 24811
28071, has_tags, 10045
31083, has_genre, 24811
31083, has_tags, 10045
38760, has_tags, 10045
38760, has_tags, 24811
Question: For what reason are EMILY MORTIMER, KATHLEEN QUINLAN, and SEE NO EVIL associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"EMILY MORTIMER",
"KATHLEEN QUINLAN",
"SEE NO EVIL"
],
"valid_edges": [
[
".45",
"has_genre",
"THRILLER"
],
[
".45",
"release_year",
"2006"
],
[
"AFTER...",
"has_genre",
"THRILLER"
],
[
"AFTER...",
"release_year",
"2006"
],
[
"ALL THE PRESIDENT'S MEN",
"has_genre",
"THRILLER"
],
[
"ALL THE PRESIDENT'S MEN",
"has_tags",
"BD-R"
],
[
"ALL THE PRESIDENT'S MEN",
"has_tags",
"THRILLER"
],
[
"AMITYVILLE 3-D",
"directed_by",
"RICHARD FLEISCHER"
],
[
"AMITYVILLE 3-D",
"has_genre",
"THRILLER"
],
[
"ASSAULT ON PRECINCT 13",
"has_genre",
"THRILLER"
],
[
"ASSAULT ON PRECINCT 13",
"has_tags",
"BD-R"
],
[
"BASIC INSTINCT 2",
"has_genre",
"THRILLER"
],
[
"BASIC INSTINCT 2",
"release_year",
"2006"
],
[
"BLACK BOOK",
"has_genre",
"THRILLER"
],
[
"BLACK BOOK",
"release_year",
"2006"
],
[
"BLACKMAIL",
"has_genre",
"THRILLER"
],
[
"BLACKMAIL",
"has_tags",
"BD-R"
],
[
"BLOOD DIAMOND",
"has_genre",
"THRILLER"
],
[
"BLOOD DIAMOND",
"release_year",
"2006"
],
[
"BREAKDOWN",
"has_tags",
"THRILLER"
],
[
"BREAKDOWN",
"starred_actors",
"KATHLEEN QUINLAN"
],
[
"BUNNY LAKE IS MISSING",
"has_genre",
"THRILLER"
],
[
"BUNNY LAKE IS MISSING",
"has_tags",
"BD-R"
],
[
"CARGO",
"has_genre",
"THRILLER"
],
[
"CARGO",
"release_year",
"2006"
],
[
"CIVIC DUTY",
"has_genre",
"THRILLER"
],
[
"CIVIC DUTY",
"release_year",
"2006"
],
[
"COMPULSION",
"directed_by",
"RICHARD FLEISCHER"
],
[
"COMPULSION",
"has_genre",
"THRILLER"
],
[
"COMPULSION",
"has_tags",
"BD-R"
],
[
"COMPULSION",
"has_tags",
"RICHARD FLEISCHER"
],
[
"DARK RIDE",
"has_genre",
"THRILLER"
],
[
"DARK RIDE",
"release_year",
"2006"
],
[
"DEAD RINGER",
"has_genre",
"THRILLER"
],
[
"DEAD RINGER",
"has_tags",
"BD-R"
],
[
"DELIVERANCE",
"has_genre",
"THRILLER"
],
[
"DELIVERANCE",
"has_tags",
"BD-R"
],
[
"DELIVERANCE",
"has_tags",
"THRILLER"
],
[
"DEMENTIA 13",
"has_genre",
"THRILLER"
],
[
"DEMENTIA 13",
"has_tags",
"BD-R"
],
[
"DETOUR",
"has_genre",
"THRILLER"
],
[
"DETOUR",
"has_tags",
"BD-R"
],
[
"DIAL M FOR MURDER",
"has_genre",
"THRILLER"
],
[
"DIAL M FOR MURDER",
"has_tags",
"BD-R"
],
[
"DON",
"has_genre",
"THRILLER"
],
[
"DON",
"release_year",
"2006"
],
[
"DRESSED TO KILL",
"has_genre",
"THRILLER"
],
[
"DRESSED TO KILL",
"has_tags",
"BD-R"
],
[
"DUEL",
"has_genre",
"THRILLER"
],
[
"DUEL",
"has_tags",
"THRILLER"
],
[
"DUEL",
"release_year",
"1971"
],
[
"EYES OF LAURA MARS",
"has_genre",
"THRILLER"
],
[
"EYES OF LAURA MARS",
"has_tags",
"BD-R"
],
[
"FADE TO BLACK",
"has_genre",
"THRILLER"
],
[
"FADE TO BLACK",
"release_year",
"2006"
],
[
"FIREWALL",
"has_genre",
"THRILLER"
],
[
"FIREWALL",
"release_year",
"2006"
],
[
"FIRST SNOW",
"has_genre",
"THRILLER"
],
[
"FIRST SNOW",
"release_year",
"2006"
],
[
"FIVE FINGERS",
"has_genre",
"THRILLER"
],
[
"FIVE FINGERS",
"release_year",
"2006"
],
[
"FOREIGN CORRESPONDENT",
"has_genre",
"THRILLER"
],
[
"FOREIGN CORRESPONDENT",
"has_tags",
"BD-R"
],
[
"FRIGHT",
"has_genre",
"THRILLER"
],
[
"FRIGHT",
"has_tags",
"BD-R"
],
[
"FRIGHT",
"release_year",
"1971"
],
[
"FUNNY GAMES",
"has_genre",
"THRILLER"
],
[
"FUNNY GAMES",
"has_tags",
"BD-R"
],
[
"FUNNY GAMES",
"has_tags",
"THRILLER"
],
[
"GASLIGHT",
"has_genre",
"THRILLER"
],
[
"GASLIGHT",
"has_tags",
"BD-R"
],
[
"GET CARTER",
"has_genre",
"THRILLER"
],
[
"GET CARTER",
"has_tags",
"BD-R"
],
[
"GET CARTER",
"release_year",
"1971"
],
[
"GOOD NEIGHBORS",
"has_genre",
"THRILLER"
],
[
"GOOD NEIGHBORS",
"has_tags",
"BD-R"
],
[
"GREEN FOR DANGER",
"has_genre",
"THRILLER"
],
[
"GREEN FOR DANGER",
"has_tags",
"BD-R"
],
[
"HARD LUCK",
"has_genre",
"THRILLER"
],
[
"HARD LUCK",
"release_year",
"2006"
],
[
"HOLLOW MAN",
"has_genre",
"THRILLER"
],
[
"HOLLOW MAN",
"has_tags",
"BD-R"
],
[
"INSIDE MAN",
"has_genre",
"THRILLER"
],
[
"INSIDE MAN",
"release_year",
"2006"
],
[
"KISS OF DEATH",
"has_genre",
"THRILLER"
],
[
"KISS OF DEATH",
"has_tags",
"BD-R"
],
[
"KLUTE",
"has_genre",
"THRILLER"
],
[
"KLUTE",
"has_tags",
"THRILLER"
],
[
"KLUTE",
"release_year",
"1971"
],
[
"LADY IN THE WATER",
"has_genre",
"THRILLER"
],
[
"LADY IN THE WATER",
"release_year",
"2006"
],
[
"LUCKY NUMBER SLEVIN",
"has_tags",
"THRILLER"
],
[
"LUCKY NUMBER SLEVIN",
"release_year",
"2006"
],
[
"MACABRE",
"has_genre",
"THRILLER"
],
[
"MACABRE",
"has_tags",
"BD-R"
],
[
"MEMORY",
"has_genre",
"THRILLER"
],
[
"MEMORY",
"release_year",
"2006"
],
[
"MIRANDA",
"has_genre",
"THRILLER"
],
[
"MIRANDA",
"has_tags",
"BD-R"
],
[
"MYSTERY OF THE WAX MUSEUM",
"has_genre",
"THRILLER"
],
[
"MYSTERY OF THE WAX MUSEUM",
"has_tags",
"BD-R"
],
[
"NOTES ON A SCANDAL",
"has_genre",
"THRILLER"
],
[
"NOTES ON A SCANDAL",
"release_year",
"2006"
],
[
"OBSESSION",
"has_genre",
"THRILLER"
],
[
"OBSESSION",
"has_tags",
"BD-R"
],
[
"PEEPING TOM",
"has_genre",
"THRILLER"
],
[
"PEEPING TOM",
"has_tags",
"BD-R"
],
[
"PLAY MISTY FOR ME",
"has_genre",
"THRILLER"
],
[
"PLAY MISTY FOR ME",
"release_year",
"1971"
],
[
"REBECCA",
"has_genre",
"THRILLER"
],
[
"REBECCA",
"has_tags",
"BD-R"
],
[
"RIGHT AT YOUR DOOR",
"has_genre",
"THRILLER"
],
[
"RIGHT AT YOUR DOOR",
"has_tags",
"THRILLER"
],
[
"RIGHT AT YOUR DOOR",
"release_year",
"2006"
],
[
"SEE NO EVIL",
"directed_by",
"RICHARD FLEISCHER"
],
[
"SEE NO EVIL",
"has_genre",
"THRILLER"
],
[
"SEE NO EVIL",
"has_tags",
"BD-R"
],
[
"SEE NO EVIL",
"release_year",
"1971"
],
[
"SEE NO EVIL",
"release_year",
"2006"
],
[
"SEVEN DAYS IN MAY",
"has_genre",
"THRILLER"
],
[
"SEVEN DAYS IN MAY",
"has_tags",
"BD-R"
],
[
"SEVEN DAYS IN MAY",
"has_tags",
"THRILLER"
],
[
"SEVEN DAYS TO NOON",
"has_genre",
"THRILLER"
],
[
"SEVEN DAYS TO NOON",
"has_tags",
"BD-R"
],
[
"SHADOW MAN",
"has_genre",
"THRILLER"
],
[
"SHADOW MAN",
"release_year",
"2006"
],
[
"SIN CITY",
"has_genre",
"THRILLER"
],
[
"SIN CITY",
"has_tags",
"BD-R"
],
[
"SLEUTH",
"has_genre",
"THRILLER"
],
[
"SLEUTH",
"has_tags",
"BD-R"
],
[
"SNAKES ON A PLANE",
"has_genre",
"THRILLER"
],
[
"SNAKES ON A PLANE",
"release_year",
"2006"
],
[
"STRAIT-JACKET",
"has_genre",
"THRILLER"
],
[
"STRAIT-JACKET",
"has_tags",
"BD-R"
],
[
"STRANGERS ON A TRAIN",
"has_genre",
"THRILLER"
],
[
"STRANGERS ON A TRAIN",
"has_tags",
"BD-R"
],
[
"STRAW DOGS",
"has_genre",
"THRILLER"
],
[
"STRAW DOGS",
"release_year",
"1971"
],
[
"SUSPICION",
"has_genre",
"THRILLER"
],
[
"SUSPICION",
"has_tags",
"BD-R"
],
[
"TELL NO ONE",
"has_tags",
"THRILLER"
],
[
"TELL NO ONE",
"release_year",
"2006"
],
[
"THE ABANDONED",
"has_genre",
"THRILLER"
],
[
"THE ABANDONED",
"release_year",
"2006"
],
[
"THE ANDROMEDA STRAIN",
"has_genre",
"THRILLER"
],
[
"THE ANDROMEDA STRAIN",
"release_year",
"1971"
],
[
"THE BACKWOODS",
"has_genre",
"THRILLER"
],
[
"THE BACKWOODS",
"release_year",
"2006"
],
[
"THE BUTTERFLY EFFECT 2",
"has_genre",
"THRILLER"
],
[
"THE BUTTERFLY EFFECT 2",
"release_year",
"2006"
],
[
"THE CANYONS",
"has_genre",
"THRILLER"
],
[
"THE CANYONS",
"has_tags",
"BD-R"
],
[
"THE CHINA SYNDROME",
"has_genre",
"THRILLER"
],
[
"THE CHINA SYNDROME",
"has_tags",
"BD-R"
],
[
"THE DA VINCI CODE",
"has_genre",
"THRILLER"
],
[
"THE DA VINCI CODE",
"release_year",
"2006"
],
[
"THE END",
"has_genre",
"THRILLER"
],
[
"THE END",
"has_tags",
"BD-R"
],
[
"THE FIFTH CORD",
"has_genre",
"THRILLER"
],
[
"THE FIFTH CORD",
"release_year",
"1971"
],
[
"THE FIFTH ESTATE",
"has_genre",
"THRILLER"
],
[
"THE FIFTH ESTATE",
"has_tags",
"BD-R"
],
[
"THE GHOST SHIP",
"has_genre",
"THRILLER"
],
[
"THE GHOST SHIP",
"has_tags",
"BD-R"
],
[
"THE HUMAN FACTOR",
"has_genre",
"THRILLER"
],
[
"THE HUMAN FACTOR",
"has_tags",
"BD-R"
],
[
"THE LADY VANISHES",
"has_genre",
"THRILLER"
],
[
"THE LADY VANISHES",
"has_tags",
"BD-R"
],
[
"THE LADYKILLERS",
"has_genre",
"THRILLER"
],
[
"THE LADYKILLERS",
"has_tags",
"BD-R"
],
[
"THE LAST WINTER",
"has_genre",
"THRILLER"
],
[
"THE LAST WINTER",
"release_year",
"2006"
],
[
"THE LETTER",
"has_genre",
"THRILLER"
],
[
"THE LETTER",
"has_tags",
"BD-R"
],
[
"THE MAN BETWEEN",
"has_genre",
"THRILLER"
],
[
"THE MAN BETWEEN",
"has_tags",
"BD-R"
],
[
"THE MANCHURIAN CANDIDATE",
"has_genre",
"THRILLER"
],
[
"THE MANCHURIAN CANDIDATE",
"has_tags",
"BD-R"
],
[
"THE MANCHURIAN CANDIDATE",
"has_tags",
"THRILLER"
],
[
"THE NIGHT OF THE HUNTER",
"has_tags",
"BD-R"
],
[
"THE NIGHT OF THE HUNTER",
"has_tags",
"THRILLER"
],
[
"THE NIGHT VISITOR",
"has_genre",
"THRILLER"
],
[
"THE NIGHT VISITOR",
"release_year",
"1971"
],
[
"THE PARALLAX VIEW",
"has_genre",
"THRILLER"
],
[
"THE PARALLAX VIEW",
"has_tags",
"BD-R"
],
[
"THE PRESTIGE",
"has_genre",
"THRILLER"
],
[
"THE PRESTIGE",
"has_tags",
"THRILLER"
],
[
"THE PRESTIGE",
"release_year",
"2006"
],
[
"THE RAVEN",
"has_genre",
"THRILLER"
],
[
"THE RAVEN",
"has_tags",
"BD-R"
],
[
"THE RAVEN",
"release_year",
"2006"
],
[
"THE RETURN",
"has_genre",
"THRILLER"
],
[
"THE RETURN",
"release_year",
"2006"
],
[
"THE SENTINEL",
"has_genre",
"THRILLER"
],
[
"THE SENTINEL",
"has_tags",
"THRILLER"
],
[
"THE SENTINEL",
"release_year",
"2006"
],
[
"THE SILENCE",
"has_genre",
"THRILLER"
],
[
"THE SILENCE",
"has_tags",
"BD-R"
],
[
"THE STEPFORD WIVES",
"has_genre",
"THRILLER"
],
[
"THE STEPFORD WIVES",
"has_tags",
"BD-R"
],
[
"THE STEPFORD WIVES",
"has_tags",
"THRILLER"
],
[
"THE UNKNOWN WOMAN",
"has_genre",
"THRILLER"
],
[
"THE UNKNOWN WOMAN",
"release_year",
"2006"
],
[
"THE VANISHING",
"has_genre",
"THRILLER"
],
[
"THE VANISHING",
"has_tags",
"BD-R"
],
[
"THE WICKER MAN",
"has_genre",
"THRILLER"
],
[
"THE WICKER MAN",
"has_tags",
"BD-R"
],
[
"THE WICKER MAN",
"release_year",
"2006"
],
[
"THE WRONG MAN",
"has_genre",
"THRILLER"
],
[
"THE WRONG MAN",
"has_tags",
"BD-R"
],
[
"TRANSSIBERIAN",
"has_tags",
"EMILY MORTIMER"
],
[
"TRANSSIBERIAN",
"has_tags",
"THRILLER"
],
[
"TRANSSIBERIAN",
"starred_actors",
"EMILY MORTIMER"
],
[
"UNKNOWN",
"has_genre",
"THRILLER"
],
[
"UNKNOWN",
"release_year",
"2006"
],
[
"VANISHING ON 7TH STREET",
"has_genre",
"THRILLER"
],
[
"VANISHING ON 7TH STREET",
"has_tags",
"BD-R"
],
[
"WAIT UNTIL DARK",
"has_genre",
"THRILLER"
],
[
"WAIT UNTIL DARK",
"has_tags",
"BD-R"
],
[
"WAIT UNTIL DARK",
"has_tags",
"THRILLER"
],
[
"WAKE IN FRIGHT",
"has_genre",
"THRILLER"
],
[
"WAKE IN FRIGHT",
"release_year",
"1971"
],
[
"WESTWORLD",
"has_genre",
"THRILLER"
],
[
"WESTWORLD",
"has_tags",
"BD-R"
],
[
"WHAT EVER HAPPENED TO BABY JANE?",
"has_genre",
"THRILLER"
],
[
"WHAT EVER HAPPENED TO BABY JANE?",
"has_tags",
"BD-R"
],
[
"WRONG IS RIGHT",
"has_genre",
"THRILLER"
],
[
"WRONG IS RIGHT",
"has_tags",
"BD-R"
],
[
"Z",
"has_tags",
"BD-R"
],
[
"Z",
"has_tags",
"THRILLER"
]
]
}
|
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
1006, 1996
2594, BASQUIAT
33410, BEFORE NIGHT FALLS
31783, ENGLISH
33240, JORGE BLANCO
35885, JULIAN SCHNABEL
19264, KISSED
7273, NECROPHILIA
8266, PLANET 51
src, edge_attr, dst
2594, directed_by, 35885
2594, has_tags, 35885
2594, release_year, 1006
2594, written_by, 35885
33410, directed_by, 35885
33410, has_tags, 35885
33410, in_language, 31783
33410, written_by, 35885
19264, has_tags, 7273
19264, release_year, 1006
8266, directed_by, 33240
8266, in_language, 31783
8266, written_by, 33240
Question: How are JORGE BLANCO, JULIAN SCHNABEL, and NECROPHILIA related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"JORGE BLANCO",
"JULIAN SCHNABEL",
"NECROPHILIA"
],
"valid_edges": [
[
"BASQUIAT",
"directed_by",
"JULIAN SCHNABEL"
],
[
"BASQUIAT",
"has_tags",
"JULIAN SCHNABEL"
],
[
"BASQUIAT",
"release_year",
"1996"
],
[
"BASQUIAT",
"written_by",
"JULIAN SCHNABEL"
],
[
"BEFORE NIGHT FALLS",
"directed_by",
"JULIAN SCHNABEL"
],
[
"BEFORE NIGHT FALLS",
"has_tags",
"JULIAN SCHNABEL"
],
[
"BEFORE NIGHT FALLS",
"in_language",
"ENGLISH"
],
[
"BEFORE NIGHT FALLS",
"written_by",
"JULIAN SCHNABEL"
],
[
"KISSED",
"has_tags",
"NECROPHILIA"
],
[
"KISSED",
"release_year",
"1996"
],
[
"PLANET 51",
"directed_by",
"JORGE BLANCO"
],
[
"PLANET 51",
"in_language",
"ENGLISH"
],
[
"PLANET 51",
"written_by",
"JORGE BLANCO"
]
]
}
|
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
21950, 'R XMAS
33823, 15 MINUTES
13408, 2001
13747, 25 WATTS
5478, 30 YEARS TO LIFE
26646, 3000 MILES TO GRACELAND
39540, A FINE PAIR
8200, ALL OVER THE GUY
32427, ALL THE QUEEN'S MEN
17687, AMERICA'S SWEETHEARTS
34899, AMERICAN PIE 2
12224, AMÉLIE
5593, BABY BOY
12144, BAD BOYS
23952, BANDITS
13418, BARTLEBY
38657, BEAT THE DEVIL
38736, BIG MOMMA'S HOUSE 2
5099, BIG NOTHING
19633, BIRTHDAY GIRL
9654, BLACK KNIGHT
35213, BLOW DRY
23128, BRIDGET JONES'S DIARY
19026, BUBBLE BOY
29342, BULLY
17892, CAMOUFLAGE
25632, CARO DIARIO
30463, COMEDY
2605, CORKY ROMANO
14724, CRIME
18980, CROCODILE DUNDEE IN LOS ANGELES
9986, DELITTO A PORTA ROMANA
1915, DIL CHAHTA HAI
33382, DOM HEMINGWAY
12217, DON'T TEMPT ME
7023, DOUBLE TAKE
19756, DOWN TO EARTH
8704, DR. DOLITTLE 2
36212, DRAMA
28808, ESCANABA IN DA MOONLIGHT
23470, EVOLUTION
28256, FILTH
18217, FIND ME GUILTY
34555, FLAWLESS
32047, FLYPAPER
6915, FOCUS
21322, FREDDY GOT FINGERED
27305, GANG TAPES
37360, GASOLINE
23511, GAUDI AFTERNOON
37949, GET OVER IT
12664, GHOST WORLD
18445, GOD IS GREAT AND I'M NOT
10113, GOOD ADVICE
30479, GRIDLOCK'D
17938, HANNIBAL
8648, HAPPY CAMPERS
29107, HARLEM NIGHTS
21060, HARVARD MAN
37229, HE DIED WITH A FELAFEL IN HIS HAND
11344, HEARTBREAKERS
1292, HEDWIG AND THE ANGRY INCH
31450, HEIST
38901, HIGH HEELS AND LOW LIFES
10703, HOW HIGH
35625, HUMAN NATURE
20430, IN THE BEDROOM
16200, ITALIAN
23526, JACKPOT
263, JAY AND SILENT BOB STRIKE BACK
32383, JOE DIRT
12610, JOE SOMEBODY
10109, JOSIE AND THE PUSSYCATS
30384, JUMP TOMORROW
16839, JUST VISITING
7699, KINGDOM COME
20428, KISSING JESSICA STEIN
17559, LEGALLY BLONDE
29734, LITTLE SECRETS
26731, LUCKY BREAK
34517, LUV
28660, MADE
10560, MAN BITES DOG
6068, MAX KEEBLE'S BIG MOVE
33714, MEAN MACHINE
33853, MONKEYBONE
20003, MONSTERS, INC.
24616, MOSTLY MARTHA
33535, MY KINGDOM
12944, MY LIFE WITHOUT ME
36451, NANCI KINCAID
36577, NANNI MORETTI
26151, NOBODY'S BABY
5731, NOT ANOTHER TEEN MOVIE
29029, NOVOCAINE
21875, OCEAN'S ELEVEN
6959, ON THE LINE
32186, ONE MAN UP
8935, ONE NIGHT AT MCCOOL'S
11056, PAULETTE
28044, PAULINE AND PAULETTE
31445, PONTEROSA
13381, POOTIE TANG
28182, RARE BIRDS
32180, RAT RACE
38381, ROCK STAR
33108, RUNNING SCARED
9530, RUSH HOUR 2
1789, SAVING SILVERMAN
37244, SAY IT ISN'T SO
5880, SERENDIPITY
35100, SHALLOW HAL
7519, SHAOLIN SOCCER
36159, SHREK
30089, SIDEWALKS OF NEW YORK
2407, SON OF THE BRIDE
24221, SPEAKING OF SEX
35843, SPUN
7949, STORYTELLING
2235, SUMMER CATCH
4783, SUPER TROOPERS
27762, SWEET NOVEMBER
30932, SWORDFISH
345, TANGUY
23280, THE ANIMAL
15795, THE ANNIVERSARY PARTY
25674, THE BROTHERS
36932, THE CAIMAN
30164, THE CLOSET
4927, THE CURSE OF THE JADE SCORPION
38918, THE FAMILY
24493, THE FUNERAL
17778, THE HAPPINESS OF THE KATAKURIS
28107, THE LAST KISS
24108, THE MAN
10353, THE MAN WHO SUED GOD
27713, THE MEXICAN
23086, THE PRINCESS DIARIES
7206, THE QUICKIE
20728, THE ROYAL TENENBAUMS
14886, THE SCORE
36231, THE SHRINK IS IN
26296, THE SON'S ROOM
26678, THE SWINDLE
37184, THE TRIUMPH OF LOVE
33449, THE WEDDING PLANNER
37331, TO DIE FOR
11027, TOMCATS
35988, TORTILLA SOUP
36468, TOUGH GUYS DON'T DANCE
17169, TRAINING DAY
19451, TWO CAN PLAY THAT GAME
21790, VERY ANNIE MARY
3137, VISITOR Q
35443, VIZONTELE
29077, WASABI
25414, WATERBOYS
35511, WE HAVE A POPE
27083, WET HOT AMERICAN SUMMER
37358, WHAT'S THE WORST THAT COULD HAPPEN?
23844, WHO IS CLETIS TOUT?
