state stringlengths 0 129k | kind stringclasses 3
values | id stringlengths 22 167 | options listlengths 0 235 | target listlengths 1 235 | question stringlengths 18 5.4k | source stringclasses 662
values | variant stringclasses 6
values | split stringclasses 1
value | group_id stringlengths 22 82 | question_id stringlengths 4 117 | example_id stringlengths 16 16 | license stringclasses 69
values | license_use stringclasses 3
values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Item A:
text_A: Mary went back to the kitchen. John travelled to the garden. Daniel moved to the kitchen. Sandra moved to the kitchen. John went back to the bathroom. John travelled to the bedroom. Mary went to the office. John went back to the kitchen. Daniel moved to the bedroom. Sandra went back to the garden. John ... | choice | babi-nli-three-supporting-facts-f6540ced19:train:pack-296ab52155fa:label-A | [
"not-entailed",
"entailed"
] | [
1,
0
] | Each item answers: "Does text_A entail text_B?"
Choose the criterion that best describes Item A. | babi_nli/three-supporting-facts | packed_derived | train | babi-nli-three-supporting-facts-f6540ced19:train:pack-296ab52155fa | label-A | 1d4bfc0352078669 | bsd | commercial |
Item A:
text_A: Mary went back to the kitchen. John travelled to the garden. Daniel moved to the kitchen. Sandra moved to the kitchen. John went back to the bathroom. John travelled to the bedroom. Mary went to the office. John went back to the kitchen. Daniel moved to the bedroom. Sandra went back to the garden. John ... | noul | babi-nli-three-supporting-facts-f6540ced19:train:pack-296ab52155fa:same-A-B | [] | [
0
] | Each item answers: "Does text_A entail text_B?"
Do Item A and Item B have the same label? Possible labels: "not-entailed", "entailed". | babi_nli/three-supporting-facts | packed_derived | train | babi-nli-three-supporting-facts-f6540ced19:train:pack-296ab52155fa | same-A-B | 1d4bfc0352078669 | bsd | commercial |
Item A:
text_A: Mary went back to the kitchen. John travelled to the garden. Daniel moved to the kitchen. Sandra moved to the kitchen. John went back to the bathroom. John travelled to the bedroom. Mary went to the office. John went back to the kitchen. Daniel moved to the bedroom. Sandra went back to the garden. John ... | noul | babi-nli-three-supporting-facts-f6540ced19:train:pack-296ab52155fa:all-same | [] | [
0
] | Each item answers: "Does text_A entail text_B?"
Do all items have the same label? Possible labels: "not-entailed", "entailed". | babi_nli/three-supporting-facts | packed_derived | train | babi-nli-three-supporting-facts-f6540ced19:train:pack-296ab52155fa | all-same | 1d4bfc0352078669 | bsd | commercial |
Item A:
text_A: Mary went back to the kitchen. John travelled to the garden. Daniel moved to the kitchen. Sandra moved to the kitchen. John went back to the bathroom. John travelled to the bedroom. Mary went to the office. John went back to the kitchen. Daniel moved to the bedroom. Sandra went back to the garden. John ... | score | babi-nli-three-supporting-facts-f6540ced19:train:pack-296ab52155fa:count-1 | [
"0",
"1",
"2"
] | [
0,
1,
0
] | Each item answers: "Does text_A entail text_B?"
How many items have the label "entailed"? Possible labels: "not-entailed", "entailed". | babi_nli/three-supporting-facts | packed_derived | train | babi-nli-three-supporting-facts-f6540ced19:train:pack-296ab52155fa | count-1 | 1d4bfc0352078669 | bsd | commercial |
text_A: Bill travelled to the park this morning. Bill moved to the office yesterday. This morning Mary went to the cinema. Yesterday Mary went to the kitchen. Yesterday Julie travelled to the kitchen. Bill travelled to the school this afternoon. This morning Julie went to the bedroom. Bill journeyed to the office this ... | choice | babi-nli-time-reasoning-f89e7fc8a2:train:25 | [
"not-entailed",
"entailed"
] | [
1,
0
] | Does text_A entail text_B? | babi_nli/time-reasoning | direct | train | babi-nli-time-reasoning-f89e7fc8a2:train:25 | decision | 67cd327ddc15a5b9 | bsd | commercial |
Passage A:
Bill travelled to the park this morning. Bill moved to the office yesterday. This morning Mary went to the cinema. Yesterday Mary went to the kitchen. Yesterday Julie travelled to the kitchen. Bill travelled to the school this afternoon. This morning Julie went to the bedroom. Bill journeyed to the office th... | choice | babi-nli-time-reasoning-f89e7fc8a2:train:25:choice-paired-text-format | [
"not-entailed",
"entailed"
] | [
1,
0
] | Does text_A entail text_B? | babi_nli/time-reasoning | paired_text_format | train | babi-nli-time-reasoning-f89e7fc8a2:train:25 | choice-paired-text-format | 67cd327ddc15a5b9 | bsd | commercial |
text_A: The garden is west of the kitchen. The hallway is east of the kitchen.
