sileod/deberta-v3-base-tasksource-nli
Zero-Shot Classification
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Updated
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19.9k
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120
lexical semantics
stringclasses 11
values | predicate-argument structure
stringclasses 24
values | logic
stringclasses 30
values | knowledge
stringclasses 3
values | domain
stringclasses 5
values | premise
stringlengths 11
296
| hypothesis
stringlengths 11
296
| label
class label 0
2
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Negation | Artificial | The cat sat on the mat. | The cat did not sit on the mat. | 2contradiction
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Negation | Artificial | The cat did not sit on the mat. | The cat sat on the mat. | 2contradiction
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Negation | News | 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. | 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. | 1neutral
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Negation | News | 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. | 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. | 1neutral
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Negation | Wikipedia | Out of the box, Ouya supports media apps such as Twitch.tv and XBMC media player. | Out of the box, Ouya doesn't support media apps such as Twitch.tv and XBMC media player. | 2contradiction
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Negation | Wikipedia | Out of the box, Ouya doesn't support media apps such as Twitch.tv and XBMC media player. | Out of the box, Ouya supports media apps such as Twitch.tv and XBMC media player. | 2contradiction
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Anaphora/Coreference | Wikipedia | Out of the box, Ouya supports media apps such as Twitch.tv and XBMC media player. | Out of the box, Ouya supports Twitch.tv and XBMC media player. | 0entailment
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Anaphora/Coreference | Wikipedia | Out of the box, Ouya supports Twitch.tv and XBMC media player. | Out of the box, Ouya supports media apps such as Twitch.tv and XBMC media player. | 0entailment
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Negation | ACL | Considering this definition, it is surprising to find frequent use of sarcastic language in opinionated user generated content. | Considering this definition, it is not surprising to find frequent use of sarcastic language in opinionated user generated content. | 2contradiction
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Negation | ACL | Considering this definition, it is not surprising to find frequent use of sarcastic language in opinionated user generated content. | Considering this definition, it is surprising to find frequent use of sarcastic language in opinionated user generated content. | 2contradiction
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Morphological negation | Negation | Artificial | The new gaming console is affordable. | The new gaming console is unaffordable. | 2contradiction
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Morphological negation | Negation | Artificial | The new gaming console is unaffordable. | The new gaming console is affordable. | 2contradiction
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Morphological negation | Negation | News | 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. | 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. | 2contradiction
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Morphological negation | Negation | News | 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. | 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. | 2contradiction
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Morphological negation | Negation | Reddit | We built our society on unclean energy. | We built our society on clean energy. | 2contradiction
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Morphological negation | Negation | Reddit | We built our society on clean energy. | We built our society on unclean energy. | 2contradiction
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Morphological negation | Negation | Wikipedia | Pursuing a strategy of nonviolent protest, Gandhi took the administration by surprise and won concessions from the authorities. | Pursuing a strategy of violent protest, Gandhi took the administration by surprise and won concessions from the authorities. | 2contradiction
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Morphological negation | Negation | Wikipedia | Pursuing a strategy of violent protest, Gandhi took the administration by surprise and won concessions from the authorities. | Pursuing a strategy of nonviolent protest, Gandhi took the administration by surprise and won concessions from the authorities. | 2contradiction
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Intersectivity | Wikipedia | Pursuing a strategy of nonviolent protest, Gandhi took the administration by surprise and won concessions from the authorities. | Pursuing a strategy of protest, Gandhi took the administration by surprise and won concessions from the authorities. | 0entailment
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Intersectivity | Wikipedia | Pursuing a strategy of protest, Gandhi took the administration by surprise and won concessions from the authorities. | Pursuing a strategy of nonviolent protest, Gandhi took the administration by surprise and won concessions from the authorities. | 1neutral
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Morphological negation | Negation;Conditionals | ACL | And if both apply, they are essentially impossible. | And if both apply, they are essentially possible. | 2contradiction
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Morphological negation | Negation;Conditionals | ACL | And if both apply, they are essentially possible. | And if both apply, they are essentially impossible. | 2contradiction
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Morphological negation | Double negation | Artificial | Writing Java is not too different from programming with handcuffs. | Writing Java is similar to programming with handcuffs. | 0entailment
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Morphological negation | Double negation | Artificial | Writing Java is similar to programming with handcuffs. | Writing Java is not too different from programming with handcuffs. | 0entailment
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Morphological negation | Double negation | News | The market is about to get harder, but not impossible to navigate. | The market is about to get harder, but possible to navigate. | 0entailment
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Morphological negation | Double negation | News | The market is about to get harder, but possible to navigate. | The market is about to get harder, but not impossible to navigate. | 0entailment