4063, ZOOLANDER
src, edge_attr, dst
21950, has_genre, 14724
21950, release_year, 13408
33823, has_genre, 14724
33823, release_year, 13408
13747, has_genre, 30463
13747, release_year, 13408
5478, has_genre, 30463
5478, release_year, 13408
26646, has_genre, 14724
26646, release_year, 13408
39540, has_genre, 30463
39540, has_genre, 14724
8200, has_genre, 30463
8200, release_year, 13408
32427, has_genre, 30463
32427, release_year, 13408
17687, has_genre, 30463
17687, release_year, 13408
34899, has_genre, 30463
34899, has_tags, 30463
34899, release_year, 13408
12224, has_genre, 30463
12224, has_tags, 30463
12224, release_year, 13408
5593, has_genre, 30463
5593, release_year, 13408
12144, has_genre, 30463
12144, has_genre, 14724
12144, has_tags, 30463
23952, has_genre, 30463
23952, has_genre, 14724
23952, release_year, 13408
13418, has_genre, 30463
13418, release_year, 13408
38657, has_genre, 30463
38657, has_tags, 14724
38736, has_genre, 30463
38736, has_genre, 14724
5099, has_genre, 30463
5099, has_genre, 14724
5099, has_tags, 30463
5099, has_tags, 14724
19633, has_genre, 14724
19633, release_year, 13408
9654, has_genre, 30463
9654, has_tags, 30463
9654, release_year, 13408
35213, has_genre, 30463
35213, release_year, 13408
23128, has_genre, 30463
23128, has_tags, 30463
23128, release_year, 13408
19026, has_genre, 30463
19026, release_year, 13408
29342, has_genre, 14724
29342, release_year, 13408
17892, has_genre, 30463
17892, release_year, 13408
25632, directed_by, 36577
25632, has_tags, 36577
25632, in_language, 16200
25632, starred_actors, 36577
25632, written_by, 36577
2605, has_genre, 30463
2605, release_year, 13408
18980, has_genre, 30463
18980, release_year, 13408
9986, has_genre, 30463
9986, has_genre, 14724
1915, has_genre, 30463
1915, has_tags, 30463
1915, release_year, 13408
33382, has_genre, 30463
33382, has_genre, 14724
12217, has_genre, 30463
12217, release_year, 13408
7023, has_genre, 30463
7023, release_year, 13408
19756, has_genre, 30463
19756, release_year, 13408
8704, has_genre, 30463
8704, release_year, 13408
28808, has_genre, 30463
28808, release_year, 13408
23470, has_genre, 30463
23470, has_tags, 30463
23470, release_year, 13408
28256, has_genre, 30463
28256, has_genre, 14724
18217, has_genre, 30463
18217, has_genre, 14724
34555, has_genre, 30463
34555, has_genre, 14724
32047, has_genre, 30463
32047, has_genre, 14724
6915, has_genre, 30463
6915, release_year, 13408
21322, has_genre, 30463
21322, release_year, 13408
27305, has_genre, 14724
27305, release_year, 13408
37360, has_genre, 14724
37360, release_year, 13408
23511, has_genre, 30463
23511, release_year, 13408
37949, has_genre, 30463
37949, has_tags, 30463
37949, release_year, 13408
12664, has_genre, 30463
12664, release_year, 13408
18445, has_genre, 30463
18445, release_year, 13408
10113, has_genre, 30463
10113, release_year, 13408
30479, has_genre, 30463
30479, has_genre, 14724
17938, has_genre, 14724
17938, release_year, 13408
8648, has_genre, 30463
8648, release_year, 13408
29107, has_genre, 30463
29107, has_genre, 14724
21060, has_genre, 30463
21060, has_genre, 14724
21060, release_year, 13408
37229, has_genre, 30463
37229, release_year, 13408
11344, has_genre, 30463
11344, release_year, 13408
1292, has_genre, 30463
1292, release_year, 13408
31450, has_genre, 14724
31450, release_year, 13408
38901, has_genre, 30463
38901, release_year, 13408
10703, has_genre, 30463
10703, release_year, 13408
35625, has_genre, 30463
35625, release_year, 13408
20430, has_genre, 14724
20430, release_year, 13408
23526, has_genre, 30463
23526, release_year, 13408
263, has_genre, 30463
263, has_tags, 30463
263, release_year, 13408
32383, has_genre, 30463
32383, release_year, 13408
12610, has_genre, 30463
12610, release_year, 13408
10109, has_genre, 30463
10109, release_year, 13408
30384, has_genre, 30463
30384, release_year, 13408
16839, has_genre, 30463
16839, release_year, 13408
7699, has_genre, 30463
7699, release_year, 13408
20428, has_genre, 30463
20428, release_year, 13408
17559, has_genre, 30463
17559, has_tags, 30463
17559, release_year, 13408
29734, has_genre, 30463
29734, release_year, 13408
26731, has_genre, 30463
26731, release_year, 13408
34517, has_genre, 30463
34517, has_genre, 14724
28660, has_genre, 30463
28660, has_genre, 14724
28660, release_year, 13408
10560, has_genre, 30463
10560, has_genre, 14724
6068, has_genre, 30463
6068, release_year, 13408
33714, has_genre, 30463
33714, release_year, 13408
33853, has_genre, 30463
33853, release_year, 13408
20003, has_genre, 30463
20003, has_tags, 30463
20003, release_year, 13408
24616, has_genre, 30463
24616, release_year, 13408
33535, has_genre, 14724
33535, release_year, 13408
12944, has_genre, 36212
12944, written_by, 36451
26151, has_genre, 30463
26151, release_year, 13408
5731, has_genre, 30463
5731, release_year, 13408
29029, has_genre, 30463
29029, release_year, 13408
21875, has_tags, 30463
21875, release_year, 13408
6959, has_genre, 30463
6959, release_year, 13408
32186, has_genre, 30463
32186, release_year, 13408
8935, has_genre, 30463
8935, has_genre, 14724
8935, release_year, 13408
11056, has_genre, 30463
11056, has_genre, 14724
28044, has_genre, 30463
28044, release_year, 13408
31445, has_genre, 30463
31445, has_tags, 30463
31445, release_year, 13408
13381, has_genre, 30463
13381, release_year, 13408
28182, has_genre, 30463
28182, release_year, 13408
32180, has_genre, 30463
32180, has_tags, 30463
32180, release_year, 13408
38381, has_genre, 30463
38381, release_year, 13408
33108, has_genre, 30463
33108, has_genre, 14724
9530, has_genre, 30463
9530, has_tags, 30463
9530, release_year, 13408
1789, has_genre, 30463
1789, has_tags, 30463
1789, release_year, 13408
37244, has_genre, 30463
37244, release_year, 13408
5880, has_genre, 30463
5880, release_year, 13408
35100, has_genre, 30463
35100, release_year, 13408
7519, has_genre, 30463
7519, release_year, 13408
36159, has_genre, 30463
36159, has_tags, 30463
36159, release_year, 13408
30089, has_genre, 30463
30089, release_year, 13408
2407, has_genre, 30463
2407, release_year, 13408
24221, has_genre, 30463
24221, release_year, 13408
35843, has_genre, 30463
35843, has_genre, 14724
7949, has_genre, 30463
7949, release_year, 13408
2235, has_genre, 30463
2235, release_year, 13408
4783, has_genre, 30463
4783, has_tags, 30463
4783, release_year, 13408
27762, has_genre, 30463
27762, release_year, 13408
30932, has_genre, 14724
30932, release_year, 13408
345, has_genre, 30463
345, release_year, 13408
23280, has_genre, 30463
23280, release_year, 13408
15795, has_genre, 30463
15795, release_year, 13408
25674, has_genre, 30463
25674, release_year, 13408
36932, directed_by, 36577
36932, has_genre, 30463
36932, has_genre, 36212
36932, in_language, 16200
36932, written_by, 36577
30164, has_genre, 30463
30164, has_tags, 30463
30164, release_year, 13408
4927, has_genre, 30463
4927, has_genre, 14724
4927, release_year, 13408
38918, has_genre, 30463
38918, has_genre, 14724
24493, has_genre, 30463
24493, has_genre, 14724
17778, has_genre, 30463
17778, release_year, 13408
28107, has_genre, 30463
28107, release_year, 13408
24108, has_genre, 30463
24108, has_genre, 14724
24108, has_tags, 30463
10353, has_genre, 30463
10353, release_year, 13408
27713, has_genre, 30463
27713, has_tags, 30463
27713, release_year, 13408
23086, has_genre, 30463
23086, has_tags, 30463
23086, release_year, 13408
7206, has_genre, 14724
7206, release_year, 13408
20728, has_genre, 30463
20728, has_tags, 30463
20728, release_year, 13408
14886, has_genre, 14724
14886, release_year, 13408
36231, has_genre, 30463
36231, release_year, 13408
26296, directed_by, 36577
26296, has_tags, 36577
26296, in_language, 16200
26296, release_year, 13408
26296, starred_actors, 36577
26296, written_by, 36577
26678, has_genre, 30463
26678, has_genre, 14724
37184, has_genre, 30463
37184, release_year, 13408
33449, has_genre, 30463
33449, release_year, 13408
37331, has_genre, 30463
37331, has_genre, 14724
11027, has_genre, 30463
11027, release_year, 13408
35988, has_genre, 30463
35988, release_year, 13408
36468, has_genre, 30463
36468, has_genre, 14724
17169, has_genre, 14724
17169, release_year, 13408
19451, has_genre, 30463
19451, release_year, 13408
21790, has_genre, 30463
21790, release_year, 13408
3137, has_genre, 30463
3137, release_year, 13408
35443, has_genre, 30463
35443, has_tags, 30463
35443, release_year, 13408
29077, has_genre, 30463
29077, has_tags, 30463
29077, release_year, 13408
25414, has_genre, 30463
25414, release_year, 13408
35511, directed_by, 36577
35511, has_genre, 30463
35511, has_genre, 36212
35511, has_tags, 30463
35511, has_tags, 16200
35511, in_language, 16200
35511, written_by, 36577
27083, has_genre, 30463
27083, release_year, 13408
37358, has_genre, 30463
37358, release_year, 13408
23844, has_genre, 30463
23844, has_genre, 14724
23844, release_year, 13408
4063, has_genre, 30463
4063, has_tags, 30463
4063, release_year, 13408
Question: In what context are NANCI KINCAID, NANNI MORETTI, and THE CURSE OF THE JADE SCORPION connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"NANCI KINCAID",
"NANNI MORETTI",
"THE CURSE OF THE JADE SCORPION"
],
"valid_edges": [
[
"'R XMAS",
"has_genre",
"CRIME"
],
[
"'R XMAS",
"release_year",
"2001"
],
[
"15 MINUTES",
"has_genre",
"CRIME"
],
[
"15 MINUTES",
"release_year",
"2001"
],
[
"25 WATTS",
"has_genre",
"COMEDY"
],
[
"25 WATTS",
"release_year",
"2001"
],
[
"30 YEARS TO LIFE",
"has_genre",
"COMEDY"
],
[
"30 YEARS TO LIFE",
"release_year",
"2001"
],
[
"3000 MILES TO GRACELAND",
"has_genre",
"CRIME"
],
[
"3000 MILES TO GRACELAND",
"release_year",
"2001"
],
[
"A FINE PAIR",
"has_genre",
"COMEDY"
],
[
"A FINE PAIR",
"has_genre",
"CRIME"
],
[
"ALL OVER THE GUY",
"has_genre",
"COMEDY"
],
[
"ALL OVER THE GUY",
"release_year",
"2001"
],
[
"ALL THE QUEEN'S MEN",
"has_genre",
"COMEDY"
],
[
"ALL THE QUEEN'S MEN",
"release_year",
"2001"
],
[
"AMERICA'S SWEETHEARTS",
"has_genre",
"COMEDY"
],
[
"AMERICA'S SWEETHEARTS",
"release_year",
"2001"
],
[
"AMERICAN PIE 2",
"has_genre",
"COMEDY"
],
[
"AMERICAN PIE 2",
"has_tags",
"COMEDY"
],
[
"AMERICAN PIE 2",
"release_year",
"2001"
],
[
"AMÉLIE",
"has_genre",
"COMEDY"
],
[
"AMÉLIE",
"has_tags",
"COMEDY"
],
[
"AMÉLIE",
"release_year",
"2001"
],
[
"BABY BOY",
"has_genre",
"COMEDY"
],
[
"BABY BOY",
"release_year",
"2001"
],
[
"BAD BOYS",
"has_genre",
"COMEDY"
],
[
"BAD BOYS",
"has_genre",
"CRIME"
],
[
"BAD BOYS",
"has_tags",
"COMEDY"
],
[
"BANDITS",
"has_genre",
"COMEDY"
],
[
"BANDITS",
"has_genre",
"CRIME"
],
[
"BANDITS",
"release_year",
"2001"
],
[
"BARTLEBY",
"has_genre",
"COMEDY"
],
[
"BARTLEBY",
"release_year",
"2001"
],
[
"BEAT THE DEVIL",
"has_genre",
"COMEDY"
],
[
"BEAT THE DEVIL",
"has_tags",
"CRIME"
],
[
"BIG MOMMA'S HOUSE 2",
"has_genre",
"COMEDY"
],
[
"BIG MOMMA'S HOUSE 2",
"has_genre",
"CRIME"
],
[
"BIG NOTHING",
"has_genre",
"COMEDY"
],
[
"BIG NOTHING",
"has_genre",
"CRIME"
],
[
"BIG NOTHING",
"has_tags",
"COMEDY"
],
[
"BIG NOTHING",
"has_tags",
"CRIME"
],
[
"BIRTHDAY GIRL",
"has_genre",
"CRIME"
],
[
"BIRTHDAY GIRL",
"release_year",
"2001"
],
[
"BLACK KNIGHT",
"has_genre",
"COMEDY"
],
[
"BLACK KNIGHT",
"has_tags",
"COMEDY"
],
[
"BLACK KNIGHT",
"release_year",
"2001"
],
[
"BLOW DRY",
"has_genre",
"COMEDY"
],
[
"BLOW DRY",
"release_year",
"2001"
],
[
"BRIDGET JONES'S DIARY",
"has_genre",
"COMEDY"
],
[
"BRIDGET JONES'S DIARY",
"has_tags",
"COMEDY"
],
[
"BRIDGET JONES'S DIARY",
"release_year",
"2001"
],
[
"BUBBLE BOY",
"has_genre",
"COMEDY"
],
[
"BUBBLE BOY",
"release_year",
"2001"
],
[
"BULLY",
"has_genre",
"CRIME"
],
[
"BULLY",
"release_year",
"2001"
],
[
"CAMOUFLAGE",
"has_genre",
"COMEDY"
],
[
"CAMOUFLAGE",
"release_year",
"2001"
],
[
"CARO DIARIO",
"directed_by",
"NANNI MORETTI"
],
[
"CARO DIARIO",
"has_tags",
"NANNI MORETTI"
],
[
"CARO DIARIO",
"in_language",
"ITALIAN"
],
[
"CARO DIARIO",
"starred_actors",
"NANNI MORETTI"
],
[
"CARO DIARIO",
"written_by",
"NANNI MORETTI"
],
[
"CORKY ROMANO",
"has_genre",
"COMEDY"
],
[
"CORKY ROMANO",
"release_year",
"2001"
],
[
"CROCODILE DUNDEE IN LOS ANGELES",
"has_genre",
"COMEDY"
],
[
"CROCODILE DUNDEE IN LOS ANGELES",
"release_year",
"2001"
],
[
"DELITTO A PORTA ROMANA",
"has_genre",
"COMEDY"
],
[
"DELITTO A PORTA ROMANA",
"has_genre",
"CRIME"
],
[
"DIL CHAHTA HAI",
"has_genre",
"COMEDY"
],
[
"DIL CHAHTA HAI",
"has_tags",
"COMEDY"
],
[
"DIL CHAHTA HAI",
"release_year",
"2001"
],
[
"DOM HEMINGWAY",
"has_genre",
"COMEDY"
],
[
"DOM HEMINGWAY",
"has_genre",
"CRIME"
],
[
"DON'T TEMPT ME",
"has_genre",
"COMEDY"
],
[
"DON'T TEMPT ME",
"release_year",
"2001"
],
[
"DOUBLE TAKE",
"has_genre",
"COMEDY"
],
[
"DOUBLE TAKE",
"release_year",
"2001"
],
[
"DOWN TO EARTH",
"has_genre",
"COMEDY"
],
[
"DOWN TO EARTH",
"release_year",
"2001"
],
[
"DR. DOLITTLE 2",
"has_genre",
"COMEDY"
],
[
"DR. DOLITTLE 2",
"release_year",
"2001"
],
[
"ESCANABA IN DA MOONLIGHT",
"has_genre",
"COMEDY"
],
[
"ESCANABA IN DA MOONLIGHT",
"release_year",
"2001"
],
[
"EVOLUTION",
"has_genre",
"COMEDY"
],
[
"EVOLUTION",
"has_tags",
"COMEDY"
],
[
"EVOLUTION",
"release_year",
"2001"
],
[
"FILTH",
"has_genre",
"COMEDY"
],
[
"FILTH",
"has_genre",
"CRIME"
],
[
"FIND ME GUILTY",
"has_genre",
"COMEDY"
],
[
"FIND ME GUILTY",
"has_genre",
"CRIME"
],
[
"FLAWLESS",
"has_genre",
"COMEDY"
],
[
"FLAWLESS",
"has_genre",
"CRIME"
],
[
"FLYPAPER",
"has_genre",
"COMEDY"
],
[
"FLYPAPER",
"has_genre",
"CRIME"
],
[
"FOCUS",
"has_genre",
"COMEDY"
],
[
"FOCUS",
"release_year",
"2001"
],
[
"FREDDY GOT FINGERED",
"has_genre",
"COMEDY"
],
[
"FREDDY GOT FINGERED",
"release_year",
"2001"
],
[
"GANG TAPES",
"has_genre",
"CRIME"
],
[
"GANG TAPES",
"release_year",
"2001"
],
[
"GASOLINE",
"has_genre",
"CRIME"
],
[
"GASOLINE",
"release_year",
"2001"
],
[
"GAUDI AFTERNOON",
"has_genre",
"COMEDY"
],
[
"GAUDI AFTERNOON",
"release_year",
"2001"
],
[
"GET OVER IT",
"has_genre",
"COMEDY"
],
[
"GET OVER IT",
"has_tags",
"COMEDY"
],
[
"GET OVER IT",
"release_year",
"2001"
],
[
"GHOST WORLD",
"has_genre",
"COMEDY"
],
[
"GHOST WORLD",
"release_year",
"2001"
],
[
"GOD IS GREAT AND I'M NOT",
"has_genre",
"COMEDY"
],
[
"GOD IS GREAT AND I'M NOT",
"release_year",
"2001"
],
[
"GOOD ADVICE",
"has_genre",
"COMEDY"
],
[
"GOOD ADVICE",
"release_year",
"2001"
],
[
"GRIDLOCK'D",
"has_genre",
"COMEDY"
],
[
"GRIDLOCK'D",
"has_genre",
"CRIME"
],
[
"HANNIBAL",
"has_genre",
"CRIME"
],
[
"HANNIBAL",
"release_year",
"2001"
],
[
"HAPPY CAMPERS",
"has_genre",
"COMEDY"
],
[
"HAPPY CAMPERS",
"release_year",
"2001"
],
[
"HARLEM NIGHTS",
"has_genre",
"COMEDY"
],
[
"HARLEM NIGHTS",
"has_genre",
"CRIME"
],
[
"HARVARD MAN",
"has_genre",
"COMEDY"
],
[
"HARVARD MAN",
"has_genre",
"CRIME"
],
[
"HARVARD MAN",
"release_year",
"2001"
],
[
"HE DIED WITH A FELAFEL IN HIS HAND",
"has_genre",
"COMEDY"
],
[
"HE DIED WITH A FELAFEL IN HIS HAND",
"release_year",
"2001"
],
[
"HEARTBREAKERS",
"has_genre",
"COMEDY"
],
[
"HEARTBREAKERS",
"release_year",
"2001"
],
[
"HEDWIG AND THE ANGRY INCH",
"has_genre",
"COMEDY"
],
[
"HEDWIG AND THE ANGRY INCH",
"release_year",
"2001"
],
[
"HEIST",
"has_genre",
"CRIME"
],
[
"HEIST",
"release_year",
"2001"
],
[
"HIGH HEELS AND LOW LIFES",
"has_genre",
"COMEDY"
],
[
"HIGH HEELS AND LOW LIFES",
"release_year",
"2001"
],
[
"HOW HIGH",
"has_genre",
"COMEDY"
],
[
"HOW HIGH",
"release_year",
"2001"
],
[
"HUMAN NATURE",
"has_genre",
"COMEDY"
],
[
"HUMAN NATURE",
"release_year",
"2001"
],
[
"IN THE BEDROOM",
"has_genre",
"CRIME"
],
[
"IN THE BEDROOM",
"release_year",
"2001"
],
[
"JACKPOT",
"has_genre",
"COMEDY"
],
[
"JACKPOT",
"release_year",
"2001"
],
[
"JAY AND SILENT BOB STRIKE BACK",
"has_genre",
"COMEDY"
],
[
"JAY AND SILENT BOB STRIKE BACK",
"has_tags",
"COMEDY"
],
[
"JAY AND SILENT BOB STRIKE BACK",
"release_year",
"2001"
],
[
"JOE DIRT",
"has_genre",
"COMEDY"
],
[
"JOE DIRT",
"release_year",
"2001"
],
[
"JOE SOMEBODY",
"has_genre",
"COMEDY"
],
[
"JOE SOMEBODY",
"release_year",
"2001"
],
[
"JOSIE AND THE PUSSYCATS",
"has_genre",
"COMEDY"
],
[
"JOSIE AND THE PUSSYCATS",
"release_year",
"2001"
],
[
"JUMP TOMORROW",
"has_genre",
"COMEDY"
],
[
"JUMP TOMORROW",
"release_year",
"2001"
],
[
"JUST VISITING",
"has_genre",
"COMEDY"
],
[
"JUST VISITING",
"release_year",
"2001"
],
[
"KINGDOM COME",
"has_genre",
"COMEDY"
],
[
"KINGDOM COME",
"release_year",
"2001"
],
[
"KISSING JESSICA STEIN",
"has_genre",
"COMEDY"
],
[
"KISSING JESSICA STEIN",
"release_year",
"2001"
],
[
"LEGALLY BLONDE",
"has_genre",
"COMEDY"
],
[
"LEGALLY BLONDE",
"has_tags",
"COMEDY"
],
[
"LEGALLY BLONDE",
"release_year",
"2001"
],
[
"LITTLE SECRETS",
"has_genre",
"COMEDY"
],
[
"LITTLE SECRETS",
"release_year",
"2001"
],
[
"LUCKY BREAK",
"has_genre",
"COMEDY"
],
[
"LUCKY BREAK",
"release_year",
"2001"
],
[
"LUV",
"has_genre",
"COMEDY"
],
[
"LUV",
"has_genre",
"CRIME"
],
[
"MADE",
"has_genre",
"COMEDY"
],
[
"MADE",
"has_genre",
"CRIME"
],
[
"MADE",
"release_year",
"2001"
],
[
"MAN BITES DOG",
"has_genre",
"COMEDY"
],
[
"MAN BITES DOG",
"has_genre",
"CRIME"
],
[
"MAX KEEBLE'S BIG MOVE",
"has_genre",
"COMEDY"
],
[
"MAX KEEBLE'S BIG MOVE",
"release_year",
"2001"
],
[
"MEAN MACHINE",
"has_genre",
"COMEDY"
],
[
"MEAN MACHINE",
"release_year",
"2001"
],
[
"MONKEYBONE",
"has_genre",
"COMEDY"
],
[
"MONKEYBONE",
"release_year",
"2001"
],
[
"MONSTERS, INC.",
"has_genre",
"COMEDY"
],
[
"MONSTERS, INC.",
"has_tags",
"COMEDY"
],
[
"MONSTERS, INC.",
"release_year",
"2001"
],
[
"MOSTLY MARTHA",
"has_genre",
"COMEDY"
],
[
"MOSTLY MARTHA",
"release_year",
"2001"
],
[
"MY KINGDOM",
"has_genre",
"CRIME"
],
[
"MY KINGDOM",
"release_year",
"2001"
],
[
"MY LIFE WITHOUT ME",
"has_genre",
"DRAMA"
],
[
"MY LIFE WITHOUT ME",
"written_by",
"NANCI KINCAID"
],
[
"NOBODY'S BABY",
"has_genre",
"COMEDY"
],
[
"NOBODY'S BABY",
"release_year",
"2001"
],
[
"NOT ANOTHER TEEN MOVIE",
"has_genre",
"COMEDY"
],
[
"NOT ANOTHER TEEN MOVIE",
"release_year",
"2001"
],
[
"NOVOCAINE",
"has_genre",
"COMEDY"
],
[
"NOVOCAINE",
"release_year",
"2001"
],
[
"OCEAN'S ELEVEN",
"has_tags",
"COMEDY"
],
[
"OCEAN'S ELEVEN",
"release_year",
"2001"
],
[
"ON THE LINE",
"has_genre",
"COMEDY"
],
[
"ON THE LINE",
"release_year",
"2001"
],
[
"ONE MAN UP",
"has_genre",
"COMEDY"
],
[
"ONE MAN UP",
"release_year",
"2001"
],
[
"ONE NIGHT AT MCCOOL'S",
"has_genre",
"COMEDY"
],
[
"ONE NIGHT AT MCCOOL'S",
"has_genre",
"CRIME"
],
[
"ONE NIGHT AT MCCOOL'S",
"release_year",
"2001"
],
[
"PAULETTE",
"has_genre",
"COMEDY"
],
[
"PAULETTE",
"has_genre",
"CRIME"
],
[
"PAULINE AND PAULETTE",
"has_genre",
"COMEDY"
],
[
"PAULINE AND PAULETTE",
"release_year",
"2001"
],
[
"PONTEROSA",
"has_genre",
"COMEDY"
],
[
"PONTEROSA",
"has_tags",
"COMEDY"
],
[
"PONTEROSA",
"release_year",
"2001"
],
[
"POOTIE TANG",
"has_genre",
"COMEDY"
],
[
"POOTIE TANG",
"release_year",
"2001"
],
[
"RARE BIRDS",
"has_genre",
"COMEDY"
],
[
"RARE BIRDS",
"release_year",
"2001"
],
[
"RAT RACE",
"has_genre",
"COMEDY"
],
[
"RAT RACE",
"has_tags",
"COMEDY"
],
[
"RAT RACE",
"release_year",
"2001"
],
[
"ROCK STAR",
"has_genre",
"COMEDY"
],
[
"ROCK STAR",
"release_year",
"2001"
],
[
"RUNNING SCARED",
"has_genre",
"COMEDY"
],
[
"RUNNING SCARED",
"has_genre",
"CRIME"
],
[
"RUSH HOUR 2",
"has_genre",
"COMEDY"
],
[
"RUSH HOUR 2",
"has_tags",
"COMEDY"
],
[
"RUSH HOUR 2",
"release_year",
"2001"
],
[
"SAVING SILVERMAN",
"has_genre",
"COMEDY"
],
[
"SAVING SILVERMAN",
"has_tags",
"COMEDY"
],
[
"SAVING SILVERMAN",
"release_year",
"2001"
],
[
"SAY IT ISN'T SO",
"has_genre",
"COMEDY"
],
[
"SAY IT ISN'T SO",
"release_year",
"2001"
],
[
"SERENDIPITY",
"has_genre",
"COMEDY"
],
[
"SERENDIPITY",
"release_year",
"2001"
],
[
"SHALLOW HAL",
"has_genre",
"COMEDY"
],
[
"SHALLOW HAL",
"release_year",
"2001"
],
[
"SHAOLIN SOCCER",
"has_genre",
"COMEDY"
],
[
"SHAOLIN SOCCER",
"release_year",
"2001"
],
[
"SHREK",
"has_genre",
"COMEDY"
],
[
"SHREK",
"has_tags",
"COMEDY"
],
[
"SHREK",
"release_year",
"2001"
],
[
"SIDEWALKS OF NEW YORK",
"has_genre",
"COMEDY"
],
[
"SIDEWALKS OF NEW YORK",
"release_year",
"2001"
],
[
"SON OF THE BRIDE",
"has_genre",
"COMEDY"
],
[
"SON OF THE BRIDE",
"release_year",
"2001"
],
[
"SPEAKING OF SEX",
"has_genre",
"COMEDY"
],
[
"SPEAKING OF SEX",
"release_year",
"2001"
],
[
"SPUN",
"has_genre",
"COMEDY"
],
[
"SPUN",
"has_genre",
"CRIME"
],
[
"STORYTELLING",
"has_genre",
"COMEDY"
],
[
"STORYTELLING",
"release_year",
"2001"
],
[
"SUMMER CATCH",
"has_genre",
"COMEDY"
],
[
"SUMMER CATCH",
"release_year",
"2001"
],
[
"SUPER TROOPERS",
"has_genre",
"COMEDY"
],
[
"SUPER TROOPERS",
"has_tags",
"COMEDY"
],
[
"SUPER TROOPERS",
"release_year",
"2001"
],
[
"SWEET NOVEMBER",
"has_genre",
"COMEDY"
],
[
"SWEET NOVEMBER",
"release_year",
"2001"
],
[
"SWORDFISH",
"has_genre",
"CRIME"
],
[
"SWORDFISH",
"release_year",
"2001"
],
[
"TANGUY",
"has_genre",
"COMEDY"
],
[
"TANGUY",
"release_year",
"2001"
],
[
"THE ANIMAL",
"has_genre",
"COMEDY"
],
[
"THE ANIMAL",
"release_year",
"2001"
],
[
"THE ANNIVERSARY PARTY",
"has_genre",
"COMEDY"
],
[
"THE ANNIVERSARY PARTY",
"release_year",
"2001"
],
[
"THE BROTHERS",
"has_genre",
"COMEDY"
],
[
"THE BROTHERS",
"release_year",
"2001"
],
[
"THE CAIMAN",
"directed_by",
"NANNI MORETTI"
],
[
"THE CAIMAN",
"has_genre",
"COMEDY"
],
[
"THE CAIMAN",
"has_genre",
"DRAMA"
],
[
"THE CAIMAN",
"in_language",
"ITALIAN"
],
[
"THE CAIMAN",
"written_by",
"NANNI MORETTI"
],
[
"THE CLOSET",
"has_genre",
"COMEDY"
],
[
"THE CLOSET",
"has_tags",
"COMEDY"
],
[
"THE CLOSET",
"release_year",
"2001"
],
[
"THE CURSE OF THE JADE SCORPION",
"has_genre",
"COMEDY"
],
[
"THE CURSE OF THE JADE SCORPION",
"has_genre",
"CRIME"
],
[
"THE CURSE OF THE JADE SCORPION",
"release_year",
"2001"
],
[
"THE FAMILY",
"has_genre",
"COMEDY"
],
[
"THE FAMILY",
"has_genre",
"CRIME"
],
[
"THE FUNERAL",
"has_genre",
"COMEDY"
],
[
"THE FUNERAL",
"has_genre",
"CRIME"
],
[
"THE HAPPINESS OF THE KATAKURIS",
"has_genre",
"COMEDY"
],
[
"THE HAPPINESS OF THE KATAKURIS",
"release_year",
"2001"
],
[
"THE LAST KISS",
"has_genre",
"COMEDY"
],
[
"THE LAST KISS",
"release_year",
"2001"
],
[
"THE MAN",
"has_genre",
"COMEDY"
],
[
"THE MAN",
"has_genre",
"CRIME"
],
[
"THE MAN",
"has_tags",
"COMEDY"
],
[
"THE MAN WHO SUED GOD",
"has_genre",
"COMEDY"
],
[
"THE MAN WHO SUED GOD",
"release_year",
"2001"
],
[
"THE MEXICAN",
"has_genre",
"COMEDY"
],
[
"THE MEXICAN",
"has_tags",
"COMEDY"
],
[
"THE MEXICAN",
"release_year",
"2001"
],
[
"THE PRINCESS DIARIES",
"has_genre",
"COMEDY"
],
[
"THE PRINCESS DIARIES",
"has_tags",
"COMEDY"
],
[
"THE PRINCESS DIARIES",
"release_year",
"2001"
],
[
"THE QUICKIE",
"has_genre",
"CRIME"
],
[
"THE QUICKIE",
"release_year",
"2001"
],
[
"THE ROYAL TENENBAUMS",
"has_genre",
"COMEDY"
],
[
"THE ROYAL TENENBAUMS",
"has_tags",
"COMEDY"
],
[
"THE ROYAL TENENBAUMS",
"release_year",
"2001"
],
[
"THE SCORE",
"has_genre",
"CRIME"
],
[
"THE SCORE",
"release_year",
"2001"
],
[
"THE SHRINK IS IN",
"has_genre",
"COMEDY"
],
[
"THE SHRINK IS IN",
"release_year",
"2001"
],
[
"THE SON'S ROOM",
"directed_by",
"NANNI MORETTI"
],
[
"THE SON'S ROOM",
"has_tags",
"NANNI MORETTI"
],
[
"THE SON'S ROOM",
"in_language",
"ITALIAN"
],
[
"THE SON'S ROOM",
"release_year",
"2001"
],
[
"THE SON'S ROOM",
"starred_actors",
"NANNI MORETTI"
],
[
"THE SON'S ROOM",
"written_by",
"NANNI MORETTI"
],
[
"THE SWINDLE",
"has_genre",
"COMEDY"
],
[
"THE SWINDLE",
"has_genre",
"CRIME"
],
[
"THE TRIUMPH OF LOVE",
"has_genre",
"COMEDY"
],
[
"THE TRIUMPH OF LOVE",
"release_year",
"2001"
],
[
"THE WEDDING PLANNER",
"has_genre",
"COMEDY"
],
[
"THE WEDDING PLANNER",
"release_year",
"2001"
],
[
"TO DIE FOR",
"has_genre",
"COMEDY"
],
[
"TO DIE FOR",
"has_genre",
"CRIME"
],
[
"TOMCATS",
"has_genre",
"COMEDY"
],
[
"TOMCATS",
"release_year",
"2001"
],
[
"TORTILLA SOUP",
"has_genre",
"COMEDY"
],
[
"TORTILLA SOUP",
"release_year",
"2001"
],
[
"TOUGH GUYS DON'T DANCE",
"has_genre",
"COMEDY"
],
[
"TOUGH GUYS DON'T DANCE",
"has_genre",
"CRIME"
],
[
"TRAINING DAY",
"has_genre",
"CRIME"
],
[
"TRAINING DAY",
"release_year",
"2001"
],
[
"TWO CAN PLAY THAT GAME",
"has_genre",
"COMEDY"
],
[
"TWO CAN PLAY THAT GAME",
"release_year",
"2001"
],
[
"VERY ANNIE MARY",
"has_genre",
"COMEDY"
],
[
"VERY ANNIE MARY",
"release_year",
"2001"
],
[
"VISITOR Q",
"has_genre",
"COMEDY"
],
[
"VISITOR Q",
"release_year",
"2001"
],
[
"VIZONTELE",
"has_genre",
"COMEDY"
],
[
"VIZONTELE",
"has_tags",
"COMEDY"
],
[
"VIZONTELE",
"release_year",
"2001"
],
[
"WASABI",
"has_genre",
"COMEDY"
],
[
"WASABI",
"has_tags",
"COMEDY"
],
[
"WASABI",
"release_year",
"2001"
],
[
"WATERBOYS",
"has_genre",
"COMEDY"
],
[
"WATERBOYS",
"release_year",
"2001"
],
[
"WE HAVE A POPE",
"directed_by",
"NANNI MORETTI"
],
[
"WE HAVE A POPE",
"has_genre",
"COMEDY"
],
[
"WE HAVE A POPE",
"has_genre",
"DRAMA"
],
[
"WE HAVE A POPE",
"has_tags",
"COMEDY"
],
[
"WE HAVE A POPE",
"has_tags",
"ITALIAN"
],
[
"WE HAVE A POPE",
"in_language",
"ITALIAN"
],
[
"WE HAVE A POPE",
"written_by",
"NANNI MORETTI"
],
[
"WET HOT AMERICAN SUMMER",
"has_genre",
"COMEDY"
],
[
"WET HOT AMERICAN SUMMER",
"release_year",
"2001"
],
[
"WHAT'S THE WORST THAT COULD HAPPEN?",
"has_genre",
"COMEDY"
],
[
"WHAT'S THE WORST THAT COULD HAPPEN?",
"release_year",
"2001"
],
[
"WHO IS CLETIS TOUT?",
"has_genre",
"COMEDY"
],
[
"WHO IS CLETIS TOUT?",
"has_genre",
"CRIME"
],
[
"WHO IS CLETIS TOUT?",
"release_year",
"2001"
],
[
"ZOOLANDER",
"has_genre",
"COMEDY"
],
[
"ZOOLANDER",
"has_tags",
"COMEDY"
],
[
"ZOOLANDER",
"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
17480, 1988
27261, 2009
30146, A CHRISTMAS CAROL
23490, ADRIAN MITCHELL
4763, ADVENTURE
16054, ADVENTURES IN BABYSITTING
10341, ADVENTURES OF DON JUAN
16831, ALADIN
38021, ALICE
29638, ALICE IN WONDERLAND
17157, ARABIAN NIGHTS
4017, ARIEL
10045, BD-R
38657, BEAT THE DEVIL
15771, BENGAZI
11779, BIG TOP PEE-WEE
18599, BILOXI BLUES
1040, CAPTAIN BLOOD
7646, D.O.A.
21286, DAVID COPPERFIELD
8381, DETOUR
5881, ELEPHANT BOY
26308, FLIPPER
34657, FROM TIME TO TIME
31198, GIALLO
17384, GUNGA DIN
4830, HALLOWEEN
20941, HAMLET
12087, HOWL'S MOVING CASTLE
36299, IT'S THE GREAT PUMPKIN, CHARLIE BROWN
7539, IVANHOE
847, JACK THE GIANT KILLER
20567, JOHN CARTER
35705, JOURNEY TO THE CENTER OF THE EARTH
38986, JUNGLE BOOK
19098, KING KONG
14156, KING SOLOMON'S MINES
37100, KNIGHTS OF THE ROUND TABLE
36940, LABYRINTH
25097, LAND OF THE LOST
30029, LAWRENCE OF ARABIA
33160, LITTLE DORRIT
37435, MAC AND ME
20579, MARAT/SADE
17189, NIGHT OF THE DEMONS
32358, NORTH
1994, NOTORIOUS
14797, O BROTHER, WHERE ART THOU?
27496, ONE MILLION YEARS B.C.
15651, PREHISTORIC WOMEN
24066, REEL INJUN
15873, ROBIN AND MARIAN
35586, SAHARA
5629, SCOOBY-DOO! THE MYSTERY BEGINS
27626, SHEENA
31316, SHERLOCK HOLMES AND THE SECRET WEAPON
11262, SHOOT TO KILL
4314, SOLOMON KANE
34989, STAR TREK
15194, STORY OF WOMEN
21003, TANNER HALL
20121, TAPEHEADS
11699, TARZAN THE APE MAN
18715, TARZAN'S NEW YORK ADVENTURE
2584, THE ADVENTURES OF BARON MUNCHAUSEN
21608, THE ADVENTURES OF HUCKLEBERRY FINN
3354, THE BROTHERS GRIMM
7639, THE CHARGE OF THE LIGHT BRIGADE
21330, THE CRIMSON PIRATE
16800, THE DECEIVERS
38631, THE FLAME AND THE ARROW
11635, THE FOUR FEATHERS
9166, THE GUNS OF NAVARONE
15754, THE LAND BEFORE TIME
32231, THE LAND THAT TIME FORGOT
29109, THE LODGER
4182, THE MAN IN THE IRON MASK
13295, THE MARK OF ZORRO
4029, THE MASK OF FU MANCHU
2432, THE MASTER OF BALLANTRAE
26820, THE MUMMY
26460, THE NEW ADVENTURES OF PIPPI LONGSTOCKING
5575, THE PEOPLE THAT TIME FORGOT
24512, THE PHANTOM TOLLBOOTH
22486, THE PRINCE AND THE PAUPER
31851, THE PRISONER OF ZENDA
8477, THE SCARLET PIMPERNEL
30746, THE SECRET LIFE OF WALTER MITTY
31647, THE SON OF THE SHEIK
7816, THE THREE MUSKETEERS
983, THE TREASURE OF THE SIERRA MADRE
17568, THE VANISHING
12308, THE VIKINGS
27609, THE WIND AND THE LION
27963, THEY LIVE
24789, TO HAVE AND HAVE NOT
25443, TOM JONES
6724, TOM SAWYER
37876, TROMA'S WAR
2902, TRUE HEART
5574, UP
38723, VIBES
11659, VIVA MARIA!