text_B: The kitchen west of is kitchen. | choice | babi-nli-two-arg-relations-9fc54432c3:train:2 | [
"not-entailed",
"entailed"
] | [
1,
0
] | Does text_A entail text_B? | babi_nli/two-arg-relations | direct | train | babi-nli-two-arg-relations-9fc54432c3:train:2 | decision | 0754df3e5544e2b5 | bsd | commercial |
text_A: The garden is west of the kitchen. The hallway is east of the kitchen.
text_B: The kitchen west of is kitchen. | noul | babi-nli-two-arg-relations-9fc54432c3:train:2:noul-label-verification | [] | [
0
] | Does text_A entail text_B? Is "entailed" the correct answer? | babi_nli/two-arg-relations | label_verification | train | babi-nli-two-arg-relations-9fc54432c3:train:2 | noul-label-verification | 0754df3e5544e2b5 | bsd | commercial |
text_A: Mary took the football there. Sandra took the apple there. Sandra put down the apple. John grabbed the apple there. John put down the apple. Mary left the football. Sandra took the football there. Daniel moved to the office. Sandra discarded the football. Mary picked up the apple there. John got the football th... | choice | babi-nli-two-supporting-facts-1756bf4c34:train:22 | [
"not-entailed",
"entailed"
] | [
0,
1
] | Does text_A entail text_B? | babi_nli/two-supporting-facts | direct | train | babi-nli-two-supporting-facts-1756bf4c34:train:22 | decision | 7c78c506b5b647c7 | bsd | commercial |
Passage A:
Mary took the football there. Sandra took the apple there. Sandra put down the apple. John grabbed the apple there. John put down the apple. Mary left the football. Sandra took the football there. Daniel moved to the office. Sandra discarded the football. Mary picked up the apple there. John got the football... | choice | babi-nli-two-supporting-facts-1756bf4c34:train:22:choice-paired-text-format | [
"not-entailed",
"entailed"
] | [
0,
1
] | Does text_A entail text_B? | babi_nli/two-supporting-facts | paired_text_format | train | babi-nli-two-supporting-facts-1756bf4c34:train:22 | choice-paired-text-format | 7c78c506b5b647c7 | bsd | commercial |
Item A:
text_A: Daniel went to the bathroom. Mary travelled to the bathroom. Mary journeyed to the kitchen. Mary went to the garden. Mary got the football there. John moved to the bathroom.
text_B: Mary is in the bathroom.
Item B:
text_A: Daniel went back to the bedroom. Sandra moved to the hallway. Mary went back to ... | choice | babi-nli-yes-no-questions-53d08980f1:train:pack-411af226091f:label-A | [
"not-entailed",
"entailed"
] | [
1,
0
] | Each item answers: "Does text_A entail text_B?"
Choose the criterion that best describes Item A. | babi_nli/yes-no-questions | packed_derived | train | babi-nli-yes-no-questions-53d08980f1:train:pack-411af226091f | label-A | b38af297c1abef8e | bsd | commercial |
Item A:
text_A: Daniel went to the bathroom. Mary travelled to the bathroom. Mary journeyed to the kitchen. Mary went to the garden. Mary got the football there. John moved to the bathroom.
text_B: Mary is in the bathroom.
Item B:
text_A: Daniel went back to the bedroom. Sandra moved to the hallway. Mary went back to ... | noul | babi-nli-yes-no-questions-53d08980f1:train:pack-411af226091f:same-A-B | [] | [
0
] | Each item answers: "Does text_A entail text_B?"
