state stringlengths 0 129k | kind stringclasses 3
values | id stringlengths 22 168 | options listlengths 0 235 | target listlengths 1 235 | question stringlengths 18 11.4k | source stringclasses 668
values | variant stringclasses 6
values | split stringclasses 1
value | group_id stringlengths 22 82 | question_id stringlengths 4 118 | license stringclasses 69
values | license_use stringclasses 3
values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
Item A:
This film is about a man who has been too caught up with the accepted convention of success, trying to be ever upwardly mobile, working hard so that he could be proud of owning his own home. He assumes this is all there is to life until he accidentally takes up dancing, all because he wanted to get a closer loo... | noul | counterfactually-augmented-imdb-72396a9ef6:train:pack-5acf7a6d6f46:exists-0 | [] | [
1
] | Each item answers: "What sentiment does the text express?"
Does at least one item have the label "Negative"? Possible labels: "Negative", "Positive". | counterfactually-augmented-imdb | packed_derived | train | counterfactually-augmented-imdb-72396a9ef6:train:pack-5acf7a6d6f46 | exists-0 | unspecified | unspecified |
Item A:
This film is about a man who has been too caught up with the accepted convention of success, trying to be ever upwardly mobile, working hard so that he could be proud of owning his own home. He assumes this is all there is to life until he accidentally takes up dancing, all because he wanted to get a closer loo... | score | counterfactually-augmented-imdb-72396a9ef6:train:pack-5acf7a6d6f46:count-0 | [
"0",
"1",
"2"
] | [
0,
0,
1
] | Each item answers: "What sentiment does the text express?"
How many items have the label "Negative"? Possible labels: "Negative", "Positive". | counterfactually-augmented-imdb | packed_derived | train | counterfactually-augmented-imdb-72396a9ef6:train:pack-5acf7a6d6f46 | count-0 | unspecified | unspecified |
text_A: A blond man speaking to a brunette woman with her arms crossed.
text_B: A woman is talking to another woman. | choice | counterfactually-augmented-snli-283b54ff0e:train:12 | [
"entailment",
"neutral",
"contradiction"
] | [
0,
0,
1
] | Does text_A entail text_B, contradict it, or neither? | counterfactually-augmented-snli | direct | train | counterfactually-augmented-snli-283b54ff0e:train:12 | decision | unspecified | unspecified |
First text:
A blond man speaking to a brunette woman with her arms crossed.
Second text:
A woman is talking to another woman. | choice | counterfactually-augmented-snli-283b54ff0e:train:12:choice-paired-text-format | [
"entailment",
"neutral",
"contradiction"
] | [
0,
0,
1
] | Does text_A entail text_B, contradict it, or neither? | counterfactually-augmented-snli | paired_text_format | train | counterfactually-augmented-snli-283b54ff0e:train:12 | choice-paired-text-format | unspecified | unspecified |
@AmericanAir Please help AA 2258 Monday Cancelled Flightled. Can you advise on reFlight Booking Problems / refund. Have children and need to make plans now | choice | crowdflower-airline-sentiment-c06fbee03f:train:2301 | [
"negative",
"neutral",
"positive"
] | [
0,
1,
0
] | What sentiment does the tweet express about the airline? | crowdflower/airline-sentiment | direct | train | crowdflower-airline-sentiment-c06fbee03f:train:2301 | decision | unspecified | unspecified |
@AmericanAir Please help AA 2258 Monday Cancelled Flightled. Can you advise on reFlight Booking Problems / refund. Have children and need to make plans now | choice | crowdflower-airline-sentiment-c06fbee03f:train:2301:choice-criteria-permutation | [
"positive",
"negative",
"neutral"
] | [
0,
0,
1
] | What sentiment does the tweet express about the airline? | crowdflower/airline-sentiment | criteria_permutation | train | crowdflower-airline-sentiment-c06fbee03f:train:2301 | choice-criteria-permutation | unspecified | unspecified |
Ingenuity fuels learning-Belo Horizonte City Council increases ed. access 4 children < 5 http://t.co/0ZmIVYWw8S #FTCitiAwards #progressmakers | choice | crowdflower-corporate-messaging-2d92c990c1:train:0 | [
"Information",
"Action",
"Exclude",
"Dialogue"
] | [
1,
0,
0,
0
] | What type of corporate social-media message is this? | crowdflower/corporate-messaging | direct | train | crowdflower-corporate-messaging-2d92c990c1:train:0 | decision | unspecified | unspecified |
Ask an American business forecaster where the U.S. economy seems headed -- up, sideways or down -- and the response will probably begin with another question:
Will West Germany and Japan take solid steps to stimulate their own economies? If they do, expansion in the U.S. will persist and strengthen. If they don't, the... | choice | crowdflower-economic-news-569d369f2f:train:261 | [
"not sure",
"yes",
"no"
] | [
0,
0,
1
] | Is this article relevant to the U.S. economy? | crowdflower/economic-news | direct | train | crowdflower-economic-news-569d369f2f:train:261 | decision | unspecified | unspecified |
Ask an American business forecaster where the U.S. economy seems headed -- up, sideways or down -- and the response will probably begin with another question:
Will West Germany and Japan take solid steps to stimulate their own economies? If they do, expansion in the U.S. will persist and strengthen. If they don't, the... | choice | crowdflower-economic-news-569d369f2f:train:261:choice-criteria-permutation | [
"no",
"yes",
"not sure"
] | [
1,
0,
0
] | Is this article relevant to the U.S. economy? | crowdflower/economic-news | criteria_permutation | train | crowdflower-economic-news-569d369f2f:train:261 | choice-criteria-permutation | unspecified | unspecified |
Enjoyed sitting down with the First District‰Ûªs very own Faiz Rehman, host of Voice of America‰Ûªs CafÌ© DC show. We spoke about a variety of topics including ISIS, Afghanistan and even the local hunting scene. Check out the interview here! | choice | crowdflower-political-media-audience-87459b89a3:train:14 | [
"constituency",
"national"
] | [
1,
0
] | Is this political message aimed at a constituency or a national audience? | crowdflower/political-media-audience | direct | train | crowdflower-political-media-audience-87459b89a3:train:14 | decision | unspecified | unspecified |
I applaud #POTUS for using legal authority to improve our broken immigration system, but only #Congress can provide #CIR #ImmigrationAction | choice | crowdflower-political-media-bias-7814a90a0d:train:477 | [
"partisan",
"neutral"
] | [
0,
1
] | Is this political message partisan or neutral? | crowdflower/political-media-bias | direct | train | crowdflower-political-media-bias-7814a90a0d:train:477 | decision | unspecified | unspecified |
I applaud #POTUS for using legal authority to improve our broken immigration system, but only #Congress can provide #CIR #ImmigrationAction | choice | crowdflower-political-media-bias-7814a90a0d:train:477:choice-criteria-permutation | [
"neutral",
"partisan"
] | [
1,
0
] | Is this political message partisan or neutral? | crowdflower/political-media-bias | criteria_permutation | train | crowdflower-political-media-bias-7814a90a0d:train:477 | choice-criteria-permutation | unspecified | unspecified |
Obama plans to attack the second amendment (gun ownership rights) with 19 executive orders. http://www.politico.com/story/2013/01/biden-guns-executive-actions-86187.html?hp=t1_3 | choice | crowdflower-political-media-message-c60703ffb4:train:9 | [
"information",
"support",
"policy",
"constituency",
"personal",
"other",
"media",
"mobilization",
"attack"
] | [
0,
0,
1,
0,
0,
0,
0,
0,
0
] | What type of political message is this? | crowdflower/political-media-message | direct | train | crowdflower-political-media-message-c60703ffb4:train:9 | decision | unspecified | unspecified |
Item A:
RT @mention More good news...Russia proposes to construct nuclear plants in Iran {link}
Item B:
RT @mention In #national #science and #politics news: PM says Nuclear energy vital for growth! | choice | crowdflower-sentiment-nuclear-power-c779d545d8:train:pack-3c9a76347d6d:label-A | [
"Neutral / author is just sharing information",
"Negative",
"Tweet NOT related to nuclear energy",
"Positive"
] | [
0,
0,
0,
1
] | Each item answers: "What is the tweet's sentiment toward nuclear energy, or is it unrelated?"