src, edge_attr, dst
30146, has_tags, 10045
30146, release_year, 27261
16054, has_genre, 4763
16054, has_tags, 4763
16054, has_tags, 10045
10341, has_genre, 4763
10341, has_tags, 10045
16831, has_genre, 4763
16831, release_year, 27261
38021, has_genre, 4763
38021, release_year, 17480
29638, has_genre, 4763
29638, has_tags, 10045
17157, has_genre, 4763
17157, has_tags, 10045
4017, has_tags, 10045
4017, release_year, 17480
38657, has_genre, 4763
38657, has_tags, 10045
15771, has_genre, 4763
15771, has_tags, 10045
11779, has_genre, 4763
11779, release_year, 17480
18599, has_tags, 10045
18599, release_year, 17480
1040, has_genre, 4763
1040, has_tags, 4763
1040, has_tags, 10045
7646, has_tags, 10045
7646, release_year, 17480
21286, has_genre, 4763
21286, has_tags, 10045
8381, has_tags, 10045
8381, release_year, 27261
5881, has_genre, 4763
5881, has_tags, 10045
26308, has_genre, 4763
26308, has_tags, 10045
34657, has_genre, 4763
34657, release_year, 27261
31198, has_tags, 10045
31198, release_year, 27261
17384, has_genre, 4763
17384, has_tags, 10045
4830, has_tags, 4830
20941, has_tags, 10045
20941, release_year, 27261
12087, has_genre, 4763
12087, has_tags, 4763
12087, has_tags, 10045
36299, has_tags, 10045
36299, has_tags, 4830
7539, has_genre, 4763
7539, has_tags, 10045
847, has_genre, 4763
847, has_tags, 10045
20567, has_genre, 4763
20567, has_tags, 10045
35705, has_genre, 4763
35705, has_tags, 4763
35705, has_tags, 10045
38986, has_genre, 4763
38986, has_tags, 10045
19098, has_genre, 4763
19098, has_tags, 4763
19098, has_tags, 10045
14156, has_genre, 4763
14156, has_tags, 4763
14156, has_tags, 10045
37100, has_genre, 4763
37100, has_tags, 10045
36940, has_genre, 4763
36940, has_tags, 4763
36940, has_tags, 10045
25097, has_genre, 4763
25097, release_year, 27261
30029, has_genre, 4763
30029, has_tags, 10045
33160, has_tags, 10045
33160, release_year, 17480
37435, has_genre, 4763
37435, release_year, 17480
20579, has_tags, 10045
20579, written_by, 23490
17189, has_tags, 10045
17189, has_tags, 4830
17189, release_year, 17480
17189, release_year, 27261
32358, has_genre, 4763
32358, release_year, 27261
1994, has_tags, 10045
1994, release_year, 27261
14797, has_genre, 4763
14797, has_tags, 4763
14797, has_tags, 10045
27496, has_genre, 4763
27496, has_tags, 10045
15651, has_genre, 4763
15651, has_tags, 10045
24066, has_tags, 10045
24066, release_year, 27261
15873, has_genre, 4763
15873, has_tags, 10045
35586, has_genre, 4763
35586, has_tags, 10045
5629, has_genre, 4763
5629, release_year, 27261
27626, has_genre, 4763
27626, has_tags, 10045
31316, has_genre, 4763
31316, has_tags, 10045
11262, has_genre, 4763
11262, release_year, 17480
4314, has_genre, 4763
4314, release_year, 27261
34989, has_genre, 4763
34989, has_tags, 4763
34989, release_year, 27261
15194, has_tags, 10045
15194, release_year, 17480
21003, has_tags, 10045
21003, release_year, 27261
20121, has_tags, 10045
20121, release_year, 17480
11699, has_genre, 4763
11699, has_tags, 10045
18715, has_genre, 4763
18715, has_tags, 10045
2584, has_genre, 4763
2584, release_year, 17480
21608, has_genre, 4763
21608, has_tags, 10045
3354, has_genre, 4763
3354, has_tags, 4763
3354, has_tags, 10045
7639, has_genre, 4763
7639, has_tags, 10045
21330, has_genre, 4763
21330, has_tags, 10045
16800, has_genre, 4763
16800, has_tags, 10045
16800, release_year, 17480
38631, has_genre, 4763
38631, has_tags, 10045
11635, has_genre, 4763
11635, has_tags, 10045
9166, has_genre, 4763
9166, has_tags, 10045
15754, has_genre, 4763
15754, release_year, 17480
32231, has_genre, 4763
32231, has_tags, 4763
32231, has_tags, 10045
29109, has_tags, 10045
29109, release_year, 27261
4182, has_genre, 4763
4182, has_tags, 4763
4182, has_tags, 10045
13295, has_genre, 4763
13295, has_tags, 10045
4029, has_genre, 4763
4029, has_tags, 10045
2432, has_genre, 4763
2432, has_tags, 10045
26820, has_genre, 4763
26820, has_tags, 4763
26820, has_tags, 10045
26460, has_genre, 4763
26460, release_year, 17480
5575, has_genre, 4763
5575, has_tags, 10045
24512, has_genre, 4763
24512, has_tags, 10045
22486, has_genre, 4763
22486, has_tags, 10045
31851, has_genre, 4763
31851, has_tags, 10045
8477, has_genre, 4763
8477, has_tags, 10045
30746, has_genre, 4763
30746, has_tags, 10045
31647, has_genre, 4763
31647, has_tags, 10045
7816, has_genre, 4763
7816, has_tags, 10045
983, has_genre, 4763
983, has_tags, 10045
17568, has_tags, 10045
17568, release_year, 17480
12308, has_genre, 4763
12308, has_tags, 10045
27609, has_genre, 4763
27609, has_tags, 10045
27963, has_tags, 10045
27963, release_year, 17480
24789, has_genre, 4763
24789, has_tags, 10045
25443, has_genre, 4763
25443, has_tags, 10045
6724, has_genre, 4763
6724, has_tags, 10045
37876, has_genre, 4763
37876, release_year, 17480
2902, has_genre, 4763
5574, has_genre, 4763
5574, has_tags, 4763
5574, release_year, 27261
38723, has_genre, 4763
38723, release_year, 17480
11659, has_genre, 4763
11659, has_tags, 10045
Question: In what context are ADRIAN MITCHELL, NIGHT OF THE DEMONS, and TRUE HEART connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"ADRIAN MITCHELL",
"NIGHT OF THE DEMONS",
"TRUE HEART"
],
"valid_edges": [
[
"A CHRISTMAS CAROL",
"has_tags",
"BD-R"
],
[
"A CHRISTMAS CAROL",
"release_year",
"2009"
],
[
"ADVENTURES IN BABYSITTING",
"has_genre",
"ADVENTURE"
],
[
"ADVENTURES IN BABYSITTING",
"has_tags",
"ADVENTURE"
],
[
"ADVENTURES IN BABYSITTING",
"has_tags",
"BD-R"
],
[
"ADVENTURES OF DON JUAN",
"has_genre",
"ADVENTURE"
],
[
"ADVENTURES OF DON JUAN",
"has_tags",
"BD-R"
],
[
"ALADIN",
"has_genre",
"ADVENTURE"
],
[
"ALADIN",
"release_year",
"2009"
],
[
"ALICE",
"has_genre",
"ADVENTURE"
],
[
"ALICE",
"release_year",
"1988"
],
[
"ALICE IN WONDERLAND",
"has_genre",
"ADVENTURE"
],
[
"ALICE IN WONDERLAND",
"has_tags",
"BD-R"
],
[
"ARABIAN NIGHTS",
"has_genre",
"ADVENTURE"
],
[
"ARABIAN NIGHTS",
"has_tags",
"BD-R"
],
[
"ARIEL",
"has_tags",
"BD-R"
],
[
"ARIEL",
"release_year",
"1988"
],
[
"BEAT THE DEVIL",
"has_genre",
"ADVENTURE"
],
[
"BEAT THE DEVIL",
"has_tags",
"BD-R"
],
[
"BENGAZI",
"has_genre",
"ADVENTURE"
],
[
"BENGAZI",
"has_tags",
"BD-R"
],
[
"BIG TOP PEE-WEE",
"has_genre",
"ADVENTURE"
],
[
"BIG TOP PEE-WEE",
"release_year",
"1988"
],
[
"BILOXI BLUES",
"has_tags",
"BD-R"
],
[
"BILOXI BLUES",
"release_year",
"1988"
],
[
"CAPTAIN BLOOD",
"has_genre",
"ADVENTURE"
],
[
"CAPTAIN BLOOD",
"has_tags",
"ADVENTURE"
],
[
"CAPTAIN BLOOD",
"has_tags",
"BD-R"
],
[
"D.O.A.",
"has_tags",
"BD-R"
],
[
"D.O.A.",
"release_year",
"1988"
],
[
"DAVID COPPERFIELD",
"has_genre",
"ADVENTURE"
],
[
"DAVID COPPERFIELD",
"has_tags",
"BD-R"
],
[
"DETOUR",
"has_tags",
"BD-R"
],
[
"DETOUR",
"release_year",
"2009"
],
[
"ELEPHANT BOY",
"has_genre",
"ADVENTURE"
],
[
"ELEPHANT BOY",
"has_tags",
"BD-R"
],
[
"FLIPPER",
"has_genre",
"ADVENTURE"
],
[
"FLIPPER",
"has_tags",
"BD-R"
],
[
"FROM TIME TO TIME",
"has_genre",
"ADVENTURE"
],
[
"FROM TIME TO TIME",
"release_year",
"2009"
],
[
"GIALLO",
"has_tags",
"BD-R"
],
[
"GIALLO",
"release_year",
"2009"
],
[
"GUNGA DIN",
"has_genre",
"ADVENTURE"
],
[
"GUNGA DIN",
"has_tags",
"BD-R"
],
[
"HALLOWEEN",
"has_tags",
"HALLOWEEN"
],
[
"HAMLET",
"has_tags",
"BD-R"
],
[
"HAMLET",
"release_year",
"2009"
],
[
"HOWL'S MOVING CASTLE",
"has_genre",
"ADVENTURE"
],
[
"HOWL'S MOVING CASTLE",
"has_tags",
"ADVENTURE"
],
[
"HOWL'S MOVING CASTLE",
"has_tags",
"BD-R"
],
[
"IT'S THE GREAT PUMPKIN, CHARLIE BROWN",
"has_tags",
"BD-R"
],
[
"IT'S THE GREAT PUMPKIN, CHARLIE BROWN",
"has_tags",
"HALLOWEEN"
],
[
"IVANHOE",
"has_genre",
"ADVENTURE"
],
[
"IVANHOE",
"has_tags",
"BD-R"
],
[
"JACK THE GIANT KILLER",
"has_genre",
"ADVENTURE"
],
[
"JACK THE GIANT KILLER",
"has_tags",
"BD-R"
],
[
"JOHN CARTER",
"has_genre",
"ADVENTURE"
],
[
"JOHN CARTER",
"has_tags",
"BD-R"
],
[
"JOURNEY TO THE CENTER OF THE EARTH",
"has_genre",
"ADVENTURE"
],
[
"JOURNEY TO THE CENTER OF THE EARTH",
"has_tags",
"ADVENTURE"
],
[
"JOURNEY TO THE CENTER OF THE EARTH",
"has_tags",
"BD-R"
],
[
"JUNGLE BOOK",
"has_genre",
"ADVENTURE"
],
[
"JUNGLE BOOK",
"has_tags",
"BD-R"
],
[
"KING KONG",
"has_genre",
"ADVENTURE"
],
[
"KING KONG",
"has_tags",
"ADVENTURE"
],
[
"KING KONG",
"has_tags",
"BD-R"
],
[
"KING SOLOMON'S MINES",
"has_genre",
"ADVENTURE"
],
[
"KING SOLOMON'S MINES",
"has_tags",
"ADVENTURE"
],
[
"KING SOLOMON'S MINES",
"has_tags",
"BD-R"
],
[
"KNIGHTS OF THE ROUND TABLE",
"has_genre",
"ADVENTURE"
],
[
"KNIGHTS OF THE ROUND TABLE",
"has_tags",
"BD-R"
],
[
"LABYRINTH",
"has_genre",
"ADVENTURE"
],
[
"LABYRINTH",
"has_tags",
"ADVENTURE"
],
[
"LABYRINTH",
"has_tags",
"BD-R"
],
[
"LAND OF THE LOST",
"has_genre",
"ADVENTURE"
],
[
"LAND OF THE LOST",
"release_year",
"2009"
],
[
"LAWRENCE OF ARABIA",
"has_genre",
"ADVENTURE"
],
[
"LAWRENCE OF ARABIA",
"has_tags",
"BD-R"
],
[
"LITTLE DORRIT",
"has_tags",
"BD-R"
],
[
"LITTLE DORRIT",
"release_year",
"1988"
],
[
"MAC AND ME",
"has_genre",
"ADVENTURE"
],
[
"MAC AND ME",
"release_year",
"1988"
],
[
"MARAT/SADE",
"has_tags",
"BD-R"
],
[
"MARAT/SADE",
"written_by",
"ADRIAN MITCHELL"
],
[
"NIGHT OF THE DEMONS",
"has_tags",
"BD-R"
],
[
"NIGHT OF THE DEMONS",
"has_tags",
"HALLOWEEN"
],
[
"NIGHT OF THE DEMONS",
"release_year",
"1988"
],
[
"NIGHT OF THE DEMONS",
"release_year",
"2009"
],
[
"NORTH",
"has_genre",
"ADVENTURE"
],
[
"NORTH",
"release_year",
"2009"
],
[
"NOTORIOUS",
"has_tags",
"BD-R"
],
[
"NOTORIOUS",
"release_year",
"2009"
],
[
"O BROTHER, WHERE ART THOU?",
"has_genre",
"ADVENTURE"
],
[
"O BROTHER, WHERE ART THOU?",
"has_tags",
"ADVENTURE"
],
[
"O BROTHER, WHERE ART THOU?",
"has_tags",
"BD-R"
],
[
"ONE MILLION YEARS B.C.",
"has_genre",
"ADVENTURE"
],
[
"ONE MILLION YEARS B.C.",
"has_tags",
"BD-R"
],
[
"PREHISTORIC WOMEN",
"has_genre",
"ADVENTURE"
],
[
"PREHISTORIC WOMEN",
"has_tags",
"BD-R"
],
[
"REEL INJUN",
"has_tags",
"BD-R"
],
[
"REEL INJUN",
"release_year",
"2009"
],
[
"ROBIN AND MARIAN",
"has_genre",
"ADVENTURE"
],
[
"ROBIN AND MARIAN",
"has_tags",
"BD-R"
],
[
"SAHARA",
"has_genre",
"ADVENTURE"
],
[
"SAHARA",
"has_tags",
"BD-R"
],
[
"SCOOBY-DOO! THE MYSTERY BEGINS",
"has_genre",
"ADVENTURE"
],
[
"SCOOBY-DOO! THE MYSTERY BEGINS",
"release_year",
"2009"
],
[
"SHEENA",
"has_genre",
"ADVENTURE"
],
[
"SHEENA",
"has_tags",
"BD-R"
],
[
"SHERLOCK HOLMES AND THE SECRET WEAPON",
"has_genre",
"ADVENTURE"
],
[
"SHERLOCK HOLMES AND THE SECRET WEAPON",
"has_tags",
"BD-R"
],
[
"SHOOT TO KILL",
"has_genre",
"ADVENTURE"
],
[
"SHOOT TO KILL",
"release_year",
"1988"
],
[
"SOLOMON KANE",
"has_genre",
"ADVENTURE"
],
[
"SOLOMON KANE",
"release_year",
"2009"
],
[
"STAR TREK",
"has_genre",
"ADVENTURE"
],
[
"STAR TREK",
"has_tags",
"ADVENTURE"
],
[
"STAR TREK",
"release_year",
"2009"
],
[
"STORY OF WOMEN",
"has_tags",
"BD-R"
],
[
"STORY OF WOMEN",
"release_year",
"1988"
],
[
"TANNER HALL",
"has_tags",
"BD-R"
],
[
"TANNER HALL",
"release_year",
"2009"
],
[
"TAPEHEADS",
"has_tags",
"BD-R"
],
[
"TAPEHEADS",
"release_year",
"1988"
],
[
"TARZAN THE APE MAN",
"has_genre",
"ADVENTURE"
],
[
"TARZAN THE APE MAN",
"has_tags",
"BD-R"
],
[
"TARZAN'S NEW YORK ADVENTURE",
"has_genre",
"ADVENTURE"
],
[
"TARZAN'S NEW YORK ADVENTURE",
"has_tags",
"BD-R"
],
[
"THE ADVENTURES OF BARON MUNCHAUSEN",
"has_genre",
"ADVENTURE"
],
[
"THE ADVENTURES OF BARON MUNCHAUSEN",
"release_year",
"1988"
],
[
"THE ADVENTURES OF HUCKLEBERRY FINN",
"has_genre",
"ADVENTURE"
],
[
"THE ADVENTURES OF HUCKLEBERRY FINN",
"has_tags",
"BD-R"
],
[
"THE BROTHERS GRIMM",
"has_genre",
"ADVENTURE"
],
[
"THE BROTHERS GRIMM",
"has_tags",
"ADVENTURE"
],
[
"THE BROTHERS GRIMM",
"has_tags",
"BD-R"
],
[
"THE CHARGE OF THE LIGHT BRIGADE",
"has_genre",
"ADVENTURE"
],
[
"THE CHARGE OF THE LIGHT BRIGADE",
"has_tags",
"BD-R"
],
[
"THE CRIMSON PIRATE",
"has_genre",
"ADVENTURE"
],
[
"THE CRIMSON PIRATE",
"has_tags",
"BD-R"
],
[
"THE DECEIVERS",
"has_genre",
"ADVENTURE"
],
[
"THE DECEIVERS",
"has_tags",
"BD-R"
],
[
"THE DECEIVERS",
"release_year",
"1988"
],
[
"THE FLAME AND THE ARROW",
"has_genre",
"ADVENTURE"
],
[
"THE FLAME AND THE ARROW",
"has_tags",
"BD-R"
],
[
"THE FOUR FEATHERS",
"has_genre",
"ADVENTURE"
],
[
"THE FOUR FEATHERS",
"has_tags",
"BD-R"
],
[
"THE GUNS OF NAVARONE",
"has_genre",
"ADVENTURE"
],
[
"THE GUNS OF NAVARONE",
"has_tags",
"BD-R"
],
[
"THE LAND BEFORE TIME",
"has_genre",
"ADVENTURE"
],
[
"THE LAND BEFORE TIME",
"release_year",
"1988"
],
[
"THE LAND THAT TIME FORGOT",
"has_genre",
"ADVENTURE"
],
[
"THE LAND THAT TIME FORGOT",
"has_tags",
"ADVENTURE"
],
[
"THE LAND THAT TIME FORGOT",
"has_tags",
"BD-R"
],
[
"THE LODGER",
"has_tags",
"BD-R"
],
[
"THE LODGER",
"release_year",
"2009"
],
[
"THE MAN IN THE IRON MASK",
"has_genre",
"ADVENTURE"
],
[
"THE MAN IN THE IRON MASK",
"has_tags",
"ADVENTURE"
],
[
"THE MAN IN THE IRON MASK",
"has_tags",
"BD-R"
],
[
"THE MARK OF ZORRO",
"has_genre",
"ADVENTURE"
],
[
"THE MARK OF ZORRO",
"has_tags",
"BD-R"
],
[
"THE MASK OF FU MANCHU",
"has_genre",
"ADVENTURE"
],
[
"THE MASK OF FU MANCHU",
"has_tags",
"BD-R"
],
[
"THE MASTER OF BALLANTRAE",
"has_genre",
"ADVENTURE"
],
[
"THE MASTER OF BALLANTRAE",
"has_tags",
"BD-R"
],
[
"THE MUMMY",
"has_genre",
"ADVENTURE"
],
[
"THE MUMMY",
"has_tags",
"ADVENTURE"
],
[
"THE MUMMY",
"has_tags",
"BD-R"
],
[
"THE NEW ADVENTURES OF PIPPI LONGSTOCKING",
"has_genre",
"ADVENTURE"
],
[
"THE NEW ADVENTURES OF PIPPI LONGSTOCKING",
"release_year",
"1988"
],
[
"THE PEOPLE THAT TIME FORGOT",
"has_genre",
"ADVENTURE"
],
[
"THE PEOPLE THAT TIME FORGOT",
"has_tags",
"BD-R"
],
[
"THE PHANTOM TOLLBOOTH",
"has_genre",
"ADVENTURE"
],
[
"THE PHANTOM TOLLBOOTH",
"has_tags",
"BD-R"
],
[
"THE PRINCE AND THE PAUPER",
"has_genre",
"ADVENTURE"
],
[
"THE PRINCE AND THE PAUPER",
"has_tags",
"BD-R"
],
[
"THE PRISONER OF ZENDA",
"has_genre",
"ADVENTURE"
],
[
"THE PRISONER OF ZENDA",
"has_tags",
"BD-R"
],
[
"THE SCARLET PIMPERNEL",
"has_genre",
"ADVENTURE"
],
[
"THE SCARLET PIMPERNEL",
"has_tags",
"BD-R"
],
[
"THE SECRET LIFE OF WALTER MITTY",
"has_genre",
"ADVENTURE"
],
[
"THE SECRET LIFE OF WALTER MITTY",
"has_tags",
"BD-R"
],
[
"THE SON OF THE SHEIK",
"has_genre",
"ADVENTURE"
],
[
"THE SON OF THE SHEIK",
"has_tags",
"BD-R"
],
[
"THE THREE MUSKETEERS",
"has_genre",
"ADVENTURE"
],
[
"THE THREE MUSKETEERS",
"has_tags",
"BD-R"
],
[
"THE TREASURE OF THE SIERRA MADRE",
"has_genre",
"ADVENTURE"
],
[
"THE TREASURE OF THE SIERRA MADRE",
"has_tags",
"BD-R"
],
[
"THE VANISHING",
"has_tags",
"BD-R"
],
[
"THE VANISHING",
"release_year",
"1988"
],
[
"THE VIKINGS",
"has_genre",
"ADVENTURE"
],
[
"THE VIKINGS",
"has_tags",
"BD-R"
],
[
"THE WIND AND THE LION",
"has_genre",
"ADVENTURE"
],
[
"THE WIND AND THE LION",
"has_tags",
"BD-R"
],
[
"THEY LIVE",
"has_tags",
"BD-R"
],
[
"THEY LIVE",
"release_year",
"1988"
],
[
"TO HAVE AND HAVE NOT",
"has_genre",
"ADVENTURE"
],
[
"TO HAVE AND HAVE NOT",
"has_tags",
"BD-R"
],
[
"TOM JONES",
"has_genre",
"ADVENTURE"
],
[
"TOM JONES",
"has_tags",
"BD-R"
],
[
"TOM SAWYER",
"has_genre",
"ADVENTURE"
],
[
"TOM SAWYER",
"has_tags",
"BD-R"
],
[
"TROMA'S WAR",
"has_genre",
"ADVENTURE"
],
[
"TROMA'S WAR",
"release_year",
"1988"
],
[
"TRUE HEART",
"has_genre",
"ADVENTURE"
],
[
"UP",
"has_genre",
"ADVENTURE"
],
[
"UP",
"has_tags",
"ADVENTURE"
],
[
"UP",
"release_year",
"2009"
],
[
"VIBES",
"has_genre",
"ADVENTURE"
],
[
"VIBES",
"release_year",
"1988"
],
[
"VIVA MARIA!",
"has_genre",
"ADVENTURE"
],
[
"VIVA MARIA!",
"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
35935, 2002
37484, 2004
39289, ACTION
39085, BILLY ELLIOT
27411, BRIAN COX
12474, DESPERATE MEASURES
2664, GARY LEWIS
7614, JOHN PINETTE
25451, JOSEPH FIENNES
37052, MANHUNTER
13081, R
5766, RUNNING WITH SCISSORS
801, SIMON SEZ
29403, THE BOURNE SUPREMACY
9522, THE ESCAPIST
34842, THE GLIMMER MAN
39950, THE TRIALS OF HENRY KISSINGER
24811, THRILLER
5729, TROY
22214, WAR
src, edge_attr, dst
39085, starred_actors, 2664
12474, has_genre, 39289
12474, starred_actors, 27411
37052, has_genre, 24811
37052, starred_actors, 27411
5766, has_tags, 13081
5766, starred_actors, 27411
5766, starred_actors, 25451
801, has_genre, 39289
801, has_tags, 39289
801, starred_actors, 7614
29403, has_genre, 39289
29403, has_tags, 39289
29403, release_year, 37484
29403, starred_actors, 27411
9522, has_genre, 24811
9522, has_tags, 27411
9522, has_tags, 25451
9522, release_year, 35935
9522, starred_actors, 27411
9522, starred_actors, 2664
9522, starred_actors, 25451
34842, has_genre, 39289
34842, starred_actors, 27411
39950, has_tags, 22214
39950, release_year, 35935
39950, starred_actors, 27411
5729, has_tags, 39289
5729, has_tags, 13081
5729, has_tags, 22214
5729, release_year, 37484
5729, starred_actors, 27411
Question: In what context are BILLY ELLIOT, BRIAN COX, and JOHN PINETTE connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"BILLY ELLIOT",
"BRIAN COX",
"JOHN PINETTE"
],
"valid_edges": [
[
"BILLY ELLIOT",
"starred_actors",
"GARY LEWIS"
],
[
"DESPERATE MEASURES",
"has_genre",
"ACTION"
],
[
"DESPERATE MEASURES",
"starred_actors",
"BRIAN COX"
],
[
"MANHUNTER",
"has_genre",
"THRILLER"
],
[
"MANHUNTER",
"starred_actors",
"BRIAN COX"
],
[
"RUNNING WITH SCISSORS",
"has_tags",
"R"
],
[
"RUNNING WITH SCISSORS",
"starred_actors",
"BRIAN COX"
],
[
"RUNNING WITH SCISSORS",
"starred_actors",
"JOSEPH FIENNES"
],
[
"SIMON SEZ",
"has_genre",
"ACTION"
],
[
"SIMON SEZ",
"has_tags",
"ACTION"
],
[
"SIMON SEZ",
"starred_actors",
"JOHN PINETTE"
],
[
"THE BOURNE SUPREMACY",
"has_genre",
"ACTION"
],
[
"THE BOURNE SUPREMACY",
"has_tags",
"ACTION"
],
[
"THE BOURNE SUPREMACY",
"release_year",
"2004"
],
[
"THE BOURNE SUPREMACY",
"starred_actors",
"BRIAN COX"
],
[
"THE ESCAPIST",
"has_genre",
"THRILLER"
],
[
"THE ESCAPIST",
"has_tags",
"BRIAN COX"
],
[
"THE ESCAPIST",
"has_tags",
"JOSEPH FIENNES"
],
[
"THE ESCAPIST",
"release_year",
"2002"
],
[
"THE ESCAPIST",
"starred_actors",
"BRIAN COX"
],
[
"THE ESCAPIST",
"starred_actors",
"GARY LEWIS"
],
[
"THE ESCAPIST",
"starred_actors",
"JOSEPH FIENNES"
],
[
"THE GLIMMER MAN",
"has_genre",
"ACTION"
],
[
"THE GLIMMER MAN",
"starred_actors",
"BRIAN COX"
],
[
"THE TRIALS OF HENRY KISSINGER",
"has_tags",
"WAR"
],
[
"THE TRIALS OF HENRY KISSINGER",
"release_year",
"2002"
],
[
"THE TRIALS OF HENRY KISSINGER",
"starred_actors",
"BRIAN COX"
],
[
"TROY",
"has_tags",
"ACTION"
],
[
"TROY",
"has_tags",
"R"
],
[
"TROY",
"has_tags",
"WAR"
],
[
"TROY",
"release_year",
"2004"
],
[
"TROY",
"starred_actors",
"BRIAN COX"
]
]
}
|
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
17315, 2007
7918, BROKEDOWN PALACE
18016, CLICK
32863, COLD COMFORT FARM
30463, COMEDY
36212, DRAMA
25109, EMMA
23387, EVERYBODY'S FINE
16427, KATE BECKINSALE
29840, LAUREL CANYON
31377, MUCH ADO ABOUT NOTHING
16867, NORA'S WILL
234, PEARL HARBOR
8379, ROMANCE
30377, SAM ROCKWELL
5880, SERENDIPITY
3826, SNOW ANGELS
6439, THE AVIATOR
9059, THE LAST DAYS OF DISCO
13703, THE LAW OF ENCLOSURES
36860, THE TRIALS OF CATE MCCALL
10238, UNDERWORLD
30621, VACANCY
src, edge_attr, dst
7918, has_genre, 36212
7918, starred_actors, 16427
18016, has_genre, 30463
18016, has_genre, 36212
18016, has_tags, 30463
18016, has_tags, 16427
18016, starred_actors, 16427
32863, has_genre, 30463
32863, starred_actors, 16427
25109, has_genre, 30463
25109, has_genre, 36212
25109, starred_actors, 16427
23387, has_genre, 36212
23387, starred_actors, 16427
23387, starred_actors, 30377
29840, has_genre, 36212
29840, has_tags, 16427
29840, starred_actors, 16427
31377, has_genre, 30463
31377, has_tags, 30463
31377, has_tags, 16427
31377, starred_actors, 16427
16867, has_genre, 36212
234, has_genre, 36212
234, has_genre, 8379
234, has_tags, 36212
234, has_tags, 16427
234, has_tags, 8379
234, starred_actors, 16427
8379, has_genre, 36212
5880, has_genre, 30463
5880, has_tags, 16427
5880, has_tags, 5880
5880, starred_actors, 16427
3826, has_genre, 36212
3826, has_tags, 16427
3826, has_tags, 30377
3826, release_year, 17315
3826, starred_actors, 16427
3826, starred_actors, 30377
6439, has_genre, 36212
6439, has_tags, 36212
6439, has_tags, 16427
6439, starred_actors, 16427
9059, has_genre, 30463
9059, has_genre, 36212
9059, starred_actors, 16427
13703, has_genre, 36212
36860, has_genre, 36212
36860, starred_actors, 16427
10238, has_genre, 30463
10238, has_tags, 16427
10238, starred_actors, 16427
30621, release_year, 17315
30621, starred_actors, 16427
Question: In what context are KATE BECKINSALE, NORA'S WILL, and THE LAW OF ENCLOSURES connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"KATE BECKINSALE",
"NORA'S WILL",
"THE LAW OF ENCLOSURES"
],
"valid_edges": [
[
"BROKEDOWN PALACE",
"has_genre",
"DRAMA"
],
[
"BROKEDOWN PALACE",
"starred_actors",
"KATE BECKINSALE"
],
[
"CLICK",
"has_genre",
"COMEDY"
],
[
"CLICK",
"has_genre",
"DRAMA"
],
[
"CLICK",
"has_tags",
"COMEDY"
],
[
"CLICK",
"has_tags",
"KATE BECKINSALE"
],
[
"CLICK",
"starred_actors",
"KATE BECKINSALE"
],
[
"COLD COMFORT FARM",
"has_genre",
"COMEDY"
],
[
"COLD COMFORT FARM",
"starred_actors",
"KATE BECKINSALE"
],
[
"EMMA",
"has_genre",
"COMEDY"
],
[
"EMMA",
"has_genre",
"DRAMA"
],
[
"EMMA",
"starred_actors",
"KATE BECKINSALE"
],
[
"EVERYBODY'S FINE",
"has_genre",
"DRAMA"
],
[
"EVERYBODY'S FINE",
"starred_actors",
"KATE BECKINSALE"
],
[
"EVERYBODY'S FINE",
"starred_actors",
"SAM ROCKWELL"
],
[
"LAUREL CANYON",
"has_genre",
"DRAMA"
],
[
"LAUREL CANYON",
"has_tags",
"KATE BECKINSALE"
],
[
"LAUREL CANYON",
"starred_actors",
"KATE BECKINSALE"
],
[
"MUCH ADO ABOUT NOTHING",
"has_genre",
"COMEDY"
],
[
"MUCH ADO ABOUT NOTHING",
"has_tags",
"COMEDY"
],
[
"MUCH ADO ABOUT NOTHING",
"has_tags",
"KATE BECKINSALE"
],
[
"MUCH ADO ABOUT NOTHING",
"starred_actors",
"KATE BECKINSALE"
],
[
"NORA'S WILL",
"has_genre",
"DRAMA"
],
[
"PEARL HARBOR",
"has_genre",
"DRAMA"
],
[
"PEARL HARBOR",
"has_genre",
"ROMANCE"
],
[
"PEARL HARBOR",
"has_tags",
"DRAMA"
],
[
"PEARL HARBOR",
"has_tags",
"KATE BECKINSALE"
],
[
"PEARL HARBOR",
"has_tags",
"ROMANCE"
],
[
"PEARL HARBOR",
"starred_actors",
"KATE BECKINSALE"
],
[
"ROMANCE",
"has_genre",
"DRAMA"
],
[
"SERENDIPITY",
"has_genre",
"COMEDY"
],
[
"SERENDIPITY",
"has_tags",
"KATE BECKINSALE"
],
[
"SERENDIPITY",
"has_tags",
"SERENDIPITY"
],
[
"SERENDIPITY",
"starred_actors",
"KATE BECKINSALE"
],
[
"SNOW ANGELS",
"has_genre",
"DRAMA"
],
[
"SNOW ANGELS",
"has_tags",
"KATE BECKINSALE"
],
[
"SNOW ANGELS",
"has_tags",
"SAM ROCKWELL"
],
[
"SNOW ANGELS",
"release_year",
"2007"
],
[
"SNOW ANGELS",
"starred_actors",
"KATE BECKINSALE"
],
[
"SNOW ANGELS",
"starred_actors",
"SAM ROCKWELL"
],
[
"THE AVIATOR",
"has_genre",
"DRAMA"
],
[
"THE AVIATOR",
"has_tags",
"DRAMA"
],
[
"THE AVIATOR",
"has_tags",
"KATE BECKINSALE"
],
[
"THE AVIATOR",
"starred_actors",
"KATE BECKINSALE"
],
[
"THE LAST DAYS OF DISCO",
"has_genre",
"COMEDY"
],
[
"THE LAST DAYS OF DISCO",
"has_genre",
"DRAMA"
],
[
"THE LAST DAYS OF DISCO",
"starred_actors",
"KATE BECKINSALE"
],
[
"THE LAW OF ENCLOSURES",
"has_genre",
"DRAMA"
],
[
"THE TRIALS OF CATE MCCALL",
"has_genre",
"DRAMA"
],
[
"THE TRIALS OF CATE MCCALL",
"starred_actors",
"KATE BECKINSALE"
],
[
"UNDERWORLD",
"has_genre",
"COMEDY"
],
[
"UNDERWORLD",
"has_tags",
"KATE BECKINSALE"
],
[
"UNDERWORLD",
"starred_actors",
"KATE BECKINSALE"
],
[
"VACANCY",
"release_year",
"2007"
],
[
"VACANCY",
"starred_actors",
"KATE BECKINSALE"
]
]
}
|
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
29838, A SIMPLE TWIST OF FATE
37043, CHRIS MENGES
2408, CRISSCROSS
35734, DAVID COOK
3439, GEORGE ELIOT
20098, GILLIES MACKINNON
22496, SECOND BEST
19717, THE PLAYBOYS
src, edge_attr, dst
29838, directed_by, 20098
29838, written_by, 3439
2408, directed_by, 37043
2408, release_year, 24818
22496, directed_by, 37043
22496, written_by, 35734
19717, directed_by, 20098
19717, release_year, 24818
Question: How are 1992, DAVID COOK, and GEORGE ELIOT related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"1992",
"DAVID COOK",
"GEORGE ELIOT"
],
"valid_edges": [
[
"A SIMPLE TWIST OF FATE",
"directed_by",
"GILLIES MACKINNON"
],
[
"A SIMPLE TWIST OF FATE",
"written_by",
"GEORGE ELIOT"
],
[
"CRISSCROSS",
"directed_by",
"CHRIS MENGES"
],
[
"CRISSCROSS",
"release_year",
"1992"
],
[
"SECOND BEST",
"directed_by",
"CHRIS MENGES"
],
[
"SECOND BEST",
"written_by",
"DAVID COOK"
],
[
"THE PLAYBOYS",
"directed_by",
"GILLIES MACKINNON"
],
[
"THE PLAYBOYS",
"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
1266, 100 WAYS TO MURDER YOUR WIFE
4981, 1965
28171, 1986
10419, A FINE MESS
18169, APRIL FOOL'S DAY
12952, ARMED AND DANGEROUS
35779, ARMOUR OF GOD
29060, BACK TO SCHOOL
39908, BEVERLY HILLS COP
24579, BEVERLY HILLS COP II
8732, BIG TROUBLE
9860, BRIGHTON BEACH MEMOIRS
14884, CLASS OF NUKE 'EM HIGH
30330, CLEAVANT DERRICKS
5984, CLOCKWISE
32393, CLUB PARADISE
30463, COMEDY
37018, CRIMES OF THE HEART
6743, CRITTERS
30019, CROSSROADS
30433, DELUSIONS OF GRANDEUR
20998, DOWN AND OUT IN BEVERLY HILLS
6715, FAST TIMES AT RIDGEMONT HIGH
3890, FERRIS BUELLER'S DAY OFF
2191, FLODDER
6012, FRENCH
15135, GINGER AND FRED
1889, GUNG HO
17767, GÉRARD OURY
1937, HANNAH AND HER SISTERS
21720, HAUNTED HONEYMOON
24557, HEAD OFFICE
10147, HOUSE
358, HOWARD THE DUCK
22258, JUDGE REINHOLD
2938, JUMPIN' JACK FLASH
39615, KIN-DZA-DZA!