Do Item A and Item B have the same label? Possible labels: "not-entailed", "entailed". | babi_nli/yes-no-questions | packed_derived | train | babi-nli-yes-no-questions-53d08980f1:train:pack-411af226091f | same-A-B | b38af297c1abef8e | bsd | commercial |
Item A:
text_A: Daniel went to the bathroom. Mary travelled to the bathroom. Mary journeyed to the kitchen. Mary went to the garden. Mary got the football there. John moved to the bathroom.
text_B: Mary is in the bathroom.
Item B:
text_A: Daniel went back to the bedroom. Sandra moved to the hallway. Mary went back to ... | noul | babi-nli-yes-no-questions-53d08980f1:train:pack-411af226091f:exists-0 | [] | [
1
] | Each item answers: "Does text_A entail text_B?"
Does at least one item have the label "not-entailed"? Possible labels: "not-entailed", "entailed". | babi_nli/yes-no-questions | packed_derived | train | babi-nli-yes-no-questions-53d08980f1:train:pack-411af226091f | exists-0 | b38af297c1abef8e | bsd | commercial |
Item A:
text_A: Daniel went to the bathroom. Mary travelled to the bathroom. Mary journeyed to the kitchen. Mary went to the garden. Mary got the football there. John moved to the bathroom.
text_B: Mary is in the bathroom.
Item B:
text_A: Daniel went back to the bedroom. Sandra moved to the hallway. Mary went back to ... | score | babi-nli-yes-no-questions-53d08980f1:train:pack-411af226091f:count-0 | [
"0",
"1",
"2",
"3"
] | [
0,
0,
1,
0
] | Each item answers: "Does text_A entail text_B?"
How many items have the label "not-entailed"? Possible labels: "not-entailed", "entailed". | babi_nli/yes-no-questions | packed_derived | train | babi-nli-yes-no-questions-53d08980f1:train:pack-411af226091f | count-0 | b38af297c1abef8e | bsd | commercial |
I reached the top of the building. What was the cause of this? | choice | balanced-copa-90d823fa83:train:435 | [
"I ran five miles.",
"I walked upstairs."
] | [
0,
1
] | Which supplied option best answers the question? | balanced-copa | direct | train | balanced-copa-90d823fa83:train:435 | decision | 7783e6016662d20b | cc-by-4.0, BSD 2-Clause License (DPI) | commercial |
Why isn't my id verifying? | choice | banking77-8ef8a39243:train:68 | [
"activate_my_card",
"age_limit",
"apple_pay_or_google_pay",
"atm_support",
"automatic_top_up",
"balance_not_updated_after_bank_transfer",
"balance_not_updated_after_cheque_or_cash_deposit",
"beneficiary_not_allowed",
"cancel_transfer",
"card_about_to_expire",
"card_acceptance",
"card_arrival",... | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
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0,
0,
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0,
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0,
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0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | Choose the criterion that best describes the state. | banking77 | direct | train | banking77-8ef8a39243:train:68 | decision | ea86deb29462aaed | cc-by-4.0, CC BY 4.0 (DPI) | commercial |
Why isn't my id verifying? | noul | banking77-8ef8a39243:train:68:noul-label-verification | [] | [
0
] | Is "transfer_not_received_by_recipient" the correct label for this example? | banking77 | label_verification | train | banking77-8ef8a39243:train:68 | noul-label-verification | ea86deb29462aaed | cc-by-4.0, CC BY 4.0 (DPI) | commercial |
text_A: The aim of this study was to assess specialty-related differences in the treatment for patients with acute heart failure (AHF) in the acute phase and subsequent prognostic differences. Methods and Results: We analyzed hospitalizations for AHF in REALITY-AHF, a multicenter prospective registry focused on very ea... | choice | biosift-nli-9ea8641dce:train:134 | [
"entailment",
"not-entailment"
] | [
1,
0
] | Does text_A entail text_B? | biosift-nli | direct | train | biosift-nli-9ea8641dce:train:134 | decision | e5486a8d490a6de0 | unspecified | unspecified |
First text:
The aim of this study was to assess specialty-related differences in the treatment for patients with acute heart failure (AHF) in the acute phase and subsequent prognostic differences. Methods and Results: We analyzed hospitalizations for AHF in REALITY-AHF, a multicenter prospective registry focused on ver... | choice | biosift-nli-9ea8641dce:train:134:choice-paired-text-format | [
"entailment",
"not-entailment"
] | [
1,
0
] | Does text_A entail text_B? | biosift-nli | paired_text_format | train | biosift-nli-9ea8641dce:train:134 | choice-paired-text-format | e5486a8d490a6de0 | unspecified | unspecified |
Item A:
Seems like everyone gat ride problems....I ain ga b able 2 go unless danny n jess come (that wul b my ride back up 2 bayview cuz i sure as hell ain walkin there!). I think we jus gone n planned all this stuff on a really messed up weekend dread...but I got some good news (along with bad news). I got ... | choice | blog-authorship-corpus-age-8880d04019:train:pack-b0848e7c5c3e:label-A | [
"13-17",
"23-27",
"33-48"
] | [
1,
0,
0
] | Each item answers: "What is the blogger's age group?"
