budecosystem/superglue_ax_b huggingface dataset:
Premise: The cat sat on the mat.
Hypothesis: The cat did not sit on the mat.
Label: not_entailment
Logic: Negation
Premise: The cat did not sit on the mat.
Hypothesis: The cat sat on the mat.
Label: not_entailment
Logic: Negation
Premise: When you've got no snow, it's really hard to learn a snow sport so we looked at all the different ways I could mimic being on snow without actually being on snow.
Hypothesis: When you've got snow, it's really hard to learn a snow sport so we looked at all the different ways I could mimic being on snow without actually being on snow.
Label: not_entailment
Logic: Negation
Premise: When you've got snow, it's really hard to learn a snow sport so we looked at all the different ways I could mimic being on snow without actually being on snow.
Hypothesis: When you've got no snow, it's really hard to learn a snow sport so we looked at all the different ways I could mimic being on snow without actually being on snow.
Label: not_entailment
Logic: Negation
Premise: Out of the box, Ouya supports media apps such as Twitch.tv and XBMC media player.
Hypothesis: Out of the box, Ouya doesn't support media apps such as Twitch.tv and XBMC media player.
Label: not_entailment
Logic: Negation
Premise: Out of the box, Ouya doesn't support media apps such as Twitch.tv and XBMC media player.
Hypothesis: Out of the box, Ouya supports media apps such as Twitch.tv and XBMC media player.
Label: not_entailment
Logic: Negation
Premise: Out of the box, Ouya supports media apps such as Twitch.tv and XBMC media player.
Hypothesis: Out of the box, Ouya supports Twitch.tv and XBMC media player.
Label: entailment
Predicate-argument structure: Anaphora/Coreference
Premise: Out of the box, Ouya supports Twitch.tv and XBMC media player.
Hypothesis: Out of the box, Ouya supports media apps such as Twitch.tv and XBMC media player.
Label: entailment
Predicate-argument structure: Anaphora/Coreference
Premise: Considering this definition, it is surprising to find frequent use of sarcastic language in opinionated user generated content.
Hypothesis: Considering this definition, it is not surprising to find frequent use of sarcastic language in opinionated user generated content.
Label: not_entailment
Logic: Negation
Premise: Considering this definition, it is not surprising to find frequent use of sarcastic language in opinionated user generated content.
Hypothesis: Considering this definition, it is surprising to find frequent use of sarcastic language in opinionated user generated content.
Label: not_entailment
Logic: Negation
Premise: The new gaming console is affordable.
Hypothesis: The new gaming console is unaffordable.
Label: not_entailment
Logic: Negation
Lexical semantics: Morphological negation
Premise: The new gaming console is unaffordable.
Hypothesis: The new gaming console is affordable.
Label: not_entailment
Logic: Negation
Lexical semantics: Morphological negation
Premise: Brexit is an irreversible decision, Sir Mike Rake, the chairman of WorldPay and ex-chairman of BT group, said as calls for a second EU referendum were sparked last week.
Hypothesis: Brexit is a reversible decision, Sir Mike Rake, the chairman of WorldPay and ex-chairman of BT group, said as calls for a second EU referendum were sparked last week.
Label: not_entailment
Logic: Negation
Lexical semantics: Morphological negation
Premise: Brexit is a reversible decision, Sir Mike Rake, the chairman of WorldPay and ex-chairman of BT group, said as calls for a second EU referendum were sparked last week.
Hypothesis: Brexit is an irreversible decision, Sir Mike Rake, the chairman of WorldPay and ex-chairman of BT group, said as calls for a second EU referendum were sparked last week.
Label: not_entailment
Logic: Negation
Lexical semantics: Morphological negation
Premise: We built our society on unclean energy.
Hypothesis: We built our society on clean energy.
Label: not_entailment
Logic: Negation
Lexical semantics: Morphological negation
Premise: We built our society on clean energy.
Hypothesis: We built our society on unclean energy.
Label: not_entailment
Logic: Negation
Lexical semantics: Morphological negation
Premise: Pursuing a strategy of nonviolent protest, Gandhi took the administration by surprise and won concessions from the authorities.
Hypothesis: Pursuing a strategy of violent protest, Gandhi took the administration by surprise and won concessions from the authorities.
Label: not_entailment
Logic: Negation
Lexical semantics: Morphological negation
Premise: Pursuing a strategy of violent protest, Gandhi took the administration by surprise and won concessions from the authorities.
Hypothesis: Pursuing a strategy of nonviolent protest, Gandhi took the administration by surprise and won concessions from the authorities.
Label: not_entailment
Logic: Negation
Lexical semantics: Morphological negation
Premise: Pursuing a strategy of nonviolent protest, Gandhi took the administration by surprise and won concessions from the authorities.
Hypothesis: Pursuing a strategy of protest, Gandhi took the administration by surprise and won concessions from the authorities.
Label: entailment
Predicate-argument structure: Intersectivity
Premise: Pursuing a strategy of protest, Gandhi took the administration by surprise and won concessions from the authorities.