Choose the criterion that best describes Item A. | crowdflower/sentiment_nuclear_power | packed_derived | train | crowdflower-sentiment-nuclear-power-c779d545d8:train:pack-3c9a76347d6d | label-A | unspecified | unspecified |
Item A:
RT @mention More good news...Russia proposes to construct nuclear plants in Iran {link}
Item B:
RT @mention In #national #science and #politics news: PM says Nuclear energy vital for growth! | noul | crowdflower-sentiment-nuclear-power-c779d545d8:train:pack-3c9a76347d6d:same-A-B | [] | [
1
] | Each item answers: "What is the tweet's sentiment toward nuclear energy, or is it unrelated?"
Do Item A and Item B have the same label? Possible labels: "Neutral / author is just sharing information", "Negative", "Tweet NOT related to nuclear energy", "Positive". | crowdflower/sentiment_nuclear_power | packed_derived | train | crowdflower-sentiment-nuclear-power-c779d545d8:train:pack-3c9a76347d6d | same-A-B | unspecified | unspecified |
Item A:
RT @mention More good news...Russia proposes to construct nuclear plants in Iran {link}
Item B:
RT @mention In #national #science and #politics news: PM says Nuclear energy vital for growth! | noul | crowdflower-sentiment-nuclear-power-c779d545d8:train:pack-3c9a76347d6d:all-same | [] | [
1
] | Each item answers: "What is the tweet's sentiment toward nuclear energy, or is it unrelated?"
Do all items have the same label? Possible labels: "Neutral / author is just sharing information", "Negative", "Tweet NOT related to nuclear energy", "Positive". | crowdflower/sentiment_nuclear_power | packed_derived | train | crowdflower-sentiment-nuclear-power-c779d545d8:train:pack-3c9a76347d6d | all-same | unspecified | unspecified |
Item A:
RT @mention More good news...Russia proposes to construct nuclear plants in Iran {link}
Item B:
RT @mention In #national #science and #politics news: PM says Nuclear energy vital for growth! | score | crowdflower-sentiment-nuclear-power-c779d545d8:train:pack-3c9a76347d6d:count-2 | [
"0",
"1",
"2"
] | [
1,
0,
0
] | Each item answers: "What is the tweet's sentiment toward nuclear energy, or is it unrelated?"
How many items have the label "Tweet NOT related to nuclear energy"? Possible labels: "Neutral / author is just sharing information", "Negative", "Tweet NOT related to nuclear energy", "Positive". | crowdflower/sentiment_nuclear_power | packed_derived | train | crowdflower-sentiment-nuclear-power-c779d545d8:train:pack-3c9a76347d6d | count-2 | unspecified | unspecified |
Back to work! How you doin? | choice | crowdflower-text-emotion-cf5d652530:train:143 | [
"sadness",
"empty",
"relief",
"hate",
"worry",
"enthusiasm",
"happiness",
"neutral",
"love",
"fun",
"anger",
"surprise",
"boredom"
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0
] | What emotion does the text express? | crowdflower/text_emotion | direct | train | crowdflower-text-emotion-cf5d652530:train:143 | decision | unspecified | unspecified |
RT @noreenahertz: RT @mpondfield:How we can afford to tackle climate change...good read http://nyti.ms/doCiD8 | choice | crowdflower-tweet-global-warming-6cc81c33a4:train:52 | [
"Yes",
"No"
] | [
1,
0
] | Does the tweet indicate that the author believes global warming is occurring? | crowdflower/tweet_global_warming | direct | train | crowdflower-tweet-global-warming-6cc81c33a4:train:52 | decision | unspecified | unspecified |
RT @noreenahertz: RT @mpondfield:How we can afford to tackle climate change...good read http://nyti.ms/doCiD8 | noul | crowdflower-tweet-global-warming-6cc81c33a4:train:52:noul-label-verification | [] | [
1
] | Does the tweet indicate that the author believes global warming is occurring? Is "Yes" the correct answer? | crowdflower/tweet_global_warming | label_verification | train | crowdflower-tweet-global-warming-6cc81c33a4:train:52 | noul-label-verification | unspecified | unspecified |
Cliff is friends with everyone from Summer Town. He's enemies with everyone from Spring Town. He doesn't know about anyone who lives outside those two towns. Joy lives in Winter Town. True or False: Cliff and Joy are on friendly terms. | choice | cycic-classification-caefcb941f:train:1 | [
"False",
"True"
] | [
1,
0
] | Choose the criterion that best describes the state. | cycic_classification | direct | train | cycic-classification-caefcb941f:train:1 | decision | apache-2.0 | commercial |
In Strange Town, you're only allowed to play a team sport in the theater district, you're only allowed to attend entertainment events in the graveyard, and you're only allowed to engage in politics in the shipyard. Joy is baseball play. Where is Joy? | choice | cycic-multiplechoice-0ddffa14f6:train:5 | [
"the shipyard",
"the botanical garden",
"the graveyard",
"the physical universe",
"the financial district"
] | [
0,
0,
0,
1,
0
] | Which supplied option best answers the question? | cycic_multiplechoice | direct | train | cycic-multiplechoice-0ddffa14f6:train:5 | decision | apache-2.0 | commercial |
In Strange Town, you're only allowed to play a team sport in the theater district, you're only allowed to attend entertainment events in the graveyard, and you're only allowed to engage in politics in the shipyard. Joy is baseball play. Where is Joy? | noul | cycic-multiplechoice-0ddffa14f6:train:5:noul-label-verification | [] | [
1
] | Is "the physical universe" the correct answer to the question? | cycic_multiplechoice | label_verification | train | cycic-multiplechoice-0ddffa14f6:train:5 | noul-label-verification | apache-2.0 | commercial |
text_A: Michael Faraday was born at Newington, Surrey, on September 22, 1791, and was the third of four children. His father, James Faraday, was the son of Robert and Elizabeth Faraday, of Clapham Wood Hall, in the north-west of Yorkshire, and was brought up as a blacksmith. He was the third of ten children, and, in 17... | choice | dadc-limit-nli-4fbb41ab4c:train:50 | [
"contradiction",
"entailment"
] | [
0,
1
] | Which of the supplied criteria best matches the state? | dadc-limit-nli | direct | train | dadc-limit-nli-4fbb41ab4c:train:50 | decision | cc | unspecified |
text_A: Michael Faraday was born at Newington, Surrey, on September 22, 1791, and was the third of four children. His father, James Faraday, was the son of Robert and Elizabeth Faraday, of Clapham Wood Hall, in the north-west of Yorkshire, and was brought up as a blacksmith. He was the third of ten children, and, in 17... | choice | dadc-limit-nli-4fbb41ab4c:train:50:choice-criteria-permutation | [
"entailment",
"contradiction"
] | [
1,
0
] | Which of the supplied criteria best matches the state? | dadc-limit-nli | criteria_permutation | train | dadc-limit-nli-4fbb41ab4c:train:50 | choice-criteria-permutation | cc | unspecified |
A: Michael Faraday was born at Newington, Surrey, on September 22, 1791, and was the third of four children. His father, James Faraday, was the son of Robert and Elizabeth Faraday, of Clapham Wood Hall, in the north-west of Yorkshire, and was brought up as a blacksmith. He was the third of ten children, and, in 1786, m... | choice | dadc-limit-nli-4fbb41ab4c:train:50:choice-paired-text-format | [
"contradiction",
"entailment"
] | [
0,
1
] | Which of the supplied criteria best matches the state? | dadc-limit-nli | paired_text_format | train | dadc-limit-nli-4fbb41ab4c:train:50 | choice-paired-text-format | cc | unspecified |
Item A:
text_A: bodoi.info - information about domain
- Server Status: available
- Server IP: 213.186.33.17
- Server Response Time: 96ms
Our site strives to provide helpful information to our readers. By offering not only fact-based whois information, but also an informative overview of each website, we seek to give yo... | choice | dataset-train-nli-91e59a492d:train:pack-188107ea57f9:label-B | [
"entailment",
"not_entailment"
] | [
0,
1
] | Each item answers: "Does text_A entail text_B?"
