sentence1
stringlengths 11
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| sentence2
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|---|---|---|---|
Bees do not follow the same rules as airplanes.
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Bees fly using a different mechanism from airplanes.
| 200
| 0entailment
|
Bees fly using a different mechanism from airplanes.
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Bees do not follow the same rules as airplanes.
| 201
| 0entailment
|
Bees do not follow the same rules as airplanes.
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Bees fly using the same mechanism as airplanes.
| 202
| 1not_entailment
|
Bees fly using the same mechanism as airplanes.
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Bees do not follow the same rules as airplanes.
| 203
| 1not_entailment
|
Bees do not follow the same rules as airplanes.
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Bees are more energy-efficient flyers than airplanes.
| 204
| 1not_entailment
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Bees are more energy-efficient flyers than airplanes.
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Bees do not follow the same rules as airplanes.
| 205
| 1not_entailment
|
Leslie Dixon is married to fellow screenwriter and producer Tom Ropelewski.
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Tom Ropelewski is married to fellow screenwriter and producer Leslie Dixon.
| 206
| 0entailment
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Tom Ropelewski is married to fellow screenwriter and producer Leslie Dixon.
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Leslie Dixon is married to fellow screenwriter and producer Tom Ropelewski.
| 207
| 0entailment
|
This means that solving analogy questions with vector arithmetic is mathematically equivalent to seeking a word that is similar to x and y but is different from z.
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This means that seeking a word that is similar to x and y but is different from z is mathematically equivalent to solving analogy questions with vector arithmetic.
| 208
| 0entailment
|
This means that seeking a word that is similar to x and y but is different from z is mathematically equivalent to solving analogy questions with vector arithmetic.
|
This means that solving analogy questions with vector arithmetic is mathematically equivalent to seeking a word that is similar to x and y but is different from z.
| 209
| 0entailment
|
Bob married Alice.
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Bob and Alice got married.
| 210
| 0entailment
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Bob and Alice got married.
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Bob married Alice.
| 211
| 0entailment
|
Tulsi Gabbard disagrees with Bernie Sanders on what is the best way to deal with Bashar al-Assad.
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Tulsi Gabbard and Bernie Sanders disagree on what is the best way to deal with Bashar al-Assad.
| 212
| 0entailment
|
Tulsi Gabbard and Bernie Sanders disagree on what is the best way to deal with Bashar al-Assad.
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Tulsi Gabbard disagrees with Bernie Sanders on what is the best way to deal with Bashar al-Assad.
| 213
| 0entailment
|
It reminds me of the times I played Super Mario with my little brother.
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It reminds me of the times my little brother and I played Super Mario.
| 214
| 0entailment
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It reminds me of the times my little brother and I played Super Mario.
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It reminds me of the times I played Super Mario with my little brother.
| 215
| 0entailment
|
In this PC game, Shredder fights the turtles in his Manhattan hideout.
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In this PC game, Shredder and the turtles fight in his Manhattan hideout.
| 216
| 0entailment
|
In this PC game, Shredder and the turtles fight in his Manhattan hideout.
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In this PC game, Shredder fights the turtles in his Manhattan hideout.
| 217
| 0entailment
|
If their vectors' cosine similarity is high, we can conclude that "cat" is similar to "dog".
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If their vectors' cosine similarity is high, we can conclude that "cat" and "dog" are similar.
| 218
| 0entailment
|
If their vectors' cosine similarity is high, we can conclude that "cat" and "dog" are similar.
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If their vectors' cosine similarity is high, we can conclude that "cat" is similar to "dog".
| 219
| 0entailment
|
Jane had a party on Sunday.
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On Sunday, Jane had a party.
| 220
| 0entailment
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On Sunday, Jane had a party.
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Jane had a party on Sunday.
| 221
| 0entailment
|
For decades, the FBI has been trusted to investigate corruption inside the government.
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The FBI has been trusted to investigate corruption inside the government for decades.
| 222
| 0entailment
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The FBI has been trusted to investigate corruption inside the government for decades.
|
For decades, the FBI has been trusted to investigate corruption inside the government.
| 223
| 0entailment
|
I was driving through my neighborhood a few weeks ago, and there was a lady holding a child's hand, standing on the side of the road talking to someone parked in a car.