Choose the criterion that best describes Item A. | blog_authorship_corpus/age | packed_derived | train | blog-authorship-corpus-age-8880d04019:train:pack-b0848e7c5c3e | label-A | 0b0764e908f8f99b | apache-2.0 | commercial |
Item A:
Seems like everyone gat ride problems....I ain ga b able 2 go unless danny n jess come (that wul b my ride back up 2 bayview cuz i sure as hell ain walkin there!). I think we jus gone n planned all this stuff on a really messed up weekend dread...but I got some good news (along with bad news). I got ... | noul | blog-authorship-corpus-age-8880d04019:train:pack-b0848e7c5c3e:same-A-B | [] | [
1
] | Each item answers: "What is the blogger's age group?"
Do Item A and Item B have the same label? Possible labels: "13-17", "23-27", "33-48". | blog_authorship_corpus/age | packed_derived | train | blog-authorship-corpus-age-8880d04019:train:pack-b0848e7c5c3e | same-A-B | 0b0764e908f8f99b | apache-2.0 | commercial |
Item A:
Seems like everyone gat ride problems....I ain ga b able 2 go unless danny n jess come (that wul b my ride back up 2 bayview cuz i sure as hell ain walkin there!). I think we jus gone n planned all this stuff on a really messed up weekend dread...but I got some good news (along with bad news). I got ... | noul | blog-authorship-corpus-age-8880d04019:train:pack-b0848e7c5c3e:all-same | [] | [
1
] | Each item answers: "What is the blogger's age group?"
Do all items have the same label? Possible labels: "13-17", "23-27", "33-48". | blog_authorship_corpus/age | packed_derived | train | blog-authorship-corpus-age-8880d04019:train:pack-b0848e7c5c3e | all-same | 0b0764e908f8f99b | apache-2.0 | commercial |
Item A:
Seems like everyone gat ride problems....I ain ga b able 2 go unless danny n jess come (that wul b my ride back up 2 bayview cuz i sure as hell ain walkin there!). I think we jus gone n planned all this stuff on a really messed up weekend dread...but I got some good news (along with bad news). I got ... | choice | blog-authorship-corpus-age-8880d04019:train:pack-b0848e7c5c3e:most-common | [
"13-17",
"23-27",
"33-48"
] | [
1,
0,
0
] | Each item answers: "What is the blogger's age group?"
Which label is shared by the most items? | blog_authorship_corpus/age | packed_derived | train | blog-authorship-corpus-age-8880d04019:train:pack-b0848e7c5c3e | most-common | 0b0764e908f8f99b | apache-2.0 | commercial |
urlLink From out of nowhere, the news has broken of the recently filmed sequel to Cast Away, entitled 'The Cowbell Conspiracy'. Tom Hanks will be reprising his role as the Fed-Ex guru Chuck Noland, the plane crash survivor who discovered a knack for crab meat and learned the intricacies of talking to a volle... | choice | blog-authorship-corpus-gender-5fe8900d6d:train:4579 | [
"female",
"male"
] | [
0,
1
] | What is the blogger's gender? | blog_authorship_corpus/gender | direct | train | blog-authorship-corpus-gender-5fe8900d6d:train:4579 | decision | 63ad6e1bffeb6478 | apache-2.0, Custom (DPI) | commercial |
Item A:
urlLink urlLink
Item B:
Has anyone else noticed the new and improved Blogger features? Neato-burrito! | choice | blog-authorship-corpus-job-b565e07828:train:pack-d0577bc2cc67:label-B | [
"Accounting",
"Advertising",
"Agriculture",
"Architecture",
"Arts",
"Automotive",
"Banking",
"Biotech",
"BusinessServices",
"Chemicals",
"Communications-Media",
"Construction",
"Consulting",
"Education",
"Engineering",
"Environment",
"Fashion",
"Government",
"HumanResources",
"... | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0
] | Each item answers: "In which industry does the blogger work?"