Hypothesis: Pursuing a strategy of nonviolent protest, Gandhi took the administration by surprise and won concessions from the authorities.
Label: not_entailment
Predicate-argument structure: Intersectivity
Premise: And if both apply, they are essentially impossible.
Hypothesis: And if both apply, they are essentially possible.
Label: not_entailment
Logic: Negation;Conditionals
Lexical semantics: Morphological negation
Premise: And if both apply, they are essentially possible.
Hypothesis: And if both apply, they are essentially impossible.
Label: not_entailment
Logic: Negation;Conditionals
Lexical semantics: Morphological negation
Premise: Writing Java is not too different from programming with handcuffs.
Hypothesis: Writing Java is similar to programming with handcuffs.
Label: entailment
Logic: Double negation
Lexical semantics: Morphological negation
Premise: Writing Java is similar to programming with handcuffs.
Hypothesis: Writing Java is not too different from programming with handcuffs.
Label: entailment
Logic: Double negation
Lexical semantics: Morphological negation
Premise: The market is about to get harder, but not impossible to navigate.
Hypothesis: The market is about to get harder, but possible to navigate.
Label: entailment
Logic: Double negation
Lexical semantics: Morphological negation
Premise: The market is about to get harder, but possible to navigate.
Hypothesis: The market is about to get harder, but not impossible to navigate.
Label: entailment
Logic: Double negation
Lexical semantics: Morphological negation
Premise: Even after now finding out that it's animal feed, I won't ever stop being addicted to Flamin' Hot Cheetos.
Hypothesis: Even after now finding out that it's animal feed, I will never stop being addicted to Flamin' Hot Cheetos.
Label: entailment
Logic: Double negation
Lexical semantics: Morphological negation
Premise: Even after now finding out that it's animal feed, I will never stop being addicted to Flamin' Hot Cheetos.
Hypothesis: Even after now finding out that it's animal feed, I won't ever stop being addicted to Flamin' Hot Cheetos.
Label: entailment
Logic: Double negation
Lexical semantics: Morphological negation
Premise: He did not disagree with the party's position, but felt that if he resigned, his popularity with Indians would cease to stifle the party's membership.
Hypothesis: He agreed with the party's position, but felt that if he resigned, his popularity with Indians would cease to stifle the party's membership.
Label: entailment
Logic: Double negation
Lexical semantics: Morphological negation
Premise: He agreed with the party's position, but felt that if he resigned, his popularity with Indians would cease to stifle the party's membership.
Hypothesis: He did not disagree with the party's position, but felt that if he resigned, his popularity with Indians would cease to stifle the party's membership.
Label: entailment
Logic: Double negation
Lexical semantics: Morphological negation
Premise: If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, a negative impact on the pipeline results would be expected.
Hypothesis: If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, a negative impact on the pipeline results would not be unexpected.
Label: entailment
Logic: Double negation
Lexical semantics: Morphological negation
Premise: If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, a negative impact on the pipeline results would not be unexpected.
Hypothesis: If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, a negative impact on the pipeline results would be expected.
Label: entailment
Logic: Double negation
Lexical semantics: Morphological negation
Premise: If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, a negative impact on the pipeline results would be expected.
Hypothesis: If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, it would be expected to negatively impact the pipeline results.
Label: entailment
Predicate-argument structure: Nominalization
Premise: If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, it would be expected to negatively impact the pipeline results.
Hypothesis: If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, a negative impact on the pipeline results would be expected.
Label: entailment
Predicate-argument structure: Nominalization
Premise: If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, a negative impact on the pipeline results would be expected.
Hypothesis: If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, it would not be unexpected for it to negatively impact the pipeline results.
Label: entailment
Logic: Double negation
Predicate-argument structure: Nominalization
Lexical semantics: Morphological negation
Premise: If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, it would not be unexpected for it to negatively impact the pipeline results.
Hypothesis: If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, a negative impact on the pipeline results would be expected.
Label: entailment
Logic: Double negation
Predicate-argument structure: Nominalization
Lexical semantics: Morphological negation
Premise: The water is too hot.
Hypothesis: The water is too cold.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: The water is too cold.
Hypothesis: The water is too hot.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: Falcon Heavy is the largest rocket since NASA's Saturn V booster, which was used for the Moon missions in the 1970s.
Hypothesis: Falcon Heavy is the smallest rocket since NASA's Saturn V booster, which was used for the Moon missions in the 1970s.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: Falcon Heavy is the smallest rocket since NASA's Saturn V booster, which was used for the Moon missions in the 1970s.
Hypothesis: Falcon Heavy is the largest rocket since NASA's Saturn V booster, which was used for the Moon missions in the 1970s.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: Adenoiditis symptoms often persist for ten or more days, and often include pus-like discharge from nose.
Hypothesis: Adenoiditis symptoms often pass within ten days or less, and often include pus-like discharge from nose.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: Adenoiditis symptoms often pass within ten days or less, and often include pus-like discharge from nose.