Choose the criterion that best describes Item B. | dataset_train_nli | packed_derived | train | dataset-train-nli-91e59a492d:train:pack-188107ea57f9 | label-B | unspecified | unspecified |
Item A:
text_A: bodoi.info - information about domain
- Server Status: available
- Server IP: 213.186.33.17
- Server Response Time: 96ms
Our site strives to provide helpful information to our readers. By offering not only fact-based whois information, but also an informative overview of each website, we seek to give yo... | noul | dataset-train-nli-91e59a492d:train:pack-188107ea57f9:same-A-B | [] | [
1
] | Each item answers: "Does text_A entail text_B?"
Do Item A and Item B have the same label? Possible labels: "entailment", "not_entailment". | dataset_train_nli | packed_derived | train | dataset-train-nli-91e59a492d:train:pack-188107ea57f9 | same-A-B | unspecified | unspecified |
Item A:
text_A: bodoi.info - information about domain
- Server Status: available
- Server IP: 213.186.33.17
- Server Response Time: 96ms
Our site strives to provide helpful information to our readers. By offering not only fact-based whois information, but also an informative overview of each website, we seek to give yo... | noul | dataset-train-nli-91e59a492d:train:pack-188107ea57f9:exists-1 | [] | [
1
] | Each item answers: "Does text_A entail text_B?"
Does at least one item have the label "not_entailment"? Possible labels: "entailment", "not_entailment". | dataset_train_nli | packed_derived | train | dataset-train-nli-91e59a492d:train:pack-188107ea57f9 | exists-1 | unspecified | unspecified |
Item A:
text_A: bodoi.info - information about domain
- Server Status: available
- Server IP: 213.186.33.17
- Server Response Time: 96ms
Our site strives to provide helpful information to our readers. By offering not only fact-based whois information, but also an informative overview of each website, we seek to give yo... | choice | dataset-train-nli-91e59a492d:train:pack-188107ea57f9:most-common | [
"entailment",
"not_entailment"
] | [
0,
1
] | Each item answers: "Does text_A entail text_B?"
Which label is shared by the most items? | dataset_train_nli | packed_derived | train | dataset-train-nli-91e59a492d:train:pack-188107ea57f9 | most-common | unspecified | unspecified |
Richard Lai Sung-lung (4 August 1946 Shanghai Republic of China — 27 March 2008 Shanghai People's Republic of China) was a former member of the Legislative Council of Hong Kong.Lai was born in Shanghai in a family doing jewellery and property business before he moved to Hong Kong in 1950. | choice | dbpedia-14-dbpedia-14-3a7337124e:train:83 | [
"Company",
"EducationalInstitution",
"Artist",
"Athlete",
"OfficeHolder",
"MeanOfTransportation",
"Building",
"NaturalPlace",
"Village",
"Animal",
"Plant",
"Album",
"Film",
"WrittenWork"
] | [
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0
] | Choose the most appropriate category for the state. | dbpedia_14/dbpedia_14 | direct | train | dbpedia-14-dbpedia-14-3a7337124e:train:83 | decision | cc-by-sa-3.0 | commercial |
Richard Lai Sung-lung (4 August 1946 Shanghai Republic of China — 27 March 2008 Shanghai People's Republic of China) was a former member of the Legislative Council of Hong Kong.Lai was born in Shanghai in a family doing jewellery and property business before he moved to Hong Kong in 1950. | choice | dbpedia-14-dbpedia-14-3a7337124e:train:83:choice-instruction-paraphrase | [
"Company",
"EducationalInstitution",
"Artist",
"Athlete",
"OfficeHolder",
"MeanOfTransportation",
"Building",
"NaturalPlace",
"Village",
"Animal",
"Plant",
"Album",
"Film",
"WrittenWork"
] | [
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0
] | Select the label that best applies to the state. | dbpedia_14/dbpedia_14 | instruction_paraphrase | train | dbpedia-14-dbpedia-14-3a7337124e:train:83 | choice-instruction-paraphrase | cc-by-sa-3.0 | commercial |
Passage A:
PersonX wins the gold medal Because PersonX wanted to win
Passage B:
X bribed the judges. | choice | defeasible-nli-atomic-ed90d0c960:train:1582 | [
"strengthener",
"weakener"
] | [
0,
1
] | Choose the criterion that best describes the state. | defeasible-nli/atomic | direct | train | defeasible-nli-atomic-ed90d0c960:train:1582 | decision | apache-2.0, MIT License (DPI) | commercial |
Passage A:
PersonX wins the gold medal Because PersonX wanted to win
Passage B:
X bribed the judges. | noul | defeasible-nli-atomic-ed90d0c960:train:1582:noul-label-verification | [] | [
1
] | Is "weakener" the correct label for this example? | defeasible-nli/atomic | label_verification | train | defeasible-nli-atomic-ed90d0c960:train:1582 | noul-label-verification | apache-2.0, MIT License (DPI) | commercial |
Passage A:
Three people in sunglasses are sitting down and eating or drinking. Three friends are meeting for lunch.
