premise
stringlengths 11
296
| hypothesis
stringlengths 11
296
| label
class label 0
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int32 0
1.1k
|
|---|---|---|---|
Bees do not follow the same rules as airplanes.
|
Bees fly using a different mechanism from airplanes.
| -1no label
| 200
|
Bees fly using a different mechanism from airplanes.
|
Bees do not follow the same rules as airplanes.
| -1no label
| 201
|
Bees do not follow the same rules as airplanes.
|
Bees fly using the same mechanism as airplanes.
| -1no label
| 202
|
Bees fly using the same mechanism as airplanes.
|
Bees do not follow the same rules as airplanes.
| -1no label
| 203
|
Bees do not follow the same rules as airplanes.
|
Bees are more energy-efficient flyers than airplanes.
| -1no label
| 204
|
Bees are more energy-efficient flyers than airplanes.
|
Bees do not follow the same rules as airplanes.
| -1no label
| 205
|
Leslie Dixon is married to fellow screenwriter and producer Tom Ropelewski.
|
Tom Ropelewski is married to fellow screenwriter and producer Leslie Dixon.
| -1no label
| 206
|
Tom Ropelewski is married to fellow screenwriter and producer Leslie Dixon.
|
Leslie Dixon is married to fellow screenwriter and producer Tom Ropelewski.
| -1no label
| 207
|
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.
|
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.
| -1no label
| 208
|
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.
| -1no label
| 209
|
Bob married Alice.
|
Bob and Alice got married.
| -1no label
| 210
|
Bob and Alice got married.
|
Bob married Alice.
| -1no label
| 211
|
Tulsi Gabbard disagrees with Bernie Sanders on what is the best way to deal with Bashar al-Assad.
|
Tulsi Gabbard and Bernie Sanders disagree on what is the best way to deal with Bashar al-Assad.
| -1no label
| 212
|
Tulsi Gabbard and Bernie Sanders disagree on what is the best way to deal with Bashar al-Assad.
|
Tulsi Gabbard disagrees with Bernie Sanders on what is the best way to deal with Bashar al-Assad.
| -1no label
| 213
|
It reminds me of the times I played Super Mario with my little brother.
|
It reminds me of the times my little brother and I played Super Mario.
| -1no label
| 214
|
It reminds me of the times my little brother and I played Super Mario.
|
It reminds me of the times I played Super Mario with my little brother.
| -1no label
| 215
|
In this PC game, Shredder fights the turtles in his Manhattan hideout.
|
In this PC game, Shredder and the turtles fight in his Manhattan hideout.
| -1no label
| 216
|
In this PC game, Shredder and the turtles fight in his Manhattan hideout.
|
In this PC game, Shredder fights the turtles in his Manhattan hideout.
| -1no label
| 217
|
If their vectors' cosine similarity is high, we can conclude that "cat" is similar to "dog".
|
If their vectors' cosine similarity is high, we can conclude that "cat" and "dog" are similar.
| -1no label
| 218
|
If their vectors' cosine similarity is high, we can conclude that "cat" and "dog" are similar.
|
If their vectors' cosine similarity is high, we can conclude that "cat" is similar to "dog".
| -1no label
| 219
|
Jane had a party on Sunday.
|
On Sunday, Jane had a party.
| -1no label
| 220
|
On Sunday, Jane had a party.
|
Jane had a party on Sunday.
| -1no label
| 221
|
For decades, the FBI has been trusted to investigate corruption inside the government.
|
The FBI has been trusted to investigate corruption inside the government for decades.
| -1no label
| 222
|
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.
| -1no label
| 223
|
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.
|
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.
| -1no label
| 224
|
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.
| -1no label
| 225
|
Bass River timber was used in construction of the Empire State Building.
|
In construction of the Empire State Building, Bass River timber was used.
| -1no label
| 226
|
In construction of the Empire State Building, Bass River timber was used.
|
Bass River timber was used in construction of the Empire State Building.
| -1no label
| 227
|
In this paper, we present an approach to acquire trivial physical knowledge from unstructured natural language text.
|
We present in this paper an approach to acquire trivial physical knowledge from unstructured natural language text.
| -1no label
| 228
|
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.
| -1no label
| 229
|
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.
| -1no label
| 230
|
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.
| -1no label
| 231
|
I ate pizza with friends.
|
I ate pizza.
| -1no label
| 232
|
I ate pizza.
|
I ate pizza with friends.
| -1no label
| 233
|
I ate pizza with some friends.
|
I ate some friends.
| -1no label
| 234
|
I ate some friends.
|
I ate pizza with some friends.
| -1no label
| 235
|
I ate pizza with olives.
|
I ate pizza.
| -1no label
| 236
|
I ate pizza.
|
I ate pizza with olives.
| -1no label
| 237
|
I ate pizza with olives.
|
I ate olives.
| -1no label
| 238
|
I ate olives.
|
I ate pizza with olives.
| -1no label
| 239
|
Mueller received a mandate to investigate possible collusion with Russia.
|
Mueller received a mandate to investigate possible collusion.
| -1no label
| 240
|
Mueller received a mandate to investigate possible collusion.
|
Mueller received a mandate to investigate possible collusion with Russia.
| -1no label
| 241
|
Mueller received a mandate to investigate possible collusion with Russia.