Hypothesis: Adenoiditis symptoms often persist for ten or more days, and often include pus-like discharge from nose.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings.
Hypothesis: In example (1) it is quite difficult to see the exaggerated positive sentiment used in order to convey strong negative feelings.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: In example (1) it is quite difficult to see the exaggerated positive sentiment used in order to convey strong negative feelings.
Hypothesis: In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings.
Hypothesis: In example (1) it is quite easy to see the exaggerated positive sentiment used in order to convey strong negative feelings.
Label: entailment
Lexical semantics: Lexical entailment
Premise: In example (1) it is quite easy to see the exaggerated positive sentiment used in order to convey strong negative feelings.
Hypothesis: In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings.
Label: entailment
Lexical semantics: Lexical entailment
Premise: In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings.
Hypothesis: In example (1) it is quite important to see the exaggerated positive sentiment used in order to convey strong negative feelings.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: In example (1) it is quite important to see the exaggerated positive sentiment used in order to convey strong negative feelings.
Hypothesis: In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: Some dogs like to scratch their ears.
Hypothesis: Some animals like to scratch their ears.
Label: entailment
Logic: Upward monotone
Lexical semantics: Lexical entailment
Premise: Some animals like to scratch their ears.
Hypothesis: Some dogs like to scratch their ears.
Label: not_entailment
Logic: Upward monotone
Lexical semantics: Lexical entailment
Premise: Cruz has frequently derided as "amnesty" various plans that confer legal status or citizenship on people living in the country illegally.
Hypothesis: Cruz has frequently derided as "amnesty" various bills that confer legal status or citizenship on people living in the country illegally.
Label: not_entailment
Logic: Upward monotone
Knowledge: World knowledge
Premise: Cruz has frequently derided as "amnesty" various bills that confer legal status or citizenship on people living in the country illegally.
Hypothesis: Cruz has frequently derided as "amnesty" various plans that confer legal status or citizenship on people living in the country illegally.
Label: entailment
Logic: Upward monotone
Knowledge: World knowledge
Premise: Most of the graduates of my program have moved on to other things because the jobs suck.
Hypothesis: Some of the graduates of my program have moved on to other things because the jobs suck.
Label: entailment
Lexical semantics: Quantifiers
Premise: Some of the graduates of my program have moved on to other things because the jobs suck.
Hypothesis: Most of the graduates of my program have moved on to other things because the jobs suck.
Label: not_entailment
Lexical semantics: Quantifiers
Premise: In many developed areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
Hypothesis: In many areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
Label: entailment
Logic: Upward monotone
Predicate-argument structure: Intersectivity
Premise: In many areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
Hypothesis: In many developed areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
Label: not_entailment
Logic: Upward monotone
Predicate-argument structure: Intersectivity
Premise: We consider some context words as positive examples and sample negatives at random from the dictionary.
Hypothesis: We consider some words as positive examples and sample negatives at random from the dictionary.
Label: entailment
Logic: Upward monotone
Predicate-argument structure: Intersectivity
Premise: We consider some words as positive examples and sample negatives at random from the dictionary.
Hypothesis: We consider some context words as positive examples and sample negatives at random from the dictionary.
Label: not_entailment
Logic: Upward monotone
Predicate-argument structure: Intersectivity
Premise: We consider some context words as positive examples and sample negatives at random from the dictionary.
Hypothesis: We consider all context words as positive examples and sample many negatives at random from the dictionary.
Label: not_entailment
Lexical semantics: Quantifiers
Premise: We consider all context words as positive examples and sample many negatives at random from the dictionary.
Hypothesis: We consider some context words as positive examples and sample negatives at random from the dictionary.
Label: not_entailment
Lexical semantics: Quantifiers
Premise: We consider some context words as positive examples and sample negatives at random from the dictionary.
Hypothesis: We consider many context words as positive examples and sample negatives at random from the dictionary.
Label: not_entailment
Lexical semantics: Quantifiers
Premise: We consider many context words as positive examples and sample negatives at random from the dictionary.
Hypothesis: We consider some context words as positive examples and sample negatives at random from the dictionary.
Label: entailment
Lexical semantics: Quantifiers
Premise: We consider all context words as positive examples and sample negatives at random from the dictionary.
Hypothesis: We consider all words as positive examples and sample negatives at random from the dictionary.
Label: not_entailment
Logic: Downward monotone
Predicate-argument structure: Intersectivity
Premise: We consider all words as positive examples and sample negatives at random from the dictionary.
Hypothesis: We consider all context words as positive examples and sample negatives at random from the dictionary.
Label: entailment
Logic: Downward monotone
Predicate-argument structure: Intersectivity
Premise: All dogs like to scratch their ears.
Hypothesis: All animals like to scratch their ears.
Label: not_entailment
Logic: Downward monotone
Lexical semantics: Lexical entailment
Premise: All animals like to scratch their ears.
