sentence1
stringlengths 11
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| sentence2
stringlengths 11
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1.1k
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|---|---|---|---|
Bees do not follow the same rules as airplanes.
|
Bees fly using a different mechanism from airplanes.
| 200 | 0entailment
|
Bees fly using a different mechanism from airplanes.
|
Bees do not follow the same rules as airplanes.
| 201 | 0entailment
|
Bees do not follow the same rules as airplanes.
|
Bees fly using the same mechanism as airplanes.
| 202 | 1not_entailment
|
Bees fly using the same mechanism as airplanes.
|
Bees do not follow the same rules as airplanes.
| 203 | 1not_entailment
|
Bees do not follow the same rules as airplanes.
|
Bees are more energy-efficient flyers than airplanes.
| 204 | 1not_entailment
|
Bees are more energy-efficient flyers than airplanes.
|
Bees do not follow the same rules as airplanes.
| 205 | 1not_entailment
|
Leslie Dixon is married to fellow screenwriter and producer Tom Ropelewski.
|
Tom Ropelewski is married to fellow screenwriter and producer Leslie Dixon.
| 206 | 0entailment
|
Tom Ropelewski is married to fellow screenwriter and producer Leslie Dixon.
|
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.
|
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.
|
Bob and Alice got married.
| 210 | 0entailment
|
Bob and Alice got married.
|
Bob married Alice.
| 211 | 0entailment
|
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.
| 212 | 0entailment
|
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.
| 213 | 0entailment
|
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.
| 214 | 0entailment
|
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.
| 215 | 0entailment
|
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.
| 216 | 0entailment
|
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.
| 217 | 0entailment
|
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.
| 218 | 0entailment
|
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".
| 219 | 0entailment
|
Jane had a party on Sunday.
|
On Sunday, Jane had a party.
| 220 | 0entailment
|
On Sunday, Jane had a party.
|
Jane had a party on Sunday.
| 221 | 0entailment
|
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.
| 222 | 0entailment
|
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.
|
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.
|
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.
|
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.
|
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.
|
I ate pizza.
| 232 | 0entailment
|
I ate pizza.
|
I ate pizza with friends.
| 233 | 0entailment
|
I ate pizza with some friends.
|
I ate some friends.
| 234 | 1not_entailment
|
I ate some friends.
|
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
|
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