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A few weeks ago, I was driving through my neighborhood, and there was a lady holding a child's hand, standing on the side of the road talking to someone parked in a car.
| 224
| 0entailment
|
A few weeks ago, I was driving through my neighborhood, and there was a lady holding a child's hand, standing on the side of the road talking to someone parked in a car.
|
I was driving through my neighborhood a few weeks ago, and there was a lady holding a child's hand, standing on the side of the road talking to someone parked in a car.
| 225
| 0entailment
|
Bass River timber was used in construction of the Empire State Building.
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In construction of the Empire State Building, Bass River timber was used.
| 226
| 0entailment
|
In construction of the Empire State Building, Bass River timber was used.
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Bass River timber was used in construction of the Empire State Building.
| 227
| 0entailment
|
In this paper, we present an approach to acquire trivial physical knowledge from unstructured natural language text.
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We present in this paper an approach to acquire trivial physical knowledge from unstructured natural language text.
| 228
| 0entailment
|
We present in this paper an approach to acquire trivial physical knowledge from unstructured natural language text.
|
In this paper, we present an approach to acquire trivial physical knowledge from unstructured natural language text.
| 229
| 0entailment
|
In this paper, we present an approach to acquire trivial physical knowledge from unstructured natural language text.
|
We present an approach to acquire trivial physical knowledge from the unstructured natural language text of this paper.
| 230
| 1not_entailment
|
We present an approach to acquire trivial physical knowledge from the unstructured natural language text of this paper.
|
In this paper, we present an approach to acquire trivial physical knowledge from unstructured natural language text.
| 231
| 1not_entailment
|
I ate pizza with friends.
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I ate pizza.
| 232
| 0entailment
|
I ate pizza.
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I ate pizza with friends.
| 233
| 0entailment
|
I ate pizza with some friends.
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I ate some friends.
| 234
| 1not_entailment
|
I ate some friends.
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I ate pizza with some friends.
| 235
| 1not_entailment
|
I ate pizza with olives.
|
I ate pizza.
| 236
| 0entailment
|
I ate pizza.
|
I ate pizza with olives.
| 237
| 1not_entailment
|
I ate pizza with olives.
|
I ate olives.
| 238
| 0entailment
|
I ate olives.
|
I ate pizza with olives.
| 239
| 1not_entailment
|
Mueller received a mandate to investigate possible collusion with Russia.
|
Mueller received a mandate to investigate possible collusion.
| 240
| 0entailment
|
Mueller received a mandate to investigate possible collusion.
|
Mueller received a mandate to investigate possible collusion with Russia.
| 241
| 1not_entailment
|
Mueller received a mandate to investigate possible collusion with Russia.
|
Mueller received a mandate to investigate with Russia.
| 242
| 1not_entailment
|
Mueller received a mandate to investigate with Russia.
|
Mueller received a mandate to investigate possible collusion with Russia.
| 243
| 1not_entailment
|
Mueller received a mandate to investigate possible collusion with vast resources.
|
Mueller received a mandate to investigate possible collusion.
| 244
| 0entailment
|
Mueller received a mandate to investigate possible collusion.
|
Mueller received a mandate to investigate possible collusion with vast resources.
| 245
| 1not_entailment
|
Mueller received a mandate to investigate possible collusion with vast resources.
|
Mueller received a mandate to investigate with vast resources.
| 246
| 0entailment
|
Mueller received a mandate to investigate with vast resources.
|
Mueller received a mandate to investigate possible collusion with vast resources.
| 247
| 1not_entailment
|
They should be attached to the lifting mechanism in the faucet.
|
They should be attached to the lifting mechanism.
| 248
| 0entailment
|
They should be attached to the lifting mechanism.
|
They should be attached to the lifting mechanism in the faucet.
| 249
| 1not_entailment
|
They should be attached to the lifting mechanism in the faucet.
|
They should be attached in the faucet.
| 250
| 0entailment
|
They should be attached in the faucet.
|
They should be attached to the lifting mechanism in the faucet.
| 251
| 1not_entailment
|
They should be attached to the lifting mechanism in an unbreakable knot.
|
They should be attached to the lifting mechanism.