Hypothesis: All dogs like to scratch their ears.
Label: entailment
Logic: Downward monotone
Lexical semantics: Lexical entailment
Premise: Cruz has frequently derided as "amnesty" any plan that confers legal status or citizenship on people living in the country illegally.
Hypothesis: Cruz has frequently derided as "amnesty" any bill that confers legal status or citizenship on people living in the country illegally.
Label: entailment
Logic: Downward monotone
Knowledge: World knowledge
Premise: Cruz has frequently derided as "amnesty" any bill that confers legal status or citizenship on people living in the country illegally.
Hypothesis: Cruz has frequently derided as "amnesty" any plan that confers legal status or citizenship on people living in the country illegally.
Label: not_entailment
Logic: Downward monotone
Knowledge: World knowledge
Premise: Most of the graduates of my program have moved on to other things because the jobs suck.
Hypothesis: None of the graduates of my program have moved on to other things because the jobs suck.
Label: not_entailment
Lexical semantics: Quantifiers
Premise: None of the graduates of my program have moved on to other things because the jobs suck.
Hypothesis: Most of the graduates of my program have moved on to other things because the jobs suck.
Label: not_entailment
Lexical semantics: Quantifiers
Premise: Most of the graduates of my program have moved on to other things because the jobs suck.
Hypothesis: All of the graduates of my program have moved on to other things because the jobs suck.
Label: not_entailment
Lexical semantics: Quantifiers
Premise: All of the graduates of my program have moved on to other things because the jobs suck.
Hypothesis: Most of the graduates of my program have moved on to other things because the jobs suck.
Label: not_entailment
Lexical semantics: Quantifiers
Premise: In all areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
Hypothesis: In all developed areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
Label: entailment
Logic: Downward monotone
Predicate-argument structure: Intersectivity
Premise: In all developed areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
Hypothesis: In all areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
Label: not_entailment
Logic: Downward monotone
Predicate-argument structure: Intersectivity
Premise: Tom and Adam were whispering in the theater.
Hypothesis: Tom and Adam were whispering quietly in the theater.
Label: entailment
Lexical semantics: Redundancy
Premise: Tom and Adam were whispering quietly in the theater.
Hypothesis: Tom and Adam were whispering in the theater.
Label: entailment
Lexical semantics: Redundancy
Premise: Tom and Adam were whispering in the theater.
Hypothesis: Tom and Adam were whispering loudly in the theater.
Label: not_entailment
Lexical semantics: Redundancy
Premise: Tom and Adam were whispering loudly in the theater.
Hypothesis: Tom and Adam were whispering in the theater.
Label: entailment
Lexical semantics: Redundancy
Premise: Prior to the dance, which is voluntary, students are told to fill out a card by selecting five people they want to dance with.
Hypothesis: Prior to the dance, which is voluntary, students are told to fill out a card by selecting five different people they want to dance with.
Label: entailment
Lexical semantics: Redundancy
Premise: Prior to the dance, which is voluntary, students are told to fill out a card by selecting five different people they want to dance with.
Hypothesis: Prior to the dance, which is voluntary, students are told to fill out a card by selecting five people they want to dance with.
Label: entailment
Lexical semantics: Redundancy
Premise: Notifications about Farmville and other crap had become unbearable, then the shift to the non-chronological timeline happened and the content from your friends started to be replaced by ads and other cringy wannabe-viral campaigns.
Hypothesis: Notifications about Farmville and other crappy apps had become unbearable, then the shift to the non-chronological timeline happened and the content from your friends started to be replaced by ads and other cringy wannabe-viral campaigns.
Label: entailment
Lexical semantics: Redundancy
Premise: Notifications about Farmville and other crappy apps had become unbearable, then the shift to the non-chronological timeline happened and the content from your friends started to be replaced by ads and other cringy wannabe-viral campaigns.
Hypothesis: Notifications about Farmville and other crap had become unbearable, then the shift to the non-chronological timeline happened and the content from your friends started to be replaced by ads and other cringy wannabe-viral campaigns.
Label: entailment
Lexical semantics: Redundancy
Premise: Chicago City Hall is the official seat of government of the City of Chicago.
Hypothesis: Chicago City Hall is the official seat of government of Chicago.
Label: entailment
Lexical semantics: Redundancy
Premise: Chicago City Hall is the official seat of government of Chicago.
Hypothesis: Chicago City Hall is the official seat of government of the City of Chicago.
Label: entailment
Lexical semantics: Redundancy
Premise: The question generation aspect is unique to our formulation, and corresponds roughly to identifying what semantic role labels are present in previous formulations of the task.
Hypothesis: The question generation aspect is unique to our formulation, and corresponds roughly to identifying what semantic role labels are present in previous other formulations of the task.
Label: entailment
Lexical semantics: Redundancy
Premise: The question generation aspect is unique to our formulation, and corresponds roughly to identifying what semantic role labels are present in previous other formulations of the task.