Passage B:
The three friends met at an outdoor cafe to discuss their upcoming vacation plans. | choice | defeasible-nli-snli-175344aed9:train:17 | [
"strengthener",
"weakener"
] | [
1,
0
] | Which of the supplied criteria best matches the state? | defeasible-nli/snli | direct | train | defeasible-nli-snli-175344aed9:train:17 | decision | apache-2.0, MIT License (DPI) | commercial |
Item A:
text_A: It's wrong to do something to sway someone's decisions about things when it's not what's best for them.
text_B: it's the best for a large number of people
Item B:
text_A: It's okay to want someone you care about to go out of their way and do something nice for you.
text_B: You did the same for them and... | choice | defeasible-nli-social-7479767344:train:pack-3b97ea6e5757:label-A | [
"strengthener",
"weakener"
] | [
0,
1
] | Choose the criterion that best describes Item A. | defeasible-nli/social | packed_derived | train | defeasible-nli-social-7479767344:train:pack-3b97ea6e5757 | label-A | apache-2.0 | commercial |
Item A:
text_A: It's wrong to do something to sway someone's decisions about things when it's not what's best for them.
text_B: it's the best for a large number of people
Item B:
text_A: It's okay to want someone you care about to go out of their way and do something nice for you.
text_B: You did the same for them and... | noul | defeasible-nli-social-7479767344:train:pack-3b97ea6e5757:in-B-0 | [] | [
1
] | Is the label of Item B "strengthener"? Possible labels: "strengthener", "weakener". | defeasible-nli/social | packed_derived | train | defeasible-nli-social-7479767344:train:pack-3b97ea6e5757 | in-B-0 | apache-2.0 | commercial |
Item A:
text_A: It's wrong to do something to sway someone's decisions about things when it's not what's best for them.
text_B: it's the best for a large number of people
Item B:
text_A: It's okay to want someone you care about to go out of their way and do something nice for you.
text_B: You did the same for them and... | noul | defeasible-nli-social-7479767344:train:pack-3b97ea6e5757:exists-0 | [] | [
1
] | Does at least one item have the label "strengthener"? Possible labels: "strengthener", "weakener". | defeasible-nli/social | packed_derived | train | defeasible-nli-social-7479767344:train:pack-3b97ea6e5757 | exists-0 | apache-2.0 | commercial |
Item A:
text_A: It's wrong to do something to sway someone's decisions about things when it's not what's best for them.
text_B: it's the best for a large number of people
Item B:
text_A: It's okay to want someone you care about to go out of their way and do something nice for you.
text_B: You did the same for them and... | score | defeasible-nli-social-7479767344:train:pack-3b97ea6e5757:count-0 | [
"0",
"1",
"2",
"3",
"4"
] | [
0,
0,
1,
0,
0
] | How many items have the label "strengthener"? Possible labels: "strengthener", "weakener". | defeasible-nli/social | packed_derived | train | defeasible-nli-social-7479767344:train:pack-3b97ea6e5757 | count-0 | apache-2.0 | commercial |
Sally was really happy that Beth finally got a job because she is a concerned friend.
Who or what does "she" refer to? | choice | definite-pronoun-resolution-634ed1e850:train:0 | [
"Beth",
"Sally"
] | [
0,
1
] | Choose the most appropriate answer from the supplied options. | definite_pronoun_resolution | direct | train | definite-pronoun-resolution-634ed1e850:train:0 | decision | unspecified | unspecified |
A student rubs his hands together to warm them. His hands get warm due to **blank** | choice | dgen-6235199bd5:train:12 | [
"friction",
"sound",
"magnetism",
"gravity"
] | [
1,
0,
0,
0
] | Which supplied option best answers the question? | dgen | direct | train | dgen-6235199bd5:train:12 | decision | mit | commercial |
A student rubs his hands together to warm them. His hands get warm due to **blank** | noul | dgen-6235199bd5:train:12:noul-label-verification | [] | [
1
] | Is "friction" the correct answer to the question? | dgen | label_verification | train | dgen-6235199bd5:train:12 | noul-label-verification | mit | commercial |
text_A: i cant concentrate too . . . always daydreaming at work .
text_B: i do not pick the right people . | choice | dialogue-nli-83a239d75f:train:12 | [
"entailment",
"neutral",
"contradiction"
] | [
0,
1,
0
] | Does text_A entail text_B, contradict it, or neither? | dialogue_nli | direct | train | dialogue-nli-83a239d75f:train:12 | decision | unspecified | unspecified |
First text:
i cant concentrate too . . . always daydreaming at work .
Second text:
i do not pick the right people . | choice | dialogue-nli-83a239d75f:train:12:choice-paired-text-format | [
"entailment",
"neutral",
"contradiction"
] | [
0,
1,
0
] | Does text_A entail text_B, contradict it, or neither? | dialogue_nli | paired_text_format | train | dialogue-nli-83a239d75f:train:12 | choice-paired-text-format | unspecified | unspecified |
The third season reveals that any woman who conceives on the island dies before the baby is born. | choice | discosense-abc1ebbc44:train:10 | [
"Any woman giving birth to a stillborn or dying woman is cast into the sea.",
"The island of dr moreausees miss temple travel to the dr.",
"The pregnancy goes well until about midway through the second trimester, where complications arise.",
"The episode focusses on what happens when a woman gives birth on an... | [
0,
0,
1,
0
] | Choose the most appropriate answer from the supplied options. | discosense | direct | train | discosense-abc1ebbc44:train:10 | decision | unspecified | unspecified |
The third season reveals that any woman who conceives on the island dies before the baby is born. | choice | discosense-abc1ebbc44:train:10:choice-criteria-permutation | [
"The pregnancy goes well until about midway through the second trimester, where complications arise.",
"The island of dr moreausees miss temple travel to the dr.",
"The episode focusses on what happens when a woman gives birth on an island, and how the fetus disappears into the sea.",
"Any woman giving birth ... | [
1,
0,
0,
0
] | Choose the most appropriate answer from the supplied options. | discosense | criteria_permutation | train | discosense-abc1ebbc44:train:10 | choice-criteria-permutation | unspecified | unspecified |
text_A: We note that such a practice would continue to be permitted under Rule 14a-4 (b) (1).
text_B: We do not know what is gained by including this prohibition against voting for nominees as a group. | choice | discovery-discovery-4cdfae9f6c:train:2 | [
"[no-conn]",
"absolutely,",
"accordingly",
"actually,",
"additionally",
"admittedly,",
"afterward",
"again,",
"already,",
"also,",
"alternately,",
"alternatively",
"although,",
"altogether,",
"amazingly,",
"and",
"anyway,",
"apparently,",
"arguably,",
"as_a_result,",
"basical... | [
0,
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0... | Which discourse marker best links text_A to text_B? | discovery/discovery | direct | train | discovery-discovery-4cdfae9f6c:train:2 | decision | apache-2.0 | commercial |
text_A: our model is more accurate out-of-domain ,
text_B: is four times faster , | choice | disrpt-eng-dep-scidtb-rels-615591f14c:train:63 | [
"attribution",
"bg-compare",
"bg-general",
"bg-goal",
"cause",
"comparison",
"condition",
"contrast",
"elab-addition",
"elab-aspect",
"elab-definition",
"elab-enumember",
"elab-example",
"elab-process_step",
"enablement",
"evaluation",
"exp-evidence",
"exp-reason",
"joint",
"ma... | [
0,
0,
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0,
0,
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0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0
] | Which discourse relation links unit text_B to unit text_A? | disrpt/eng.dep.scidtb.rels | direct | train | disrpt-eng-dep-scidtb-rels-615591f14c:train:63 | decision | apache-2.0 | commercial |
text_A: our model is more accurate out-of-domain ,
text_B: is four times faster , | choice | disrpt-eng-dep-scidtb-rels-615591f14c:train:63:choice-criteria-permutation | [
"bg-compare",
"bg-goal",
"elab-definition",
"condition",
"temporal",
"attribution",
"joint",
"summary",
"comparison",
"progression",
"exp-evidence",
"elab-addition",
"bg-general",
"result",
"evaluation",
"cause",
"manner-means",
"elab-aspect",
"elab-enumember",
"enablement",
... | [
0,
0,
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1,
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0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] | Which discourse relation links unit text_B to unit text_A? | disrpt/eng.dep.scidtb.rels | criteria_permutation | train | disrpt-eng-dep-scidtb-rels-615591f14c:train:63 | choice-criteria-permutation | apache-2.0 | commercial |
text_A: Ryan forfeited the blinch.