| 252
| 0entailment
|
They should be attached to the lifting mechanism.
|
They should be attached to the lifting mechanism in an unbreakable knot.
| 253
| 1not_entailment
|
They should be attached to the lifting mechanism in an unbreakable knot.
|
They should be attached in an unbreakable knot.
| 254
| 0entailment
|
They should be attached in an unbreakable knot.
|
They should be attached to the lifting mechanism in an unbreakable knot.
| 255
| 1not_entailment
|
Tanks were developed by Britain and France, and were first used in combat by the British during a battle with only partial success.
|
Tanks were developed by Britain and France, and were first used with only partial success.
| 256
| 0entailment
|
Tanks were developed by Britain and France, and were first used with only partial success.
|
Tanks were developed by Britain and France, and were first used in combat by the British during a battle with only partial success.
| 257
| 1not_entailment
|
Tanks were developed by Britain and France, and were first used in combat by the British during a battle with only partial success.
|
Tanks were developed by Britain and France, and were first used in combat by the British during a battle.
| 258
| 0entailment
|
Tanks were developed by Britain and France, and were first used in combat by the British during a battle.
|
Tanks were developed by Britain and France, and were first used in combat by the British during a battle with only partial success.
| 259
| 1not_entailment
|
Tanks were developed by Britain and France, and were first used in combat by the British during a battle with German forces.
|
Tanks were developed by Britain and France, and were first used with German forces.
| 260
| 0entailment
|
Tanks were developed by Britain and France, and were first used with German forces.
|
Tanks were developed by Britain and France, and were first used in combat by the British during a battle with German forces.
| 261
| 1not_entailment
|
Tanks were developed by Britain and France, and were first used in combat by the British during a battle with German forces.
|
Tanks were developed by Britain and France, and were first used in combat by the British during a battle.
| 262
| 0entailment
|
Tanks were developed by Britain and France, and were first used in combat by the British during a battle.
|
Tanks were developed by Britain and France, and were first used in combat by the British during a battle with German forces.
| 263
| 1not_entailment
|
We propose models of the probability distribution from which the attested vowel inventories have been drawn.
|
We propose models of the probability distribution.
| 264
| 0entailment
|
We propose models of the probability distribution.
|
We propose models of the probability distribution from which the attested vowel inventories have been drawn.
| 265
| 1not_entailment
|
We propose models of the probability distribution from which the attested vowel inventories have been drawn.
|
We propose models from which the attested vowel inventories have been drawn.
| 266
| 1not_entailment
|
We propose models from which the attested vowel inventories have been drawn.
|
We propose models of the probability distribution from which the attested vowel inventories have been drawn.
| 267
| 1not_entailment
|
We propose models of the probability distribution from a restricted space of linear functions.
|
We propose models of the probability distribution.
| 268
| 0entailment
|
We propose models of the probability distribution.
|
We propose models of the probability distribution from a restricted space of linear functions.
| 269
| 1not_entailment
|
We propose models of the probability distribution from a restricted space of linear functions.
|
We propose models from a restricted space of linear functions.
| 270
| 0entailment
|
We propose models from a restricted space of linear functions.
|
We propose models of the probability distribution from a restricted space of linear functions.
| 271
| 1not_entailment
|
George went to the lake to catch a fish, but he fell into the water.
|
George fell into the water.
| 272
| 0entailment
|
George fell into the water.
|
George went to the lake to catch a fish, but he fell into the water.
| 273
| 1not_entailment
|
George went to the lake to catch a fish, but he fell into the water.
|
A fish fell into the water.
| 274
| 1not_entailment
|
A fish fell into the water.
|
George went to the lake to catch a fish, but he fell into the water.
| 275
| 1not_entailment
|
The Republican party almost universally opposed that bill in 2009, which cost $787 billion over 10 years, on the grounds that it would increase the debt too much.
|
That bill would increase the debt too much.
| 276
| 0entailment
|
That bill would increase the debt too much.
|
The Republican party almost universally opposed that bill in 2009, which cost $787 billion over 10 years, on the grounds that it would increase the debt too much.
| 277
| 1not_entailment
|
The Republican party almost universally opposed that bill in 2009, which cost $787 billion over 10 years, on the grounds that it would increase the debt too much.