Hypothesis: The question generation aspect is unique to our formulation, and corresponds roughly to identifying what semantic role labels are present in previous formulations of the task.
Label: entailment
Lexical semantics: Redundancy
Premise: John ate pasta for dinner.
Hypothesis: John ate pasta for supper.
Label: entailment
Lexical semantics: Lexical entailment
Premise: John ate pasta for supper.
Hypothesis: John ate pasta for dinner.
Label: entailment
Lexical semantics: Lexical entailment
Premise: John ate pasta for dinner.
Hypothesis: John ate pasta for breakfast.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: John ate pasta for breakfast.
Hypothesis: John ate pasta for dinner.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: House Speaker Paul Ryan was facing problems from fellow Republicans dissatisfied with his leadership.
Hypothesis: House Speaker Paul Ryan was facing problems from fellow Republicans unhappy with his leadership.
Label: entailment
Lexical semantics: Lexical entailment
Premise: House Speaker Paul Ryan was facing problems from fellow Republicans unhappy with his leadership.
Hypothesis: House Speaker Paul Ryan was facing problems from fellow Republicans dissatisfied with his leadership.
Label: entailment
Lexical semantics: Lexical entailment
Premise: House Speaker Paul Ryan was facing problems uniquely from fellow Republicans dissatisfied with his leadership.
Hypothesis: House Speaker Paul Ryan was facing problems uniquely from fellow Republicans supportive of his leadership.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: House Speaker Paul Ryan was facing problems uniquely from fellow Republicans supportive of his leadership.
Hypothesis: House Speaker Paul Ryan was facing problems uniquely from fellow Republicans dissatisfied with his leadership.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: I can actually see him climbing into a Lincoln saying this.
Hypothesis: I can actually see him getting into a Lincoln saying this.
Label: entailment
Lexical semantics: Lexical entailment
Premise: I can actually see him getting into a Lincoln saying this.
Hypothesis: I can actually see him climbing into a Lincoln saying this.
Label: entailment
Lexical semantics: Lexical entailment
Premise: I can actually see him climbing into a Lincoln saying this.
Hypothesis: I can actually see him climbing into a Mazda saying this.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: I can actually see him climbing into a Mazda saying this.
Hypothesis: I can actually see him climbing into a Lincoln saying this.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: The villain is the character who tends to have a negative effect on other characters.
Hypothesis: The villain is the character who tends to have a negative impact on other characters.
Label: entailment
Lexical semantics: Lexical entailment
Premise: The villain is the character who tends to have a negative impact on other characters.
Hypothesis: The villain is the character who tends to have a negative effect on other characters.
Label: entailment
Lexical semantics: Lexical entailment
Premise: The villain is the character who tends to have a negative effect on other characters.
Hypothesis: The villain is the character who tends to have a negative correlation with other characters.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: The villain is the character who tends to have a negative correlation with other characters.
Hypothesis: The villain is the character who tends to have a negative effect on other characters.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: Semantic parsing typically requires using a set of operations to query the knowledge base and process the results.
Hypothesis: Semantic parsing typically needs a set of operations to query the knowledge base and process the results.
Label: entailment
Lexical semantics: Lexical entailment
Premise: Semantic parsing typically needs a set of operations to query the knowledge base and process the results.
Hypothesis: Semantic parsing typically requires using a set of operations to query the knowledge base and process the results.
Label: entailment
Lexical semantics: Lexical entailment
Premise: Semantic parsing typically requires using a set of operations to query the knowledge base and process the results.
Hypothesis: Semantic parsing typically creates a set of operations to query the knowledge base and process the results.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: Semantic parsing typically creates a set of operations to query the knowledge base and process the results.
Hypothesis: Semantic parsing typically requires using a set of operations to query the knowledge base and process the results.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: Semantic parsing typically requires using a set of operations to query the knowledge base and process the results.
Hypothesis: Semantic parsing infrequently creates a set of operations to query the knowledge base and process the results.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: Semantic parsing infrequently creates a set of operations to query the knowledge base and process the results.
Hypothesis: Semantic parsing typically requires using a set of operations to query the knowledge base and process the results.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: John broke the window.
Hypothesis: The window was broken by John.
Label: entailment
Predicate-argument structure: Active/Passive
Premise: The window was broken by John.
Hypothesis: John broke the window.
Label: entailment
Predicate-argument structure: Active/Passive
Premise: John broke the window.
Hypothesis: The window broke John.
Label: not_entailment
Predicate-argument structure: Active/Passive
Premise: The window broke John.
Hypothesis: John broke the window.
Label: not_entailment
Predicate-argument structure: Active/Passive
Premise: Mueller’s team asked former senior Justice Department officials for information.
Hypothesis: Former senior Justice Department officials were asked for information by Mueller's team.
Label: entailment
Predicate-argument structure: Active/Passive
Premise: Former senior Justice Department officials were asked for information by Mueller's team.
Hypothesis: Mueller’s team asked former senior Justice Department officials for information.