text_B: Someone did not move from their location . | choice | dnc-f60932f360:train:6 | [
"not-entailed",
"entailed"
] | [
0,
1
] | Does text_A entail text_B? | dnc | direct | train | dnc-f60932f360:train:6 | decision | Various (DPI) | non-commercial |
Bye Brianna Moonlight! | choice | dnd-style-intents-b8511d0b07:train:67 | [
"Attack",
"Complete quest",
"Deliver",
"Drival",
"Exchange",
"Farewell",
"Follow",
"General",
"Greeting",
"Join",
"Joke",
"Knowledge",
"Message",
"Move",
"Protect",
"Recieve quest",
"Threat"
] | [
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] | Which of the supplied criteria best matches the state? | dnd_style_intents | direct | train | dnd-style-intents-b8511d0b07:train:67 | decision | apache-2.0 | commercial |
Bye Brianna Moonlight! | choice | dnd-style-intents-b8511d0b07:train:67:choice-criteria-permutation | [
"Complete quest",
"Follow",
"Drival",
"Join",
"Protect",
"Farewell",
"Recieve quest",
"Attack",
"General",
"Deliver",
"Knowledge",
"Joke",
"Message",
"Threat",
"Greeting",
"Move",
"Exchange"
] | [
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] | Which of the supplied criteria best matches the state? | dnd_style_intents | criteria_permutation | train | dnd-style-intents-b8511d0b07:train:67 | choice-criteria-permutation | apache-2.0 | commercial |
text_A: Cobb caught three of five targets for 25 yards in Sunday's 20-17 loss to the Cardinals, playing 61 of 76 snaps (80 percent) on offense. Cobb didn't have any workload limitations in his first appearance since Week 9, but he also didn't do much to help the Packers avoid an embarrassing loss. The team may want to ... | choice | doc-nli-3c305b0aa7:train:1 | [
"entailment",
"not_entailment"
] | [
0,
1
] | Does text_A entail text_B? | doc-nli | direct | train | doc-nli-3c305b0aa7:train:1 | decision | bsd | commercial |
A: Ridge Canipe ( born July 13 , 1994 ) is an American actor .
Ridge is best known for his roles in Walk the Line ( in which he played Johnny Cash as a boy ) , the thriller Baby Blues in 2008 and the 2005 version of Bad News Bears .
He also co - starred in the 231st presentation of the Hallmark Hall of Fame production ... | choice | docred-84d225f1d6:train:60 | [
"P1001",
"P102",
"P1056",
"P108",
"P112",
"P118",
"P1198",
"P123",
"P127",
"P131",
"P1336",
"P1344",
"P136",
"P1365",
"P1366",
"P137",
"P1376",
"P140",
"P1412",
"P1441",
"P150",
"P155",
"P156",
"P159",
"P161",
"P162",
"P166",
"P17",
"P170",
"P171",
"P172",... | [
0,
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0,
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0,
0,
0,
0... | Which of the supplied criteria best matches the state? | docred | direct | train | docred-84d225f1d6:train:60 | decision | mit | commercial |
A: Ridge Canipe ( born July 13 , 1994 ) is an American actor .
Ridge is best known for his roles in Walk the Line ( in which he played Johnny Cash as a boy ) , the thriller Baby Blues in 2008 and the 2005 version of Bad News Bears .
He also co - starred in the 231st presentation of the Hallmark Hall of Fame production ... | noul | docred-84d225f1d6:train:60:noul-label-verification | [] | [
0
] | Is "P86" the correct label for this example? | docred | label_verification | train | docred-84d225f1d6:train:60 | noul-label-verification | mit | commercial |
W: Well, I'm afraid my cooking isn't to your taste.
M: Actually, I like it very much.
W: I'm glad you enjoy it. Let me serve you some more fish.
M: No, thank you. I've had enough fish, but I'd like some soup.
W: Here it is. Help yourself!
M: Thanks. I didn't know you were so good at cooking. If only my wife could learn... | choice | dream-5f04a8843e:train:1 | [
"It's better than what he does.",
"It's very good indeed.",
"It's really terrible."
] | [
0,
1,
0
] | Which supplied option best answers the question? | dream | direct | train | dream-5f04a8843e:train:1 | decision | unspecified | unspecified |
I could never endorse the death penalty. Unless its to shut up that femile bitch neighbour of ours! | choice | dynahate-224d6896b5:train:755 | [
"hate",
"nothate"
] | [
1,
0
] | Choose the criterion that best describes the state. | dynahate | direct | train | dynahate-224d6896b5:train:755 | decision | gpl | commercial |
I could never endorse the death penalty. Unless its to shut up that femile bitch neighbour of ours! | choice | dynahate-224d6896b5:train:755:choice-criteria-permutation | [
"nothate",
"hate"
] | [
0,
1
] | Choose the criterion that best describes the state. | dynahate | criteria_permutation | train | dynahate-224d6896b5:train:755 | choice-criteria-permutation | gpl | commercial |
For dessert, I skipped my usual chocolate - they offered Chocolate Mousse, Chocolate Cheesecake and Dark Chocolate Raspberry Bread Pudding. | choice | dynabench-dynasent-8074025339:train:d3f1d7e6c28d0798:dynasent-r1_votes | [
"positive",
"negative",
"neutral",
"mixed"
] | [
0,
0,
1,
0
] | How would annotators label the sentiment of the sentence? | dynasent/r1_votes | direct | train | dynabench-dynasent-8074025339:train:d3f1d7e6c28d0798 | dynasent-r1_votes | CC BY 4.0 (DPI) | commercial |
My wife was disappointed. | choice | dynabench-dynasent-8074025339:train:7d56190d2c0d33ef:dynasent-r2_votes | [
"positive",
"negative",
"neutral",
"mixed"
] | [
0,
1,
0,
0
] | How would annotators label the sentiment of the sentence? | dynasent/r2_votes | direct | train | dynabench-dynasent-8074025339:train:7d56190d2c0d33ef | dynasent-r2_votes | CC BY 4.0 (DPI) | commercial |
My wife was disappointed. | noul | dynabench-dynasent-8074025339:train:7d56190d2c0d33ef:dynasent-r2_votes:noul-label-verification | [] | [
1
] | How would annotators label the sentiment of the sentence? Is "negative" the correct answer? | dynasent/r2_votes | label_verification | train | dynabench-dynasent-8074025339:train:7d56190d2c0d33ef | dynasent-r2_votes:noul-label-verification | CC BY 4.0 (DPI) | commercial |
She has got a piece of gold with high sense of fineness. What was the cause of this? | choice | e-CARE-9c8f2660a1:train:23 | [
"Max bought his daughter Periwinkles.",
"Lucy has paid a lot of money."