191, LEAVING NORMAL
8851, LITTLE SHOP OF HORRORS
32181, LUCAS
28081, MEG TILLY
36992, MICHAEL DINNER
7848, MIRACLES
20500, MONSTER IN THE CLOSET
38118, MOSCOW ON THE HUDSON
15395, MY CHAUFFEUR
4398, NOBODY'S FOOL
2654, NOTHING IN COMMON
9271, OFF BEAT
24854, ONE CRAZY SUMMER
20473, PEGGY SUE GOT MARRIED
2391, PIRATES
2388, PLAYING FOR KEEPS
31652, PRETTY IN PINK
23115, RENATO MORETTI
36548, ROSALIE GOES SHOPPING
33108, RUNNING SCARED
1871, RUTHLESS PEOPLE
37803, SHADOWS IN PARADISE
2808, SHE'S GOTTA HAVE IT
1374, SLEEP WITH ME
34888, SOMETHING WILD
2446, SOUL MAN
5570, SWEET LIBERTY
5932, TERRORVISION
5469, THE BEST OF TIMES
14643, THE BRAIN
39489, THE CREW
13316, THE DECLINE OF THE AMERICAN EMPIRE
31439, THE GOLDEN CHILD
17527, THE MIRROR HAS TWO FACES
26338, THE MONEY PIT
15930, THE SUCKER
9715, THE TEXAS CHAINSAW MASSACRE 2
11639, TOUGH GUYS
832, TRUE STORIES
21967, VICE VERSA
19918, WILD, WILD PLANET
21709, WISE GUYS
1731, ZEISTERS
33462, ¡THREE AMIGOS!
src, edge_attr, dst
1266, has_genre, 30463
1266, release_year, 28171
10419, has_genre, 30463
10419, release_year, 28171
18169, has_genre, 30463
18169, release_year, 28171
12952, has_genre, 30463
12952, release_year, 28171
35779, has_genre, 30463
35779, release_year, 28171
29060, has_genre, 30463
29060, release_year, 28171
39908, has_genre, 30463
39908, has_tags, 30463
39908, has_tags, 22258
39908, starred_actors, 22258
24579, has_genre, 30463
24579, starred_actors, 22258
8732, has_genre, 30463
8732, release_year, 28171
9860, has_genre, 30463
9860, has_tags, 30463
9860, release_year, 28171
14884, has_genre, 30463
14884, release_year, 28171
5984, has_genre, 30463
5984, release_year, 28171
32393, has_genre, 30463
32393, release_year, 28171
37018, has_genre, 30463
37018, release_year, 28171
6743, has_genre, 30463
6743, release_year, 28171
30019, has_genre, 30463
30019, release_year, 28171
30433, directed_by, 17767
30433, has_genre, 30463
30433, has_tags, 17767
30433, in_language, 6012
30433, written_by, 17767
20998, has_genre, 30463
20998, release_year, 28171
6715, has_genre, 30463
6715, has_tags, 22258
6715, starred_actors, 22258
3890, has_genre, 30463
3890, has_tags, 30463
3890, release_year, 28171
2191, has_genre, 30463
2191, release_year, 28171
15135, has_genre, 30463
15135, release_year, 28171
1889, has_genre, 30463
1889, release_year, 28171
1937, has_genre, 30463
1937, has_tags, 30463
1937, release_year, 28171
21720, has_genre, 30463
21720, release_year, 28171
24557, has_genre, 30463
24557, starred_actors, 22258
10147, has_genre, 30463
10147, release_year, 28171
358, has_genre, 30463
358, release_year, 28171
2938, has_genre, 30463
2938, release_year, 28171
39615, has_genre, 30463
39615, release_year, 28171
191, has_genre, 30463
191, starred_actors, 28081
8851, has_genre, 30463
8851, release_year, 28171
32181, has_genre, 30463
32181, release_year, 28171
7848, has_genre, 30463
7848, release_year, 28171
20500, has_genre, 30463
20500, release_year, 28171
38118, has_genre, 30463
38118, starred_actors, 30330
15395, has_genre, 30463
15395, release_year, 28171
4398, has_genre, 30463
4398, release_year, 28171
2654, has_genre, 30463
2654, release_year, 28171
9271, directed_by, 36992
9271, has_genre, 30463
9271, release_year, 28171
9271, starred_actors, 30330
9271, starred_actors, 22258
9271, starred_actors, 28081
24854, has_genre, 30463
24854, release_year, 28171
20473, has_genre, 30463
20473, release_year, 28171
2391, has_genre, 30463
2391, release_year, 28171
2388, has_genre, 30463
2388, release_year, 28171
31652, has_genre, 30463
31652, has_tags, 30463
31652, release_year, 28171
36548, has_genre, 30463
36548, starred_actors, 22258
33108, has_genre, 30463
33108, release_year, 28171
33108, starred_actors, 22258
1871, has_genre, 30463
1871, has_tags, 30463
1871, release_year, 28171
1871, starred_actors, 22258
37803, has_genre, 30463
37803, release_year, 28171
2808, has_genre, 30463
2808, release_year, 28171
1374, has_genre, 30463
1374, starred_actors, 28081
34888, has_genre, 30463
34888, release_year, 28171
2446, has_genre, 30463
2446, release_year, 28171
5570, has_genre, 30463
5570, release_year, 28171
5932, has_genre, 30463
5932, release_year, 28171
5469, has_genre, 30463
5469, release_year, 28171
14643, directed_by, 17767
14643, has_genre, 30463
14643, in_language, 6012
14643, written_by, 17767
39489, directed_by, 36992
39489, has_genre, 30463
13316, has_genre, 30463
13316, release_year, 28171
31439, has_genre, 30463
31439, release_year, 28171
17527, has_genre, 30463
17527, written_by, 17767
26338, has_genre, 30463
26338, has_tags, 30463
26338, release_year, 28171
15930, directed_by, 17767
15930, has_genre, 30463
15930, has_tags, 17767
15930, in_language, 6012
15930, release_year, 4981
15930, written_by, 17767
9715, has_genre, 30463
9715, release_year, 28171
11639, has_genre, 30463
11639, release_year, 28171
832, has_genre, 30463
832, release_year, 28171
21967, has_genre, 30463
21967, starred_actors, 22258
19918, release_year, 4981
19918, written_by, 23115
21709, has_genre, 30463
21709, release_year, 28171
1731, has_genre, 30463
1731, release_year, 28171
33462, has_genre, 30463
33462, has_tags, 30463
33462, release_year, 28171
Question: How are GÉRARD OURY, OFF BEAT, and RENATO MORETTI related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"GÉRARD OURY",
"OFF BEAT",
"RENATO MORETTI"
],
"valid_edges": [
[
"100 WAYS TO MURDER YOUR WIFE",
"has_genre",
"COMEDY"
],
[
"100 WAYS TO MURDER YOUR WIFE",
"release_year",
"1986"
],
[
"A FINE MESS",
"has_genre",
"COMEDY"
],
[
"A FINE MESS",
"release_year",
"1986"
],
[
"APRIL FOOL'S DAY",
"has_genre",
"COMEDY"
],
[
"APRIL FOOL'S DAY",
"release_year",
"1986"
],
[
"ARMED AND DANGEROUS",
"has_genre",
"COMEDY"
],
[
"ARMED AND DANGEROUS",
"release_year",
"1986"
],
[
"ARMOUR OF GOD",
"has_genre",
"COMEDY"
],
[
"ARMOUR OF GOD",
"release_year",
"1986"
],
[
"BACK TO SCHOOL",
"has_genre",
"COMEDY"
],
[
"BACK TO SCHOOL",
"release_year",
"1986"
],
[
"BEVERLY HILLS COP",
"has_genre",
"COMEDY"
],
[
"BEVERLY HILLS COP",
"has_tags",
"COMEDY"
],
[
"BEVERLY HILLS COP",
"has_tags",
"JUDGE REINHOLD"
],
[
"BEVERLY HILLS COP",
"starred_actors",
"JUDGE REINHOLD"
],
[
"BEVERLY HILLS COP II",
"has_genre",
"COMEDY"
],
[
"BEVERLY HILLS COP II",
"starred_actors",
"JUDGE REINHOLD"
],
[
"BIG TROUBLE",
"has_genre",
"COMEDY"
],
[
"BIG TROUBLE",
"release_year",
"1986"
],
[
"BRIGHTON BEACH MEMOIRS",
"has_genre",
"COMEDY"
],
[
"BRIGHTON BEACH MEMOIRS",
"has_tags",
"COMEDY"
],
[
"BRIGHTON BEACH MEMOIRS",
"release_year",
"1986"
],
[
"CLASS OF NUKE 'EM HIGH",
"has_genre",
"COMEDY"
],
[
"CLASS OF NUKE 'EM HIGH",
"release_year",
"1986"
],
[
"CLOCKWISE",
"has_genre",
"COMEDY"
],
[
"CLOCKWISE",
"release_year",
"1986"
],
[
"CLUB PARADISE",
"has_genre",
"COMEDY"
],
[
"CLUB PARADISE",
"release_year",
"1986"
],
[
"CRIMES OF THE HEART",
"has_genre",
"COMEDY"
],
[
"CRIMES OF THE HEART",
"release_year",
"1986"
],
[
"CRITTERS",
"has_genre",
"COMEDY"
],
[
"CRITTERS",
"release_year",
"1986"
],
[
"CROSSROADS",
"has_genre",
"COMEDY"
],
[
"CROSSROADS",
"release_year",
"1986"
],
[
"DELUSIONS OF GRANDEUR",
"directed_by",
"GÉRARD OURY"
],
[
"DELUSIONS OF GRANDEUR",
"has_genre",
"COMEDY"
],
[
"DELUSIONS OF GRANDEUR",
"has_tags",
"GÉRARD OURY"
],
[
"DELUSIONS OF GRANDEUR",
"in_language",
"FRENCH"
],
[
"DELUSIONS OF GRANDEUR",
"written_by",
"GÉRARD OURY"
],
[
"DOWN AND OUT IN BEVERLY HILLS",
"has_genre",
"COMEDY"
],
[
"DOWN AND OUT IN BEVERLY HILLS",
"release_year",
"1986"
],
[
"FAST TIMES AT RIDGEMONT HIGH",
"has_genre",
"COMEDY"
],
[
"FAST TIMES AT RIDGEMONT HIGH",
"has_tags",
"JUDGE REINHOLD"
],
[
"FAST TIMES AT RIDGEMONT HIGH",
"starred_actors",
"JUDGE REINHOLD"
],
[
"FERRIS BUELLER'S DAY OFF",
"has_genre",
"COMEDY"
],
[
"FERRIS BUELLER'S DAY OFF",
"has_tags",
"COMEDY"
],
[
"FERRIS BUELLER'S DAY OFF",
"release_year",
"1986"
],
[
"FLODDER",
"has_genre",
"COMEDY"
],
[
"FLODDER",
"release_year",
"1986"
],
[
"GINGER AND FRED",
"has_genre",
"COMEDY"
],
[
"GINGER AND FRED",
"release_year",
"1986"
],
[
"GUNG HO",
"has_genre",
"COMEDY"
],
[
"GUNG HO",
"release_year",
"1986"
],
[
"HANNAH AND HER SISTERS",
"has_genre",
"COMEDY"
],
[
"HANNAH AND HER SISTERS",
"has_tags",
"COMEDY"
],
[
"HANNAH AND HER SISTERS",
"release_year",
"1986"
],
[
"HAUNTED HONEYMOON",
"has_genre",
"COMEDY"
],
[
"HAUNTED HONEYMOON",
"release_year",
"1986"
],
[
"HEAD OFFICE",
"has_genre",
"COMEDY"
],
[
"HEAD OFFICE",
"starred_actors",
"JUDGE REINHOLD"
],
[
"HOUSE",
"has_genre",
"COMEDY"
],
[
"HOUSE",
"release_year",
"1986"
],
[
"HOWARD THE DUCK",
"has_genre",
"COMEDY"
],
[
"HOWARD THE DUCK",
"release_year",
"1986"
],
[
"JUMPIN' JACK FLASH",
"has_genre",
"COMEDY"
],
[
"JUMPIN' JACK FLASH",
"release_year",
"1986"
],
[
"KIN-DZA-DZA!",
"has_genre",
"COMEDY"
],
[
"KIN-DZA-DZA!",
"release_year",
"1986"
],
[
"LEAVING NORMAL",
"has_genre",
"COMEDY"
],
[
"LEAVING NORMAL",
"starred_actors",
"MEG TILLY"
],
[
"LITTLE SHOP OF HORRORS",
"has_genre",
"COMEDY"
],
[
"LITTLE SHOP OF HORRORS",
"release_year",
"1986"
],
[
"LUCAS",
"has_genre",
"COMEDY"
],
[
"LUCAS",
"release_year",
"1986"
],
[
"MIRACLES",
"has_genre",
"COMEDY"
],
[
"MIRACLES",
"release_year",
"1986"
],
[
"MONSTER IN THE CLOSET",
"has_genre",
"COMEDY"
],
[
"MONSTER IN THE CLOSET",
"release_year",
"1986"
],
[
"MOSCOW ON THE HUDSON",
"has_genre",
"COMEDY"
],
[
"MOSCOW ON THE HUDSON",
"starred_actors",
"CLEAVANT DERRICKS"
],
[
"MY CHAUFFEUR",
"has_genre",
"COMEDY"
],
[
"MY CHAUFFEUR",
"release_year",
"1986"
],
[
"NOBODY'S FOOL",
"has_genre",
"COMEDY"
],
[
"NOBODY'S FOOL",
"release_year",
"1986"
],
[
"NOTHING IN COMMON",
"has_genre",
"COMEDY"
],
[
"NOTHING IN COMMON",
"release_year",
"1986"
],
[
"OFF BEAT",
"directed_by",
"MICHAEL DINNER"
],
[
"OFF BEAT",
"has_genre",
"COMEDY"
],
[
"OFF BEAT",
"release_year",
"1986"
],
[
"OFF BEAT",
"starred_actors",
"CLEAVANT DERRICKS"
],
[
"OFF BEAT",
"starred_actors",
"JUDGE REINHOLD"
],
[
"OFF BEAT",
"starred_actors",
"MEG TILLY"
],
[
"ONE CRAZY SUMMER",
"has_genre",
"COMEDY"
],
[
"ONE CRAZY SUMMER",
"release_year",
"1986"
],
[
"PEGGY SUE GOT MARRIED",
"has_genre",
"COMEDY"
],
[
"PEGGY SUE GOT MARRIED",
"release_year",
"1986"
],
[
"PIRATES",
"has_genre",
"COMEDY"
],
[
"PIRATES",
"release_year",
"1986"
],
[
"PLAYING FOR KEEPS",
"has_genre",
"COMEDY"
],
[
"PLAYING FOR KEEPS",
"release_year",
"1986"
],
[
"PRETTY IN PINK",
"has_genre",
"COMEDY"
],
[
"PRETTY IN PINK",
"has_tags",
"COMEDY"
],
[
"PRETTY IN PINK",
"release_year",
"1986"
],
[
"ROSALIE GOES SHOPPING",
"has_genre",
"COMEDY"
],
[
"ROSALIE GOES SHOPPING",
"starred_actors",
"JUDGE REINHOLD"
],
[
"RUNNING SCARED",
"has_genre",
"COMEDY"
],
[
"RUNNING SCARED",
"release_year",
"1986"
],
[
"RUNNING SCARED",
"starred_actors",
"JUDGE REINHOLD"
],
[
"RUTHLESS PEOPLE",
"has_genre",
"COMEDY"
],
[
"RUTHLESS PEOPLE",
"has_tags",
"COMEDY"
],
[
"RUTHLESS PEOPLE",
"release_year",
"1986"
],
[
"RUTHLESS PEOPLE",
"starred_actors",
"JUDGE REINHOLD"
],
[
"SHADOWS IN PARADISE",
"has_genre",
"COMEDY"
],
[
"SHADOWS IN PARADISE",
"release_year",
"1986"
],
[
"SHE'S GOTTA HAVE IT",
"has_genre",
"COMEDY"
],
[
"SHE'S GOTTA HAVE IT",
"release_year",
"1986"
],
[
"SLEEP WITH ME",
"has_genre",
"COMEDY"
],
[
"SLEEP WITH ME",
"starred_actors",
"MEG TILLY"
],
[
"SOMETHING WILD",
"has_genre",
"COMEDY"
],
[
"SOMETHING WILD",
"release_year",
"1986"
],
[
"SOUL MAN",
"has_genre",
"COMEDY"
],
[
"SOUL MAN",
"release_year",
"1986"
],
[
"SWEET LIBERTY",
"has_genre",
"COMEDY"
],
[
"SWEET LIBERTY",
"release_year",
"1986"
],
[
"TERRORVISION",
"has_genre",
"COMEDY"
],
[
"TERRORVISION",
"release_year",
"1986"
],
[
"THE BEST OF TIMES",
"has_genre",
"COMEDY"
],
[
"THE BEST OF TIMES",
"release_year",
"1986"
],
[
"THE BRAIN",
"directed_by",
"GÉRARD OURY"
],
[
"THE BRAIN",
"has_genre",
"COMEDY"
],
[
"THE BRAIN",
"in_language",
"FRENCH"
],
[
"THE BRAIN",
"written_by",
"GÉRARD OURY"
],
[
"THE CREW",
"directed_by",
"MICHAEL DINNER"
],
[
"THE CREW",
"has_genre",
"COMEDY"
],
[
"THE DECLINE OF THE AMERICAN EMPIRE",
"has_genre",
"COMEDY"
],
[
"THE DECLINE OF THE AMERICAN EMPIRE",
"release_year",
"1986"
],
[
"THE GOLDEN CHILD",
"has_genre",
"COMEDY"
],
[
"THE GOLDEN CHILD",
"release_year",
"1986"
],
[
"THE MIRROR HAS TWO FACES",
"has_genre",
"COMEDY"
],
[
"THE MIRROR HAS TWO FACES",
"written_by",
"GÉRARD OURY"
],
[
"THE MONEY PIT",
"has_genre",
"COMEDY"
],
[
"THE MONEY PIT",
"has_tags",
"COMEDY"
],
[
"THE MONEY PIT",
"release_year",
"1986"
],
[
"THE SUCKER",
"directed_by",
"GÉRARD OURY"
],
[
"THE SUCKER",
"has_genre",
"COMEDY"
],
[
"THE SUCKER",
"has_tags",
"GÉRARD OURY"
],
[
"THE SUCKER",
"in_language",
"FRENCH"
],
[
"THE SUCKER",
"release_year",
"1965"
],
[
"THE SUCKER",
"written_by",
"GÉRARD OURY"
],
[
"THE TEXAS CHAINSAW MASSACRE 2",
"has_genre",
"COMEDY"
],
[
"THE TEXAS CHAINSAW MASSACRE 2",
"release_year",
"1986"
],
[
"TOUGH GUYS",
"has_genre",
"COMEDY"
],
[
"TOUGH GUYS",
"release_year",
"1986"
],
[
"TRUE STORIES",
"has_genre",
"COMEDY"
],
[
"TRUE STORIES",
"release_year",
"1986"
],
[
"VICE VERSA",
"has_genre",
"COMEDY"
],
[
"VICE VERSA",
"starred_actors",
"JUDGE REINHOLD"
],
[
"WILD, WILD PLANET",
"release_year",
"1965"
],
[
"WILD, WILD PLANET",
"written_by",
"RENATO MORETTI"
],
[
"WISE GUYS",
"has_genre",
"COMEDY"
],
[
"WISE GUYS",
"release_year",
"1986"
],
[
"ZEISTERS",
"has_genre",
"COMEDY"
],
[
"ZEISTERS",
"release_year",
"1986"
],
[
"¡THREE AMIGOS!",
"has_genre",
"COMEDY"
],
[
"¡THREE AMIGOS!",
"has_tags",
"COMEDY"
],
[
"¡THREE AMIGOS!",
"release_year",
"1986"
]
]
}
|
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
28340, 20 MILLION MILES TO EARTH
26646, 3000 MILES TO GRACELAND
2439, CHARLES LAUGHTON
24717, ELVIS
5829, FIRE DOWN BELOW
28397, KEVIN COSTNER
11333, KURT RUSSELL
21772, MR. BROOKS
39935, ROBERT MITCHUM
10981, SERIAL KILLER
33115, SHELLEY WINTERS
828, THE ENEMY BELOW
27599, THE NIGHT OF THE HUNTER
3001, WITNESS FOR THE PROSECUTION
src, edge_attr, dst
28340, release_year, 39624
26646, has_tags, 28397
26646, has_tags, 11333
26646, starred_actors, 28397
26646, starred_actors, 11333
24717, starred_actors, 11333
24717, starred_actors, 33115
5829, release_year, 39624
5829, starred_actors, 39935
21772, has_tags, 28397
21772, has_tags, 10981
21772, starred_actors, 28397
828, release_year, 39624
828, starred_actors, 39935
27599, directed_by, 2439
27599, directed_by, 39935
27599, has_tags, 2439
27599, has_tags, 39935
27599, has_tags, 10981
27599, has_tags, 33115
27599, starred_actors, 39935
27599, starred_actors, 33115
3001, has_tags, 2439
3001, release_year, 39624
3001, starred_actors, 2439
Question: In what context are 20 MILLION MILES TO EARTH, 3000 MILES TO GRACELAND, and THE NIGHT OF THE HUNTER connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"20 MILLION MILES TO EARTH",
"3000 MILES TO GRACELAND",
"THE NIGHT OF THE HUNTER"
],
"valid_edges": [
[
"20 MILLION MILES TO EARTH",
"release_year",
"1957"
],
[
"3000 MILES TO GRACELAND",
"has_tags",
"KEVIN COSTNER"
],
[
"3000 MILES TO GRACELAND",
"has_tags",
"KURT RUSSELL"
],
[
"3000 MILES TO GRACELAND",
"starred_actors",
"KEVIN COSTNER"
],
[
"3000 MILES TO GRACELAND",
"starred_actors",
"KURT RUSSELL"
],
[
"ELVIS",
"starred_actors",
"KURT RUSSELL"
],
[
"ELVIS",
"starred_actors",
"SHELLEY WINTERS"
],
[
"FIRE DOWN BELOW",
"release_year",
"1957"
],
[
"FIRE DOWN BELOW",
"starred_actors",
"ROBERT MITCHUM"
],
[
"MR. BROOKS",
"has_tags",
"KEVIN COSTNER"
],
[
"MR. BROOKS",
"has_tags",
"SERIAL KILLER"
],
[
"MR. BROOKS",
"starred_actors",
"KEVIN COSTNER"
],
[
"THE ENEMY BELOW",
"release_year",
"1957"
],
[
"THE ENEMY BELOW",
"starred_actors",
"ROBERT MITCHUM"
],
[
"THE NIGHT OF THE HUNTER",
"directed_by",
"CHARLES LAUGHTON"
],
[
"THE NIGHT OF THE HUNTER",
"directed_by",
"ROBERT MITCHUM"
],
[
"THE NIGHT OF THE HUNTER",
"has_tags",
"CHARLES LAUGHTON"
],
[
"THE NIGHT OF THE HUNTER",
"has_tags",
"ROBERT MITCHUM"
],
[
"THE NIGHT OF THE HUNTER",
"has_tags",
"SERIAL KILLER"
],
[
"THE NIGHT OF THE HUNTER",
"has_tags",
"SHELLEY WINTERS"
],
[
"THE NIGHT OF THE HUNTER",
"starred_actors",
"ROBERT MITCHUM"
],
[
"THE NIGHT OF THE HUNTER",
"starred_actors",
"SHELLEY WINTERS"
],
[
"WITNESS FOR THE PROSECUTION",
"has_tags",
"CHARLES LAUGHTON"
],
[
"WITNESS FOR THE PROSECUTION",
"release_year",
"1957"
],
[
"WITNESS FOR THE PROSECUTION",
"starred_actors",
"CHARLES LAUGHTON"
]
]
}
|
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
4559, ALEX CORD
14724, CRIME
3425, DARRAGH BYRNE
36212, DRAMA
7679, PARKED
22275, THE BROTHERHOOD
34862, THE POPE OF GREENWICH VILLAGE
12659, VINCENT PATRICK
src, edge_attr, dst
7679, directed_by, 3425
7679, has_genre, 36212
22275, has_genre, 14724
22275, has_genre, 36212
22275, starred_actors, 4559
34862, has_genre, 14724
34862, written_by, 12659
Question: In what context are ALEX CORD, DARRAGH BYRNE, and VINCENT PATRICK connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"ALEX CORD",
"DARRAGH BYRNE",
"VINCENT PATRICK"
],
"valid_edges": [
[
"PARKED",
"directed_by",
"DARRAGH BYRNE"
],
[
"PARKED",
"has_genre",
"DRAMA"
],
[
"THE BROTHERHOOD",
"has_genre",
"CRIME"
],
[
"THE BROTHERHOOD",
"has_genre",
"DRAMA"
],
[
"THE BROTHERHOOD",
"starred_actors",
"ALEX CORD"
],
[
"THE POPE OF GREENWICH VILLAGE",
"has_genre",
"CRIME"
],
[
"THE POPE OF GREENWICH VILLAGE",
"written_by",
"VINCENT PATRICK"
]
]
}
|
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
10293, CONSPIRACY
14724, CRIME
27446, IN TOO DEEP
33950, LUCKY NUMBER SLEVIN
15787, MONEY FOR NOTHING
16476, MÍA MAESTRO
13081, R
5573, RAMÓN MENÉNDEZ
30131, STANLEY TUCCI
15340, THE SPEED OF THOUGHT
24811, THRILLER
21455, TOM MUSCA
35988, TORTILLA SOUP
src, edge_attr, dst
10293, has_tags, 10293
10293, has_tags, 13081
10293, release_year, 13408
10293, starred_actors, 30131
27446, has_genre, 14724
27446, has_genre, 24811
27446, starred_actors, 30131
33950, has_genre, 14724
33950, has_tags, 14724
33950, has_tags, 13081
33950, has_tags, 30131
33950, has_tags, 24811
15787, directed_by, 5573
15787, has_genre, 14724
15787, written_by, 5573
15787, written_by, 21455
15340, has_genre, 24811
15340, starred_actors, 16476
35988, release_year, 13408
35988, written_by, 5573
35988, written_by, 21455
Question: In what context are MÍA MAESTRO, STANLEY TUCCI, and TOM MUSCA connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"MÍA MAESTRO",
"STANLEY TUCCI",
"TOM MUSCA"
],
"valid_edges": [
[
"CONSPIRACY",
"has_tags",
"CONSPIRACY"
],
[
"CONSPIRACY",
"has_tags",
"R"
],
[
"CONSPIRACY",
"release_year",
"2001"
],
[
"CONSPIRACY",
"starred_actors",
"STANLEY TUCCI"
],
[
"IN TOO DEEP",
"has_genre",
"CRIME"
],
[
"IN TOO DEEP",
"has_genre",
"THRILLER"
],
[
"IN TOO DEEP",
"starred_actors",
"STANLEY TUCCI"
],
[
"LUCKY NUMBER SLEVIN",
"has_genre",
"CRIME"
],
[
"LUCKY NUMBER SLEVIN",
"has_tags",
"CRIME"
],
[
"LUCKY NUMBER SLEVIN",
"has_tags",
"R"
],
[
"LUCKY NUMBER SLEVIN",
"has_tags",
"STANLEY TUCCI"
],
[
"LUCKY NUMBER SLEVIN",
"has_tags",
"THRILLER"
],
[
"MONEY FOR NOTHING",
"directed_by",
"RAMÓN MENÉNDEZ"
],
[
"MONEY FOR NOTHING",
"has_genre",
"CRIME"
],
[
"MONEY FOR NOTHING",
"written_by",
"RAMÓN MENÉNDEZ"
],
[
"MONEY FOR NOTHING",
"written_by",
"TOM MUSCA"
],
[
"THE SPEED OF THOUGHT",
"has_genre",
"THRILLER"
],
[
"THE SPEED OF THOUGHT",
"starred_actors",
"MÍA MAESTRO"
],
[
"TORTILLA SOUP",
"release_year",
"2001"
],
[
"TORTILLA SOUP",
"written_by",
"RAMÓN MENÉNDEZ"
],
[
"TORTILLA SOUP",
"written_by",
"TOM MUSCA"
]
]
}
|
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
39289, ACTION
32014, BALLAD OF A SOLDIER
7417, BILLY CONNOLLY
25274, BLACK ORPHEUS
27958, FIRES ON THE PLAIN
24086, FLYING LEATHERNECKS
12435, JOHN WAYNE
33687, MARCEL CAMUS
32058, MUPPET TREASURE ISLAND
33297, OPERATION PETTICOAT
23515, PORK CHOP HILL
36102, RIO BRAVO
30840, SHAKE HANDS WITH THE DEVIL
19998, THE GREAT WAR
5663, THE HORSE SOLDIERS
38032, THE LAST BLITZKRIEG
27237, THE LONGEST DAY
19813, VERBOTEN!
22214, WAR
26524, YESTERDAY'S ENEMY
src, edge_attr, dst
32014, has_genre, 22214
32014, release_year, 33637
25274, directed_by, 33687
25274, release_year, 33637
25274, starred_actors, 33687
25274, written_by, 33687
27958, has_genre, 22214
27958, release_year, 33637
24086, has_genre, 22214
24086, starred_actors, 12435
32058, has_genre, 39289
32058, has_tags, 7417
32058, starred_actors, 7417
33297, has_genre, 22214
33297, release_year, 33637
23515, has_genre, 22214
23515, release_year, 33637
36102, has_tags, 12435
36102, release_year, 33637
36102, starred_actors, 12435
30840, has_genre, 22214
30840, release_year, 33637
19998, has_genre, 22214
19998, has_tags, 22214
19998, release_year, 33637
5663, has_genre, 22214
5663, has_tags, 12435
5663, release_year, 33637
5663, starred_actors, 12435
38032, has_genre, 22214
38032, release_year, 33637
27237, has_tags, 12435
27237, has_tags, 22214
19813, has_genre, 22214
19813, release_year, 33637
22214, has_genre, 39289
26524, has_genre, 22214
26524, release_year, 33637
Question: How are BILLY CONNOLLY, MARCEL CAMUS, and THE HORSE SOLDIERS related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"BILLY CONNOLLY",
"MARCEL CAMUS",
"THE HORSE SOLDIERS"
],
"valid_edges": [
[
"BALLAD OF A SOLDIER",
"has_genre",
"WAR"
],
[
"BALLAD OF A SOLDIER",
"release_year",
"1959"
],
[
"BLACK ORPHEUS",
"directed_by",
"MARCEL CAMUS"
],
[
"BLACK ORPHEUS",
"release_year",
"1959"
],
[
"BLACK ORPHEUS",
"starred_actors",
"MARCEL CAMUS"
],
[
"BLACK ORPHEUS",
"written_by",
"MARCEL CAMUS"
],
[
"FIRES ON THE PLAIN",
"has_genre",
"WAR"
],
[
"FIRES ON THE PLAIN",
"release_year",
"1959"
],
[
"FLYING LEATHERNECKS",
"has_genre",
"WAR"
],
[
"FLYING LEATHERNECKS",
"starred_actors",
"JOHN WAYNE"
],
[
"MUPPET TREASURE ISLAND",
"has_genre",
"ACTION"
],
[
"MUPPET TREASURE ISLAND",
"has_tags",
"BILLY CONNOLLY"
],
[
"MUPPET TREASURE ISLAND",
"starred_actors",
"BILLY CONNOLLY"
],
[
"OPERATION PETTICOAT",
"has_genre",
"WAR"
],
[
"OPERATION PETTICOAT",
"release_year",
"1959"
],
[
"PORK CHOP HILL",
"has_genre",
"WAR"
],
[
"PORK CHOP HILL",
"release_year",
"1959"
],
[
"RIO BRAVO",
"has_tags",
"JOHN WAYNE"
],
[
"RIO BRAVO",
"release_year",
"1959"
],
[
"RIO BRAVO",
"starred_actors",
"JOHN WAYNE"
],
[
"SHAKE HANDS WITH THE DEVIL",
"has_genre",
"WAR"
],
[
"SHAKE HANDS WITH THE DEVIL",
"release_year",
"1959"
],
[
"THE GREAT WAR",
"has_genre",
"WAR"
],
[
"THE GREAT WAR",
"has_tags",
"WAR"
],
[
"THE GREAT WAR",
"release_year",
"1959"
],
[
"THE HORSE SOLDIERS",
"has_genre",
"WAR"
],
[
"THE HORSE SOLDIERS",
"has_tags",
"JOHN WAYNE"
],
[
"THE HORSE SOLDIERS",
"release_year",
"1959"
],
[
"THE HORSE SOLDIERS",
"starred_actors",
"JOHN WAYNE"
],
[
"THE LAST BLITZKRIEG",
"has_genre",
"WAR"
],
[
"THE LAST BLITZKRIEG",
"release_year",
"1959"
],
[
"THE LONGEST DAY",
"has_tags",
"JOHN WAYNE"
],
[
"THE LONGEST DAY",
"has_tags",
"WAR"
],
[
"VERBOTEN!",
"has_genre",
"WAR"
],
[
"VERBOTEN!",
"release_year",
"1959"
],
[
"WAR",
"has_genre",
"ACTION"
],
[
"YESTERDAY'S ENEMY",
"has_genre",
"WAR"
],
[
"YESTERDAY'S ENEMY",
"release_year",
"1959"
]
]
}
|
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
20774, 127 HOURS
10702, 1991
35845, 2006
29424, 2011
15407, 29TH STREET
39705, A LITTLE STIFF
23683, ALL I WANT FOR CHRISTMAS
9846, ANNAPOLIS
30578, ANOTHER YOU
27426, AS I LAY DYING
9414, BINGO
38486, CALENDAR GIRLS
14746, CAMILLE
28295, CAREER OPPORTUNITIES
13901, CHARLIE WILSON'S WAR
3493, CHILD OF GOD
15585, CITY SLICKERS
30463, COMEDY
29148, CRAZY SAFARI
14724, CRIME
8100, CURLY SUE
39523, DANNY MCBRIDE
306, DAVID GORDON GREEN
31214, DEFENDING YOUR LIFE
29485, DELIRIOUS
37395, DEN OFRIVILLIGE GOLFAREN
3160, DOC HOLLYWOOD
16978, DON'T TELL MOM THE BABYSITTER'S DEAD
36212, DRAMA
20846, DROP DEAD FRED
31008, DUTCH
36202, ERNEST SCARED STUPID
36066, FANTASY
38250, FATHER OF THE BRIDE
18217, FIND ME GUILTY
1273, FLYBOYS
35150, FRIED GREEN TOMATOES
397, GOOD TIME MAX
18119, HE SAID, SHE SAID
34320, HEAR MY SONG
25610, HIGH STRUNG
6546, HOT SHOTS!
39726, HUDSON HAWK
16960, I LOVE YOU PHILLIP MORRIS
3909, IF LOOKS COULD KILL
24010, JAMES FRANCO
528, JOHNNY STECCHINO
30015, KING RALPH
7439, L.A. STORY
29323, LIFE STINKS
32627, MYSTERY DATE
25620, NECESSARY ROUGHNESS
40059, ONCE AROUND
23735, ONLY THE LONELY
30662, OSCAR
17667, OTHER PEOPLE'S MONEY
15521, OZ THE GREAT AND POWERFUL
14253, PALO ALTO
25824, PARADISE
32423, PERFECTLY NORMAL
1697, PINEAPPLE EXPRESS
23297, PROBLEM CHILD 2
39, PURE LUCK
25772, PYRATES
29601, QUEENS LOGIC
16685, RISE OF THE PLANET OF THE APES
31600, RUBIN AND ED
33607, SEX AND ZEN
8932, SLACKER
11883, SOAPDISH
7083, SONNY
38762, SPEAKING OF THE DEVIL
19149, SPRING BREAK
17346, SPRING BREAKERS
29906, SUBURBAN COMMANDO
35064, SWITCH
8210, THE BUTCHER'S WIFE
4345, THE COMMITMENTS
252, THE DARK BACKWARD
20229, THE FISHER KING
31393, THE GREAT RAID
32102, THE HARD WAY
4223, THE INTERVIEW
37565, THE LAST BOY SCOUT
12947, THE MARRYING MAN
2739, THE SAPPHIRES
1545, THE SUPER
21715, THIS IS THE END
13384, TOTO THE HERO
16292, TRUE STORY
22214, WAR
7593, WHAT ABOUT BOB?