Label: entailment
Predicate-argument structure: Active/Passive
Premise: Mueller’s team asked former senior Justice Department officials for information.
Hypothesis: Mueller’s team was asked for information by former senior Justice Department officials.
Label: not_entailment
Predicate-argument structure: Active/Passive
Premise: Mueller’s team was asked for information by former senior Justice Department officials.
Hypothesis: Mueller’s team asked former senior Justice Department officials for information.
Label: not_entailment
Predicate-argument structure: Active/Passive
Premise: Mueller’s team asked former senior Justice Department officials for information.
Hypothesis: Mueller’s team was asked for information.
Label: not_entailment
Predicate-argument structure: Active/Passive
Premise: Mueller’s team was asked for information.
Hypothesis: Mueller’s team asked former senior Justice Department officials for information.
Label: not_entailment
Predicate-argument structure: Active/Passive
Premise: Mueller’s team asked former senior Justice Department officials for information.
Hypothesis: Former senior Justice Department officials weren't asked for information.
Label: not_entailment
Logic: Negation
Predicate-argument structure: Active/Passive
Premise: Former senior Justice Department officials weren't asked for information.
Hypothesis: Mueller’s team asked former senior Justice Department officials for information.
Label: not_entailment
Logic: Negation
Predicate-argument structure: Active/Passive
Premise: Everyone should be afraid of the part when he asked Congress to allow his cabinet secretaries to terminate whoever they want.
Hypothesis: Everyone should be afraid of the part when Congress was asked to allow his cabinet secretaries to terminate whoever they want.
Label: entailment
Predicate-argument structure: Active/Passive
Premise: Everyone should be afraid of the part when Congress was asked to allow his cabinet secretaries to terminate whoever they want.
Hypothesis: Everyone should be afraid of the part when he asked Congress to allow his cabinet secretaries to terminate whoever they want.
Label: entailment
Predicate-argument structure: Active/Passive
Premise: Everyone should be afraid of the part when he asked Congress to allow his cabinet secretaries to terminate whoever they want.
Hypothesis: Everyone should be afraid of the part when he was asked to allow his cabinet secretaries to terminate whoever they want.
Label: not_entailment
Predicate-argument structure: Active/Passive
Premise: Everyone should be afraid of the part when he was asked to allow his cabinet secretaries to terminate whoever they want.
Hypothesis: Everyone should be afraid of the part when he asked Congress to allow his cabinet secretaries to terminate whoever they want.
Label: not_entailment
Predicate-argument structure: Active/Passive
Premise: Cape sparrows eat seeds, along with soft plant parts and insects.
Hypothesis: Seeds, along with soft plant parts and insects, are eaten by cape sparrows.
Label: entailment
Predicate-argument structure: Active/Passive
Premise: Seeds, along with soft plant parts and insects, are eaten by cape sparrows.
Hypothesis: Cape sparrows eat seeds, along with soft plant parts and insects.
Label: entailment
Predicate-argument structure: Active/Passive
Premise: Cape sparrows eat seeds, along with soft plant parts and insects.
Hypothesis: Cape sparrows are eaten by seeds, along with soft plant parts and insects.
Label: not_entailment
Predicate-argument structure: Active/Passive
Premise: Cape sparrows are eaten by seeds, along with soft plant parts and insects.
Hypothesis: Cape sparrows eat seeds, along with soft plant parts and insects.
Label: not_entailment
Predicate-argument structure: Active/Passive
Premise: Cape sparrows eat seeds, along with soft plant parts and insects.
Hypothesis: Cape sparrows are eaten.
Label: not_entailment
Predicate-argument structure: Active/Passive
Premise: Cape sparrows are eaten.
Hypothesis: Cape sparrows eat seeds, along with soft plant parts and insects.
Label: not_entailment
Predicate-argument structure: Active/Passive
Premise: Cape sparrows eat seeds, along with soft plant parts and insects.
Hypothesis: Soft plant parts and insects eat seeds.
Label: not_entailment
Predicate-argument structure: Prepositional phrases
Premise: Soft plant parts and insects eat seeds.
Hypothesis: Cape sparrows eat seeds, along with soft plant parts and insects.
Label: not_entailment
Predicate-argument structure: Prepositional phrases
Premise: Cape sparrows eat seeds, along with soft plant parts and insects.
Hypothesis: Soft plant parts and insects are eaten.
Label: entailment
Predicate-argument structure: Active/Passive;Prepositional phrases
Premise: Soft plant parts and insects are eaten.
Hypothesis: Cape sparrows eat seeds, along with soft plant parts and insects.
Label: not_entailment
Predicate-argument structure: Active/Passive;Prepositional phrases
Premise: Relation extraction systems populate knowledge bases with facts from unstructured text corpora.
Hypothesis: Knowledge bases are populated with facts from unstructured text corpora by relation extraction systems.
Label: entailment
Predicate-argument structure: Active/Passive
Premise: Knowledge bases are populated with facts from unstructured text corpora by relation extraction systems.