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Morphological negation | Double negation | Reddit | Even after now finding out that it's animal feed, I won't ever stop being addicted to Flamin' Hot Cheetos. | Even after now finding out that it's animal feed, I will never stop being addicted to Flamin' Hot Cheetos. | 0entailment
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Morphological negation | Double negation | Reddit | Even after now finding out that it's animal feed, I will never stop being addicted to Flamin' Hot Cheetos. | Even after now finding out that it's animal feed, I won't ever stop being addicted to Flamin' Hot Cheetos. | 0entailment
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Morphological negation | Double negation | Wikipedia | 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. | 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. | 0entailment
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Morphological negation | Double negation | Wikipedia | 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. | 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. | 0entailment
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Morphological negation | Double negation | ACL | 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. | 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. | 0entailment
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Morphological negation | Double negation | ACL | 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. | 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. | 0entailment
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Nominalization | ACL | 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. | 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. | 0entailment
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Nominalization | ACL | 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. | 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. | 0entailment
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Morphological negation | Nominalization | Double negation | ACL | 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. | 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. | 0entailment
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Morphological negation | Nominalization | Double negation | ACL | 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. | 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. | 0entailment
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Lexical entailment | Artificial | The water is too hot. | The water is too cold. | 2contradiction
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Lexical entailment | Artificial | The water is too cold. | The water is too hot. | 2contradiction
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Lexical entailment | News | Falcon Heavy is the largest rocket since NASA's Saturn V booster, which was used for the Moon missions in the 1970s. | Falcon Heavy is the smallest rocket since NASA's Saturn V booster, which was used for the Moon missions in the 1970s. | 2contradiction
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Lexical entailment | News | Falcon Heavy is the smallest rocket since NASA's Saturn V booster, which was used for the Moon missions in the 1970s. | Falcon Heavy is the largest rocket since NASA's Saturn V booster, which was used for the Moon missions in the 1970s. | 2contradiction
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Lexical entailment | Wikipedia | Adenoiditis symptoms often persist for ten or more days, and often include pus-like discharge from nose. | Adenoiditis symptoms often pass within ten days or less, and often include pus-like discharge from nose. | 2contradiction
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Lexical entailment | Wikipedia | Adenoiditis symptoms often pass within ten days or less, and often include pus-like discharge from nose. | Adenoiditis symptoms often persist for ten or more days, and often include pus-like discharge from nose. | 2contradiction
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Lexical entailment | ACL | In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings. | In example (1) it is quite difficult to see the exaggerated positive sentiment used in order to convey strong negative feelings. | 2contradiction
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Lexical entailment | ACL | In example (1) it is quite difficult to see the exaggerated positive sentiment used in order to convey strong negative feelings. | In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings. | 2contradiction
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Lexical entailment | ACL | In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings. | In example (1) it is quite easy to see the exaggerated positive sentiment used in order to convey strong negative feelings. | 0entailment
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Lexical entailment | ACL | In example (1) it is quite easy to see the exaggerated positive sentiment used in order to convey strong negative feelings. | In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings. | 0entailment
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Lexical entailment | ACL | In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings. | In example (1) it is quite important to see the exaggerated positive sentiment used in order to convey strong negative feelings. | 1neutral
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Lexical entailment | ACL | In example (1) it is quite important to see the exaggerated positive sentiment used in order to convey strong negative feelings. | In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings. | 1neutral
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Lexical entailment | Upward monotone | Artificial | Some dogs like to scratch their ears. | Some animals like to scratch their ears. | 0entailment
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Lexical entailment | Upward monotone | Artificial | Some animals like to scratch their ears. | Some dogs like to scratch their ears. | 1neutral
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Upward monotone | World knowledge | News | Cruz has frequently derided as "amnesty" various plans that confer legal status or citizenship on people living in the country illegally. | Cruz has frequently derided as "amnesty" various bills that confer legal status or citizenship on people living in the country illegally. | 1neutral
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Upward monotone | World knowledge | News | Cruz has frequently derided as "amnesty" various bills that confer legal status or citizenship on people living in the country illegally. | Cruz has frequently derided as "amnesty" various plans that confer legal status or citizenship on people living in the country illegally. | 0entailment