10935, WHO'S YOUR DADDY?
21510, YOUR HIGHNESS
src, edge_attr, dst
20774, has_genre, 36212
20774, has_tags, 36212
20774, has_tags, 24010
20774, starred_actors, 24010
15407, has_genre, 30463
15407, release_year, 10702
39705, has_genre, 30463
39705, release_year, 10702
23683, has_genre, 30463
23683, release_year, 10702
9846, has_genre, 36212
9846, has_tags, 24010
9846, release_year, 35845
9846, starred_actors, 24010
30578, has_genre, 30463
30578, release_year, 10702
27426, directed_by, 24010
27426, has_genre, 36212
27426, starred_actors, 24010
27426, written_by, 24010
9414, has_genre, 30463
9414, release_year, 10702
38486, has_genre, 30463
38486, has_tags, 16292
14746, has_genre, 36212
14746, starred_actors, 24010
28295, has_genre, 30463
28295, release_year, 10702
13901, has_genre, 30463
13901, has_tags, 16292
3493, directed_by, 24010
3493, has_genre, 36212
3493, starred_actors, 24010
3493, written_by, 24010
15585, has_genre, 30463
15585, release_year, 10702
29148, has_genre, 30463
29148, release_year, 10702
8100, has_genre, 30463
8100, release_year, 10702
31214, has_genre, 30463
31214, release_year, 10702
29485, has_genre, 30463
29485, release_year, 10702
37395, has_genre, 30463
37395, release_year, 10702
3160, has_genre, 30463
3160, has_tags, 30463
3160, release_year, 10702
16978, has_genre, 30463
16978, release_year, 10702
20846, has_genre, 30463
20846, release_year, 10702
31008, has_genre, 30463
31008, release_year, 10702
36202, has_genre, 30463
36202, release_year, 10702
38250, has_genre, 30463
38250, has_tags, 30463
38250, release_year, 10702
18217, has_genre, 30463
18217, has_tags, 16292
1273, has_genre, 36212
1273, has_tags, 24010
1273, has_tags, 22214
1273, release_year, 35845
1273, starred_actors, 24010
35150, has_genre, 30463
35150, release_year, 10702
397, directed_by, 24010
397, has_genre, 36212
397, starred_actors, 24010
397, written_by, 24010
18119, has_genre, 30463
18119, release_year, 10702
34320, has_genre, 30463
34320, release_year, 10702
25610, has_genre, 30463
25610, release_year, 10702
6546, has_genre, 30463
6546, has_tags, 30463
6546, release_year, 10702
39726, has_genre, 30463
39726, has_tags, 30463
39726, release_year, 10702
16960, has_genre, 30463
16960, has_tags, 30463
16960, has_tags, 16292
3909, has_genre, 30463
3909, release_year, 10702
528, has_genre, 30463
528, release_year, 10702
30015, has_genre, 30463
30015, has_tags, 30463
30015, release_year, 10702
7439, has_genre, 30463
7439, release_year, 10702
29323, has_genre, 30463
29323, release_year, 10702
32627, has_genre, 30463
32627, release_year, 10702
25620, has_genre, 30463
25620, release_year, 10702
40059, has_genre, 30463
40059, release_year, 10702
23735, has_genre, 30463
23735, release_year, 10702
30662, has_genre, 30463
30662, release_year, 10702
17667, has_genre, 30463
17667, release_year, 10702
15521, has_genre, 36066
15521, has_tags, 36066
15521, has_tags, 24010
15521, starred_actors, 24010
14253, has_genre, 36212
14253, written_by, 24010
25824, has_genre, 30463
25824, release_year, 10702
32423, has_genre, 30463
32423, release_year, 10702
1697, directed_by, 306
1697, has_genre, 30463
1697, has_tags, 30463
1697, has_tags, 306
1697, has_tags, 24010
1697, starred_actors, 24010
23297, has_genre, 30463
23297, release_year, 10702
39, has_genre, 30463
39, release_year, 10702
25772, has_genre, 30463
25772, release_year, 10702
29601, has_genre, 30463
29601, release_year, 10702
16685, has_tags, 24010
16685, release_year, 29424
31600, has_genre, 30463
31600, release_year, 10702
33607, has_genre, 30463
33607, release_year, 10702
8932, has_genre, 30463
8932, release_year, 10702
11883, has_genre, 30463
11883, has_tags, 30463
11883, release_year, 10702
7083, has_genre, 14724
7083, has_genre, 36212
7083, has_tags, 24010
7083, starred_actors, 24010
38762, has_genre, 30463
38762, release_year, 10702
19149, has_genre, 30463
17346, has_genre, 14724
17346, has_genre, 36212
17346, has_tags, 24010
17346, has_tags, 19149
17346, starred_actors, 24010
29906, has_genre, 30463
29906, release_year, 10702
35064, has_genre, 30463
35064, release_year, 10702
8210, has_genre, 30463
8210, release_year, 10702
4345, has_genre, 30463
4345, release_year, 10702
252, has_genre, 30463
252, release_year, 10702
20229, has_genre, 30463
20229, release_year, 10702
31393, has_genre, 22214
31393, starred_actors, 24010
32102, has_genre, 30463
32102, release_year, 10702
4223, has_genre, 30463
4223, has_tags, 30463
4223, has_tags, 24010
4223, starred_actors, 24010
37565, has_genre, 30463
37565, release_year, 10702
12947, has_genre, 30463
12947, release_year, 10702
2739, has_genre, 30463
2739, has_tags, 16292
1545, has_genre, 30463
1545, release_year, 10702
21715, has_genre, 30463
21715, has_tags, 39523
21715, has_tags, 24010
21715, starred_actors, 24010
13384, release_year, 10702
16292, has_genre, 36212
16292, has_tags, 36212
16292, starred_actors, 24010
7593, has_genre, 30463
7593, release_year, 10702
10935, has_genre, 30463
21510, directed_by, 306
21510, has_genre, 30463
21510, has_genre, 36066
21510, has_tags, 24010
21510, release_year, 29424
21510, starred_actors, 39523
21510, starred_actors, 24010
21510, written_by, 39523
Question: In what context are JAMES FRANCO, TOTO THE HERO, and WHO'S YOUR DADDY? connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"JAMES FRANCO",
"TOTO THE HERO",
"WHO'S YOUR DADDY?"
],
"valid_edges": [
[
"127 HOURS",
"has_genre",
"DRAMA"
],
[
"127 HOURS",
"has_tags",
"DRAMA"
],
[
"127 HOURS",
"has_tags",
"JAMES FRANCO"
],
[
"127 HOURS",
"starred_actors",
"JAMES FRANCO"
],
[
"29TH STREET",
"has_genre",
"COMEDY"
],
[
"29TH STREET",
"release_year",
"1991"
],
[
"A LITTLE STIFF",
"has_genre",
"COMEDY"
],
[
"A LITTLE STIFF",
"release_year",
"1991"
],
[
"ALL I WANT FOR CHRISTMAS",
"has_genre",
"COMEDY"
],
[
"ALL I WANT FOR CHRISTMAS",
"release_year",
"1991"
],
[
"ANNAPOLIS",
"has_genre",
"DRAMA"
],
[
"ANNAPOLIS",
"has_tags",
"JAMES FRANCO"
],
[
"ANNAPOLIS",
"release_year",
"2006"
],
[
"ANNAPOLIS",
"starred_actors",
"JAMES FRANCO"
],
[
"ANOTHER YOU",
"has_genre",
"COMEDY"
],
[
"ANOTHER YOU",
"release_year",
"1991"
],
[
"AS I LAY DYING",
"directed_by",
"JAMES FRANCO"
],
[
"AS I LAY DYING",
"has_genre",
"DRAMA"
],
[
"AS I LAY DYING",
"starred_actors",
"JAMES FRANCO"
],
[
"AS I LAY DYING",
"written_by",
"JAMES FRANCO"
],
[
"BINGO",
"has_genre",
"COMEDY"
],
[
"BINGO",
"release_year",
"1991"
],
[
"CALENDAR GIRLS",
"has_genre",
"COMEDY"
],
[
"CALENDAR GIRLS",
"has_tags",
"TRUE STORY"
],
[
"CAMILLE",
"has_genre",
"DRAMA"
],
[
"CAMILLE",
"starred_actors",
"JAMES FRANCO"
],
[
"CAREER OPPORTUNITIES",
"has_genre",
"COMEDY"
],
[
"CAREER OPPORTUNITIES",
"release_year",
"1991"
],
[
"CHARLIE WILSON'S WAR",
"has_genre",
"COMEDY"
],
[
"CHARLIE WILSON'S WAR",
"has_tags",
"TRUE STORY"
],
[
"CHILD OF GOD",
"directed_by",
"JAMES FRANCO"
],
[
"CHILD OF GOD",
"has_genre",
"DRAMA"
],
[
"CHILD OF GOD",
"starred_actors",
"JAMES FRANCO"
],
[
"CHILD OF GOD",
"written_by",
"JAMES FRANCO"
],
[
"CITY SLICKERS",
"has_genre",
"COMEDY"
],
[
"CITY SLICKERS",
"release_year",
"1991"
],
[
"CRAZY SAFARI",
"has_genre",
"COMEDY"
],
[
"CRAZY SAFARI",
"release_year",
"1991"
],
[
"CURLY SUE",
"has_genre",
"COMEDY"
],
[
"CURLY SUE",
"release_year",
"1991"
],
[
"DEFENDING YOUR LIFE",
"has_genre",
"COMEDY"
],
[
"DEFENDING YOUR LIFE",
"release_year",
"1991"
],
[
"DELIRIOUS",
"has_genre",
"COMEDY"
],
[
"DELIRIOUS",
"release_year",
"1991"
],
[
"DEN OFRIVILLIGE GOLFAREN",
"has_genre",
"COMEDY"
],
[
"DEN OFRIVILLIGE GOLFAREN",
"release_year",
"1991"
],
[
"DOC HOLLYWOOD",
"has_genre",
"COMEDY"
],
[
"DOC HOLLYWOOD",
"has_tags",
"COMEDY"
],
[
"DOC HOLLYWOOD",
"release_year",
"1991"
],
[
"DON'T TELL MOM THE BABYSITTER'S DEAD",
"has_genre",
"COMEDY"
],
[
"DON'T TELL MOM THE BABYSITTER'S DEAD",
"release_year",
"1991"
],
[
"DROP DEAD FRED",
"has_genre",
"COMEDY"
],
[
"DROP DEAD FRED",
"release_year",
"1991"
],
[
"DUTCH",
"has_genre",
"COMEDY"
],
[
"DUTCH",
"release_year",
"1991"
],
[
"ERNEST SCARED STUPID",
"has_genre",
"COMEDY"
],
[
"ERNEST SCARED STUPID",
"release_year",
"1991"
],
[
"FATHER OF THE BRIDE",
"has_genre",
"COMEDY"
],
[
"FATHER OF THE BRIDE",
"has_tags",
"COMEDY"
],
[
"FATHER OF THE BRIDE",
"release_year",
"1991"
],
[
"FIND ME GUILTY",
"has_genre",
"COMEDY"
],
[
"FIND ME GUILTY",
"has_tags",
"TRUE STORY"
],
[
"FLYBOYS",
"has_genre",
"DRAMA"
],
[
"FLYBOYS",
"has_tags",
"JAMES FRANCO"
],
[
"FLYBOYS",
"has_tags",
"WAR"
],
[
"FLYBOYS",
"release_year",
"2006"
],
[
"FLYBOYS",
"starred_actors",
"JAMES FRANCO"
],
[
"FRIED GREEN TOMATOES",
"has_genre",
"COMEDY"
],
[
"FRIED GREEN TOMATOES",
"release_year",
"1991"
],
[
"GOOD TIME MAX",
"directed_by",
"JAMES FRANCO"
],
[
"GOOD TIME MAX",
"has_genre",
"DRAMA"
],
[
"GOOD TIME MAX",
"starred_actors",
"JAMES FRANCO"
],
[
"GOOD TIME MAX",
"written_by",
"JAMES FRANCO"
],
[
"HE SAID, SHE SAID",
"has_genre",
"COMEDY"
],
[
"HE SAID, SHE SAID",
"release_year",
"1991"
],
[
"HEAR MY SONG",
"has_genre",
"COMEDY"
],
[
"HEAR MY SONG",
"release_year",
"1991"
],
[
"HIGH STRUNG",
"has_genre",
"COMEDY"
],
[
"HIGH STRUNG",
"release_year",
"1991"
],
[
"HOT SHOTS!",
"has_genre",
"COMEDY"
],
[
"HOT SHOTS!",
"has_tags",
"COMEDY"
],
[
"HOT SHOTS!",
"release_year",
"1991"
],
[
"HUDSON HAWK",
"has_genre",
"COMEDY"
],
[
"HUDSON HAWK",
"has_tags",
"COMEDY"
],
[
"HUDSON HAWK",
"release_year",
"1991"
],
[
"I LOVE YOU PHILLIP MORRIS",
"has_genre",
"COMEDY"
],
[
"I LOVE YOU PHILLIP MORRIS",
"has_tags",
"COMEDY"
],
[
"I LOVE YOU PHILLIP MORRIS",
"has_tags",
"TRUE STORY"
],
[
"IF LOOKS COULD KILL",
"has_genre",
"COMEDY"
],
[
"IF LOOKS COULD KILL",
"release_year",
"1991"
],
[
"JOHNNY STECCHINO",
"has_genre",
"COMEDY"
],
[
"JOHNNY STECCHINO",
"release_year",
"1991"
],
[
"KING RALPH",
"has_genre",
"COMEDY"
],
[
"KING RALPH",
"has_tags",
"COMEDY"
],
[
"KING RALPH",
"release_year",
"1991"
],
[
"L.A. STORY",
"has_genre",
"COMEDY"
],
[
"L.A. STORY",
"release_year",
"1991"
],
[
"LIFE STINKS",
"has_genre",
"COMEDY"
],
[
"LIFE STINKS",
"release_year",
"1991"
],
[
"MYSTERY DATE",
"has_genre",
"COMEDY"
],
[
"MYSTERY DATE",
"release_year",
"1991"
],
[
"NECESSARY ROUGHNESS",
"has_genre",
"COMEDY"
],
[
"NECESSARY ROUGHNESS",
"release_year",
"1991"
],
[
"ONCE AROUND",
"has_genre",
"COMEDY"
],
[
"ONCE AROUND",
"release_year",
"1991"
],
[
"ONLY THE LONELY",
"has_genre",
"COMEDY"
],
[
"ONLY THE LONELY",
"release_year",
"1991"
],
[
"OSCAR",
"has_genre",
"COMEDY"
],
[
"OSCAR",
"release_year",
"1991"
],
[
"OTHER PEOPLE'S MONEY",
"has_genre",
"COMEDY"
],
[
"OTHER PEOPLE'S MONEY",
"release_year",
"1991"
],
[
"OZ THE GREAT AND POWERFUL",
"has_genre",
"FANTASY"
],
[
"OZ THE GREAT AND POWERFUL",
"has_tags",
"FANTASY"
],
[
"OZ THE GREAT AND POWERFUL",
"has_tags",
"JAMES FRANCO"
],
[
"OZ THE GREAT AND POWERFUL",
"starred_actors",
"JAMES FRANCO"
],
[
"PALO ALTO",
"has_genre",
"DRAMA"
],
[
"PALO ALTO",
"written_by",
"JAMES FRANCO"
],
[
"PARADISE",
"has_genre",
"COMEDY"
],
[
"PARADISE",
"release_year",
"1991"
],
[
"PERFECTLY NORMAL",
"has_genre",
"COMEDY"
],
[
"PERFECTLY NORMAL",
"release_year",
"1991"
],
[
"PINEAPPLE EXPRESS",
"directed_by",
"DAVID GORDON GREEN"
],
[
"PINEAPPLE EXPRESS",
"has_genre",
"COMEDY"
],
[
"PINEAPPLE EXPRESS",
"has_tags",
"COMEDY"
],
[
"PINEAPPLE EXPRESS",
"has_tags",
"DAVID GORDON GREEN"
],
[
"PINEAPPLE EXPRESS",
"has_tags",
"JAMES FRANCO"
],
[
"PINEAPPLE EXPRESS",
"starred_actors",
"JAMES FRANCO"
],
[
"PROBLEM CHILD 2",
"has_genre",
"COMEDY"
],
[
"PROBLEM CHILD 2",
"release_year",
"1991"
],
[
"PURE LUCK",
"has_genre",
"COMEDY"
],
[
"PURE LUCK",
"release_year",
"1991"
],
[
"PYRATES",
"has_genre",
"COMEDY"
],
[
"PYRATES",
"release_year",
"1991"
],
[
"QUEENS LOGIC",
"has_genre",
"COMEDY"
],
[
"QUEENS LOGIC",
"release_year",
"1991"
],
[
"RISE OF THE PLANET OF THE APES",
"has_tags",
"JAMES FRANCO"
],
[
"RISE OF THE PLANET OF THE APES",
"release_year",
"2011"
],
[
"RUBIN AND ED",
"has_genre",
"COMEDY"
],
[
"RUBIN AND ED",
"release_year",
"1991"
],
[
"SEX AND ZEN",
"has_genre",
"COMEDY"
],
[
"SEX AND ZEN",
"release_year",
"1991"
],
[
"SLACKER",
"has_genre",
"COMEDY"
],
[
"SLACKER",
"release_year",
"1991"
],
[
"SOAPDISH",
"has_genre",
"COMEDY"
],
[
"SOAPDISH",
"has_tags",
"COMEDY"
],
[
"SOAPDISH",
"release_year",
"1991"
],
[
"SONNY",
"has_genre",
"CRIME"
],
[
"SONNY",
"has_genre",
"DRAMA"
],
[
"SONNY",
"has_tags",
"JAMES FRANCO"
],
[
"SONNY",
"starred_actors",
"JAMES FRANCO"
],
[
"SPEAKING OF THE DEVIL",
"has_genre",
"COMEDY"
],
[
"SPEAKING OF THE DEVIL",
"release_year",
"1991"
],
[
"SPRING BREAK",
"has_genre",
"COMEDY"
],
[
"SPRING BREAKERS",
"has_genre",
"CRIME"
],
[
"SPRING BREAKERS",
"has_genre",
"DRAMA"
],
[
"SPRING BREAKERS",
"has_tags",
"JAMES FRANCO"
],
[
"SPRING BREAKERS",
"has_tags",
"SPRING BREAK"
],
[
"SPRING BREAKERS",
"starred_actors",
"JAMES FRANCO"
],
[
"SUBURBAN COMMANDO",
"has_genre",
"COMEDY"
],
[
"SUBURBAN COMMANDO",
"release_year",
"1991"
],
[
"SWITCH",
"has_genre",
"COMEDY"
],
[
"SWITCH",
"release_year",
"1991"
],
[
"THE BUTCHER'S WIFE",
"has_genre",
"COMEDY"
],
[
"THE BUTCHER'S WIFE",
"release_year",
"1991"
],
[
"THE COMMITMENTS",
"has_genre",
"COMEDY"
],
[
"THE COMMITMENTS",
"release_year",
"1991"
],
[
"THE DARK BACKWARD",
"has_genre",
"COMEDY"
],
[
"THE DARK BACKWARD",
"release_year",
"1991"
],
[
"THE FISHER KING",
"has_genre",
"COMEDY"
],
[
"THE FISHER KING",
"release_year",
"1991"
],
[
"THE GREAT RAID",
"has_genre",
"WAR"
],
[
"THE GREAT RAID",
"starred_actors",
"JAMES FRANCO"
],
[
"THE HARD WAY",
"has_genre",
"COMEDY"
],
[
"THE HARD WAY",
"release_year",
"1991"
],
[
"THE INTERVIEW",
"has_genre",
"COMEDY"
],
[
"THE INTERVIEW",
"has_tags",
"COMEDY"
],
[
"THE INTERVIEW",
"has_tags",
"JAMES FRANCO"
],
[
"THE INTERVIEW",
"starred_actors",
"JAMES FRANCO"
],
[
"THE LAST BOY SCOUT",
"has_genre",
"COMEDY"
],
[
"THE LAST BOY SCOUT",
"release_year",
"1991"
],
[
"THE MARRYING MAN",
"has_genre",
"COMEDY"
],
[
"THE MARRYING MAN",
"release_year",
"1991"
],
[
"THE SAPPHIRES",
"has_genre",
"COMEDY"
],
[
"THE SAPPHIRES",
"has_tags",
"TRUE STORY"
],
[
"THE SUPER",
"has_genre",
"COMEDY"
],
[
"THE SUPER",
"release_year",
"1991"
],
[
"THIS IS THE END",
"has_genre",
"COMEDY"
],
[
"THIS IS THE END",
"has_tags",
"DANNY MCBRIDE"
],
[
"THIS IS THE END",
"has_tags",
"JAMES FRANCO"
],
[
"THIS IS THE END",
"starred_actors",
"JAMES FRANCO"
],
[
"TOTO THE HERO",
"release_year",
"1991"
],
[
"TRUE STORY",
"has_genre",
"DRAMA"
],
[
"TRUE STORY",
"has_tags",
"DRAMA"
],
[
"TRUE STORY",
"starred_actors",
"JAMES FRANCO"
],
[
"WHAT ABOUT BOB?",
"has_genre",
"COMEDY"
],
[
"WHAT ABOUT BOB?",
"release_year",
"1991"
],
[
"WHO'S YOUR DADDY?",
"has_genre",
"COMEDY"
],
[
"YOUR HIGHNESS",
"directed_by",
"DAVID GORDON GREEN"
],
[
"YOUR HIGHNESS",
"has_genre",
"COMEDY"
],
[
"YOUR HIGHNESS",
"has_genre",
"FANTASY"
],
[
"YOUR HIGHNESS",
"has_tags",
"JAMES FRANCO"
],
[
"YOUR HIGHNESS",
"release_year",
"2011"
],
[
"YOUR HIGHNESS",
"starred_actors",
"DANNY MCBRIDE"
],
[
"YOUR HIGHNESS",
"starred_actors",
"JAMES FRANCO"
],
[
"YOUR HIGHNESS",
"written_by",
"DANNY MCBRIDE"
]
]
}
|
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
14259, 1997
24626, A CHILD IS WAITING
13192, ABBY MANN
14310, BARAN BO ODAR
38776, BURT LANCASTER
611, DERRICK SANDERS
6480, GERMAN
3713, IT'S IN THE WATER
22600, JUDGMENT AT NUREMBERG
22194, THE LEOPARD
16072, THE RAINMAKER
18785, THE SILENCE
38808, THE TRAIN
src, edge_attr, dst
24626, release_year, 13504
24626, starred_actors, 38776
24626, written_by, 13192
3713, release_year, 14259
3713, starred_actors, 611
22600, in_language, 6480
22600, starred_actors, 38776
22600, written_by, 13192
22194, release_year, 13504
22194, starred_actors, 38776
16072, release_year, 14259
16072, starred_actors, 38776
18785, directed_by, 14310
18785, in_language, 6480
18785, release_year, 13504
18785, written_by, 14310
38808, in_language, 6480
38808, starred_actors, 38776
Question: In what context are BARAN BO ODAR, BURT LANCASTER, and DERRICK SANDERS connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"BARAN BO ODAR",
"BURT LANCASTER",
"DERRICK SANDERS"
],
"valid_edges": [
[
"A CHILD IS WAITING",
"release_year",
"1963"
],
[
"A CHILD IS WAITING",
"starred_actors",
"BURT LANCASTER"
],
[
"A CHILD IS WAITING",
"written_by",
"ABBY MANN"
],
[
"IT'S IN THE WATER",
"release_year",
"1997"
],
[
"IT'S IN THE WATER",
"starred_actors",
"DERRICK SANDERS"
],
[
"JUDGMENT AT NUREMBERG",
"in_language",
"GERMAN"
],
[
"JUDGMENT AT NUREMBERG",
"starred_actors",
"BURT LANCASTER"
],
[
"JUDGMENT AT NUREMBERG",
"written_by",
"ABBY MANN"
],
[
"THE LEOPARD",
"release_year",
"1963"
],
[
"THE LEOPARD",
"starred_actors",
"BURT LANCASTER"
],
[
"THE RAINMAKER",
"release_year",
"1997"
],
[
"THE RAINMAKER",
"starred_actors",
"BURT LANCASTER"
],
[
"THE SILENCE",
"directed_by",
"BARAN BO ODAR"
],
[
"THE SILENCE",
"in_language",
"GERMAN"
],
[
"THE SILENCE",
"release_year",
"1963"
],
[
"THE SILENCE",
"written_by",
"BARAN BO ODAR"
],
[
"THE TRAIN",
"in_language",
"GERMAN"
],
[
"THE TRAIN",
"starred_actors",
"BURT LANCASTER"
]
]
}
|
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
21136, 10 MINUTES
37484, 2004
27261, 2009
739, 2081
673, 9
22088, A BRIDGE TOO FAR
25987, A GUY NAMED JOE
23445, A MIDNIGHT CLEAR
30750, A VERY LONG ENGAGEMENT
7663, ACTION IN THE NORTH ATLANTIC
29884, ALEXANDER
22726, ANNE FRANK REMEMBERED
36876, ATTACK
32621, AVATAR
32014, BALLAD OF A SOLDIER
34734, BATTLE OF THE BULGE
12185, BATTLEGROUND
1912, BEYOND ALL BOUNDARIES
40074, BLACK BOOK
2856, BROTHERS
24318, CASHBACK
25285, COME AND SEE
10293, CONSPIRACY
4615, DARK BLUE WORLD
18972, DAS BOOT
11363, DEFIANCE
17714, DOWNFALL
16353, EDGES OF THE LORD
22028, EMPIRE OF THE SUN
16930, ENEMY AT THE GATES
1329, ENVY
30411, FAHRENHEIT 9/11
27958, FIRES ON THE PLAIN
10315, FLAGS OF OUR FATHERS
13834, FLYING TIGERS
39145, FURY
30162, GUADALCANAL DIARY
15765, HAMSUN
33545, HART'S WAR
34055, HARVIE KRUMPET
1044, HOTEL RWANDA
22885, HOUSE OF FLYING DAGGERS
12087, HOWL'S MOVING CASTLE
15343, IN DARKNESS
28360, IN ENEMY HANDS
35518, IN HARM'S WAY
16560, INGLOURIOUS BASTERDS
6780, INTO THE STORM
38574, IT HAPPENED HERE
22012, IVAN'S CHILDHOOD
22167, KING RAT
33720, LEBANON
20200, LOGORAMA
6134, LOS BANDOLEROS
37365, MARCELLO PAGLIERO
9595, MEMPHIS BELLE
5127, MOTHER NIGHT
38294, MRS. MINIVER
20581, OPERATION PACIFIC
19562, PAPERMAN
16806, PATTON
35167, PRIVATE
7284, PULL MY DAISY
29931, ROME, OPEN CITY
33164, RUNAWAY
35586, SAHARA
23006, SANDS OF IWO JIMA
24365, SAVING PRIVATE RYAN
36899, SHORT
18869, SHORT FILM
9619, SIX SHOOTER
796, SOME FOLKS CALL IT A SLING BLADE
21196, STALAG 17
11124, STALINGRAD
7547, TAKING CHANCE
37855, TEA WITH MUSSOLINI
28461, THE ALAMO
27210, THE BEST YEARS OF OUR LIVES
7710, THE BIG RED ONE
29788, THE BRIDGE AT REMAGEN
14436, THE BURMESE HARP
36692, THE CAINE MUTINY
828, THE ENEMY BELOW
778, THE FALLEN
30507, THE FIGHTING SEABEES
6424, THE GREAT ESCAPE
31393, THE GREAT RAID
24882, THE GRUFFALO
405, THE HIDING PLACE
20299, THE HILL
5567, THE KEEPER
27237, THE LONGEST DAY
28024, THE MEN WHO STARE AT GOATS
28292, THE MESSENGER
30294, THE NIGHT OF THE GENERALS
11555, THE NOTEBOOK
12614, THE PIANIST
32618, THE RAPE OF EUROPA
4962, THE SORROW AND THE PITY
21548, THE SUN
30136, THE THIN RED LINE
35911, THE TUSKEGEE AIRMEN
3123, THEY WERE EXPENDABLE
23247, TRIAGE
5729, TROY
29947, TURTLES CAN FLY
38352, TWELVE O'CLOCK HIGH
38730, TWO MEN WENT TO WAR
37253, U-571
39558, UNDERGROUND
33011, VALKYRIE
32733, VANITY FAIR
2175, VON RYAN'S EXPRESS
22214, WAR
9159, WAR COMES TO AMERICA
5949, WHEN TRUMPETS FADE
23537, WHERE EAGLES DARE
24155, WORLD WAR II
15904, YANKS
src, edge_attr, dst
21136, has_genre, 36899
21136, has_genre, 22214
739, has_genre, 36899
739, release_year, 27261
673, has_tags, 22214
673, release_year, 27261
22088, has_genre, 22214
22088, has_tags, 22214
22088, has_tags, 24155
25987, has_genre, 22214
25987, has_tags, 24155
23445, has_genre, 22214
23445, has_tags, 22214
23445, has_tags, 24155
30750, has_tags, 22214
30750, release_year, 37484
7663, has_genre, 22214
7663, has_tags, 24155
29884, has_tags, 22214
29884, release_year, 37484
22726, has_genre, 22214
22726, has_tags, 24155
36876, has_genre, 22214
36876, has_tags, 24155
32621, has_tags, 22214
32621, release_year, 27261
32014, has_genre, 22214
32014, has_tags, 24155
34734, has_genre, 22214
34734, has_tags, 24155
12185, has_genre, 22214
12185, has_tags, 22214
12185, has_tags, 24155
1912, has_genre, 36899
1912, has_genre, 22214
1912, has_tags, 18869
1912, has_tags, 24155
1912, release_year, 27261
40074, has_genre, 22214
40074, has_tags, 24155
2856, release_year, 37484
2856, release_year, 27261
24318, has_genre, 36899
24318, has_tags, 36899
24318, release_year, 37484
25285, has_genre, 22214
25285, has_tags, 24155
10293, has_genre, 22214
10293, has_tags, 24155
4615, has_genre, 22214
4615, has_tags, 24155
18972, has_genre, 22214
18972, has_tags, 22214
18972, has_tags, 24155
11363, has_tags, 22214
11363, has_tags, 24155
17714, has_tags, 22214
17714, release_year, 37484
16353, has_genre, 22214
16353, has_tags, 24155
22028, has_genre, 22214
22028, has_tags, 22214
22028, has_tags, 24155
16930, has_tags, 22214
16930, has_tags, 24155
1329, release_year, 37484
1329, release_year, 27261
30411, has_tags, 22214
30411, release_year, 37484
27958, has_genre, 22214
27958, has_tags, 24155
10315, has_genre, 22214
10315, has_tags, 22214
10315, has_tags, 24155
13834, has_genre, 22214
13834, has_tags, 24155
39145, has_genre, 22214
39145, has_tags, 22214
39145, has_tags, 24155
30162, has_genre, 22214
30162, has_tags, 24155
15765, has_genre, 22214
15765, has_tags, 24155
33545, has_genre, 22214
33545, has_tags, 24155
34055, has_genre, 36899
34055, has_tags, 36899
34055, has_tags, 18869
1044, has_genre, 22214
1044, has_tags, 22214
1044, release_year, 37484
22885, has_tags, 22214
22885, release_year, 37484
12087, has_tags, 22214
12087, release_year, 37484
15343, has_genre, 22214
15343, has_tags, 22214
15343, has_tags, 24155
28360, has_genre, 22214
28360, release_year, 37484
35518, has_genre, 22214
35518, has_tags, 24155
16560, has_genre, 22214
16560, has_tags, 22214
16560, release_year, 27261
6780, has_tags, 24155
6780, release_year, 27261
38574, has_genre, 22214
38574, has_tags, 24155
22012, has_genre, 22214
22012, has_tags, 22214
22012, has_tags, 24155
22167, has_genre, 22214
22167, has_tags, 24155
33720, has_genre, 22214
33720, has_tags, 22214
33720, release_year, 27261
20200, has_genre, 36899
20200, release_year, 27261
6134, has_genre, 36899
6134, release_year, 27261
9595, has_genre, 22214
9595, has_tags, 24155
5127, has_genre, 22214
5127, has_tags, 24155
38294, has_genre, 22214
38294, has_tags, 24155
20581, has_genre, 22214
20581, has_tags, 24155
19562, has_genre, 36899
19562, has_tags, 36899
19562, has_tags, 18869
16806, has_genre, 22214
16806, has_tags, 22214
16806, has_tags, 24155
35167, has_genre, 22214
35167, release_year, 37484
7284, has_genre, 36899
7284, has_tags, 36899
7284, has_tags, 18869
29931, has_genre, 22214
29931, starred_actors, 37365
33164, has_genre, 36899
33164, has_tags, 36899
33164, release_year, 27261