Hypothesis: Relation extraction systems populate knowledge bases with facts from unstructured text corpora.
Label: entailment
Predicate-argument structure: Active/Passive
Premise: Relation extraction systems populate knowledge bases with facts from unstructured text corpora.
Hypothesis: Knowledge bases are populated by relation extraction systems with facts from unstructured text corpora.
Label: entailment
Predicate-argument structure: Active/Passive
Premise: Knowledge bases are populated by relation extraction systems with facts from unstructured text corpora.
Hypothesis: Relation extraction systems populate knowledge bases with facts from unstructured text corpora.
Label: entailment
Predicate-argument structure: Active/Passive
Premise: Relation extraction systems populate knowledge bases with facts from unstructured text corpora.
Hypothesis: Relation extraction systems are populated by knowledge bases with facts from unstructured text corpora.
Label: not_entailment
Predicate-argument structure: Active/Passive
Premise: Relation extraction systems are populated by knowledge bases with facts from unstructured text corpora.
Hypothesis: Relation extraction systems populate knowledge bases with facts from unstructured text corpora.
Label: not_entailment
Predicate-argument structure: Active/Passive
Premise: Relation extraction systems populate knowledge bases with facts from unstructured text corpora.
Hypothesis: Relation extraction systems are populated with facts from unstructured text corpora by knowledge bases.
Label: not_entailment
Predicate-argument structure: Active/Passive
Premise: Relation extraction systems are populated with facts from unstructured text corpora by knowledge bases.
Hypothesis: Relation extraction systems populate knowledge bases with facts from unstructured text corpora.
Label: not_entailment
Predicate-argument structure: Active/Passive
Premise: Relation extraction systems populate knowledge bases with facts from unstructured text corpora.
Hypothesis: Relation extraction systems populate knowledge bases with assertions from unstructured text corpora.
Label: entailment
Lexical semantics: Lexical entailment
Knowledge: World knowledge
Premise: Relation extraction systems populate knowledge bases with assertions from unstructured text corpora.
Hypothesis: Relation extraction systems populate knowledge bases with facts from unstructured text corpora.
Label: entailment
Lexical semantics: Lexical entailment
Knowledge: World knowledge
Premise: Wal-Mart's recent move is tied to its continuing efforts to beat back competition against retailers like Amazon.
Hypothesis: The recent move by Wal-Mart is tied to its continuing efforts to beat back competition against retailers like Amazon.
Label: entailment
Predicate-argument structure: Genitives/Partitives
Premise: The recent move by Wal-Mart is tied to its continuing efforts to beat back competition against retailers like Amazon.
Hypothesis: Wal-Mart's recent move is tied to its continuing efforts to beat back competition against retailers like Amazon.
Label: entailment
Predicate-argument structure: Genitives/Partitives
Premise: Wal-Mart's recent move is tied to its continuing efforts to beat back competition against retailers like Amazon.
Hypothesis: The recent move against Wal-Mart is tied to its continuing efforts to beat back competition against retailers like Amazon.
Label: not_entailment
Predicate-argument structure: Genitives/Partitives
Premise: The recent move against Wal-Mart is tied to its continuing efforts to beat back competition against retailers like Amazon.
Hypothesis: Wal-Mart's recent move is tied to its continuing efforts to beat back competition against retailers like Amazon.
Label: not_entailment
Predicate-argument structure: Genitives/Partitives
Premise: The man gets down on one knee and inspects the bottom of the elephant's foot only to find a large thorn deeply embedded.
Hypothesis: The man gets down on one knee and inspects the bottom of the foot of the elephant only to find a large thorn deeply embedded.
Label: entailment
Predicate-argument structure: Genitives/Partitives
Premise: The man gets down on one knee and inspects the bottom of the foot of the elephant only to find a large thorn deeply embedded.
Hypothesis: The man gets down on one knee and inspects the bottom of the elephant's foot only to find a large thorn deeply embedded.
Label: entailment
Predicate-argument structure: Genitives/Partitives
Premise: The Cape sparrow's population has not decreased significantly, and is not seriously threatened by human activities.
Hypothesis: The population of the Cape sparrow has not decreased significantly, and is not seriously threatened by human activities.
Label: entailment
Predicate-argument structure: Genitives/Partitives
Premise: The population of the Cape sparrow has not decreased significantly, and is not seriously threatened by human activities.
Hypothesis: The Cape sparrow's population has not decreased significantly, and is not seriously threatened by human activities.
Label: entailment
Predicate-argument structure: Genitives/Partitives
Premise: The Cape sparrow's population has not decreased significantly, and is not seriously threatened by human activities.
Hypothesis: The population of the Cape sparrow has decreased significantly, and is seriously threatened by human activities.
Label: not_entailment
Logic: Negation
Predicate-argument structure: Genitives/Partitives
Premise: The population of the Cape sparrow has decreased significantly, and is seriously threatened by human activities.