|
The Republican party would increase the debt too much.
| 278
| 1not_entailment
|
The Republican party would increase the debt too much.
|
The Republican party almost universally opposed that bill in 2009, which cost $787 billion over 10 years, on the grounds that it would increase the debt too much.
| 279
| 1not_entailment
|
The climbing beans choked the corn, and the squash grew so big that it overshadowed several adjacent rows of beans.
|
The squash overshadowed several adjacent rows of beans.
| 280
| 0entailment
|
The squash overshadowed several adjacent rows of beans.
|
The climbing beans choked the corn, and the squash grew so big that it overshadowed several adjacent rows of beans.
| 281
| 1not_entailment
|
The climbing beans choked the corn, and the squash grew so big that it overshadowed several adjacent rows of beans.
|
The corn overshadowed several adjacent rows of beans.
| 282
| 1not_entailment
|
The corn overshadowed several adjacent rows of beans.
|
The climbing beans choked the corn, and the squash grew so big that it overshadowed several adjacent rows of beans.
| 283
| 1not_entailment
|
Because Britain still maintained control of Canada's foreign affairs under the Confederation Act, its declaration of war in 1914 automatically brought Canada into World War I.
|
Britain's declaration of war in 1914 automatically brought Canada into World War I.
| 284
| 0entailment
|
Britain's declaration of war in 1914 automatically brought Canada into World War I.
|
Because Britain still maintained control of Canada's foreign affairs under the Confederation Act, its declaration of war in 1914 automatically brought Canada into World War I.
| 285
| 1not_entailment
|
Because Britain still maintained control of Canada's foreign affairs under the Confederation Act, its declaration of war in 1914 automatically brought Canada into World War I.
|
Canada's declaration of war in 1914 automatically brought Canada into World War I.
| 286
| 1not_entailment
|
Canada's declaration of war in 1914 automatically brought Canada into World War I.
|
Because Britain still maintained control of Canada's foreign affairs under the Confederation Act, its declaration of war in 1914 automatically brought Canada into World War I.
| 287
| 1not_entailment
|
We show that if coreference resolvers mainly rely on lexical features, they can hardly generalize to unseen domains.
|
Coreference resolvers can hardly generalize to unseen domains.
| 288
| 1not_entailment
|
Coreference resolvers can hardly generalize to unseen domains.
|
We show that if coreference resolvers mainly rely on lexical features, they can hardly generalize to unseen domains.
| 289
| 1not_entailment
|
We show that if coreference resolvers mainly rely on lexical features, they can hardly generalize to unseen domains.
|
Lexical features can hardly generalize to unseen domains.
| 290
| 1not_entailment
|
Lexical features can hardly generalize to unseen domains.
|
We show that if coreference resolvers mainly rely on lexical features, they can hardly generalize to unseen domains.
| 291
| 1not_entailment
|
The sides came to an agreement after their meeting in Stockholm.
|
The sides came to an agreement after their meeting in Sweden.
| 292
| 0entailment
|
The sides came to an agreement after their meeting in Sweden.
|
The sides came to an agreement after their meeting in Stockholm.
| 293
| 1not_entailment
|
The sides came to an agreement after their meeting in Stockholm.
|
The sides came to an agreement after their meeting in Europe.
| 294
| 0entailment
|
The sides came to an agreement after their meeting in Europe.
|
The sides came to an agreement after their meeting in Stockholm.
| 295
| 1not_entailment
|
The sides came to an agreement after their meeting in Stockholm.
|
The sides came to an agreement after their meeting in Oslo.
| 296
| 1not_entailment
|
The sides came to an agreement after their meeting in Oslo.
|
The sides came to an agreement after their meeting in Stockholm.
| 297
| 1not_entailment
|
Musk decided to offer up his personal Tesla roadster.
|
Musk decided to offer up his personal car.
| 298
| 0entailment
|
Musk decided to offer up his personal car.
|
Musk decided to offer up his personal Tesla roadster.
| 299
| 1not_entailment
|
Subsets and Splits
Non-Entailment Examples Sampled
Retrieves 60 random pairs of sentences that are not entailed, providing basic filtering of the dataset.