35586, has_genre, 22214
35586, has_tags, 24155
23006, has_genre, 22214
23006, has_tags, 24155
24365, has_genre, 22214
24365, has_tags, 22214
24365, has_tags, 24155
9619, has_genre, 36899
9619, has_tags, 36899
9619, has_tags, 18869
9619, release_year, 37484
796, has_genre, 36899
796, has_tags, 36899
796, has_tags, 18869
21196, has_genre, 22214
21196, has_tags, 24155
11124, has_genre, 22214
11124, has_tags, 24155
7547, has_genre, 22214
7547, release_year, 27261
37855, has_genre, 22214
37855, has_tags, 24155
28461, has_genre, 22214
28461, has_tags, 22214
28461, release_year, 37484
27210, has_genre, 22214
27210, has_tags, 24155
7710, has_genre, 22214
7710, has_tags, 24155
29788, has_genre, 22214
29788, has_tags, 24155
14436, has_genre, 22214
14436, has_tags, 24155
36692, has_genre, 22214
36692, has_tags, 24155
828, has_tags, 22214
828, has_tags, 24155
778, has_genre, 22214
778, release_year, 37484
30507, has_genre, 22214
30507, has_tags, 24155
6424, has_tags, 22214
6424, has_tags, 24155
31393, has_genre, 22214
31393, has_tags, 24155
24882, has_genre, 36899
24882, release_year, 27261
405, has_genre, 22214
405, has_tags, 24155
20299, has_genre, 22214
20299, has_tags, 24155
5567, release_year, 37484
5567, release_year, 27261
27237, has_tags, 22214
27237, has_tags, 24155
28024, has_genre, 22214
28024, release_year, 27261
28292, has_genre, 22214
28292, release_year, 27261
30294, has_tags, 22214
30294, has_tags, 24155
11555, has_genre, 22214
11555, release_year, 37484
12614, has_genre, 22214
12614, has_tags, 22214
12614, has_tags, 24155
32618, has_genre, 22214
32618, has_tags, 24155
4962, has_genre, 22214
4962, has_tags, 24155
21548, has_tags, 22214
21548, has_tags, 24155
30136, has_genre, 22214
30136, has_tags, 22214
30136, has_tags, 24155
35911, has_genre, 22214
35911, has_tags, 24155
3123, has_genre, 22214
3123, has_tags, 24155
23247, has_genre, 22214
23247, release_year, 27261
5729, has_tags, 22214
5729, release_year, 37484
29947, has_genre, 22214
29947, release_year, 37484
38352, has_genre, 22214
38352, has_tags, 24155
38730, has_genre, 22214
38730, has_tags, 24155
37253, has_genre, 22214
37253, has_tags, 22214
37253, has_tags, 24155
39558, has_genre, 22214
39558, has_tags, 24155
33011, has_genre, 22214
33011, has_tags, 24155
32733, release_year, 37484
2175, has_genre, 22214
2175, has_tags, 24155
9159, has_genre, 22214
9159, has_tags, 24155
5949, has_genre, 22214
5949, has_tags, 24155
23537, has_genre, 22214
23537, has_tags, 24155
15904, has_genre, 22214
15904, has_tags, 24155
Question: In what context are BEYOND ALL BOUNDARIES, MARCELLO PAGLIERO, and VANITY FAIR connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"BEYOND ALL BOUNDARIES",
"MARCELLO PAGLIERO",
"VANITY FAIR"
],
"valid_edges": [
[
"10 MINUTES",
"has_genre",
"SHORT"
],
[
"10 MINUTES",
"has_genre",
"WAR"
],
[
"2081",
"has_genre",
"SHORT"
],
[
"2081",
"release_year",
"2009"
],
[
"9",
"has_tags",
"WAR"
],
[
"9",
"release_year",
"2009"
],
[
"A BRIDGE TOO FAR",
"has_genre",
"WAR"
],
[
"A BRIDGE TOO FAR",
"has_tags",
"WAR"
],
[
"A BRIDGE TOO FAR",
"has_tags",
"WORLD WAR II"
],
[
"A GUY NAMED JOE",
"has_genre",
"WAR"
],
[
"A GUY NAMED JOE",
"has_tags",
"WORLD WAR II"
],
[
"A MIDNIGHT CLEAR",
"has_genre",
"WAR"
],
[
"A MIDNIGHT CLEAR",
"has_tags",
"WAR"
],
[
"A MIDNIGHT CLEAR",
"has_tags",
"WORLD WAR II"
],
[
"A VERY LONG ENGAGEMENT",
"has_tags",
"WAR"
],
[
"A VERY LONG ENGAGEMENT",
"release_year",
"2004"
],
[
"ACTION IN THE NORTH ATLANTIC",
"has_genre",
"WAR"
],
[
"ACTION IN THE NORTH ATLANTIC",
"has_tags",
"WORLD WAR II"
],
[
"ALEXANDER",
"has_tags",
"WAR"
],
[
"ALEXANDER",
"release_year",
"2004"
],
[
"ANNE FRANK REMEMBERED",
"has_genre",
"WAR"
],
[
"ANNE FRANK REMEMBERED",
"has_tags",
"WORLD WAR II"
],
[
"ATTACK",
"has_genre",
"WAR"
],
[
"ATTACK",
"has_tags",
"WORLD WAR II"
],
[
"AVATAR",
"has_tags",
"WAR"
],
[
"AVATAR",
"release_year",
"2009"
],
[
"BALLAD OF A SOLDIER",
"has_genre",
"WAR"
],
[
"BALLAD OF A SOLDIER",
"has_tags",
"WORLD WAR II"
],
[
"BATTLE OF THE BULGE",
"has_genre",
"WAR"
],
[
"BATTLE OF THE BULGE",
"has_tags",
"WORLD WAR II"
],
[
"BATTLEGROUND",
"has_genre",
"WAR"
],
[
"BATTLEGROUND",
"has_tags",
"WAR"
],
[
"BATTLEGROUND",
"has_tags",
"WORLD WAR II"
],
[
"BEYOND ALL BOUNDARIES",
"has_genre",
"SHORT"
],
[
"BEYOND ALL BOUNDARIES",
"has_genre",
"WAR"
],
[
"BEYOND ALL BOUNDARIES",
"has_tags",
"SHORT FILM"
],
[
"BEYOND ALL BOUNDARIES",
"has_tags",
"WORLD WAR II"
],
[
"BEYOND ALL BOUNDARIES",
"release_year",
"2009"
],
[
"BLACK BOOK",
"has_genre",
"WAR"
],
[
"BLACK BOOK",
"has_tags",
"WORLD WAR II"
],
[
"BROTHERS",
"release_year",
"2004"
],
[
"BROTHERS",
"release_year",
"2009"
],
[
"CASHBACK",
"has_genre",
"SHORT"
],
[
"CASHBACK",
"has_tags",
"SHORT"
],
[
"CASHBACK",
"release_year",
"2004"
],
[
"COME AND SEE",
"has_genre",
"WAR"
],
[
"COME AND SEE",
"has_tags",
"WORLD WAR II"
],
[
"CONSPIRACY",
"has_genre",
"WAR"
],
[
"CONSPIRACY",
"has_tags",
"WORLD WAR II"
],
[
"DARK BLUE WORLD",
"has_genre",
"WAR"
],
[
"DARK BLUE WORLD",
"has_tags",
"WORLD WAR II"
],
[
"DAS BOOT",
"has_genre",
"WAR"
],
[
"DAS BOOT",
"has_tags",
"WAR"
],
[
"DAS BOOT",
"has_tags",
"WORLD WAR II"
],
[
"DEFIANCE",
"has_tags",
"WAR"
],
[
"DEFIANCE",
"has_tags",
"WORLD WAR II"
],
[
"DOWNFALL",
"has_tags",
"WAR"
],
[
"DOWNFALL",
"release_year",
"2004"
],
[
"EDGES OF THE LORD",
"has_genre",
"WAR"
],
[
"EDGES OF THE LORD",
"has_tags",
"WORLD WAR II"
],
[
"EMPIRE OF THE SUN",
"has_genre",
"WAR"
],
[
"EMPIRE OF THE SUN",
"has_tags",
"WAR"
],
[
"EMPIRE OF THE SUN",
"has_tags",
"WORLD WAR II"
],
[
"ENEMY AT THE GATES",
"has_tags",
"WAR"
],
[
"ENEMY AT THE GATES",
"has_tags",
"WORLD WAR II"
],
[
"ENVY",
"release_year",
"2004"
],
[
"ENVY",
"release_year",
"2009"
],
[
"FAHRENHEIT 9/11",
"has_tags",
"WAR"
],
[
"FAHRENHEIT 9/11",
"release_year",
"2004"
],
[
"FIRES ON THE PLAIN",
"has_genre",
"WAR"
],
[
"FIRES ON THE PLAIN",
"has_tags",
"WORLD WAR II"
],
[
"FLAGS OF OUR FATHERS",
"has_genre",
"WAR"
],
[
"FLAGS OF OUR FATHERS",
"has_tags",
"WAR"
],
[
"FLAGS OF OUR FATHERS",
"has_tags",
"WORLD WAR II"
],
[
"FLYING TIGERS",
"has_genre",
"WAR"
],
[
"FLYING TIGERS",
"has_tags",
"WORLD WAR II"
],
[
"FURY",
"has_genre",
"WAR"
],
[
"FURY",
"has_tags",
"WAR"
],
[
"FURY",
"has_tags",
"WORLD WAR II"
],
[
"GUADALCANAL DIARY",
"has_genre",
"WAR"
],
[
"GUADALCANAL DIARY",
"has_tags",
"WORLD WAR II"
],
[
"HAMSUN",
"has_genre",
"WAR"
],
[
"HAMSUN",
"has_tags",
"WORLD WAR II"
],
[
"HART'S WAR",
"has_genre",
"WAR"
],
[
"HART'S WAR",
"has_tags",
"WORLD WAR II"
],
[
"HARVIE KRUMPET",
"has_genre",
"SHORT"
],
[
"HARVIE KRUMPET",
"has_tags",
"SHORT"
],
[
"HARVIE KRUMPET",
"has_tags",
"SHORT FILM"
],
[
"HOTEL RWANDA",
"has_genre",
"WAR"
],
[
"HOTEL RWANDA",
"has_tags",
"WAR"
],
[
"HOTEL RWANDA",
"release_year",
"2004"
],
[
"HOUSE OF FLYING DAGGERS",
"has_tags",
"WAR"
],
[
"HOUSE OF FLYING DAGGERS",
"release_year",
"2004"
],
[
"HOWL'S MOVING CASTLE",
"has_tags",
"WAR"
],
[
"HOWL'S MOVING CASTLE",
"release_year",
"2004"
],
[
"IN DARKNESS",
"has_genre",
"WAR"
],
[
"IN DARKNESS",
"has_tags",
"WAR"
],
[
"IN DARKNESS",
"has_tags",
"WORLD WAR II"
],
[
"IN ENEMY HANDS",
"has_genre",
"WAR"
],
[
"IN ENEMY HANDS",
"release_year",
"2004"
],
[
"IN HARM'S WAY",
"has_genre",
"WAR"
],
[
"IN HARM'S WAY",
"has_tags",
"WORLD WAR II"
],
[
"INGLOURIOUS BASTERDS",
"has_genre",
"WAR"
],
[
"INGLOURIOUS BASTERDS",
"has_tags",
"WAR"
],
[
"INGLOURIOUS BASTERDS",
"release_year",
"2009"
],
[
"INTO THE STORM",
"has_tags",
"WORLD WAR II"
],
[
"INTO THE STORM",
"release_year",
"2009"
],
[
"IT HAPPENED HERE",
"has_genre",
"WAR"
],
[
"IT HAPPENED HERE",
"has_tags",
"WORLD WAR II"
],
[
"IVAN'S CHILDHOOD",
"has_genre",
"WAR"
],
[
"IVAN'S CHILDHOOD",
"has_tags",
"WAR"
],
[
"IVAN'S CHILDHOOD",
"has_tags",
"WORLD WAR II"
],
[
"KING RAT",
"has_genre",
"WAR"
],
[
"KING RAT",
"has_tags",
"WORLD WAR II"
],
[
"LEBANON",
"has_genre",
"WAR"
],
[
"LEBANON",
"has_tags",
"WAR"
],
[
"LEBANON",
"release_year",
"2009"
],
[
"LOGORAMA",
"has_genre",
"SHORT"
],
[
"LOGORAMA",
"release_year",
"2009"
],
[
"LOS BANDOLEROS",
"has_genre",
"SHORT"
],
[
"LOS BANDOLEROS",
"release_year",
"2009"
],
[
"MEMPHIS BELLE",
"has_genre",
"WAR"
],
[
"MEMPHIS BELLE",
"has_tags",
"WORLD WAR II"
],
[
"MOTHER NIGHT",
"has_genre",
"WAR"
],
[
"MOTHER NIGHT",
"has_tags",
"WORLD WAR II"
],
[
"MRS. MINIVER",
"has_genre",
"WAR"
],
[
"MRS. MINIVER",
"has_tags",
"WORLD WAR II"
],
[
"OPERATION PACIFIC",
"has_genre",
"WAR"
],
[
"OPERATION PACIFIC",
"has_tags",
"WORLD WAR II"
],
[
"PAPERMAN",
"has_genre",
"SHORT"
],
[
"PAPERMAN",
"has_tags",
"SHORT"
],
[
"PAPERMAN",
"has_tags",
"SHORT FILM"
],
[
"PATTON",
"has_genre",
"WAR"
],
[
"PATTON",
"has_tags",
"WAR"
],
[
"PATTON",
"has_tags",
"WORLD WAR II"
],
[
"PRIVATE",
"has_genre",
"WAR"
],
[
"PRIVATE",
"release_year",
"2004"
],
[
"PULL MY DAISY",
"has_genre",
"SHORT"
],
[
"PULL MY DAISY",
"has_tags",
"SHORT"
],
[
"PULL MY DAISY",
"has_tags",
"SHORT FILM"
],
[
"ROME, OPEN CITY",
"has_genre",
"WAR"
],
[
"ROME, OPEN CITY",
"starred_actors",
"MARCELLO PAGLIERO"
],
[
"RUNAWAY",
"has_genre",
"SHORT"
],
[
"RUNAWAY",
"has_tags",
"SHORT"
],
[
"RUNAWAY",
"release_year",
"2009"
],
[
"SAHARA",
"has_genre",
"WAR"
],
[
"SAHARA",
"has_tags",
"WORLD WAR II"
],
[
"SANDS OF IWO JIMA",
"has_genre",
"WAR"
],
[
"SANDS OF IWO JIMA",
"has_tags",
"WORLD WAR II"
],
[
"SAVING PRIVATE RYAN",
"has_genre",
"WAR"
],
[
"SAVING PRIVATE RYAN",
"has_tags",
"WAR"
],
[
"SAVING PRIVATE RYAN",
"has_tags",
"WORLD WAR II"
],
[
"SIX SHOOTER",
"has_genre",
"SHORT"
],
[
"SIX SHOOTER",
"has_tags",
"SHORT"
],
[
"SIX SHOOTER",
"has_tags",
"SHORT FILM"
],
[
"SIX SHOOTER",
"release_year",
"2004"
],
[
"SOME FOLKS CALL IT A SLING BLADE",
"has_genre",
"SHORT"
],
[
"SOME FOLKS CALL IT A SLING BLADE",
"has_tags",
"SHORT"
],
[
"SOME FOLKS CALL IT A SLING BLADE",
"has_tags",
"SHORT FILM"
],
[
"STALAG 17",
"has_genre",
"WAR"
],
[
"STALAG 17",
"has_tags",
"WORLD WAR II"
],
[
"STALINGRAD",
"has_genre",
"WAR"
],
[
"STALINGRAD",
"has_tags",
"WORLD WAR II"
],
[
"TAKING CHANCE",
"has_genre",
"WAR"
],
[
"TAKING CHANCE",
"release_year",
"2009"
],
[
"TEA WITH MUSSOLINI",
"has_genre",
"WAR"
],
[
"TEA WITH MUSSOLINI",
"has_tags",
"WORLD WAR II"
],
[
"THE ALAMO",
"has_genre",
"WAR"
],
[
"THE ALAMO",
"has_tags",
"WAR"
],
[
"THE ALAMO",
"release_year",
"2004"
],
[
"THE BEST YEARS OF OUR LIVES",
"has_genre",
"WAR"
],
[
"THE BEST YEARS OF OUR LIVES",
"has_tags",
"WORLD WAR II"
],
[
"THE BIG RED ONE",
"has_genre",
"WAR"
],
[
"THE BIG RED ONE",
"has_tags",
"WORLD WAR II"
],
[
"THE BRIDGE AT REMAGEN",
"has_genre",
"WAR"
],
[
"THE BRIDGE AT REMAGEN",
"has_tags",
"WORLD WAR II"
],
[
"THE BURMESE HARP",
"has_genre",
"WAR"
],
[
"THE BURMESE HARP",
"has_tags",
"WORLD WAR II"
],
[
"THE CAINE MUTINY",
"has_genre",
"WAR"
],
[
"THE CAINE MUTINY",
"has_tags",
"WORLD WAR II"
],
[
"THE ENEMY BELOW",
"has_tags",
"WAR"
],
[
"THE ENEMY BELOW",
"has_tags",
"WORLD WAR II"
],
[
"THE FALLEN",
"has_genre",
"WAR"
],
[
"THE FALLEN",
"release_year",
"2004"
],
[
"THE FIGHTING SEABEES",
"has_genre",
"WAR"
],
[
"THE FIGHTING SEABEES",
"has_tags",
"WORLD WAR II"
],
[
"THE GREAT ESCAPE",
"has_tags",
"WAR"
],
[
"THE GREAT ESCAPE",
"has_tags",
"WORLD WAR II"
],
[
"THE GREAT RAID",
"has_genre",
"WAR"
],
[
"THE GREAT RAID",
"has_tags",
"WORLD WAR II"
],
[
"THE GRUFFALO",
"has_genre",
"SHORT"
],
[
"THE GRUFFALO",
"release_year",
"2009"
],
[
"THE HIDING PLACE",
"has_genre",
"WAR"
],
[
"THE HIDING PLACE",
"has_tags",
"WORLD WAR II"
],
[
"THE HILL",
"has_genre",
"WAR"
],
[
"THE HILL",
"has_tags",
"WORLD WAR II"
],
[
"THE KEEPER",
"release_year",
"2004"
],
[
"THE KEEPER",
"release_year",
"2009"
],
[
"THE LONGEST DAY",
"has_tags",
"WAR"
],
[
"THE LONGEST DAY",
"has_tags",
"WORLD WAR II"
],
[
"THE MEN WHO STARE AT GOATS",
"has_genre",
"WAR"
],
[
"THE MEN WHO STARE AT GOATS",
"release_year",
"2009"
],
[
"THE MESSENGER",
"has_genre",
"WAR"
],
[
"THE MESSENGER",
"release_year",
"2009"
],
[
"THE NIGHT OF THE GENERALS",
"has_tags",
"WAR"
],
[
"THE NIGHT OF THE GENERALS",
"has_tags",
"WORLD WAR II"
],
[
"THE NOTEBOOK",
"has_genre",
"WAR"
],
[
"THE NOTEBOOK",
"release_year",
"2004"
],
[
"THE PIANIST",
"has_genre",
"WAR"
],
[
"THE PIANIST",
"has_tags",
"WAR"
],
[
"THE PIANIST",
"has_tags",
"WORLD WAR II"
],
[
"THE RAPE OF EUROPA",
"has_genre",
"WAR"
],
[
"THE RAPE OF EUROPA",
"has_tags",
"WORLD WAR II"
],
[
"THE SORROW AND THE PITY",
"has_genre",
"WAR"
],
[
"THE SORROW AND THE PITY",
"has_tags",
"WORLD WAR II"
],
[
"THE SUN",
"has_tags",
"WAR"
],
[
"THE SUN",
"has_tags",
"WORLD WAR II"
],
[
"THE THIN RED LINE",
"has_genre",
"WAR"
],
[
"THE THIN RED LINE",
"has_tags",
"WAR"
],
[
"THE THIN RED LINE",
"has_tags",
"WORLD WAR II"
],
[
"THE TUSKEGEE AIRMEN",
"has_genre",
"WAR"
],
[
"THE TUSKEGEE AIRMEN",
"has_tags",
"WORLD WAR II"
],
[
"THEY WERE EXPENDABLE",
"has_genre",
"WAR"
],
[
"THEY WERE EXPENDABLE",
"has_tags",
"WORLD WAR II"
],
[
"TRIAGE",
"has_genre",
"WAR"
],
[
"TRIAGE",
"release_year",
"2009"
],
[
"TROY",
"has_tags",
"WAR"
],
[
"TROY",
"release_year",
"2004"
],
[
"TURTLES CAN FLY",
"has_genre",
"WAR"
],
[
"TURTLES CAN FLY",
"release_year",
"2004"
],
[
"TWELVE O'CLOCK HIGH",
"has_genre",
"WAR"
],
[
"TWELVE O'CLOCK HIGH",
"has_tags",
"WORLD WAR II"
],
[
"TWO MEN WENT TO WAR",
"has_genre",
"WAR"
],
[
"TWO MEN WENT TO WAR",
"has_tags",
"WORLD WAR II"
],
[
"U-571",
"has_genre",
"WAR"
],
[
"U-571",
"has_tags",
"WAR"
],
[
"U-571",
"has_tags",
"WORLD WAR II"
],
[
"UNDERGROUND",
"has_genre",
"WAR"
],
[
"UNDERGROUND",
"has_tags",
"WORLD WAR II"
],
[
"VALKYRIE",
"has_genre",
"WAR"
],
[
"VALKYRIE",
"has_tags",
"WORLD WAR II"
],
[
"VANITY FAIR",
"release_year",
"2004"
],
[
"VON RYAN'S EXPRESS",
"has_genre",
"WAR"
],
[
"VON RYAN'S EXPRESS",
"has_tags",
"WORLD WAR II"
],
[
"WAR COMES TO AMERICA",
"has_genre",
"WAR"
],
[
"WAR COMES TO AMERICA",
"has_tags",
"WORLD WAR II"
],
[
"WHEN TRUMPETS FADE",
"has_genre",
"WAR"
],
[
"WHEN TRUMPETS FADE",
"has_tags",
"WORLD WAR II"
],
[
"WHERE EAGLES DARE",
"has_genre",
"WAR"
],
[
"WHERE EAGLES DARE",
"has_tags",
"WORLD WAR II"
],
[
"YANKS",
"has_genre",
"WAR"
],
[
"YANKS",
"has_tags",
"WORLD WAR II"
]
]
}
|
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
3458, 1951
26762, 2008
37608, AUSTRALIA
33109, CARLA BALENDA
21862, COLLEGE ROAD TRIP
3457, JAMES VANCE MARSHALL
30533, SANTA FE
23345, THE WHIP HAND
23155, WALKABOUT
src, edge_attr, dst
37608, release_year, 26762
21862, release_year, 26762
30533, release_year, 3458
30533, written_by, 3457
23345, release_year, 3458
23345, starred_actors, 33109
23155, has_tags, 37608
23155, written_by, 3457
Question: How are CARLA BALENDA, COLLEGE ROAD TRIP, and JAMES VANCE MARSHALL related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"CARLA BALENDA",
"COLLEGE ROAD TRIP",
"JAMES VANCE MARSHALL"
],
"valid_edges": [
[
"AUSTRALIA",
"release_year",
"2008"
],
[
"COLLEGE ROAD TRIP",
"release_year",
"2008"
],
[
"SANTA FE",
"release_year",
"1951"
],
[
"SANTA FE",
"written_by",
"JAMES VANCE MARSHALL"
],
[
"THE WHIP HAND",
"release_year",
"1951"
],
[
"THE WHIP HAND",
"starred_actors",
"CARLA BALENDA"
],
[
"WALKABOUT",
"has_tags",
"AUSTRALIA"
],
[
"WALKABOUT",
"written_by",
"JAMES VANCE MARSHALL"
]
]
}
|
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
30721, A BEAUTIFUL MIND
2566, A BETTER PLACE
21004, A CRY IN THE NIGHT
10997, A HIGH WIND IN JAMAICA
4390, A PATCH OF BLUE
9317, A RIVER RUNS THROUGH IT
2888, AN UNFINISHED LIFE
24409, ARARAT
1730, BABY THE RAIN MUST FALL
34734, BATTLE OF THE BULGE
20491, BRAINSTORM
25849, BRUBAKER
8709, CHRISTOPHER PLUMMER
21365, CLARA'S HEART
23205, DARLING
25805, DOCTOR ZHIVAGO
9894, DOWNHILL RACER
36212, DRAMA
5806, EION BAILEY
13912, FEAR STRIKES OUT
33571, HAVANA
10400, INDECENT PROPOSAL
36005, INSIDE DAISY CLOVER
17999, INTIMATE LIGHTING
18699, JULIET OF THE SPIRITS
31499, LE BONHEUR
24224, LIONS FOR LAMBS
7383, LITTLE FAUSS AND BIG HALSY
5885, LOVE WITH THE PROPER STRANGER
5461, MARJORIE KINNAN RAWLINGS
40131, MARJORIE MORNINGSTAR
8253, MICKEY ONE
35813, NATALIE WOOD
3656, ORDINARY PEOPLE
33056, OTHELLO
34938, OUT OF AFRICA
11072, QUIZ SHOW
26953, ROBERT MULLIGAN
34758, ROBERT REDFORD
10638, RUTH GORDON
30622, SALTO
25567, SAME TIME, NEXT YEAR
5754, SHIP OF FOOLS
8753, SPLENDOR IN THE GRASS
29113, SUMMER OF '42
22407, THE ACTRESS
9426, THE ASHES
1174, THE CANDIDATE
13685, THE CHASE
11536, THE CINCINNATI KID
32040, THE CONSPIRATOR
757, THE FLIGHT OF THE PHOENIX
2872, THE GREAT GATSBY
8847, THE GREAT WALDO PEPPER
31736, THE HORSE WHISPERER
12439, THE INSIDER
36917, THE LAKE HOUSE
4143, THE LAST CASTLE
29682, THE LAST STATION
35557, THE MAN IN THE MOON
7386, THE MILAGRO BEANFIELD WAR
18105, THE MOMENT OF TRUTH
8022, THE NEW WORLD
12657, THE PURSUIT OF HAPPINESS
34959, THE RAT RACE
25794, THE WAR GAME
32709, THE WAY WE WERE
27519, THE YEARLING
31876, THIS PROPERTY IS CONDEMNED
12764, TO KILL A MOCKINGBIRD
8595, UP THE DOWN STAIRCASE
4552, WEST SIDE STORY
4265, YOUNG CASSIDY
src, edge_attr, dst
30721, has_genre, 36212
30721, has_tags, 36212
30721, starred_actors, 8709
2566, has_genre, 36212
2566, starred_actors, 5806
21004, has_genre, 36212
21004, starred_actors, 35813
10997, has_genre, 36212
10997, release_year, 4981
4390, has_genre, 36212
4390, release_year, 4981
9317, directed_by, 34758
9317, has_genre, 36212
9317, has_tags, 34758
2888, has_genre, 36212
2888, has_tags, 34758
2888, starred_actors, 34758
24409, has_genre, 36212
24409, starred_actors, 8709
1730, directed_by, 26953
1730, has_genre, 36212
1730, release_year, 4981
34734, has_genre, 36212
34734, release_year, 4981
20491, has_genre, 36212
20491, release_year, 4981
20491, starred_actors, 35813
25849, has_genre, 36212
25849, starred_actors, 34758
21365, directed_by, 26953
21365, has_genre, 36212
23205, has_genre, 36212
23205, release_year, 4981
25805, has_genre, 36212
25805, release_year, 4981
9894, has_genre, 36212
9894, starred_actors, 34758
13912, directed_by, 26953
13912, has_genre, 36212
33571, has_genre, 36212
33571, starred_actors, 34758
10400, has_genre, 36212
10400, has_tags, 34758
10400, starred_actors, 34758
36005, directed_by, 26953
36005, has_genre, 36212
36005, release_year, 4981
36005, starred_actors, 8709
36005, starred_actors, 35813
36005, starred_actors, 34758
36005, starred_actors, 10638
17999, has_genre, 36212
17999, release_year, 4981
18699, has_genre, 36212
18699, release_year, 4981
31499, has_genre, 36212
31499, release_year, 4981
24224, directed_by, 34758
24224, has_genre, 36212
24224, has_tags, 34758
24224, starred_actors, 34758
7383, has_genre, 36212
7383, starred_actors, 34758
5885, directed_by, 26953
5885, has_genre, 36212
5885, starred_actors, 35813
40131, has_genre, 36212
40131, starred_actors, 35813
8253, has_genre, 36212
8253, release_year, 4981
3656, directed_by, 34758
3656, has_genre, 36212
3656, has_tags, 34758
33056, has_genre, 36212
33056, release_year, 4981
34938, has_genre, 36212
34938, has_tags, 36212
34938, has_tags, 34758
34938, starred_actors, 34758
11072, directed_by, 34758
11072, has_genre, 36212
11072, has_tags, 34758
30622, has_genre, 36212
30622, release_year, 4981
25567, directed_by, 26953
25567, has_genre, 36212
25567, has_tags, 26953
5754, has_genre, 36212
5754, release_year, 4981
8753, has_genre, 36212
8753, has_tags, 35813
8753, starred_actors, 35813
29113, directed_by, 26953
29113, has_genre, 36212
29113, has_tags, 26953
22407, has_genre, 36212
22407, written_by, 10638
9426, has_genre, 36212
9426, release_year, 4981
1174, has_genre, 36212
1174, has_tags, 34758
1174, starred_actors, 34758
13685, has_genre, 36212
13685, has_tags, 34758
13685, starred_actors, 34758
11536, has_genre, 36212
11536, release_year, 4981
32040, directed_by, 34758
32040, has_genre, 36212
32040, has_tags, 34758
757, has_genre, 36212
757, release_year, 4981
2872, has_genre, 36212
2872, has_tags, 34758
2872, starred_actors, 34758
8847, has_genre, 36212
8847, starred_actors, 34758
31736, directed_by, 34758
31736, has_genre, 36212
31736, has_tags, 34758
31736, starred_actors, 34758
12439, has_genre, 36212
12439, has_tags, 36212
12439, starred_actors, 8709
36917, has_genre, 36212
36917, starred_actors, 8709
4143, has_genre, 36212
4143, has_tags, 34758
4143, starred_actors, 34758
29682, has_genre, 36212
29682, starred_actors, 8709
35557, directed_by, 26953
35557, has_genre, 36212
35557, has_tags, 26953
7386, directed_by, 34758
7386, has_genre, 36212
7386, has_tags, 34758
18105, has_genre, 36212
18105, release_year, 4981
8022, has_genre, 36212
8022, has_tags, 8709
8022, starred_actors, 8709
12657, directed_by, 26953
12657, has_genre, 36212
34959, directed_by, 26953
34959, has_genre, 36212
25794, has_genre, 36212
25794, release_year, 4981
32709, has_genre, 36212
32709, starred_actors, 34758
27519, has_genre, 36212
27519, written_by, 5461
31876, has_genre, 36212
31876, starred_actors, 35813
31876, starred_actors, 34758
12764, directed_by, 26953
12764, has_genre, 36212
12764, has_tags, 36212
12764, has_tags, 26953
8595, directed_by, 26953
8595, has_genre, 36212
4552, has_genre, 36212
4552, has_tags, 35813
4552, starred_actors, 35813
4265, has_genre, 36212
4265, release_year, 4981
Question: In what context are EION BAILEY, INSIDE DAISY CLOVER, and MARJORIE KINNAN RAWLINGS connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"EION BAILEY",
"INSIDE DAISY CLOVER",
"MARJORIE KINNAN RAWLINGS"
],
"valid_edges": [
[
"A BEAUTIFUL MIND",
"has_genre",
"DRAMA"
],
[
"A BEAUTIFUL MIND",
"has_tags",
"DRAMA"
],
[
"A BEAUTIFUL MIND",
"starred_actors",
"CHRISTOPHER PLUMMER"
],
[
"A BETTER PLACE",
"has_genre",
"DRAMA"
],
[
"A BETTER PLACE",
"starred_actors",
"EION BAILEY"
],
[
"A CRY IN THE NIGHT",
"has_genre",
"DRAMA"
],
[
"A CRY IN THE NIGHT",
"starred_actors",
"NATALIE WOOD"
],
[
"A HIGH WIND IN JAMAICA",
"has_genre",
"DRAMA"
],
[
"A HIGH WIND IN JAMAICA",
"release_year",
"1965"
],
[
"A PATCH OF BLUE",
"has_genre",
"DRAMA"
],
[
"A PATCH OF BLUE",
"release_year",
"1965"
],
[
"A RIVER RUNS THROUGH IT",
"directed_by",
"ROBERT REDFORD"
],
[
"A RIVER RUNS THROUGH IT",
"has_genre",
"DRAMA"
],
[
"A RIVER RUNS THROUGH IT",
"has_tags",
"ROBERT REDFORD"
],
[
"AN UNFINISHED LIFE",
"has_genre",
"DRAMA"
],
[
"AN UNFINISHED LIFE",
"has_tags",
"ROBERT REDFORD"
],
[
"AN UNFINISHED LIFE",
"starred_actors",
"ROBERT REDFORD"
],
[
"ARARAT",
"has_genre",
"DRAMA"
],
[
"ARARAT",
"starred_actors",
"CHRISTOPHER PLUMMER"
],
[
"BABY THE RAIN MUST FALL",
"directed_by",
"ROBERT MULLIGAN"
],
[
"BABY THE RAIN MUST FALL",
"has_genre",
"DRAMA"
],
[
"BABY THE RAIN MUST FALL",
"release_year",
"1965"
],
[
"BATTLE OF THE BULGE",
"has_genre",
"DRAMA"
],
[
"BATTLE OF THE BULGE",
"release_year",
"1965"
],
[
"BRAINSTORM",
"has_genre",
"DRAMA"
],
[
"BRAINSTORM",
"release_year",
"1965"
],
[
"BRAINSTORM",
"starred_actors",
"NATALIE WOOD"
],
[
"BRUBAKER",
"has_genre",
"DRAMA"
],
[
"BRUBAKER",
"starred_actors",
"ROBERT REDFORD"
],
[
"CLARA'S HEART",
"directed_by",
"ROBERT MULLIGAN"
],
[
"CLARA'S HEART",
"has_genre",
"DRAMA"
],
[
"DARLING",
"has_genre",
"DRAMA"
],
[
"DARLING",
"release_year",
"1965"
],
[
"DOCTOR ZHIVAGO",