Hypothesis: The Cape sparrow's population has not decreased significantly, and is not seriously threatened by human activities.
Label: not_entailment
Logic: Negation
Predicate-argument structure: Genitives/Partitives
Premise: This paper presents an approach for understanding the contents of these message vectors by translating them into natural language.
Hypothesis: This paper presents an approach for understanding these message vectors' content by translating them into natural language.
Label: entailment
Predicate-argument structure: Genitives/Partitives
Premise: This paper presents an approach for understanding these message vectors' content by translating them into natural language.
Hypothesis: This paper presents an approach for understanding the contents of these message vectors by translating them into natural language.
Label: entailment
Predicate-argument structure: Genitives/Partitives
Premise: This paper presents an approach for understanding the contents of these message vectors by translating them into natural language.
Hypothesis: This paper presents an approach for understanding the contents of these message vectors by translating them into foreign language.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: This paper presents an approach for understanding the contents of these message vectors by translating them into foreign language.
Hypothesis: This paper presents an approach for understanding the contents of these message vectors by translating them into natural language.
Label: not_entailment
Lexical semantics: Lexical entailment
Premise: She is skilled at violin.
Hypothesis: She is a skilled violinist.
Label: entailment
Predicate-argument structure: Intersectivity
Premise: She is a skilled violinist.
Hypothesis: She is skilled at violin.
Label: entailment
Predicate-argument structure: Intersectivity
Premise: She is skilled.
Hypothesis: She is a skilled violinist.
Label: not_entailment
Predicate-argument structure: Intersectivity
Premise: She is a skilled violinist.
Hypothesis: She is skilled.
Label: entailment
Predicate-argument structure: Intersectivity
Premise: She is a surgeon and skilled violinist.
Hypothesis: She is a skilled surgeon.
Label: not_entailment
Predicate-argument structure: Intersectivity
Premise: She is a skilled surgeon.
Hypothesis: She is a surgeon and skilled violinist.
Label: not_entailment
Predicate-argument structure: Intersectivity
Premise: The combination of mentos and diet coke caused the explosion.
Hypothesis: Combining mentos and diet coke caused the explosion.
Label: entailment
Predicate-argument structure: Nominalization
Premise: Combining mentos and diet coke caused the explosion.
Hypothesis: The combination of mentos and diet coke caused the explosion.
Label: entailment
Predicate-argument structure: Nominalization
Premise: In an Oval Office meeting after Mueller's appointment, Trump told Sessions he should resign, prompting the attorney general to submit a letter of resignation, according to The New York Times.
Hypothesis: In an Oval Office meeting after Mueller's appointment, Trump told Sessions he should resign, prompting the attorney general's submission of a letter of resignation, according to The New York Times.
Label: entailment
Predicate-argument structure: Nominalization
Premise: In an Oval Office meeting after Mueller's appointment, Trump told Sessions he should resign, prompting the attorney general's submission of a letter of resignation, according to The New York Times.
Hypothesis: In an Oval Office meeting after Mueller's appointment, Trump told Sessions he should resign, prompting the attorney general to submit a letter of resignation, according to The New York Times.
Label: entailment
Predicate-argument structure: Nominalization
Premise: In an Oval Office meeting after Mueller's appointment, Trump told Sessions he should resign, prompting the attorney general to submit a letter of resignation, according to The New York Times.
Hypothesis: In an Oval Office meeting after Mueller's appointment, Trump told Sessions he should resign, prompting the attorney general's withholding of a letter of resignation, according to The New York Times.
Label: not_entailment
Predicate-argument structure: Nominalization
Lexical semantics: Lexical entailment
Premise: In an Oval Office meeting after Mueller's appointment, Trump told Sessions he should resign, prompting the attorney general's withholding of a letter of resignation, according to The New York Times.
Hypothesis: In an Oval Office meeting after Mueller's appointment, Trump told Sessions he should resign, prompting the attorney general to submit a letter of resignation, according to The New York Times.
Label: not_entailment
Predicate-argument structure: Nominalization
Lexical semantics: Lexical entailment
Premise: Thought this was super cool, and a really important step in preserving all the physical books.
Hypothesis: Thought this was super cool, and a really important step in the preservation of all the physical books.
Label: entailment
Predicate-argument structure: Nominalization
Premise: Thought this was super cool, and a really important step in the preservation of all the physical books.
Hypothesis: Thought this was super cool, and a really important step in preserving all the physical books.
Label: entailment
Predicate-argument structure: Nominalization
Premise: Thought this was super cool, and a really important step in preserving all the physical books.
Hypothesis: Thought this was super cool, and a really important step in the destruction of all the physical books.
Label: not_entailment
Predicate-argument structure: Nominalization
Lexical semantics: Lexical entailment
Premise: Thought this was super cool, and a really important step in the destruction of all the physical books.
Hypothesis: Thought this was super cool, and a really important step in preserving all the physical books.
Label: not_entailment
Predicate-argument structure: Nominalization
Lexical semantics: Lexical entailment