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2 values
sentence1
stringlengths
11
296
sentence2
stringlengths
11
296
predicate-argument-structure
stringclasses
23 values
logic
stringclasses
29 values
knowledge
stringclasses
2 values
lexical-semantics
stringclasses
10 values
0
not_entailment
The cat sat on the mat.
The cat did not sit on the mat.
null
Negation
null
null
1
not_entailment
The cat did not sit on the mat.
The cat sat on the mat.
null
Negation
null
null
2
not_entailment
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.
null
Negation
null
null
3
not_entailment
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.
null
Negation
null
null
4
not_entailment
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.
null
Negation
null
null
5
not_entailment
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.
null
Negation
null
null
6
entailment
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.
Anaphora/Coreference
null
null
null
7
entailment
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.
Anaphora/Coreference
null
null
null
8
not_entailment
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.
null
Negation
null
null
9
not_entailment
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.
null
Negation
null
null
10
not_entailment
The new gaming console is affordable.
The new gaming console is unaffordable.
null
Negation
null
Morphological negation
11
not_entailment
The new gaming console is unaffordable.
The new gaming console is affordable.
null
Negation
null
Morphological negation
12
not_entailment
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.
null
Negation
null
Morphological negation
13
not_entailment
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.
null
Negation
null
Morphological negation
14
not_entailment
We built our society on unclean energy.
We built our society on clean energy.
null
Negation
null
Morphological negation
15
not_entailment
We built our society on clean energy.
We built our society on unclean energy.
null
Negation
null
Morphological negation
16
not_entailment
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.
null
Negation
null
Morphological negation
17
not_entailment
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.
null
Negation
null
Morphological negation
18
entailment
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.
Intersectivity
null
null
null
19
not_entailment
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.
Intersectivity
null
null
null
20
not_entailment
And if both apply, they are essentially impossible.
And if both apply, they are essentially possible.
null
Negation;Conditionals
null
Morphological negation
21
not_entailment
And if both apply, they are essentially possible.
And if both apply, they are essentially impossible.
null
Negation;Conditionals
null
Morphological negation
22
entailment
Writing Java is not too different from programming with handcuffs.
Writing Java is similar to programming with handcuffs.
null
Double negation
null
Morphological negation
23
entailment
Writing Java is similar to programming with handcuffs.
Writing Java is not too different from programming with handcuffs.
null
Double negation
null
Morphological negation
24
entailment
The market is about to get harder, but not impossible to navigate.
The market is about to get harder, but possible to navigate.
null
Double negation
null
Morphological negation
25
entailment
The market is about to get harder, but possible to navigate.
The market is about to get harder, but not impossible to navigate.
null
Double negation
null
Morphological negation
26
entailment
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.
null
Double negation
null
Morphological negation
27
entailment
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.
null
Double negation
null
Morphological negation
28
entailment
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.
null
Double negation
null
Morphological negation
29
entailment
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.
null
Double negation
null
Morphological negation
30
entailment
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.
null
Double negation
null
Morphological negation
31
entailment
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.
null
Double negation
null
Morphological negation
32
entailment
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.
Nominalization
null
null
null
33
entailment
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.
Nominalization
null
null
null
34
entailment
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.
Nominalization
Double negation
null
Morphological negation
35
entailment
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.
Nominalization
Double negation
null
Morphological negation
36
not_entailment
The water is too hot.
The water is too cold.
null
null
null
Lexical entailment
37
not_entailment
The water is too cold.
The water is too hot.
null
null
null
Lexical entailment
38
not_entailment
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.
null
null
null
Lexical entailment
39
not_entailment
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.
null
null
null
Lexical entailment
40
not_entailment
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.
null
null
null
Lexical entailment
41
not_entailment
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.
null
null
null
Lexical entailment
42
not_entailment
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.
null
null
null
Lexical entailment
43
not_entailment
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.
null
null
null
Lexical entailment
44
entailment
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.
null
null
null
Lexical entailment
45
entailment
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.
null
null
null
Lexical entailment
46
not_entailment
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.
null
null
null
Lexical entailment
47
not_entailment
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.
null
null
null
Lexical entailment
48
entailment
Some dogs like to scratch their ears.
Some animals like to scratch their ears.
null
Upward monotone
null
Lexical entailment
49
not_entailment
Some animals like to scratch their ears.