"has_genre",
"DRAMA"
],
[
"DOCTOR ZHIVAGO",
"release_year",
"1965"
],
[
"DOWNHILL RACER",
"has_genre",
"DRAMA"
],
[
"DOWNHILL RACER",
"starred_actors",
"ROBERT REDFORD"
],
[
"FEAR STRIKES OUT",
"directed_by",
"ROBERT MULLIGAN"
],
[
"FEAR STRIKES OUT",
"has_genre",
"DRAMA"
],
[
"HAVANA",
"has_genre",
"DRAMA"
],
[
"HAVANA",
"starred_actors",
"ROBERT REDFORD"
],
[
"INDECENT PROPOSAL",
"has_genre",
"DRAMA"
],
[
"INDECENT PROPOSAL",
"has_tags",
"ROBERT REDFORD"
],
[
"INDECENT PROPOSAL",
"starred_actors",
"ROBERT REDFORD"
],
[
"INSIDE DAISY CLOVER",
"directed_by",
"ROBERT MULLIGAN"
],
[
"INSIDE DAISY CLOVER",
"has_genre",
"DRAMA"
],
[
"INSIDE DAISY CLOVER",
"release_year",
"1965"
],
[
"INSIDE DAISY CLOVER",
"starred_actors",
"CHRISTOPHER PLUMMER"
],
[
"INSIDE DAISY CLOVER",
"starred_actors",
"NATALIE WOOD"
],
[
"INSIDE DAISY CLOVER",
"starred_actors",
"ROBERT REDFORD"
],
[
"INSIDE DAISY CLOVER",
"starred_actors",
"RUTH GORDON"
],
[
"INTIMATE LIGHTING",
"has_genre",
"DRAMA"
],
[
"INTIMATE LIGHTING",
"release_year",
"1965"
],
[
"JULIET OF THE SPIRITS",
"has_genre",
"DRAMA"
],
[
"JULIET OF THE SPIRITS",
"release_year",
"1965"
],
[
"LE BONHEUR",
"has_genre",
"DRAMA"
],
[
"LE BONHEUR",
"release_year",
"1965"
],
[
"LIONS FOR LAMBS",
"directed_by",
"ROBERT REDFORD"
],
[
"LIONS FOR LAMBS",
"has_genre",
"DRAMA"
],
[
"LIONS FOR LAMBS",
"has_tags",
"ROBERT REDFORD"
],
[
"LIONS FOR LAMBS",
"starred_actors",
"ROBERT REDFORD"
],
[
"LITTLE FAUSS AND BIG HALSY",
"has_genre",
"DRAMA"
],
[
"LITTLE FAUSS AND BIG HALSY",
"starred_actors",
"ROBERT REDFORD"
],
[
"LOVE WITH THE PROPER STRANGER",
"directed_by",
"ROBERT MULLIGAN"
],
[
"LOVE WITH THE PROPER STRANGER",
"has_genre",
"DRAMA"
],
[
"LOVE WITH THE PROPER STRANGER",
"starred_actors",
"NATALIE WOOD"
],
[
"MARJORIE MORNINGSTAR",
"has_genre",
"DRAMA"
],
[
"MARJORIE MORNINGSTAR",
"starred_actors",
"NATALIE WOOD"
],
[
"MICKEY ONE",
"has_genre",
"DRAMA"
],
[
"MICKEY ONE",
"release_year",
"1965"
],
[
"ORDINARY PEOPLE",
"directed_by",
"ROBERT REDFORD"
],
[
"ORDINARY PEOPLE",
"has_genre",
"DRAMA"
],
[
"ORDINARY PEOPLE",
"has_tags",
"ROBERT REDFORD"
],
[
"OTHELLO",
"has_genre",
"DRAMA"
],
[
"OTHELLO",
"release_year",
"1965"
],
[
"OUT OF AFRICA",
"has_genre",
"DRAMA"
],
[
"OUT OF AFRICA",
"has_tags",
"DRAMA"
],
[
"OUT OF AFRICA",
"has_tags",
"ROBERT REDFORD"
],
[
"OUT OF AFRICA",
"starred_actors",
"ROBERT REDFORD"
],
[
"QUIZ SHOW",
"directed_by",
"ROBERT REDFORD"
],
[
"QUIZ SHOW",
"has_genre",
"DRAMA"
],
[
"QUIZ SHOW",
"has_tags",
"ROBERT REDFORD"
],
[
"SALTO",
"has_genre",
"DRAMA"
],
[
"SALTO",
"release_year",
"1965"
],
[
"SAME TIME, NEXT YEAR",
"directed_by",
"ROBERT MULLIGAN"
],
[
"SAME TIME, NEXT YEAR",
"has_genre",
"DRAMA"
],
[
"SAME TIME, NEXT YEAR",
"has_tags",
"ROBERT MULLIGAN"
],
[
"SHIP OF FOOLS",
"has_genre",
"DRAMA"
],
[
"SHIP OF FOOLS",
"release_year",
"1965"
],
[
"SPLENDOR IN THE GRASS",
"has_genre",
"DRAMA"
],
[
"SPLENDOR IN THE GRASS",
"has_tags",
"NATALIE WOOD"
],
[
"SPLENDOR IN THE GRASS",
"starred_actors",
"NATALIE WOOD"
],
[
"SUMMER OF '42",
"directed_by",
"ROBERT MULLIGAN"
],
[
"SUMMER OF '42",
"has_genre",
"DRAMA"
],
[
"SUMMER OF '42",
"has_tags",
"ROBERT MULLIGAN"
],
[
"THE ACTRESS",
"has_genre",
"DRAMA"
],
[
"THE ACTRESS",
"written_by",
"RUTH GORDON"
],
[
"THE ASHES",
"has_genre",
"DRAMA"
],
[
"THE ASHES",
"release_year",
"1965"
],
[
"THE CANDIDATE",
"has_genre",
"DRAMA"
],
[
"THE CANDIDATE",
"has_tags",
"ROBERT REDFORD"
],
[
"THE CANDIDATE",
"starred_actors",
"ROBERT REDFORD"
],
[
"THE CHASE",
"has_genre",
"DRAMA"
],
[
"THE CHASE",
"has_tags",
"ROBERT REDFORD"
],
[
"THE CHASE",
"starred_actors",
"ROBERT REDFORD"
],
[
"THE CINCINNATI KID",
"has_genre",
"DRAMA"
],
[
"THE CINCINNATI KID",
"release_year",
"1965"
],
[
"THE CONSPIRATOR",
"directed_by",
"ROBERT REDFORD"
],
[
"THE CONSPIRATOR",
"has_genre",
"DRAMA"
],
[
"THE CONSPIRATOR",
"has_tags",
"ROBERT REDFORD"
],
[
"THE FLIGHT OF THE PHOENIX",
"has_genre",
"DRAMA"
],
[
"THE FLIGHT OF THE PHOENIX",
"release_year",
"1965"
],
[
"THE GREAT GATSBY",
"has_genre",
"DRAMA"
],
[
"THE GREAT GATSBY",
"has_tags",
"ROBERT REDFORD"
],
[
"THE GREAT GATSBY",
"starred_actors",
"ROBERT REDFORD"
],
[
"THE GREAT WALDO PEPPER",
"has_genre",
"DRAMA"
],
[
"THE GREAT WALDO PEPPER",
"starred_actors",
"ROBERT REDFORD"
],
[
"THE HORSE WHISPERER",
"directed_by",
"ROBERT REDFORD"
],
[
"THE HORSE WHISPERER",
"has_genre",
"DRAMA"
],
[
"THE HORSE WHISPERER",
"has_tags",
"ROBERT REDFORD"
],
[
"THE HORSE WHISPERER",
"starred_actors",
"ROBERT REDFORD"
],
[
"THE INSIDER",
"has_genre",
"DRAMA"
],
[
"THE INSIDER",
"has_tags",
"DRAMA"
],
[
"THE INSIDER",
"starred_actors",
"CHRISTOPHER PLUMMER"
],
[
"THE LAKE HOUSE",
"has_genre",
"DRAMA"
],
[
"THE LAKE HOUSE",
"starred_actors",
"CHRISTOPHER PLUMMER"
],
[
"THE LAST CASTLE",
"has_genre",
"DRAMA"
],
[
"THE LAST CASTLE",
"has_tags",
"ROBERT REDFORD"
],
[
"THE LAST CASTLE",
"starred_actors",
"ROBERT REDFORD"
],
[
"THE LAST STATION",
"has_genre",
"DRAMA"
],
[
"THE LAST STATION",
"starred_actors",
"CHRISTOPHER PLUMMER"
],
[
"THE MAN IN THE MOON",
"directed_by",
"ROBERT MULLIGAN"
],
[
"THE MAN IN THE MOON",
"has_genre",
"DRAMA"
],
[
"THE MAN IN THE MOON",
"has_tags",
"ROBERT MULLIGAN"
],
[
"THE MILAGRO BEANFIELD WAR",
"directed_by",
"ROBERT REDFORD"
],
[
"THE MILAGRO BEANFIELD WAR",
"has_genre",
"DRAMA"
],
[
"THE MILAGRO BEANFIELD WAR",
"has_tags",
"ROBERT REDFORD"
],
[
"THE MOMENT OF TRUTH",
"has_genre",
"DRAMA"
],
[
"THE MOMENT OF TRUTH",
"release_year",
"1965"
],
[
"THE NEW WORLD",
"has_genre",
"DRAMA"
],
[
"THE NEW WORLD",
"has_tags",
"CHRISTOPHER PLUMMER"
],
[
"THE NEW WORLD",
"starred_actors",
"CHRISTOPHER PLUMMER"
],
[
"THE PURSUIT OF HAPPINESS",
"directed_by",
"ROBERT MULLIGAN"
],
[
"THE PURSUIT OF HAPPINESS",
"has_genre",
"DRAMA"
],
[
"THE RAT RACE",
"directed_by",
"ROBERT MULLIGAN"
],
[
"THE RAT RACE",
"has_genre",
"DRAMA"
],
[
"THE WAR GAME",
"has_genre",
"DRAMA"
],
[
"THE WAR GAME",
"release_year",
"1965"
],
[
"THE WAY WE WERE",
"has_genre",
"DRAMA"
],
[
"THE WAY WE WERE",
"starred_actors",
"ROBERT REDFORD"
],
[
"THE YEARLING",
"has_genre",
"DRAMA"
],
[
"THE YEARLING",
"written_by",
"MARJORIE KINNAN RAWLINGS"
],
[
"THIS PROPERTY IS CONDEMNED",
"has_genre",
"DRAMA"
],
[
"THIS PROPERTY IS CONDEMNED",
"starred_actors",
"NATALIE WOOD"
],
[
"THIS PROPERTY IS CONDEMNED",
"starred_actors",
"ROBERT REDFORD"
],
[
"TO KILL A MOCKINGBIRD",
"directed_by",
"ROBERT MULLIGAN"
],
[
"TO KILL A MOCKINGBIRD",
"has_genre",
"DRAMA"
],
[
"TO KILL A MOCKINGBIRD",
"has_tags",
"DRAMA"
],
[
"TO KILL A MOCKINGBIRD",
"has_tags",
"ROBERT MULLIGAN"
],
[
"UP THE DOWN STAIRCASE",
"directed_by",
"ROBERT MULLIGAN"
],
[
"UP THE DOWN STAIRCASE",
"has_genre",
"DRAMA"
],
[
"WEST SIDE STORY",
"has_genre",
"DRAMA"
],
[
"WEST SIDE STORY",
"has_tags",
"NATALIE WOOD"
],
[
"WEST SIDE STORY",
"starred_actors",
"NATALIE WOOD"
],
[
"YOUNG CASSIDY",
"has_genre",
"DRAMA"
],
[
"YOUNG CASSIDY",
"release_year",
"1965"
]
]
}
|
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
2133, 1998
16654, BRITISH
25595, EDEN LAKE
6583, ELIZABETH
23434, HISTORICAL
23749, JODHAA AKBAR
14601, LES MISÉRABLES
38721, LOCK, STOCK AND TWO SMOKING BARRELS
3657, SHAKESPEARE IN LOVE
28065, SLIDING DOORS
12691, THE PATRIOT
33585, THURSDAY
src, edge_attr, dst
25595, has_tags, 16654
6583, has_tags, 16654
6583, release_year, 2133
23749, has_tags, 23434
14601, has_tags, 23434
14601, release_year, 2133
38721, has_tags, 16654
38721, release_year, 2133
3657, has_tags, 16654
3657, release_year, 2133
28065, has_tags, 16654
28065, release_year, 2133
12691, has_tags, 23434
12691, release_year, 2133
33585, release_year, 2133
Question: In what context are EDEN LAKE, JODHAA AKBAR, and THURSDAY connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"EDEN LAKE",
"JODHAA AKBAR",
"THURSDAY"
],
"valid_edges": [
[
"EDEN LAKE",
"has_tags",
"BRITISH"
],
[
"ELIZABETH",
"has_tags",
"BRITISH"
],
[
"ELIZABETH",
"release_year",
"1998"
],
[
"JODHAA AKBAR",
"has_tags",
"HISTORICAL"
],
[
"LES MISÉRABLES",
"has_tags",
"HISTORICAL"
],
[
"LES MISÉRABLES",
"release_year",
"1998"
],
[
"LOCK, STOCK AND TWO SMOKING BARRELS",
"has_tags",
"BRITISH"
],
[
"LOCK, STOCK AND TWO SMOKING BARRELS",
"release_year",
"1998"
],
[
"SHAKESPEARE IN LOVE",
"has_tags",
"BRITISH"
],
[
"SHAKESPEARE IN LOVE",
"release_year",
"1998"
],
[
"SLIDING DOORS",
"has_tags",
"BRITISH"
],
[
"SLIDING DOORS",
"release_year",
"1998"
],
[
"THE PATRIOT",
"has_tags",
"HISTORICAL"
],
[
"THE PATRIOT",
"release_year",
"1998"
],
[
"THURSDAY",
"release_year",
"1998"
]
]
}
|
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
36212, DRAMA
7356, JULIA WHELAN
21197, LIGHT IT UP
29869, PASCALI'S ISLAND
38139, THE SECRET LIFE OF ZOEY
src, edge_attr, dst
21197, has_genre, 36212
29869, has_genre, 36212
38139, has_genre, 36212
38139, starred_actors, 7356
Question: In what context are JULIA WHELAN, LIGHT IT UP, and PASCALI'S ISLAND connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"JULIA WHELAN",
"LIGHT IT UP",
"PASCALI'S ISLAND"
],
"valid_edges": [
[
"LIGHT IT UP",
"has_genre",
"DRAMA"
],
[
"PASCALI'S ISLAND",
"has_genre",
"DRAMA"
],
[
"THE SECRET LIFE OF ZOEY",
"has_genre",
"DRAMA"
],
[
"THE SECRET LIFE OF ZOEY",
"starred_actors",
"JULIA WHELAN"
]
]
}
|
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
27513, ALL MINE TO GIVE
16359, CAMERON MITCHELL
32880, COME BACK, LITTLE SHEBA
36212, DRAMA
25775, HOLD BACK THE DAWN
36738, KETTI FRINGS
103, LOVE ME OR LEAVE ME
31011, LYMELIFE
20283, MEAN CREEK
28273, RORY CULKIN
3578, SMALL TOWN
12162, YOU CAN COUNT ON ME
src, edge_attr, dst
27513, has_genre, 36212
27513, starred_actors, 16359
32880, has_genre, 36212
32880, written_by, 36738
25775, has_genre, 36212
25775, written_by, 36738
103, has_genre, 36212
103, starred_actors, 16359
31011, has_genre, 36212
31011, starred_actors, 28273
20283, has_genre, 36212
20283, has_tags, 36212
20283, has_tags, 28273
20283, has_tags, 3578
20283, starred_actors, 28273
12162, has_genre, 36212
12162, has_tags, 3578
12162, starred_actors, 28273
Question: How are CAMERON MITCHELL, KETTI FRINGS, and RORY CULKIN related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"CAMERON MITCHELL",
"KETTI FRINGS",
"RORY CULKIN"
],
"valid_edges": [
[
"ALL MINE TO GIVE",
"has_genre",
"DRAMA"
],
[
"ALL MINE TO GIVE",
"starred_actors",
"CAMERON MITCHELL"
],
[
"COME BACK, LITTLE SHEBA",
"has_genre",
"DRAMA"
],
[
"COME BACK, LITTLE SHEBA",
"written_by",
"KETTI FRINGS"
],
[
"HOLD BACK THE DAWN",
"has_genre",
"DRAMA"
],
[
"HOLD BACK THE DAWN",
"written_by",
"KETTI FRINGS"
],
[
"LOVE ME OR LEAVE ME",
"has_genre",
"DRAMA"
],
[
"LOVE ME OR LEAVE ME",
"starred_actors",
"CAMERON MITCHELL"
],
[
"LYMELIFE",
"has_genre",
"DRAMA"
],
[
"LYMELIFE",
"starred_actors",
"RORY CULKIN"
],
[
"MEAN CREEK",
"has_genre",
"DRAMA"
],
[
"MEAN CREEK",
"has_tags",
"DRAMA"
],
[
"MEAN CREEK",
"has_tags",
"RORY CULKIN"
],
[
"MEAN CREEK",
"has_tags",
"SMALL TOWN"
],
[
"MEAN CREEK",
"starred_actors",
"RORY CULKIN"
],
[
"YOU CAN COUNT ON ME",
"has_genre",
"DRAMA"
],
[
"YOU CAN COUNT ON ME",
"has_tags",
"SMALL TOWN"
],
[
"YOU CAN COUNT ON ME",
"starred_actors",
"RORY CULKIN"
]
]
}
|
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
8473, ADAPTATION
5314, CHAN IS MISSING
5994, ISAAC CRONIN
7539, IVANHOE
34266, KEN POGUE
11255, THE GREY FOX
src, edge_attr, dst
5314, release_year, 8539
5314, written_by, 5994
7539, has_tags, 8473
7539, release_year, 8539
11255, release_year, 8539
11255, starred_actors, 34266
Question: In what context are ADAPTATION, ISAAC CRONIN, and KEN POGUE connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"ADAPTATION",
"ISAAC CRONIN",
"KEN POGUE"
],
"valid_edges": [
[
"CHAN IS MISSING",
"release_year",
"1982"
],
[
"CHAN IS MISSING",
"written_by",
"ISAAC CRONIN"
],
[
"IVANHOE",
"has_tags",
"ADAPTATION"
],
[
"IVANHOE",
"release_year",
"1982"
],
[
"THE GREY FOX",
"release_year",
"1982"
],
[
"THE GREY FOX",
"starred_actors",
"KEN POGUE"
]
]
}
|
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
28171, 1986
7841, 1987
4713, A RETURN TO SALEM'S LOT
39750, ALIENS
25905, ANGEL HEART
6748, ANGUISH
18169, APRIL FOOL'S DAY
34587, BAD TASTE
36535, CHOPPING MALL
14884, CLASS OF NUKE 'EM HIGH
22349, CRAWLSPACE
19984, CREEPSHOW 2
6743, CRITTERS
21213, DEADLY FRIEND
31980, DEMONS 2
23612, DOLLS
16661, EVIL DEAD II
3270, FROM BEYOND
30778, GOTHIC
1889, GUNG HO
12498, HELLRAISER
5870, HORROR
10147, HOUSE
13070, INVADERS FROM MARS
24952, LINK
8851, LITTLE SHOP OF HORRORS
3129, MAXIMUM OVERDRIVE
20500, MONSTER IN THE CLOSET
18402, MOUNTAINTOP MOTEL MASSACRE
36631, MUNCHIES
14237, NEAR DARK
15661, NEKROMANTIK
11181, NIGHT OF THE CREEPS
39105, NOMADS
38962, OPERA
24051, PARASOMNIA
4323, PRINCE OF DARKNESS
17526, PSYCHO III
31164, RAWHEAD REX
9184, RETURN TO HORROR HIGH
18856, ROCK 'N' ROLL NIGHTMARE
11041, SILENT NIGHT, DEADLY NIGHT PART 2
5932, TERRORVISION
28739, THE BELIEVERS
8063, THE CURSE
16105, THE DEAD
32392, THE FLY
38230, THE GATE
3318, THE LOST BOYS
33993, THE MONSTER SQUAD
35993, THE STEPFATHER
9715, THE TEXAS CHAINSAW MASSACRE 2
17409, TRICK OR TREAT
8589, WICKED CITY
6981, WISH YOU WERE HERE
36013, WITCHBOARD
src, edge_attr, dst
4713, has_genre, 5870
4713, release_year, 7841
39750, has_tags, 5870
39750, release_year, 28171
25905, has_genre, 5870
25905, release_year, 7841
6748, has_genre, 5870
6748, release_year, 7841
18169, has_genre, 5870
18169, release_year, 28171
34587, has_genre, 5870
34587, release_year, 7841
36535, has_genre, 5870
36535, release_year, 28171
14884, has_genre, 5870
14884, release_year, 28171
22349, has_genre, 5870
22349, release_year, 28171
19984, has_genre, 5870
19984, release_year, 7841
6743, has_genre, 5870
6743, release_year, 28171
21213, has_genre, 5870
21213, release_year, 28171
31980, has_genre, 5870
31980, release_year, 28171
23612, has_genre, 5870
23612, release_year, 7841
16661, has_genre, 5870
16661, has_tags, 5870
16661, release_year, 7841
3270, has_genre, 5870
3270, release_year, 28171
30778, has_genre, 5870
30778, release_year, 28171
1889, release_year, 28171
12498, has_genre, 5870
12498, has_tags, 5870
12498, release_year, 7841
10147, has_genre, 5870
10147, release_year, 28171
13070, has_genre, 5870
13070, release_year, 28171
24952, has_genre, 5870
24952, release_year, 28171
8851, has_genre, 5870
8851, release_year, 28171
3129, has_genre, 5870
3129, release_year, 28171
20500, has_genre, 5870
20500, release_year, 28171
18402, has_genre, 5870
18402, release_year, 28171
36631, has_genre, 5870
36631, release_year, 7841
14237, has_genre, 5870
14237, release_year, 7841
15661, has_genre, 5870
15661, release_year, 7841
11181, has_genre, 5870
11181, release_year, 28171
39105, has_genre, 5870
39105, release_year, 28171
38962, has_genre, 5870
38962, release_year, 7841
24051, has_genre, 5870
4323, has_genre, 5870
4323, release_year, 7841
17526, has_genre, 5870
17526, release_year, 28171
31164, has_genre, 5870
31164, release_year, 28171
9184, has_genre, 5870
9184, release_year, 7841
18856, has_genre, 5870
18856, release_year, 7841
11041, has_genre, 5870
11041, release_year, 7841
5932, has_genre, 5870
5932, release_year, 28171
28739, has_genre, 5870
28739, release_year, 7841
8063, has_genre, 5870
8063, release_year, 7841
16105, has_genre, 5870
16105, release_year, 7841
32392, has_genre, 5870
32392, has_tags, 5870
32392, release_year, 28171
38230, has_genre, 5870
38230, release_year, 7841
3318, has_genre, 5870
3318, has_tags, 5870
3318, release_year, 7841
33993, has_tags, 5870
33993, release_year, 7841
35993, has_genre, 5870
35993, release_year, 7841
9715, has_genre, 5870
9715, has_tags, 5870
9715, release_year, 28171
17409, has_genre, 5870
17409, release_year, 28171
8589, has_genre, 5870
8589, release_year, 7841
6981, release_year, 7841
36013, has_genre, 5870
36013, release_year, 28171
Question: In what context are GUNG HO, PARASOMNIA, and WISH YOU WERE HERE connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"GUNG HO",
"PARASOMNIA",
"WISH YOU WERE HERE"
],
"valid_edges": [
[
"A RETURN TO SALEM'S LOT",
"has_genre",
"HORROR"
],
[
"A RETURN TO SALEM'S LOT",
"release_year",
"1987"
],
[
"ALIENS",
"has_tags",
"HORROR"
],
[
"ALIENS",
"release_year",
"1986"
],
[
"ANGEL HEART",
"has_genre",
"HORROR"
],
[
"ANGEL HEART",
"release_year",
"1987"
],
[
"ANGUISH",
"has_genre",
"HORROR"
],
[
"ANGUISH",
"release_year",
"1987"
],
[
"APRIL FOOL'S DAY",
"has_genre",
"HORROR"
],
[
"APRIL FOOL'S DAY",
"release_year",
"1986"
],
[
"BAD TASTE",
"has_genre",
"HORROR"
],
[
"BAD TASTE",
"release_year",
"1987"
],
[
"CHOPPING MALL",
"has_genre",
"HORROR"
],
[
"CHOPPING MALL",
"release_year",
"1986"
],
[
"CLASS OF NUKE 'EM HIGH",
"has_genre",
"HORROR"
],
[
"CLASS OF NUKE 'EM HIGH",
"release_year",
"1986"
],
[
"CRAWLSPACE",
"has_genre",
"HORROR"
],
[
"CRAWLSPACE",
"release_year",
"1986"
],
[
"CREEPSHOW 2",
"has_genre",
"HORROR"
],
[
"CREEPSHOW 2",
"release_year",
"1987"
],
[
"CRITTERS",
"has_genre",
"HORROR"
],
[
"CRITTERS",
"release_year",
"1986"
],
[
"DEADLY FRIEND",
"has_genre",
"HORROR"
],
[
"DEADLY FRIEND",
"release_year",
"1986"
],
[
"DEMONS 2",
"has_genre",
"HORROR"
],
[
"DEMONS 2",
"release_year",
"1986"
],
[
"DOLLS",
"has_genre",
"HORROR"
],
[
"DOLLS",
"release_year",
"1987"
],
[
"EVIL DEAD II",
"has_genre",
"HORROR"
],
[
"EVIL DEAD II",
"has_tags",
"HORROR"
],
[
"EVIL DEAD II",
"release_year",
"1987"
],
[
"FROM BEYOND",
"has_genre",
"HORROR"
],
[
"FROM BEYOND",
"release_year",
"1986"
],
[
"GOTHIC",
"has_genre",
"HORROR"
],
[
"GOTHIC",
"release_year",
"1986"
],
[
"GUNG HO",
"release_year",
"1986"
],
[
"HELLRAISER",
"has_genre",
"HORROR"
],
[
"HELLRAISER",
"has_tags",
"HORROR"
],
[
"HELLRAISER",
"release_year",
"1987"
],
[
"HOUSE",
"has_genre",
"HORROR"
],
[
"HOUSE",
"release_year",
"1986"
],
[
"INVADERS FROM MARS",
"has_genre",
"HORROR"
],
[
"INVADERS FROM MARS",
"release_year",
"1986"
],
[
"LINK",
"has_genre",
"HORROR"
],
[
"LINK",
"release_year",
"1986"
],
[
"LITTLE SHOP OF HORRORS",
"has_genre",
"HORROR"
],
[
"LITTLE SHOP OF HORRORS",
"release_year",
"1986"
],
[
"MAXIMUM OVERDRIVE",
"has_genre",
"HORROR"
],
[
"MAXIMUM OVERDRIVE",
"release_year",
"1986"
],
[
"MONSTER IN THE CLOSET",
"has_genre",
"HORROR"
],
[
"MONSTER IN THE CLOSET",
"release_year",
"1986"
],
[
"MOUNTAINTOP MOTEL MASSACRE",
"has_genre",
"HORROR"
],
[
"MOUNTAINTOP MOTEL MASSACRE",
"release_year",
"1986"
],
[
"MUNCHIES",
"has_genre",
"HORROR"
],
[
"MUNCHIES",
"release_year",
"1987"
],
[
"NEAR DARK",
"has_genre",
"HORROR"
],
[
"NEAR DARK",
"release_year",
"1987"
],
[
"NEKROMANTIK",
"has_genre",
"HORROR"
],
[
"NEKROMANTIK",
"release_year",
"1987"
],
[
"NIGHT OF THE CREEPS",
"has_genre",
"HORROR"
],
[
"NIGHT OF THE CREEPS",
"release_year",
"1986"
],
[
"NOMADS",
"has_genre",
"HORROR"
],
[
"NOMADS",
"release_year",
"1986"
],
[
"OPERA",
"has_genre",
"HORROR"
],
[
"OPERA",
"release_year",
"1987"
],
[
"PARASOMNIA",
"has_genre",
"HORROR"
],
[
"PRINCE OF DARKNESS",
"has_genre",
"HORROR"
],
[
"PRINCE OF DARKNESS",
"release_year",
"1987"
],
[
"PSYCHO III",
"has_genre",
"HORROR"
],
[
"PSYCHO III",
"release_year",
"1986"
],
[
"RAWHEAD REX",
"has_genre",
"HORROR"
],
[
"RAWHEAD REX",
"release_year",
"1986"
],
[
"RETURN TO HORROR HIGH",
"has_genre",
"HORROR"
],
[
"RETURN TO HORROR HIGH",
"release_year",
"1987"
],
[
"ROCK 'N' ROLL NIGHTMARE",
"has_genre",
"HORROR"
],
[
"ROCK 'N' ROLL NIGHTMARE",
"release_year",
"1987"
],
[
"SILENT NIGHT, DEADLY NIGHT PART 2",
"has_genre",
"HORROR"
],
[
"SILENT NIGHT, DEADLY NIGHT PART 2",
"release_year",
"1987"
],
[
"TERRORVISION",
"has_genre",
"HORROR"
],
[
"TERRORVISION",
"release_year",
"1986"
],
[
"THE BELIEVERS",
"has_genre",
"HORROR"
],
[
"THE BELIEVERS",
"release_year",
"1987"
],
[
"THE CURSE",
"has_genre",
"HORROR"
],
[
"THE CURSE",
"release_year",
"1987"
],
[
"THE DEAD",
"has_genre",
"HORROR"
],
[
"THE DEAD",
"release_year",
"1987"
],
[
"THE FLY",
"has_genre",
"HORROR"
],
[
"THE FLY",
"has_tags",
"HORROR"
],
[
"THE FLY",
"release_year",
"1986"
],
[
"THE GATE",
"has_genre",
"HORROR"
],
[
"THE GATE",
"release_year",
"1987"
],
[
"THE LOST BOYS",
"has_genre",
"HORROR"
],
[
"THE LOST BOYS",
"has_tags",
"HORROR"
],
[
"THE LOST BOYS",
"release_year",
"1987"
],
[
"THE MONSTER SQUAD",
"has_tags",
"HORROR"
],
[
"THE MONSTER SQUAD",
"release_year",
"1987"
],
[
"THE STEPFATHER",
"has_genre",
"HORROR"
],
[
"THE STEPFATHER",
"release_year",
"1987"
],
[
"THE TEXAS CHAINSAW MASSACRE 2",
"has_genre",
"HORROR"
],
[
"THE TEXAS CHAINSAW MASSACRE 2",
"has_tags",
"HORROR"
],
[
"THE TEXAS CHAINSAW MASSACRE 2",
"release_year",
"1986"
],
[
"TRICK OR TREAT",
"has_genre",
"HORROR"
],
[
"TRICK OR TREAT",
"release_year",
"1986"
],
[
"WICKED CITY",
"has_genre",
"HORROR"
],
[
"WICKED CITY",
"release_year",
"1987"
],
[
"WISH YOU WERE HERE",
"release_year",
"1987"
],
[
"WITCHBOARD",
"has_genre",
"HORROR"
],
[
"WITCHBOARD",
"release_year",
"1986"
]
]
}
|
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
11, 1940
31486, 1970
7627, A MAN CALLED HORSE
39604, A MAN CALLED SLEDGE
35381, A SWEDISH LOVE STORY
24629, AIRPORT
10018, ALEX IN WONDERLAND
4617, ALL THIS, AND HEAVEN TOO
10251, ARIZONA
25642, BLIND HUSBANDS
28626, BLOODY MAMA
16749, BROKEN ARROW
21600, CASTLE ON THE HUDSON
6702, CHISUM
9167, CITY FOR CONQUEST
32819, CROMWELL
30624, DANCES WITH WOLVES
8663, DEEP END
3443, DIARY OF A MAD HOUSEWIFE
37896, DIRTY DINGUS MAGEE
30123, DORIAN GRAY
36212, DRAMA
17266, DUST
28377, EL TOPO
21933, ERICH VON STROHEIM
1872, ESCAPE
27432, EVEN DWARFS STARTED SMALL
26417, FIVE EASY PIECES
29776, FOOLISH WIVES
11672, FOREVER AMBER
24894, FOUR SONS
31804, GODS OF THE PLAGUE
19699, HEIDI
30299, I WAS AN ADVENTURESS
37110, INVESTIGATION OF A CITIZEN ABOVE SUSPICION
21922, JANE EYRE
35629, JOE
6774, JOHANNA SPYRI
33417, JOHNNY GUITAR
1025, LEO THE LAST
33575, LITTLE BIG MAN
7383, LITTLE FAUSS AND BIG HALSY
6180, LOVE STORY
6932, M
39818, MACHIBUSE
17728, MAD LOVE
24611, MY LITTLE CHICKADEE
23166, NO TIME FOR COMEDY
23553, OUR TOWN
31056, PERFORMANCE
7760, PETER LORRE
23220, REMEMBER THE NIGHT
19539, RICHARD GREENE
667, RIO LOBO
4635, SERENITY
20390, SOLDIER BLUE
32850, SOMETIMES A GREAT NOTION
38027, SUNFLOWER
16069, THE APE
13664, THE ASSASSINATION OF JESSE JAMES BY THE COWARD ROBERT FORD
8125, THE BOYS IN THE BAND
7763, THE CHEYENNE SOCIAL CLUB
6150, THE CONFESSION
2356, THE CONFORMIST
28711, THE FACE BEHIND THE MASK
1748, THE GRAPES OF WRATH
3602, THE GREAT GABBO
33180, THE GREAT WHITE HOPE
25238, THE HI-LO COUNTRY
14626, THE HOMESMAN
2887, THE HOUSE OF THE SEVEN GABLES
33948, THE LETTER
14149, THE LIBERATION OF L.B. JONES
29117, THE LONG VOYAGE HOME
15492, THE MASK OF DIMITRIOS
13288, THE MISFITS
15853, THE MOLLY MAGUIRES
1533, THE MORTAL STORM
22829, THE MUSIC LOVERS
27029, THE PROPOSITION
144, THE RAILWAY CHILDREN
11585, THE SEA OF GRASS
33389, THE SPOILERS
279, THE VERDICT
13003, THE WELL-DIGGER'S DAUGHTER
7342, THEY CALL ME TRINITY
38674, THREE STRANGERS
16940, TORA! TORA! TORA!
33147, UNION PACIFIC
13388, URBAN COWBOY
26135, WANDA
29665, WATERLOO BRIDGE
29856, WATERMELON MAN
36026, WESTERN
23471, WHY DOES HERR R. RUN AMOK?