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Quantifiers | Reddit | Most of the graduates of my program have moved on to other things because the jobs suck. | Some of the graduates of my program have moved on to other things because the jobs suck. | 0entailment
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Quantifiers | Reddit | Some of the graduates of my program have moved on to other things because the jobs suck. | Most of the graduates of my program have moved on to other things because the jobs suck. | 1neutral
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Intersectivity | Upward monotone | Wikipedia | In many developed areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding. | In many areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding. | 0entailment
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Intersectivity | Upward monotone | Wikipedia | In many areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding. | In many developed areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding. | 1neutral
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Intersectivity | Upward monotone | ACL | We consider some context words as positive examples and sample negatives at random from the dictionary. | We consider some words as positive examples and sample negatives at random from the dictionary. | 0entailment
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Intersectivity | Upward monotone | ACL | We consider some words as positive examples and sample negatives at random from the dictionary. | We consider some context words as positive examples and sample negatives at random from the dictionary. | 1neutral
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Quantifiers | ACL | We consider some context words as positive examples and sample negatives at random from the dictionary. | We consider all context words as positive examples and sample many negatives at random from the dictionary. | 1neutral
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Quantifiers | ACL | We consider all context words as positive examples and sample many negatives at random from the dictionary. | We consider some context words as positive examples and sample negatives at random from the dictionary. | 1neutral
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Quantifiers | ACL | We consider some context words as positive examples and sample negatives at random from the dictionary. | We consider many context words as positive examples and sample negatives at random from the dictionary. | 1neutral
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Quantifiers | ACL | We consider many context words as positive examples and sample negatives at random from the dictionary. | We consider some context words as positive examples and sample negatives at random from the dictionary. | 0entailment
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Intersectivity | Downward monotone | ACL | We consider all context words as positive examples and sample negatives at random from the dictionary. | We consider all words as positive examples and sample negatives at random from the dictionary. | 1neutral
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Intersectivity | Downward monotone | ACL | We consider all words as positive examples and sample negatives at random from the dictionary. | We consider all context words as positive examples and sample negatives at random from the dictionary. | 0entailment
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Lexical entailment | Downward monotone | Artificial | All dogs like to scratch their ears. | All animals like to scratch their ears. | 1neutral
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Lexical entailment | Downward monotone | Artificial | All animals like to scratch their ears. | All dogs like to scratch their ears. | 0entailment
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Downward monotone | World knowledge | News | Cruz has frequently derided as "amnesty" any plan that confers legal status or citizenship on people living in the country illegally. | Cruz has frequently derided as "amnesty" any bill that confers legal status or citizenship on people living in the country illegally. | 0entailment
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Downward monotone | World knowledge | News | Cruz has frequently derided as "amnesty" any bill that confers legal status or citizenship on people living in the country illegally. | Cruz has frequently derided as "amnesty" any plan that confers legal status or citizenship on people living in the country illegally. | 1neutral
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Quantifiers | Reddit | Most of the graduates of my program have moved on to other things because the jobs suck. | None of the graduates of my program have moved on to other things because the jobs suck. | 2contradiction
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Quantifiers | Reddit | None of the graduates of my program have moved on to other things because the jobs suck. | Most of the graduates of my program have moved on to other things because the jobs suck. | 2contradiction
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Quantifiers | Reddit | Most of the graduates of my program have moved on to other things because the jobs suck. | All of the graduates of my program have moved on to other things because the jobs suck. | 2contradiction
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Quantifiers | Reddit | All of the graduates of my program have moved on to other things because the jobs suck. | Most of the graduates of my program have moved on to other things because the jobs suck. | 2contradiction
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Intersectivity | Downward monotone | Wikipedia | In all areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding. | In all developed areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding. | 0entailment
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Intersectivity | Downward monotone | Wikipedia | In all developed areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding. | In all areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding. | 1neutral
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Redundancy | Artificial | Tom and Adam were whispering in the theater. | Tom and Adam were whispering quietly in the theater. | 0entailment
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Redundancy | Artificial | Tom and Adam were whispering quietly in the theater. | Tom and Adam were whispering in the theater. | 0entailment
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Redundancy | Artificial | Tom and Adam were whispering in the theater. | Tom and Adam were whispering loudly in the theater. | 1neutral