] | [
0,
1
] | Select the option that best answers the question. | e-CARE | direct | train | e-CARE-9c8f2660a1:train:23 | decision | BSD 2-Clause License (DPI) | commercial |
She has got a piece of gold with high sense of fineness. What was the cause of this? | choice | e-CARE-9c8f2660a1:train:23:choice-instruction-paraphrase | [
"Max bought his daughter Periwinkles.",
"Lucy has paid a lot of money."
] | [
0,
1
] | Choose the most appropriate answer from the supplied options. | e-CARE | instruction_paraphrase | train | e-CARE-9c8f2660a1:train:23 | choice-instruction-paraphrase | BSD 2-Clause License (DPI) | commercial |
expedition:drum:morale | choice | ekar-english-c64b9556eb:train:1 | [
"competition:scream:confidence",
"drinking:negotiate:atmosphere",
"production:supervision:efficiency",
"propaganda:publish in newspapers:fame"
] | [
1,
0,
0,
0
] | Which pair is related in the same way? | ekar_english | direct | train | ekar-english-c64b9556eb:train:1 | decision | afl-3.0, CC BY-NC-SA 4.0 (DPI) | non-commercial |
expedition:drum:morale | noul | ekar-english-c64b9556eb:train:1:noul-label-verification | [] | [
1
] | Which pair is related in the same way? Is "competition:scream:confidence" the correct answer? | ekar_english | label_verification | train | ekar-english-c64b9556eb:train:1 | noul-label-verification | afl-3.0, CC BY-NC-SA 4.0 (DPI) | non-commercial |
so wanna travel with me ? :) let's go then ! :) None | choice | emo-emo2019-286304f33c:train:141 | [
"angry",
"happy",
"others",
"sad"
] | [
0,
1,
0,
0
] | Select the label that best applies to the state. | emo/emo2019 | direct | train | emo-emo2019-286304f33c:train:141 | decision | mpl-2.0 | commercial |
so wanna travel with me ? :) let's go then ! :) None | choice | emo-emo2019-286304f33c:train:141:choice-instruction-paraphrase | [
"angry",
"happy",
"others",
"sad"
] | [
0,
1,
0,
0
] | Select the label that best applies to the state. | emo/emo2019 | instruction_paraphrase | train | emo-emo2019-286304f33c:train:141 | choice-instruction-paraphrase | mpl-2.0 | commercial |
i do not feel reassured anxiety is on each side | choice | emotion-a1faba8ba8:train:15 | [
"sadness",
"joy",
"love",
"anger",
"fear",
"surprise"
] | [
0,
1,
0,
0,
0,
0
] | Choose the criterion that best describes the state. | emotion | direct | train | emotion-a1faba8ba8:train:15 | decision | other, Custom (DPI) | unspecified |
i do not feel reassured anxiety is on each side | noul | emotion-a1faba8ba8:train:15:noul-label-verification | [] | [
0
] | Is "sadness" the correct label for this example? | emotion | label_verification | train | emotion-a1faba8ba8:train:15 | noul-label-verification | other, Custom (DPI) | unspecified |
Who wants to work alone when you have a chance to work with a group like common! Working in a group is so much beneficial because within a group your able to get your work done quicker and efficient. "who doesn't want that? I know I do". With a group you can also interact and descuse with your peers about your work and... | score | english-grading-cohesion-97c0e3c3ab:train:5 | [
"1 out of 5",
"2 out of 5",
"3 out of 5",
"4 out of 5",
"5 out of 5"
] | [
0,
0,
0,
1,
0
] | What cohesion score does this English learner essay deserve? | english-grading/cohesion | direct | train | english-grading-cohesion-97c0e3c3ab:train:5 | decision | unspecified | unspecified |
The lesson I well share is to be good in all in your class and never give up in elementary school. This important to kids in elementary school so when they go to middle school it is going to be lot harder. When i was in elementary school eveyone bully me all the time but i never give up. Work hard in elementary school ... | choice | english-grading-conventions-c7df10dc80:train:315 | [
"1 out of 5",
"2 out of 5",
"3 out of 5",
"4 out of 5",
"5 out of 5"
] | [
0,
1,
0,
0,
0
] | What conventions score does this English learner essay deserve? | english-grading/conventions | direct | train | english-grading-conventions-c7df10dc80:train:315 | decision | unspecified | unspecified |
The lesson I well share is to be good in all in your class and never give up in elementary school. This important to kids in elementary school so when they go to middle school it is going to be lot harder. When i was in elementary school eveyone bully me all the time but i never give up. Work hard in elementary school ... | noul | english-grading-conventions-c7df10dc80:train:315:noul-label-verification | [] | [
0
] | What conventions score does this English learner essay deserve? Is "3 out of 5" the correct answer? | english-grading/conventions | label_verification | train | english-grading-conventions-c7df10dc80:train:315 | noul-label-verification | unspecified | unspecified |
John Lubbock, a famous writer and well known for his master peaces inspired by many others such as friends, family, and other famous writers. John Lubbock once said "Do we choose our own character traits, or is our character formed by influences beyond our control?" it is a very outstanding move, because 86% of the wri... | choice | english-grading-grammar-51f1503496:train:3 | [
"1 out of 5",
"2 out of 5",
"3 out of 5",
"4 out of 5",
"5 out of 5"
] | [
0,
0,
0,
1,
0
] | What grammar score does this English learner essay deserve? | english-grading/grammar | direct | train | english-grading-grammar-51f1503496:train:3 | decision | unspecified | unspecified |
Do you agree with Albert Einstein when he said "imagination is more important than knowledge"? I think that is true because if you have now imagination than how are you going to get knowledge. I agree because Albert Einstein had to have a strong imagination to become really smart, Albert Einstein lived through a lot so... | choice | english-grading-phraseology-7fdf4fef87:train:314 | [
"1 out of 5",
"2 out of 5",
"3 out of 5",
"4 out of 5",
"5 out of 5"
] | [
0,
0,
1,
0,
0
] | What phraseology score does this English learner essay deserve? | english-grading/phraseology | direct | train | english-grading-phraseology-7fdf4fef87:train:314 | decision | unspecified | unspecified |
Do you agree with Albert Einstein when he said "imagination is more important than knowledge"? I think that is true because if you have now imagination than how are you going to get knowledge. I agree because Albert Einstein had to have a strong imagination to become really smart, Albert Einstein lived through a lot so... | noul | english-grading-phraseology-7fdf4fef87:train:314:noul-label-verification | [] | [
1
] | What phraseology score does this English learner essay deserve? Is "3 out of 5" the correct answer? | english-grading/phraseology | label_verification | train | english-grading-phraseology-7fdf4fef87:train:314 | noul-label-verification | unspecified | unspecified |
Dear Principal
The Police i think is correct is Policy 1. I think police one is correct because not only the students sometimes need to call their parents to come to pick then up or pick up early or come bring their lunch, but also because is impossible to make everyone obey Policy number 2, even if is a school policy... | score | english-grading-syntax-ad89747a57:train:0 | [
"1 out of 5",
"2 out of 5",
"3 out of 5",
"4 out of 5",
"5 out of 5"
] | [
0,
0,
1,
0,
0
] | What syntax score does this English learner essay deserve? | english-grading/syntax | direct | train | english-grading-syntax-ad89747a57:train:0 | decision | unspecified | unspecified |
Item A:
Although most people would want to graduate and enter college or the work force a year early,others may argue that school should be the four years. One should be allowed to grow up. It should be mandatory to do four years of high school and here is why.