Choose the criterion that best describes Item B. | blog_authorship_corpus/job | packed_derived | train | blog-authorship-corpus-job-b565e07828:train:pack-d0577bc2cc67 | label-B | ebc03f3d4fa791b0 | apache-2.0, Custom (DPI) | commercial |
Item A:
urlLink urlLink
Item B:
Has anyone else noticed the new and improved Blogger features? Neato-burrito! | noul | blog-authorship-corpus-job-b565e07828:train:pack-d0577bc2cc67:same-A-B | [] | [
0
] | Each item answers: "In which industry does the blogger work?"
Do Item A and Item B have the same label? Possible labels: "Accounting", "Advertising", "Agriculture", "Architecture", "Arts", "Automotive", "Banking", "Biotech", "BusinessServices", "Chemicals", "Communications-Media", "Construction", "Consulting", "Educati... | blog_authorship_corpus/job | packed_derived | train | blog-authorship-corpus-job-b565e07828:train:pack-d0577bc2cc67 | same-A-B | ebc03f3d4fa791b0 | apache-2.0, Custom (DPI) | commercial |
Item A:
urlLink urlLink
Item B:
Has anyone else noticed the new and improved Blogger features? Neato-burrito! | noul | blog-authorship-corpus-job-b565e07828:train:pack-d0577bc2cc67:exists-14 | [] | [
0
] | Each item answers: "In which industry does the blogger work?"
Does at least one item have the label "Engineering"? Possible labels: "Accounting", "Advertising", "Agriculture", "Architecture", "Arts", "Automotive", "Banking", "Biotech", "BusinessServices", "Chemicals", "Communications-Media", "Construction", "Consulting... | blog_authorship_corpus/job | packed_derived | train | blog-authorship-corpus-job-b565e07828:train:pack-d0577bc2cc67 | exists-14 | ebc03f3d4fa791b0 | apache-2.0, Custom (DPI) | commercial |
Item A:
urlLink urlLink
Item B:
Has anyone else noticed the new and improved Blogger features? Neato-burrito! | score | blog-authorship-corpus-job-b565e07828:train:pack-d0577bc2cc67:count-25 | [
"0",
"1",
"2"
] | [
1,
0,
0
] | Each item answers: "In which industry does the blogger work?"
How many items have the label "Marketing"? Possible labels: "Accounting", "Advertising", "Agriculture", "Architecture", "Arts", "Automotive", "Banking", "Biotech", "BusinessServices", "Chemicals", "Communications-Media", "Construction", "Consulting", "Educat... | blog_authorship_corpus/job | packed_derived | train | blog-authorship-corpus-job-b565e07828:train:pack-d0577bc2cc67 | count-25 | ebc03f3d4fa791b0 | apache-2.0, Custom (DPI) | commercial |
can a hawaiin born person be vice president? | choice | boolq-natural-perturbations-508f5ac0f9:train:8296 | [
"False",
"True"
] | [
0,
1
] | Select the label that best applies to the state. | boolq-natural-perturbations | direct | train | boolq-natural-perturbations-508f5ac0f9:train:8296 | decision | 23fefcc5dbbb361c | unspecified | unspecified |
Where does a showman store his money? | choice | brainteasers-SP-a00f6024c3:train:1 | [
"In a national bank.",
"None of the other options.",
"In a snow bank.",
"In a local bank."
] | [
0,
0,
1,
0
] | Choose the most appropriate answer from the supplied options. | brainteasers/SP | direct | train | brainteasers-SP-a00f6024c3:train:1 | decision | ade1cf91e880d384 | unspecified | unspecified |
Where does a showman store his money? | noul | brainteasers-SP-a00f6024c3:train:1:noul-label-verification | [] | [
1
] | Is "In a snow bank." the correct answer to the question? | brainteasers/SP | label_verification | train | brainteasers-SP-a00f6024c3:train:1 | noul-label-verification | ade1cf91e880d384 | unspecified | unspecified |
Where does a showman store his money? | choice | brainteasers-SP-a00f6024c3:train:1:choice-instruction-paraphrase | [
"In a national bank.",
"None of the other options.",
"In a snow bank.",
"In a local bank."