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Redundancy | Artificial | Tom and Adam were whispering loudly in the theater. | Tom and Adam were whispering in the theater. | 0entailment
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Redundancy | News | Prior to the dance, which is voluntary, students are told to fill out a card by selecting five people they want to dance with. | 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. | 0entailment
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Redundancy | News | 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. | Prior to the dance, which is voluntary, students are told to fill out a card by selecting five people they want to dance with. | 0entailment
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Redundancy | Reddit | 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. | 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. | 0entailment
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Redundancy | Reddit | 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. | 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. | 0entailment
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Redundancy | Wikipedia | Chicago City Hall is the official seat of government of the City of Chicago. | Chicago City Hall is the official seat of government of Chicago. | 0entailment
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Redundancy | Wikipedia | Chicago City Hall is the official seat of government of Chicago. | Chicago City Hall is the official seat of government of the City of Chicago. | 0entailment
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Redundancy | ACL | 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. | 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. | 0entailment
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Redundancy | ACL | 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. | 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. | 0entailment
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Lexical entailment | Artificial | John ate pasta for dinner. | John ate pasta for supper. | 0entailment
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Lexical entailment | Artificial | John ate pasta for supper. | John ate pasta for dinner. | 0entailment
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Lexical entailment | Artificial | John ate pasta for dinner. | John ate pasta for breakfast. | 1neutral
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Lexical entailment | Artificial | John ate pasta for breakfast. | John ate pasta for dinner. | 1neutral
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Lexical entailment | News | House Speaker Paul Ryan was facing problems from fellow Republicans dissatisfied with his leadership. | House Speaker Paul Ryan was facing problems from fellow Republicans unhappy with his leadership. | 0entailment
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Lexical entailment | News | House Speaker Paul Ryan was facing problems from fellow Republicans unhappy with his leadership. | House Speaker Paul Ryan was facing problems from fellow Republicans dissatisfied with his leadership. | 0entailment
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Lexical entailment | News | House Speaker Paul Ryan was facing problems uniquely from fellow Republicans dissatisfied with his leadership. | House Speaker Paul Ryan was facing problems uniquely from fellow Republicans supportive of his leadership. | 2contradiction
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Lexical entailment | News | House Speaker Paul Ryan was facing problems uniquely from fellow Republicans supportive of his leadership. | House Speaker Paul Ryan was facing problems uniquely from fellow Republicans dissatisfied with his leadership. | 2contradiction
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Lexical entailment | Reddit | I can actually see him climbing into a Lincoln saying this. | I can actually see him getting into a Lincoln saying this. | 0entailment
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Lexical entailment | Reddit | I can actually see him getting into a Lincoln saying this. | I can actually see him climbing into a Lincoln saying this. | 0entailment
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Lexical entailment | Reddit | I can actually see him climbing into a Lincoln saying this. | I can actually see him climbing into a Mazda saying this. | 1neutral
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Lexical entailment | Reddit | I can actually see him climbing into a Mazda saying this. | I can actually see him climbing into a Lincoln saying this. | 1neutral
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Lexical entailment | Wikipedia | The villain is the character who tends to have a negative effect on other characters. | The villain is the character who tends to have a negative impact on other characters. | 0entailment
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Lexical entailment | Wikipedia | The villain is the character who tends to have a negative impact on other characters. | The villain is the character who tends to have a negative effect on other characters. | 0entailment
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YAML Metadata
Warning:
empty or missing yaml metadata in repo card
(https://huggingface.co/docs/hub/datasets-cards)
Overview
Original dataset available here.
Dataset curation
Filled in the empty rows of columns "lexical semantics", "predicate-argument structure",
"logic", "knowledge" with empty string "".
Labels are encoded as follows
{"entailment": 0, "neutral": 1, "contradiction": 2}
Code to create dataset
import pandas as pd
from datasets import Features, Value, ClassLabel, Dataset
df = pd.read_csv("<path to file>/diagnostic-full.tsv", sep="\t")
# column names to lower
df.columns = df.columns.str.lower()
# fill na
assert df["label"].isna().sum() == 0
df = df.fillna("")
# encode labels
df["label"] = df["label"].map({"entailment": 0, "neutral": 1, "contradiction": 2})
# cast to dataset
features = Features({
"lexical semantics": Value(dtype="string", id=None),
"predicate-argument structure": Value(dtype="string", id=None),
"logic": Value(dtype="string", id=None),
"knowledge": Value(dtype="string", id=None),
"domain": Value(dtype="string", id=None),
"premise": Value(dtype="string", id=None),
"hypothesis": Value(dtype="string", id=None),
"label": ClassLabel(num_classes=3, names=["entailment", "neutral", "contradiction"]),
})
dataset = Dataset.from_pandas(df, features=features)
dataset.push_to_hub("glue_diagnostics", token="<token>", split="test")
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Size of downloaded dataset files:
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Size of the auto-converted Parquet files:
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Number of rows:
1,104