First of all,school prepares students to face up and go a... | choice | english-grading-vocabulary-6df5aad673:train:pack-d4ae95e999e8:label-B | [
"1 out of 5",
"2 out of 5",
"3 out of 5",
"4 out of 5",
"5 out of 5"
] | [
0,
0,
1,
0,
0
] | Each item answers: "What vocabulary score does this English learner essay deserve?"
Choose the criterion that best describes Item B. | english-grading/vocabulary | packed_derived | train | english-grading-vocabulary-6df5aad673:train:pack-d4ae95e999e8 | label-B | unspecified | unspecified |
Item A:
Although most people would want to graduate and enter college or the work force a year early,others may argue that school should be the four years. One should be allowed to grow up. It should be mandatory to do four years of high school and here is why.
First of all,school prepares students to face up and go a... | noul | english-grading-vocabulary-6df5aad673:train:pack-d4ae95e999e8:in-A-0 | [] | [
0
] | Each item answers: "What vocabulary score does this English learner essay deserve?"
Is the label of Item A "1 out of 5"? Possible labels: "1 out of 5", "2 out of 5", "3 out of 5", "4 out of 5", "5 out of 5". | english-grading/vocabulary | packed_derived | train | english-grading-vocabulary-6df5aad673:train:pack-d4ae95e999e8 | in-A-0 | unspecified | unspecified |
Item A:
Although most people would want to graduate and enter college or the work force a year early,others may argue that school should be the four years. One should be allowed to grow up. It should be mandatory to do four years of high school and here is why.
First of all,school prepares students to face up and go a... | noul | english-grading-vocabulary-6df5aad673:train:pack-d4ae95e999e8:all-same | [] | [
0
] | Each item answers: "What vocabulary score does this English learner essay deserve?"
Do all items have the same label? Possible labels: "1 out of 5", "2 out of 5", "3 out of 5", "4 out of 5", "5 out of 5". | english-grading/vocabulary | packed_derived | train | english-grading-vocabulary-6df5aad673:train:pack-d4ae95e999e8 | all-same | unspecified | unspecified |
Item A:
Although most people would want to graduate and enter college or the work force a year early,others may argue that school should be the four years. One should be allowed to grow up. It should be mandatory to do four years of high school and here is why.
First of all,school prepares students to face up and go a... | score | english-grading-vocabulary-6df5aad673:train:pack-d4ae95e999e8:count-0 | [
"0",
"1",
"2"
] | [
1,
0,
0
] | Each item answers: "What vocabulary score does this English learner essay deserve?"
How many items have the label "1 out of 5"? Possible labels: "1 out of 5", "2 out of 5", "3 out of 5", "4 out of 5", "5 out of 5". | english-grading/vocabulary | packed_derived | train | english-grading-vocabulary-6df5aad673:train:pack-d4ae95e999e8 | count-0 | unspecified | unspecified |
text_A: Four in 10 Americans can't cover a $400 emergency expense, Fed finds
text_B: Four in 10 cant cover an emergency expense of $400, Fed survey finds | choice | equate-67d1d05aff:train:0 | [
"entailment",
"neutral",
"contradiction"
] | [
1,
0,
0
] | Does text_A entail text_B, contradict it, or neither? | equate | direct | train | equate-67d1d05aff:train:0 | decision | apache-2.0 | commercial |
Item A:
text_A: 2 tent person tent with vestibule
text_B: Coleman Camping Tent | Skydome Tent with Full Fly Vestibule
Coleman
Evergreen
QUICK PITCH: Sets up in under 5 minutes thanks to pre-attached poles
EXTRA SPACE: 10 x 4 ft. full-fly vestibule creates a protected entry and extra storage
MORE HEADROOM: 20% more head... | choice | esci-c75e7e5ea0:train:pack-f3a3b597500f:label-C | [
"Complement",
"Exact",
"Irrelevant",
"Substitute"
] | [
0,
0,
0,
1
] | Choose the criterion that best describes Item C. | esci | packed_derived | train | esci-c75e7e5ea0:train:pack-f3a3b597500f | label-C | apache-2.0 | commercial |
Item A:
text_A: 2 tent person tent with vestibule
text_B: Coleman Camping Tent | Skydome Tent with Full Fly Vestibule
Coleman
Evergreen
QUICK PITCH: Sets up in under 5 minutes thanks to pre-attached poles
EXTRA SPACE: 10 x 4 ft. full-fly vestibule creates a protected entry and extra storage
MORE HEADROOM: 20% more head... | noul | esci-c75e7e5ea0:train:pack-f3a3b597500f:in-C-1 | [] | [
0
] | Is the label of Item C "Exact"? Possible labels: "Complement", "Exact", "Irrelevant", "Substitute". | esci | packed_derived | train | esci-c75e7e5ea0:train:pack-f3a3b597500f | in-C-1 | apache-2.0 | commercial |
Item A:
text_A: 2 tent person tent with vestibule
text_B: Coleman Camping Tent | Skydome Tent with Full Fly Vestibule
Coleman
Evergreen
QUICK PITCH: Sets up in under 5 minutes thanks to pre-attached poles
EXTRA SPACE: 10 x 4 ft. full-fly vestibule creates a protected entry and extra storage
MORE HEADROOM: 20% more head... | noul | esci-c75e7e5ea0:train:pack-f3a3b597500f:all-same | [] | [
1
] | Do all items have the same label? Possible labels: "Complement", "Exact", "Irrelevant", "Substitute". | esci | packed_derived | train | esci-c75e7e5ea0:train:pack-f3a3b597500f | all-same | apache-2.0 | commercial |
Item A:
text_A: 2 tent person tent with vestibule
text_B: Coleman Camping Tent | Skydome Tent with Full Fly Vestibule
Coleman
Evergreen
QUICK PITCH: Sets up in under 5 minutes thanks to pre-attached poles
EXTRA SPACE: 10 x 4 ft. full-fly vestibule creates a protected entry and extra storage
MORE HEADROOM: 20% more head... | score | esci-c75e7e5ea0:train:pack-f3a3b597500f:count-1 | [
"0",
"1",
"2",
"3"
] | [
1,
0,
0,
0
] | How many items have the label "Exact"? Possible labels: "Complement", "Exact", "Irrelevant", "Substitute". | esci | packed_derived | train | esci-c75e7e5ea0:train:pack-f3a3b597500f | count-1 | apache-2.0 | commercial |
I was tired from all the work I did at the farm. | choice | ethics-commonsense-d0c7086a87:train:7 | [
"acceptable",
"unacceptable"
] | [
1,
0
] | Choose the criterion that best describes the state. | ethics/commonsense | direct | train | ethics-commonsense-d0c7086a87:train:7 | decision | mit | commercial |
Item A:
text_A: Could you drain the water from bathtub.
text_B: But I haven't gotten in the bath yet.
Item B:
text_A: Aren't you supposed to wait at home for the electrician to come fix the lights?
text_B: No because I fixed the lights myself and canceled the appointment.
Item C:
text_A: Could you take this note t... | choice | ethics-deontology-db12e8a4e6:train:pack-31b9102b7867:label-A | [
"reasonable",
"unreasonable"
] | [
1,
0
] | Each item answers: "Is text_B a reasonable excuse or exemption for the request or duty in text_A?"