] | [
0,
0,
1,
0
] | Select the option that best answers the question. | brainteasers/SP | instruction_paraphrase | train | brainteasers-SP-a00f6024c3:train:1 | choice-instruction-paraphrase | ade1cf91e880d384 | unspecified | unspecified |
I am an odd number, but removing only one letter makes me even. Can you figure out what my number is? | choice | brainteasers-WP-b360da8d57:train:0 | [
"Seven",
"Five.",
"Eleven.",
"None of the other options."
] | [
1,
0,
0,
0
] | Choose the criterion that best answers the question. | brainteasers/WP | direct | train | brainteasers-WP-b360da8d57:train:0 | decision | 1d19d88b7ef5fd6f | unspecified | unspecified |
I am an odd number, but removing only one letter makes me even. Can you figure out what my number is? | choice | brainteasers-WP-b360da8d57:train:0:choice-instruction-paraphrase | [
"Seven",
"Five.",
"Eleven.",
"None of the other options."
] | [
1,
0,
0,
0
] | Select the option that best answers the question. | brainteasers/WP | instruction_paraphrase | train | brainteasers-WP-b360da8d57:train:0 | choice-instruction-paraphrase | 1d19d88b7ef5fd6f | unspecified | unspecified |
Item A:
text_A: Law Enforcement looks down the sight of a rifle in Thailand.
text_B: Law Enforcement looks down the sight of a rifle in Vietnam.
Item B:
text_A: A man throws a red tomato.
text_B: A man throws a green tomato.
Item C:
text_A: An old man is peeling a carrot.
text_B: An old man is peeling a vegetable.
I... | choice | breaking-nli-9bb3f705a7:train:pack-a711772b6c0a:label-B | [
"entailment",
"neutral",
"contradiction"
] | [
0,
0,
1
] | Each item answers: "Does text_A entail text_B, contradict it, or neither?"
Choose the criterion that best describes Item B. | breaking_nli | packed_derived | train | breaking-nli-9bb3f705a7:train:pack-a711772b6c0a | label-B | fba05fafd201c5d6 | CC BY-SA 4.0 (DPI) | commercial |
Item A:
text_A: Law Enforcement looks down the sight of a rifle in Thailand.
text_B: Law Enforcement looks down the sight of a rifle in Vietnam.
Item B:
text_A: A man throws a red tomato.
text_B: A man throws a green tomato.
Item C:
text_A: An old man is peeling a carrot.
text_B: An old man is peeling a vegetable.
I... | noul | breaking-nli-9bb3f705a7:train:pack-a711772b6c0a:in-A-1.2 | [] | [
1
] | Each item answers: "Does text_A entail text_B, contradict it, or neither?"
Is the label of Item A one of "neutral", "contradiction"? Possible labels: "entailment", "neutral", "contradiction". | breaking_nli | packed_derived | train | breaking-nli-9bb3f705a7:train:pack-a711772b6c0a | in-A-1.2 | fba05fafd201c5d6 | CC BY-SA 4.0 (DPI) | commercial |
Item A:
text_A: Law Enforcement looks down the sight of a rifle in Thailand.
text_B: Law Enforcement looks down the sight of a rifle in Vietnam.
Item B:
text_A: A man throws a red tomato.
text_B: A man throws a green tomato.
Item C:
text_A: An old man is peeling a carrot.
text_B: An old man is peeling a vegetable.
I... | noul | breaking-nli-9bb3f705a7:train:pack-a711772b6c0a:exists-1 | [] | [
0
] | Each item answers: "Does text_A entail text_B, contradict it, or neither?"
Does at least one item have the label "neutral"? Possible labels: "entailment", "neutral", "contradiction". | breaking_nli | packed_derived | train | breaking-nli-9bb3f705a7:train:pack-a711772b6c0a | exists-1 | fba05fafd201c5d6 | CC BY-SA 4.0 (DPI) | commercial |
Item A:
text_A: Law Enforcement looks down the sight of a rifle in Thailand.
text_B: Law Enforcement looks down the sight of a rifle in Vietnam.
Item B:
text_A: A man throws a red tomato.
text_B: A man throws a green tomato.
Item C:
text_A: An old man is peeling a carrot.
text_B: An old man is peeling a vegetable.