17354, WITCHHAMMER
25840, WUSA
27708, WUTHERING HEIGHTS
3421, YOUNG PEOPLE
29857, ZATOICHI MEETS YOJIMBO
src, edge_attr, dst
7627, has_genre, 36026
7627, release_year, 31486
39604, has_genre, 36026
39604, release_year, 31486
35381, has_genre, 36212
35381, release_year, 31486
24629, has_genre, 36212
24629, release_year, 31486
10018, has_genre, 36212
10018, release_year, 31486
4617, has_genre, 36212
4617, release_year, 11
10251, has_genre, 36026
10251, release_year, 11
25642, directed_by, 21933
25642, has_genre, 36212
25642, starred_actors, 21933
25642, written_by, 21933
28626, has_genre, 36212
28626, release_year, 31486
16749, has_genre, 36212
16749, has_genre, 36026
21600, has_genre, 36212
21600, release_year, 11
6702, has_genre, 36026
6702, release_year, 31486
9167, has_genre, 36212
9167, release_year, 11
32819, has_genre, 36212
32819, release_year, 31486
30624, has_genre, 36212
30624, has_genre, 36026
30624, has_tags, 36212
30624, has_tags, 36026
8663, has_genre, 36212
8663, release_year, 31486
3443, has_genre, 36212
3443, release_year, 31486
37896, has_genre, 36026
37896, release_year, 31486
30123, has_genre, 36212
30123, release_year, 31486
17266, has_genre, 36212
17266, has_genre, 36026
28377, has_genre, 36026
28377, has_tags, 36026
28377, release_year, 31486
1872, has_genre, 36212
1872, release_year, 11
27432, has_genre, 36212
27432, release_year, 31486
26417, has_genre, 36212
26417, release_year, 31486
29776, directed_by, 21933
29776, has_genre, 36212
29776, has_tags, 21933
29776, written_by, 21933
11672, has_genre, 36212
11672, starred_actors, 19539
24894, has_genre, 36212
24894, release_year, 11
31804, has_genre, 36212
31804, release_year, 31486
19699, has_genre, 36212
19699, written_by, 6774
30299, has_genre, 36212
30299, release_year, 11
30299, starred_actors, 21933
30299, starred_actors, 7760
30299, starred_actors, 19539
37110, has_genre, 36212
37110, release_year, 31486
21922, has_genre, 36212
21922, release_year, 31486
35629, has_genre, 36212
35629, release_year, 31486
33417, has_genre, 36212
33417, has_genre, 36026
33417, has_tags, 36026
1025, has_genre, 36212
1025, release_year, 31486
33575, has_genre, 36026
33575, release_year, 31486
7383, has_genre, 36212
7383, release_year, 31486
6180, has_genre, 36212
6180, release_year, 31486
6932, has_genre, 36212
6932, has_tags, 7760
6932, starred_actors, 7760
39818, has_genre, 36212
39818, release_year, 31486
17728, has_genre, 36212
17728, has_tags, 7760
17728, starred_actors, 7760
24611, has_genre, 36026
24611, release_year, 11
23166, has_genre, 36212
23166, release_year, 11
23553, has_genre, 36212
23553, release_year, 11
31056, has_genre, 36212
31056, release_year, 31486
23220, has_genre, 36212
23220, release_year, 11
667, has_genre, 36026
667, release_year, 31486
4635, has_tags, 36212
4635, has_tags, 36026
20390, has_genre, 36026
20390, release_year, 31486
32850, has_genre, 36212
32850, release_year, 31486
38027, has_genre, 36212
38027, release_year, 31486
16069, has_genre, 36212
16069, release_year, 11
13664, has_genre, 36212
13664, has_tags, 36026
8125, has_genre, 36212
8125, release_year, 31486
7763, has_genre, 36026
7763, release_year, 31486
6150, has_genre, 36212
6150, release_year, 31486
2356, has_genre, 36212
2356, release_year, 31486
28711, has_genre, 36212
28711, starred_actors, 7760
1748, has_genre, 36212
1748, release_year, 11
3602, directed_by, 21933
3602, has_genre, 36212
3602, starred_actors, 21933
33180, has_genre, 36212
33180, release_year, 31486
25238, has_genre, 36212
25238, has_genre, 36026
14626, has_genre, 36212
14626, has_genre, 36026
2887, has_genre, 36212
2887, release_year, 11
33948, has_genre, 36212
33948, release_year, 11
14149, has_genre, 36212
14149, release_year, 31486
29117, has_genre, 36212
29117, release_year, 11
15492, has_genre, 36212
15492, starred_actors, 7760
13288, has_genre, 36212
13288, has_genre, 36026
15853, has_genre, 36212
15853, release_year, 31486
1533, has_genre, 36212
1533, release_year, 11
22829, has_genre, 36212
22829, release_year, 31486
27029, has_genre, 36212
27029, has_genre, 36026
144, has_genre, 36212
144, release_year, 31486
11585, has_genre, 36212
11585, has_genre, 36026
33389, has_genre, 36212
33389, has_genre, 36026
279, has_genre, 36212
279, starred_actors, 7760
13003, has_genre, 36212
13003, release_year, 11
7342, has_genre, 36026
7342, release_year, 31486
38674, has_genre, 36212
38674, starred_actors, 7760
16940, has_genre, 36212
16940, release_year, 31486
33147, has_genre, 36212
33147, has_genre, 36026
13388, has_genre, 36212
13388, has_genre, 36026
26135, has_genre, 36212
26135, release_year, 31486
29665, has_genre, 36212
29665, release_year, 11
29856, has_genre, 36212
29856, release_year, 31486
23471, has_genre, 36212
23471, release_year, 31486
17354, has_genre, 36212
17354, release_year, 31486
25840, has_genre, 36212
25840, release_year, 31486
27708, has_genre, 36212
27708, release_year, 31486
3421, has_genre, 36212
3421, release_year, 11
29857, has_genre, 36212
29857, release_year, 31486
Question: In what context are EL TOPO, I WAS AN ADVENTURESS, and JOHANNA SPYRI connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"EL TOPO",
"I WAS AN ADVENTURESS",
"JOHANNA SPYRI"
],
"valid_edges": [
[
"A MAN CALLED HORSE",
"has_genre",
"WESTERN"
],
[
"A MAN CALLED HORSE",
"release_year",
"1970"
],
[
"A MAN CALLED SLEDGE",
"has_genre",
"WESTERN"
],
[
"A MAN CALLED SLEDGE",
"release_year",
"1970"
],
[
"A SWEDISH LOVE STORY",
"has_genre",
"DRAMA"
],
[
"A SWEDISH LOVE STORY",
"release_year",
"1970"
],
[
"AIRPORT",
"has_genre",
"DRAMA"
],
[
"AIRPORT",
"release_year",
"1970"
],
[
"ALEX IN WONDERLAND",
"has_genre",
"DRAMA"
],
[
"ALEX IN WONDERLAND",
"release_year",
"1970"
],
[
"ALL THIS, AND HEAVEN TOO",
"has_genre",
"DRAMA"
],
[
"ALL THIS, AND HEAVEN TOO",
"release_year",
"1940"
],
[
"ARIZONA",
"has_genre",
"WESTERN"
],
[
"ARIZONA",
"release_year",
"1940"
],
[
"BLIND HUSBANDS",
"directed_by",
"ERICH VON STROHEIM"
],
[
"BLIND HUSBANDS",
"has_genre",
"DRAMA"
],
[
"BLIND HUSBANDS",
"starred_actors",
"ERICH VON STROHEIM"
],
[
"BLIND HUSBANDS",
"written_by",
"ERICH VON STROHEIM"
],
[
"BLOODY MAMA",
"has_genre",
"DRAMA"
],
[
"BLOODY MAMA",
"release_year",
"1970"
],
[
"BROKEN ARROW",
"has_genre",
"DRAMA"
],
[
"BROKEN ARROW",
"has_genre",
"WESTERN"
],
[
"CASTLE ON THE HUDSON",
"has_genre",
"DRAMA"
],
[
"CASTLE ON THE HUDSON",
"release_year",
"1940"
],
[
"CHISUM",
"has_genre",
"WESTERN"
],
[
"CHISUM",
"release_year",
"1970"
],
[
"CITY FOR CONQUEST",
"has_genre",
"DRAMA"
],
[
"CITY FOR CONQUEST",
"release_year",
"1940"
],
[
"CROMWELL",
"has_genre",
"DRAMA"
],
[
"CROMWELL",
"release_year",
"1970"
],
[
"DANCES WITH WOLVES",
"has_genre",
"DRAMA"
],
[
"DANCES WITH WOLVES",
"has_genre",
"WESTERN"
],
[
"DANCES WITH WOLVES",
"has_tags",
"DRAMA"
],
[
"DANCES WITH WOLVES",
"has_tags",
"WESTERN"
],
[
"DEEP END",
"has_genre",
"DRAMA"
],
[
"DEEP END",
"release_year",
"1970"
],
[
"DIARY OF A MAD HOUSEWIFE",
"has_genre",
"DRAMA"
],
[
"DIARY OF A MAD HOUSEWIFE",
"release_year",
"1970"
],
[
"DIRTY DINGUS MAGEE",
"has_genre",
"WESTERN"
],
[
"DIRTY DINGUS MAGEE",
"release_year",
"1970"
],
[
"DORIAN GRAY",
"has_genre",
"DRAMA"
],
[
"DORIAN GRAY",
"release_year",
"1970"
],
[
"DUST",
"has_genre",
"DRAMA"
],
[
"DUST",
"has_genre",
"WESTERN"
],
[
"EL TOPO",
"has_genre",
"WESTERN"
],
[
"EL TOPO",
"has_tags",
"WESTERN"
],
[
"EL TOPO",
"release_year",
"1970"
],
[
"ESCAPE",
"has_genre",
"DRAMA"
],
[
"ESCAPE",
"release_year",
"1940"
],
[
"EVEN DWARFS STARTED SMALL",
"has_genre",
"DRAMA"
],
[
"EVEN DWARFS STARTED SMALL",
"release_year",
"1970"
],
[
"FIVE EASY PIECES",
"has_genre",
"DRAMA"
],
[
"FIVE EASY PIECES",
"release_year",
"1970"
],
[
"FOOLISH WIVES",
"directed_by",
"ERICH VON STROHEIM"
],
[
"FOOLISH WIVES",
"has_genre",
"DRAMA"
],
[
"FOOLISH WIVES",
"has_tags",
"ERICH VON STROHEIM"
],
[
"FOOLISH WIVES",
"written_by",
"ERICH VON STROHEIM"
],
[
"FOREVER AMBER",
"has_genre",
"DRAMA"
],
[
"FOREVER AMBER",
"starred_actors",
"RICHARD GREENE"
],
[
"FOUR SONS",
"has_genre",
"DRAMA"
],
[
"FOUR SONS",
"release_year",
"1940"
],
[
"GODS OF THE PLAGUE",
"has_genre",
"DRAMA"
],
[
"GODS OF THE PLAGUE",
"release_year",
"1970"
],
[
"HEIDI",
"has_genre",
"DRAMA"
],
[
"HEIDI",
"written_by",
"JOHANNA SPYRI"
],
[
"I WAS AN ADVENTURESS",
"has_genre",
"DRAMA"
],
[
"I WAS AN ADVENTURESS",
"release_year",
"1940"
],
[
"I WAS AN ADVENTURESS",
"starred_actors",
"ERICH VON STROHEIM"
],
[
"I WAS AN ADVENTURESS",
"starred_actors",
"PETER LORRE"
],
[
"I WAS AN ADVENTURESS",
"starred_actors",
"RICHARD GREENE"
],
[
"INVESTIGATION OF A CITIZEN ABOVE SUSPICION",
"has_genre",
"DRAMA"
],
[
"INVESTIGATION OF A CITIZEN ABOVE SUSPICION",
"release_year",
"1970"
],
[
"JANE EYRE",
"has_genre",
"DRAMA"
],
[
"JANE EYRE",
"release_year",
"1970"
],
[
"JOE",
"has_genre",
"DRAMA"
],
[
"JOE",
"release_year",
"1970"
],
[
"JOHNNY GUITAR",
"has_genre",
"DRAMA"
],
[
"JOHNNY GUITAR",
"has_genre",
"WESTERN"
],
[
"JOHNNY GUITAR",
"has_tags",
"WESTERN"
],
[
"LEO THE LAST",
"has_genre",
"DRAMA"
],
[
"LEO THE LAST",
"release_year",
"1970"
],
[
"LITTLE BIG MAN",
"has_genre",
"WESTERN"
],
[
"LITTLE BIG MAN",
"release_year",
"1970"
],
[
"LITTLE FAUSS AND BIG HALSY",
"has_genre",
"DRAMA"
],
[
"LITTLE FAUSS AND BIG HALSY",
"release_year",
"1970"
],
[
"LOVE STORY",
"has_genre",
"DRAMA"
],
[
"LOVE STORY",
"release_year",
"1970"
],
[
"M",
"has_genre",
"DRAMA"
],
[
"M",
"has_tags",
"PETER LORRE"
],
[
"M",
"starred_actors",
"PETER LORRE"
],
[
"MACHIBUSE",
"has_genre",
"DRAMA"
],
[
"MACHIBUSE",
"release_year",
"1970"
],
[
"MAD LOVE",
"has_genre",
"DRAMA"
],
[
"MAD LOVE",
"has_tags",
"PETER LORRE"
],
[
"MAD LOVE",
"starred_actors",
"PETER LORRE"
],
[
"MY LITTLE CHICKADEE",
"has_genre",
"WESTERN"
],
[
"MY LITTLE CHICKADEE",
"release_year",
"1940"
],
[
"NO TIME FOR COMEDY",
"has_genre",
"DRAMA"
],
[
"NO TIME FOR COMEDY",
"release_year",
"1940"
],
[
"OUR TOWN",
"has_genre",
"DRAMA"
],
[
"OUR TOWN",
"release_year",
"1940"
],
[
"PERFORMANCE",
"has_genre",
"DRAMA"
],
[
"PERFORMANCE",
"release_year",
"1970"
],
[
"REMEMBER THE NIGHT",
"has_genre",
"DRAMA"
],
[
"REMEMBER THE NIGHT",
"release_year",
"1940"
],
[
"RIO LOBO",
"has_genre",
"WESTERN"
],
[
"RIO LOBO",
"release_year",
"1970"
],
[
"SERENITY",
"has_tags",
"DRAMA"
],
[
"SERENITY",
"has_tags",
"WESTERN"
],
[
"SOLDIER BLUE",
"has_genre",
"WESTERN"
],
[
"SOLDIER BLUE",
"release_year",
"1970"
],
[
"SOMETIMES A GREAT NOTION",
"has_genre",
"DRAMA"
],
[
"SOMETIMES A GREAT NOTION",
"release_year",
"1970"
],
[
"SUNFLOWER",
"has_genre",
"DRAMA"
],
[
"SUNFLOWER",
"release_year",
"1970"
],
[
"THE APE",
"has_genre",
"DRAMA"
],
[
"THE APE",
"release_year",
"1940"
],
[
"THE ASSASSINATION OF JESSE JAMES BY THE COWARD ROBERT FORD",
"has_genre",
"DRAMA"
],
[
"THE ASSASSINATION OF JESSE JAMES BY THE COWARD ROBERT FORD",
"has_tags",
"WESTERN"
],
[
"THE BOYS IN THE BAND",
"has_genre",
"DRAMA"
],
[
"THE BOYS IN THE BAND",
"release_year",
"1970"
],
[
"THE CHEYENNE SOCIAL CLUB",
"has_genre",
"WESTERN"
],
[
"THE CHEYENNE SOCIAL CLUB",
"release_year",
"1970"
],
[
"THE CONFESSION",
"has_genre",
"DRAMA"
],
[
"THE CONFESSION",
"release_year",
"1970"
],
[
"THE CONFORMIST",
"has_genre",
"DRAMA"
],
[
"THE CONFORMIST",
"release_year",
"1970"
],
[
"THE FACE BEHIND THE MASK",
"has_genre",
"DRAMA"
],
[
"THE FACE BEHIND THE MASK",
"starred_actors",
"PETER LORRE"
],
[
"THE GRAPES OF WRATH",
"has_genre",
"DRAMA"
],
[
"THE GRAPES OF WRATH",
"release_year",
"1940"
],
[
"THE GREAT GABBO",
"directed_by",
"ERICH VON STROHEIM"
],
[
"THE GREAT GABBO",
"has_genre",
"DRAMA"
],
[
"THE GREAT GABBO",
"starred_actors",
"ERICH VON STROHEIM"
],
[
"THE GREAT WHITE HOPE",
"has_genre",
"DRAMA"
],
[
"THE GREAT WHITE HOPE",
"release_year",
"1970"
],
[
"THE HI-LO COUNTRY",
"has_genre",
"DRAMA"
],
[
"THE HI-LO COUNTRY",
"has_genre",
"WESTERN"
],
[
"THE HOMESMAN",
"has_genre",
"DRAMA"
],
[
"THE HOMESMAN",
"has_genre",
"WESTERN"
],
[
"THE HOUSE OF THE SEVEN GABLES",
"has_genre",
"DRAMA"
],
[
"THE HOUSE OF THE SEVEN GABLES",
"release_year",
"1940"
],
[
"THE LETTER",
"has_genre",
"DRAMA"
],
[
"THE LETTER",
"release_year",
"1940"
],
[
"THE LIBERATION OF L.B. JONES",
"has_genre",
"DRAMA"
],
[
"THE LIBERATION OF L.B. JONES",
"release_year",
"1970"
],
[
"THE LONG VOYAGE HOME",
"has_genre",
"DRAMA"
],
[
"THE LONG VOYAGE HOME",
"release_year",
"1940"
],
[
"THE MASK OF DIMITRIOS",
"has_genre",
"DRAMA"
],
[
"THE MASK OF DIMITRIOS",
"starred_actors",
"PETER LORRE"
],
[
"THE MISFITS",
"has_genre",
"DRAMA"
],
[
"THE MISFITS",
"has_genre",
"WESTERN"
],
[
"THE MOLLY MAGUIRES",
"has_genre",
"DRAMA"
],
[
"THE MOLLY MAGUIRES",
"release_year",
"1970"
],
[
"THE MORTAL STORM",
"has_genre",
"DRAMA"
],
[
"THE MORTAL STORM",
"release_year",
"1940"
],
[
"THE MUSIC LOVERS",
"has_genre",
"DRAMA"
],
[
"THE MUSIC LOVERS",
"release_year",
"1970"
],
[
"THE PROPOSITION",
"has_genre",
"DRAMA"
],
[
"THE PROPOSITION",
"has_genre",
"WESTERN"
],
[
"THE RAILWAY CHILDREN",
"has_genre",
"DRAMA"
],
[
"THE RAILWAY CHILDREN",
"release_year",
"1970"
],
[
"THE SEA OF GRASS",
"has_genre",
"DRAMA"
],
[
"THE SEA OF GRASS",
"has_genre",
"WESTERN"
],
[
"THE SPOILERS",
"has_genre",
"DRAMA"
],
[
"THE SPOILERS",
"has_genre",
"WESTERN"
],
[
"THE VERDICT",
"has_genre",
"DRAMA"
],
[
"THE VERDICT",
"starred_actors",
"PETER LORRE"
],
[
"THE WELL-DIGGER'S DAUGHTER",
"has_genre",
"DRAMA"
],
[
"THE WELL-DIGGER'S DAUGHTER",
"release_year",
"1940"
],
[
"THEY CALL ME TRINITY",
"has_genre",
"WESTERN"
],
[
"THEY CALL ME TRINITY",
"release_year",
"1970"
],
[
"THREE STRANGERS",
"has_genre",
"DRAMA"
],
[
"THREE STRANGERS",
"starred_actors",
"PETER LORRE"
],
[
"TORA! TORA! TORA!",
"has_genre",
"DRAMA"
],
[
"TORA! TORA! TORA!",
"release_year",
"1970"
],
[
"UNION PACIFIC",
"has_genre",
"DRAMA"
],
[
"UNION PACIFIC",
"has_genre",
"WESTERN"
],
[
"URBAN COWBOY",
"has_genre",
"DRAMA"
],
[
"URBAN COWBOY",
"has_genre",
"WESTERN"
],
[
"WANDA",
"has_genre",
"DRAMA"
],
[
"WANDA",
"release_year",
"1970"
],
[
"WATERLOO BRIDGE",
"has_genre",
"DRAMA"
],
[
"WATERLOO BRIDGE",
"release_year",
"1940"
],
[
"WATERMELON MAN",
"has_genre",
"DRAMA"
],
[
"WATERMELON MAN",
"release_year",
"1970"
],
[
"WHY DOES HERR R. RUN AMOK?",
"has_genre",
"DRAMA"
],
[
"WHY DOES HERR R. RUN AMOK?",
"release_year",
"1970"
],
[
"WITCHHAMMER",
"has_genre",
"DRAMA"
],
[
"WITCHHAMMER",
"release_year",
"1970"
],
[
"WUSA",
"has_genre",
"DRAMA"
],
[
"WUSA",
"release_year",
"1970"
],
[
"WUTHERING HEIGHTS",
"has_genre",
"DRAMA"
],
[
"WUTHERING HEIGHTS",
"release_year",
"1970"
],
[
"YOUNG PEOPLE",
"has_genre",
"DRAMA"
],
[
"YOUNG PEOPLE",
"release_year",
"1940"
],
[
"ZATOICHI MEETS YOJIMBO",
"has_genre",
"DRAMA"
],
[
"ZATOICHI MEETS YOJIMBO",
"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
28545, ARCH HALL JR.
29831, CB4
30019, CROSSROADS
35838, GUNCRAZY
15677, INVASION OF THE BODY SNATCHERS
23570, KEVIN MCCARTHY
22845, MUSIC
28729, REMAKE
7300, TAMRA DAVIS
5673, WILD GUITAR
src, edge_attr, dst
29831, directed_by, 7300
29831, has_genre, 22845
29831, has_tags, 7300
30019, directed_by, 7300
30019, has_genre, 22845
35838, directed_by, 7300
35838, has_tags, 28729
15677, has_tags, 28729
15677, starred_actors, 23570
5673, has_genre, 22845
5673, starred_actors, 28545
Question: For what reason are ARCH HALL JR., KEVIN MCCARTHY, and TAMRA DAVIS associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"ARCH HALL JR.",
"KEVIN MCCARTHY",
"TAMRA DAVIS"
],
"valid_edges": [
[
"CB4",
"directed_by",
"TAMRA DAVIS"
],
[
"CB4",
"has_genre",
"MUSIC"
],
[
"CB4",
"has_tags",
"TAMRA DAVIS"
],
[
"CROSSROADS",
"directed_by",
"TAMRA DAVIS"
],
[
"CROSSROADS",
"has_genre",
"MUSIC"
],
[
"GUNCRAZY",
"directed_by",
"TAMRA DAVIS"
],
[
"GUNCRAZY",
"has_tags",
"REMAKE"
],
[
"INVASION OF THE BODY SNATCHERS",
"has_tags",
"REMAKE"
],
[
"INVASION OF THE BODY SNATCHERS",
"starred_actors",
"KEVIN MCCARTHY"
],
[
"WILD GUITAR",
"has_genre",
"MUSIC"
],
[
"WILD GUITAR",
"starred_actors",
"ARCH HALL JR."
]
]
}
|
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
6252, A CHINESE GHOST STORY
36420, A TAXING WOMAN
16054, ADVENTURES IN BABYSITTING
3473, AMAZON WOMEN ON THE MOON
17761, BABY BOOM
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
30463, COMEDY
19984, CREEPSHOW 2
5277, CRITICAL CONDITION
17866, CROSS MY HEART
12629, DATE WITH AN ANGEL
31407, DRAGNET
32705, ERNEST GOES TO CAMP
16661, EVIL DEAD II
12663, FULL METAL JACKET
21763, GOOD MORNING, VIETNAM
32384, HAMLET GOES BUSINESS
12085, HAPPY NEW YEAR
28307, HARRY AND THE HENDERSONS
36859, HELLO AGAIN
37602, HOLLYWOOD SHUFFLE
24940, HOPE AND GLORY
31686, HOT PURSUIT
23849, HOUSEKEEPING
9007, HUNK
16321, INNERSPACE
1166, ISHTAR
20866, LEIF
30420, LEONARD PART 6
39520, LETHAL WEAPON
28811, LIKE FATHER LIKE SON
7423, MAID TO ORDER
22842, MAKING MR. RIGHT
32481, MANNEQUIN
594, MITCHELL KAPNER
33763, MOONSTRUCK
16298, MORGAN STEWART'S COMING HOME
36631, MUNCHIES
20549, NADINE
29029, NOVOCAINE
36424, OUTRAGEOUS FORTUNE
253, OVERBOARD
12939, PROJECT X
15214, RADIO DAYS
21462, RAISING ARIZONA
2855, REAL MEN
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
32018, TEEN WOLF TOO
27730, THE ALLNIGHTER
10194, THE BRAVE LITTLE TOASTER
38918, THE FAMILY
33993, THE MONSTER SQUAD
17411, THE PICK-UP ARTIST
29641, THE PRINCESS BRIDE
27344, THE SQUEEZE
18065, THE WHOLE TEN YARDS
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
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
36420, has_genre, 30463
36420, release_year, 7841
16054, has_genre, 30463
16054, release_year, 7841
3473, has_genre, 30463
3473, release_year, 7841
17761, has_genre, 30463
17761, release_year, 7841
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
31407, has_genre, 30463
31407, release_year, 7841
32705, has_genre, 30463
32705, release_year, 7841
16661, has_genre, 30463
16661, release_year, 7841
12663, 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
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
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
36631, has_genre, 30463
36631, release_year, 7841
20549, has_genre, 30463
20549, release_year, 7841
29029, has_genre, 30463
36424, has_genre, 30463
36424, release_year, 7841
253, has_genre, 30463
253, release_year, 7841
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
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
32018, has_genre, 30463
32018, release_year, 7841
27730, has_genre, 30463
27730, release_year, 7841
10194, has_genre, 30463
10194, release_year, 7841
38918, has_genre, 30463
38918, release_year, 7841
33993, has_genre, 30463
33993, release_year, 7841
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
18065, has_genre, 30463
18065, written_by, 594
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
6124, has_genre, 30463
6124, release_year, 7841
16913, has_genre, 30463
16913, release_year, 7841
6981, has_genre, 30463
6981, release_year, 7841
Question: How are FULL METAL JACKET, MITCHELL KAPNER, and NOVOCAINE related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"FULL METAL JACKET",
"MITCHELL KAPNER",
"NOVOCAINE"
],
"valid_edges": [
[
"A CHINESE GHOST STORY",
"has_genre",
"COMEDY"
],
[
"A CHINESE GHOST STORY",
"release_year",
"1987"
],
[
"A TAXING WOMAN",
"has_genre",
"COMEDY"
],
[
"A TAXING WOMAN",
"release_year",
"1987"
],
[
"ADVENTURES IN BABYSITTING",
"has_genre",
"COMEDY"
],
[
"ADVENTURES IN BABYSITTING",
"release_year",
"1987"
],
[
"AMAZON WOMEN ON THE MOON",
"has_genre",
"COMEDY"
],
[
"AMAZON WOMEN ON THE MOON",
"release_year",
"1987"
],
[
"BABY BOOM",
"has_genre",
"COMEDY"
],
[
"BABY BOOM",
"release_year",
"1987"
],
[
"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"
],
[
"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"
],
[
"FULL METAL JACKET",
"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"
],
[
"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"
],
[
"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"
],
[
"MUNCHIES",
"has_genre",
"COMEDY"
],
[
"MUNCHIES",
"release_year",
"1987"
],
[
"NADINE",
"has_genre",
"COMEDY"
],
[
"NADINE",
"release_year",
"1987"
],
[
"NOVOCAINE",
"has_genre",
"COMEDY"
],
[
"OUTRAGEOUS FORTUNE",
"has_genre",
"COMEDY"
],
[
"OUTRAGEOUS FORTUNE",
"release_year",
"1987"
],
[
"OVERBOARD",
"has_genre",
"COMEDY"
],
[
"OVERBOARD",
"release_year",
"1987"
],
[
"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"
],
[
"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"
],
[
"TEEN WOLF TOO",
"has_genre",
"COMEDY"
],
[
"TEEN WOLF TOO",
"release_year",
"1987"
],
[
"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 MONSTER SQUAD",
"has_genre",
"COMEDY"
],
[
"THE MONSTER SQUAD",
"release_year",
"1987"
],
[
"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 WHOLE TEN YARDS",
"has_genre",
"COMEDY"
],
[
"THE WHOLE TEN YARDS",
"written_by",
"MITCHELL KAPNER"
],
[
"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"
],
[
"WALK LIKE A MAN",
"has_genre",
"COMEDY"
],
[
"WALK LIKE A MAN",
"release_year",
"1987"
],
[
"WHO'S THAT GIRL",
"has_genre",
"COMEDY"
],
[
"WHO'S THAT GIRL",
"release_year",
"1987"
],
[
"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
15374, 2005
658, 2012
19567, ALL ABOUT ANNA
32797, DANGEROUS LIAISONS
24098, GRAVE ENCOUNTERS 2
32874, GRY BAY
28998, KEANU REEVES
31377, MUCH ADO ABOUT NOTHING
9389, SIDE BY SIDE
15752, SPEED
12392, THE WORLD'S FASTEST INDIAN
src, edge_attr, dst
19567, release_year, 15374
19567, starred_actors, 32874
32797, has_tags, 28998
32797, release_year, 658
24098, release_year, 658
31377, has_tags, 28998
31377, release_year, 658
9389, has_tags, 28998
9389, release_year, 658
15752, has_tags, 28998
15752, has_tags, 15752
15752, starred_actors, 28998
12392, has_tags, 15752
12392, release_year, 15374
Question: In what context are GRAVE ENCOUNTERS 2, GRY BAY, and SPEED connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"GRAVE ENCOUNTERS 2",
"GRY BAY",
"SPEED"
],
"valid_edges": [
[
"ALL ABOUT ANNA",
"release_year",
"2005"
],
[
"ALL ABOUT ANNA",
"starred_actors",
"GRY BAY"
],
[
"DANGEROUS LIAISONS",
"has_tags",
"KEANU REEVES"
],
[
"DANGEROUS LIAISONS",
"release_year",
"2012"
],
[
"GRAVE ENCOUNTERS 2",
"release_year",
"2012"
],
[
"MUCH ADO ABOUT NOTHING",
"has_tags",
"KEANU REEVES"
],
[
"MUCH ADO ABOUT NOTHING",
"release_year",
"2012"
],
[
"SIDE BY SIDE",
"has_tags",
"KEANU REEVES"
],
[
"SIDE BY SIDE",
"release_year",
"2012"
],
[
"SPEED",
"has_tags",
"KEANU REEVES"
],
[
"SPEED",
"has_tags",
"SPEED"
],
[
"SPEED",
"starred_actors",
"KEANU REEVES"
],
[
"THE WORLD'S FASTEST INDIAN",
"has_tags",
"SPEED"
],
[
"THE WORLD'S FASTEST INDIAN",
"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
36212, DRAMA
34244, EHUD YONAY
21323, KENNETH NELSON
17065, MADHUR MITTAL
35465, MILLION DOLLAR ARM
8125, THE BOYS IN THE BAND
30953, TOP GUN
src, edge_attr, dst
35465, has_genre, 36212
35465, starred_actors, 17065
8125, has_genre, 36212
8125, starred_actors, 21323
30953, has_genre, 36212
30953, written_by, 34244
Question: In what context are EHUD YONAY, KENNETH NELSON, and MADHUR MITTAL connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"EHUD YONAY",
"KENNETH NELSON",
"MADHUR MITTAL"
],
"valid_edges": [
[
"MILLION DOLLAR ARM",
"has_genre",
"DRAMA"
],
[
"MILLION DOLLAR ARM",
"starred_actors",
"MADHUR MITTAL"
],
[
"THE BOYS IN THE BAND",
"has_genre",
"DRAMA"
],
[
"THE BOYS IN THE BAND",
"starred_actors",
"KENNETH NELSON"
],
[
"TOP GUN",
"has_genre",
"DRAMA"
],
[
"TOP GUN",
"written_by",
"EHUD YONAY"
]
]
}
|
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
8783, 1977
22088, A BRIDGE TOO FAR
39289, ACTION
12185, BATTLEGROUND
13715, HOME OF THE BRAVE
27285, I WAS A MALE WAR BRIDE
7629, KIERAN CULKIN
16827, NOWHERE TO RUN
23006, SANDS OF IWO JIMA
4162, THE ASCENT
20000, THE HASTY HEART
27164, THE WINDOW
38352, TWELVE O'CLOCK HIGH
22214, WAR
src, edge_attr, dst
22088, has_genre, 22214
22088, has_tags, 22214
22088, release_year, 8783
12185, has_genre, 22214
12185, has_tags, 22214
12185, release_year, 1430
13715, has_genre, 22214
13715, release_year, 1430
27285, has_genre, 22214
27285, release_year, 1430
16827, has_genre, 39289
16827, starred_actors, 7629
23006, has_genre, 22214
23006, release_year, 1430
4162, has_genre, 22214
4162, release_year, 8783
20000, has_genre, 22214
20000, release_year, 1430
27164, release_year, 1430
38352, has_genre, 22214
38352, release_year, 1430
22214, has_genre, 39289
Question: How are KIERAN CULKIN, THE ASCENT, and THE WINDOW related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"KIERAN CULKIN",
"THE ASCENT",
"THE WINDOW"
],
"valid_edges": [
[
"A BRIDGE TOO FAR",
"has_genre",
"WAR"
],
[
"A BRIDGE TOO FAR",
"has_tags",
"WAR"
],
[
"A BRIDGE TOO FAR",
"release_year",
"1977"
],
[
"BATTLEGROUND",
"has_genre",
"WAR"
],
[
"BATTLEGROUND",
"has_tags",
"WAR"
],
[
"BATTLEGROUND",
"release_year",
"1949"
],
[
"HOME OF THE BRAVE",
"has_genre",
"WAR"
],
[
"HOME OF THE BRAVE",
"release_year",
"1949"
],
[
"I WAS A MALE WAR BRIDE",
"has_genre",
"WAR"
],
[
"I WAS A MALE WAR BRIDE",
"release_year",
"1949"
],
[
"NOWHERE TO RUN",
"has_genre",
"ACTION"
],
[
"NOWHERE TO RUN",
"starred_actors",
"KIERAN CULKIN"
],
[
"SANDS OF IWO JIMA",
"has_genre",
"WAR"
],
[
"SANDS OF IWO JIMA",
"release_year",
"1949"
],
[
"THE ASCENT",
"has_genre",
"WAR"
],
[
"THE ASCENT",
"release_year",
"1977"
],
[
"THE HASTY HEART",
"has_genre",
"WAR"
],
[
"THE HASTY HEART",
"release_year",
"1949"
],
[
"THE WINDOW",
"release_year",
"1949"
],
[
"TWELVE O'CLOCK HIGH",
"has_genre",
"WAR"
],
[
"TWELVE O'CLOCK HIGH",
"release_year",
"1949"
],
[
"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
31196, 1974
10045, BD-R
2835, BLACKBALL
35745, CLAUDINE
39747, HENRY JONES
23380, INVINCIBLE
6895, LESTER PINE
7050, MONEYBALL
37334, NATIONAL VELVET
32404, SPORT
3049, SPORTS
13151, THE BAD SEED
34736, THE ENDLESS SUMMER
20223, THE LONGEST YARD
src, edge_attr, dst
2835, has_genre, 32404
2835, has_tags, 10045
2835, has_tags, 3049
35745, release_year, 31196
35745, written_by, 6895
23380, has_genre, 32404
23380, has_tags, 10045
23380, has_tags, 3049
7050, has_genre, 32404
7050, has_tags, 10045
7050, has_tags, 3049
37334, has_genre, 32404
37334, has_tags, 10045
13151, has_tags, 10045
13151, starred_actors, 39747
34736, has_genre, 32404
34736, has_tags, 10045
20223, has_genre, 32404
20223, has_tags, 3049
20223, release_year, 31196
Question: How are HENRY JONES, LESTER PINE, and SPORT related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"HENRY JONES",
"LESTER PINE",
"SPORT"
],
"valid_edges": [
[
"BLACKBALL",
"has_genre",
"SPORT"
],
[
"BLACKBALL",
"has_tags",
"BD-R"
],
[
"BLACKBALL",
"has_tags",
"SPORTS"
],
[
"CLAUDINE",
"release_year",
"1974"
],
[
"CLAUDINE",
"written_by",
"LESTER PINE"
],
[
"INVINCIBLE",
"has_genre",
"SPORT"
],
[
"INVINCIBLE",
"has_tags",
"BD-R"
],
[
"INVINCIBLE",
"has_tags",
"SPORTS"
],
[
"MONEYBALL",
"has_genre",
"SPORT"
],
[
"MONEYBALL",
"has_tags",
"BD-R"
],
[
"MONEYBALL",
"has_tags",
"SPORTS"
],
[
"NATIONAL VELVET",
"has_genre",
"SPORT"
],
[
"NATIONAL VELVET",
"has_tags",
"BD-R"
],
[
"THE BAD SEED",
"has_tags",
"BD-R"
],
[
"THE BAD SEED",
"starred_actors",
"HENRY JONES"
],
[
"THE ENDLESS SUMMER",
"has_genre",
"SPORT"
],
[
"THE ENDLESS SUMMER",
"has_tags",
"BD-R"
],
[
"THE LONGEST YARD",
"has_genre",
"SPORT"
],
[
"THE LONGEST YARD",
"has_tags",
"SPORTS"
],
[
"THE LONGEST YARD",
"release_year",
"1974"
]
]
}
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.