Choose the criterion that best describes Item A. | ethics/deontology | packed_derived | train | ethics-deontology-db12e8a4e6:train:pack-31b9102b7867 | label-A | mit | commercial |
Item A:
text_A: Could you drain the water from bathtub.
text_B: But I haven't gotten in the bath yet.
Item B:
text_A: Aren't you supposed to wait at home for the electrician to come fix the lights?
text_B: No because I fixed the lights myself and canceled the appointment.
Item C:
text_A: Could you take this note t... | noul | ethics-deontology-db12e8a4e6:train:pack-31b9102b7867:same-B-C | [] | [
1
] | Each item answers: "Is text_B a reasonable excuse or exemption for the request or duty in text_A?"
Do Item B and Item C have the same label? Possible labels: "reasonable", "unreasonable". | ethics/deontology | packed_derived | train | ethics-deontology-db12e8a4e6:train:pack-31b9102b7867 | same-B-C | mit | commercial |
Item A:
text_A: Could you drain the water from bathtub.
text_B: But I haven't gotten in the bath yet.
Item B:
text_A: Aren't you supposed to wait at home for the electrician to come fix the lights?
text_B: No because I fixed the lights myself and canceled the appointment.
Item C:
text_A: Could you take this note t... | noul | ethics-deontology-db12e8a4e6:train:pack-31b9102b7867:all-same | [] | [
1
] | Each item answers: "Is text_B a reasonable excuse or exemption for the request or duty in text_A?"
Do all items have the same label? Possible labels: "reasonable", "unreasonable". | ethics/deontology | packed_derived | train | ethics-deontology-db12e8a4e6:train:pack-31b9102b7867 | all-same | mit | commercial |
Item A:
text_A: Could you drain the water from bathtub.
text_B: But I haven't gotten in the bath yet.
Item B:
text_A: Aren't you supposed to wait at home for the electrician to come fix the lights?
text_B: No because I fixed the lights myself and canceled the appointment.
Item C:
text_A: Could you take this note t... | choice | ethics-deontology-db12e8a4e6:train:pack-31b9102b7867:most-common | [
"reasonable",
"unreasonable"
] | [
1,
0
] | Each item answers: "Is text_B a reasonable excuse or exemption for the request or duty in text_A?"
Which label is shared by the most items? | ethics/deontology | packed_derived | train | ethics-deontology-db12e8a4e6:train:pack-31b9102b7867 | most-common | mit | commercial |
I deserve to get my nails polished by my barber because I paid him to make my hair look nice. | choice | ethics-justice-9698d8c8c9:train:42 | [
"reasonable",
"unreasonable"
] | [
0,
1
] | Choose the criterion that best describes the state. | ethics/justice | direct | train | ethics-justice-9698d8c8c9:train:42 | decision | mit | commercial |
Passage A:
The family went to the buffet, but the man only ate one plate of food.
Passage B:
angry | choice | ethics-virtue-682f6ee600:train:67 | [
"trait not shown",
"trait shown"
] | [
1,
0
] | Choose the criterion that best describes the state. | ethics/virtue | direct | train | ethics-virtue-682f6ee600:train:67 | decision | mit | commercial |
Passage A:
The family went to the buffet, but the man only ate one plate of food.
Passage B:
angry | choice | ethics-virtue-682f6ee600:train:67:choice-criteria-permutation | [
"trait shown",
"trait not shown"
] | [
0,
1
] | Choose the criterion that best describes the state. | ethics/virtue | criteria_permutation | train | ethics-virtue-682f6ee600:train:67 | choice-criteria-permutation | mit | commercial |
Nice concept, good story but poor act. Try harder next time | choice | ethos-binary-335cff8921:train:0 | [
"hate speech",
"no hate speech"
] | [
0,
1
] | Choose the criterion that best describes the state. | ethos/binary | direct | train | ethos-binary-335cff8921:train:0 | decision | unspecified | unspecified |
text_A: These dogs lie through their teeth so that they can come here and set up jihad on the infidels.
text_B: Does this comment attack people for their religion? | choice | ethos-multilabel-da83722077:train:13 | [
"no",
"yes"
] | [
0,
1
] | Select the label that best applies to the state. | ethos/multilabel | direct | train | ethos-multilabel-da83722077:train:13 | decision | agpl-3.0 | commercial |
text_A: These dogs lie through their teeth so that they can come here and set up jihad on the infidels.
text_B: Does this comment attack people for their religion? | choice | ethos-multilabel-da83722077:train:13:choice-criteria-permutation | [
"yes",
"no"
] | [
1,
0
] | Select the label that best applies to the state. | ethos/multilabel | criteria_permutation | train | ethos-multilabel-da83722077:train:13 | choice-criteria-permutation | agpl-3.0 | commercial |
First text:
One is allowed to join the tournament if they satisfy the age criteria The minimum age to play a table-tennis tournament is 15 years. John was not allowed to play this tournament due to age criteria.
Second text:
John could be 11 years old. | choice | feasibilityQA-421371c2a3:train:60 | [
"False",
"True"
] | [
0,
1
] | Choose the criterion that best describes the state. | feasibilityQA | direct | train | feasibilityQA-421371c2a3:train:60 | decision | mit | commercial |
First text:
One is allowed to join the tournament if they satisfy the age criteria The minimum age to play a table-tennis tournament is 15 years. John was not allowed to play this tournament due to age criteria.
Second text:
John could be 11 years old. | choice | feasibilityQA-421371c2a3:train:60:choice-instruction-paraphrase | [
"False",
"True"
] | [
0,
1
] | Select the label that best applies to the state. | feasibilityQA | instruction_paraphrase | train | feasibilityQA-421371c2a3:train:60 | choice-instruction-paraphrase | mit | commercial |
text_A: Seppuku is defined as cutting the belly.
text_B: Seppuku -LRB- 切腹 , `` cutting -LSB- the -RSB- abdomen / belly '' , formal on reading of original Kanji -RRB- , sometimes metathesized as harakiri -LRB- 腹切り , `` abdomen / belly cutting '' -RRB- which is a native Japanese kun reading , is a form of Japanese ritual... | choice | fever-evidence-related-f5e1348e27:train:96 | [
"related",
"unrelated"
] | [
1,
0
] | Which of the supplied criteria best matches the state? | fever-evidence-related | direct | train | fever-evidence-related-f5e1348e27:train:96 | decision | cc-by-sa-3.0, gpl-3.0, CC BY-SA 4.0 (DPI) | commercial |
text_A: Seppuku is defined as cutting the belly.
text_B: Seppuku -LRB- 切腹 , `` cutting -LSB- the -RSB- abdomen / belly '' , formal on reading of original Kanji -RRB- , sometimes metathesized as harakiri -LRB- 腹切り , `` abdomen / belly cutting '' -RRB- which is a native Japanese kun reading , is a form of Japanese ritual... | noul | fever-evidence-related-f5e1348e27:train:96:noul-label-verification | [] | [
0
] | Is "unrelated" the correct label for this example? | fever-evidence-related | label_verification | train | fever-evidence-related-f5e1348e27:train:96 | noul-label-verification | cc-by-sa-3.0, gpl-3.0, CC BY-SA 4.0 (DPI) | commercial |
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