|
Mueller received a mandate to investigate with Russia.
| -1no label
| 242
|
Mueller received a mandate to investigate with Russia.
|
Mueller received a mandate to investigate possible collusion with Russia.
| -1no label
| 243
|
Mueller received a mandate to investigate possible collusion with vast resources.
|
Mueller received a mandate to investigate possible collusion.
| -1no label
| 244
|
Mueller received a mandate to investigate possible collusion.
|
Mueller received a mandate to investigate possible collusion with vast resources.
| -1no label
| 245
|
Mueller received a mandate to investigate possible collusion with vast resources.
|
Mueller received a mandate to investigate with vast resources.
| -1no label
| 246
|
Mueller received a mandate to investigate with vast resources.
|
Mueller received a mandate to investigate possible collusion with vast resources.
| -1no label
| 247
|
They should be attached to the lifting mechanism in the faucet.
|
They should be attached to the lifting mechanism.
| -1no label
| 248
|
They should be attached to the lifting mechanism.
|
They should be attached to the lifting mechanism in the faucet.
| -1no label
| 249
|
They should be attached to the lifting mechanism in the faucet.
|
They should be attached in the faucet.
| -1no label
| 250
|
They should be attached in the faucet.
|
They should be attached to the lifting mechanism in the faucet.
| -1no label
| 251
|
They should be attached to the lifting mechanism in an unbreakable knot.
|
They should be attached to the lifting mechanism.
| -1no label
| 252
|
They should be attached to the lifting mechanism.
|
They should be attached to the lifting mechanism in an unbreakable knot.
| -1no label
| 253
|
They should be attached to the lifting mechanism in an unbreakable knot.
|
They should be attached in an unbreakable knot.
| -1no label
| 254
|
They should be attached in an unbreakable knot.
|
They should be attached to the lifting mechanism in an unbreakable knot.
| -1no label
| 255
|
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.
| -1no label
| 256
|
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.
| -1no label
| 257
|
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.
| -1no label
| 258
|
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.
| -1no label
| 259
|
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.
| -1no label
| 260
|
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.
| -1no label
| 261
|
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.
| -1no label
| 262
|
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.
| -1no label
| 263
|
We propose models of the probability distribution from which the attested vowel inventories have been drawn.
|
We propose models of the probability distribution.
| -1no label
| 264
|
We propose models of the probability distribution.
|
We propose models of the probability distribution from which the attested vowel inventories have been drawn.
| -1no label
| 265
|
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.
| -1no label
| 266
|
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.
| -1no label
| 267
|
We propose models of the probability distribution from a restricted space of linear functions.
|
We propose models of the probability distribution.
| -1no label
| 268
|
We propose models of the probability distribution.
|
We propose models of the probability distribution from a restricted space of linear functions.
| -1no label
| 269
|
We propose models of the probability distribution from a restricted space of linear functions.
|
We propose models from a restricted space of linear functions.
| -1no label
| 270
|
We propose models from a restricted space of linear functions.
|
We propose models of the probability distribution from a restricted space of linear functions.
| -1no label
| 271
|
George went to the lake to catch a fish, but he fell into the water.
|
George fell into the water.
| -1no label
| 272
|
George fell into the water.
|
George went to the lake to catch a fish, but he fell into the water.
| -1no label
| 273
|
George went to the lake to catch a fish, but he fell into the water.
|
A fish fell into the water.
| -1no label
| 274
|
A fish fell into the water.
|
George went to the lake to catch a fish, but he fell into the water.
| -1no label
| 275
|
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.
| -1no label
| 276
|
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.
| -1no label
| 277
|
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.
| -1no label
| 278
|
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.
| -1no label
| 279
|
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.
| -1no label
| 280
|
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.
| -1no label
| 281
|
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.
| -1no label
| 282
|
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.
| -1no label
| 283
|
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.
| -1no label
| 284
|
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.
| -1no label
| 285
|
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.
| -1no label
| 286
|
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.
| -1no label
| 287
|
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.
| -1no label
| 288
|
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.
| -1no label
| 289
|
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.
| -1no label
| 290
|
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.
| -1no label
| 291
|
The sides came to an agreement after their meeting in Stockholm.
|
The sides came to an agreement after their meeting in Sweden.
| -1no label
| 292
|
The sides came to an agreement after their meeting in Sweden.
|
The sides came to an agreement after their meeting in Stockholm.
| -1no label
| 293
|
The sides came to an agreement after their meeting in Stockholm.
|
The sides came to an agreement after their meeting in Europe.
| -1no label
| 294
|
The sides came to an agreement after their meeting in Europe.
|
The sides came to an agreement after their meeting in Stockholm.
| -1no label
| 295
|
The sides came to an agreement after their meeting in Stockholm.
|
The sides came to an agreement after their meeting in Oslo.
| -1no label
| 296
|
The sides came to an agreement after their meeting in Oslo.
|
The sides came to an agreement after their meeting in Stockholm.
| -1no label
| 297
|
Musk decided to offer up his personal Tesla roadster.
|
Musk decided to offer up his personal car.
| -1no label
| 298
|
Musk decided to offer up his personal car.
|
Musk decided to offer up his personal Tesla roadster.
| -1no label
| 299
|
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