Some dogs like to scratch their ears.
null
Upward monotone
null
Lexical entailment
50
not_entailment
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.
null
Upward monotone
World knowledge
null
51
entailment
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.
null
Upward monotone
World knowledge
null
52
entailment
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.
null
null
null
Quantifiers
53
not_entailment
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.
null
null
null
Quantifiers
54
entailment
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.
Intersectivity
Upward monotone
null
null
55
not_entailment
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.
Intersectivity
Upward monotone
null
null
56
entailment
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.
Intersectivity
Upward monotone
null
null
57
not_entailment
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.
Intersectivity
Upward monotone
null
null
58
not_entailment
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.
null
null
null
Quantifiers
59
not_entailment
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.
null
null
null
Quantifiers
60
not_entailment
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.
null
null
null
Quantifiers
61
entailment
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.
null
null
null
Quantifiers
62
not_entailment
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.
Intersectivity
Downward monotone
null
null
63
entailment
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.
Intersectivity
Downward monotone
null
null
64
not_entailment
All dogs like to scratch their ears.
All animals like to scratch their ears.
null
Downward monotone
null
Lexical entailment
65
entailment
All animals like to scratch their ears.
All dogs like to scratch their ears.
null
Downward monotone
null
Lexical entailment
66
entailment
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.
null
Downward monotone
World knowledge
null
67
not_entailment
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.
null
Downward monotone
World knowledge
null
68
not_entailment
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.
null
null
null
Quantifiers
69
not_entailment
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.
null
null
null
Quantifiers
70
not_entailment
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.
null
null
null
Quantifiers
71
not_entailment
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.
null
null
null
Quantifiers
72
entailment
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.
Intersectivity
Downward monotone
null
null
73
not_entailment
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.
Intersectivity
Downward monotone
null
null
74
entailment
Tom and Adam were whispering in the theater.
Tom and Adam were whispering quietly in the theater.
null
null
null
Redundancy
75
entailment
Tom and Adam were whispering quietly in the theater.
Tom and Adam were whispering in the theater.
null
null
null
Redundancy
76
not_entailment
Tom and Adam were whispering in the theater.
Tom and Adam were whispering loudly in the theater.
null
null
null
Redundancy
77
entailment
Tom and Adam were whispering loudly in the theater.
Tom and Adam were whispering in the theater.
null
null
null
Redundancy
78
entailment
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.
null
null
null
Redundancy
79
entailment
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.
null
null
null
Redundancy
80
entailment
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.
null
null
null
Redundancy
81
entailment
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.
null
null
null
Redundancy
82
entailment
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.
null
null
null
Redundancy
83
entailment
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.
null
null
null
Redundancy
84
entailment
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.
null
null
null
Redundancy
85
entailment
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.
null
null
null
Redundancy
86
entailment
John ate pasta for dinner.
John ate pasta for supper.
null
null
null
Lexical entailment
87
entailment
John ate pasta for supper.
John ate pasta for dinner.
null
null
null
Lexical entailment
88
not_entailment
John ate pasta for dinner.
John ate pasta for breakfast.
null
null
null
Lexical entailment
89
not_entailment
John ate pasta for breakfast.
John ate pasta for dinner.
null
null
null
Lexical entailment
90
entailment
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.
null
null
null
Lexical entailment
91
entailment
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.
null
null
null
Lexical entailment
92
not_entailment
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.
null
null
null
Lexical entailment
93
not_entailment
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.
null
null
null
Lexical entailment
94
entailment
I can actually see him climbing into a Lincoln saying this.
I can actually see him getting into a Lincoln saying this.
null
null
null
Lexical entailment
95
entailment
I can actually see him getting into a Lincoln saying this.
I can actually see him climbing into a Lincoln saying this.
null
null
null
Lexical entailment
96
not_entailment
I can actually see him climbing into a Lincoln saying this.
I can actually see him climbing into a Mazda saying this.
null
null
null
Lexical entailment
97
not_entailment
I can actually see him climbing into a Mazda saying this.
I can actually see him climbing into a Lincoln saying this.
null
null
null
Lexical entailment
98
entailment
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.
null
null
null
Lexical entailment
99
entailment
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.
null
null
null
Lexical entailment
End of preview. Expand in Data Studio

AX-b — evaluation data (OpenCompass format)

Bud Ecosystem eval mirror. OpenCompass-native eval data for AX-b, laid out at SuperGLUE/AX-b/ exactly as the OpenCompass dataset loader expects. Sourced from the OpenCompass data distribution; license CC-BY-4.0, unchanged; all rights remain with the original authors.

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