I... | score | breaking-nli-9bb3f705a7:train:pack-a711772b6c0a:count-2 | [
"0",
"1",
"2",
"3",
"4"
] | [
0,
0,
1,
0,
0
] | Each item answers: "Does text_A entail text_B, contradict it, or neither?"
How many items have the label "contradiction"? Possible labels: "entailment", "neutral", "contradiction". | breaking_nli | packed_derived | train | breaking-nli-9bb3f705a7:train:pack-a711772b6c0a | count-2 | fba05fafd201c5d6 | CC BY-SA 4.0 (DPI) | commercial |
Passage A:
Concentration of greenhouse gases, especially CO2, have increased substantially since the beginning of the industrial revolution.
Passage B:
Global warming is not real. | choice | tasksource-chaos-mnli-ambiguity-e7d44e91ea:train:83799b00795e95d8:chaos-mnli-ambiguity-votes | [
"entailment",
"neutral",
"contradiction"
] | [
0.02,
0.32,
0.66
] | How would annotators label the relation of the hypothesis to the premise? | chaos-mnli-ambiguity/votes | direct | train | tasksource-chaos-mnli-ambiguity-e7d44e91ea:train:83799b00795e95d8 | chaos-mnli-ambiguity-votes | 1530f9878517d39c | unspecified | unspecified |
I live in Vancouver and I'm going to a graduation ceremony in United States for a few days, write me a list of items I should bring in json format. | choice | chatbot-arena-conversations-93d787d507:train:11350 | [
"Here is a list of items you may want to bring with you on your trip:\n\n{\n\"essential\": [\n\"Passport\",\n\"Driver's license or ID\",\n\"Cash and credit cards\",\n\"Phone and charger\",\n\"Camera\",\n\"Comfortable clothing and shoes\",\n\"Toiletries (toothbrush, toothpaste, etc.)\",\n\"Medication (if needed)\",\... | [
1,
0
] | Which assistant did the user prefer? | chatbot_arena_conversations | direct | train | chatbot-arena-conversations-93d787d507:train:11350 | decision | 58daad28dd901f38 | cc, CC BY 4.0 (DPI), CC BY-NC 4.0 (DPI), OpenAI (DPI) | non-commercial |
I live in Vancouver and I'm going to a graduation ceremony in United States for a few days, write me a list of items I should bring in json format. | noul | chatbot-arena-conversations-93d787d507:train:11350:noul-label-verification | [] | [
1
] | Which assistant did the user prefer? Is "Here is a list of items you may want to bring with you on your trip:
{
"essential": [
"Passport",
"Driver's license or ID",
"Cash and credit cards",
"Phone and charger",
"Camera",
"Comfortable clothing and shoes",
"Toiletries (toothbrush, toothpaste, etc.)",
"Medication (if nee... | chatbot_arena_conversations | label_verification | train | chatbot-arena-conversations-93d787d507:train:11350 | noul-label-verification | 58daad28dd901f38 | cc, CC BY 4.0 (DPI), CC BY-NC 4.0 (DPI), OpenAI (DPI) | non-commercial |
I live in Vancouver and I'm going to a graduation ceremony in United States for a few days, write me a list of items I should bring in json format. | choice | chatbot-arena-conversations-93d787d507:train:11350:choice-criteria-permutation | [
"{\n \"passport\": true,\n \"visa\": true,\n \"flight ticket\": true,\n \"cash\": true,\n \"credit/debit card\": true,\n \"travel adapter\": true,\n \"phone charger\": true,\n \"toiletries\": true,\n \"medications\": true,\n \"appropriate clothing for graduation ceremony\": true,\n \"comfortable walking ... | [
0,
1
] | Which assistant did the user prefer? | chatbot_arena_conversations | criteria_permutation | train | chatbot-arena-conversations-93d787d507:train:11350 | choice-criteria-permutation | 58daad28dd901f38 | cc, CC BY 4.0 (DPI), CC BY-NC 4.0 (DPI), OpenAI (DPI) | non-commercial |
text_A: Emerging role of epidermal growth factor receptor inhibition in therapy for advanced malignancy: focus on NSCLC.
Combination chemotherapy regimens have emerged as the standard approach in advanced non-small-cell lung cancer. Meta-analyses have demonstrated a 2-month increase in median survival after platinum-ba... | choice | chemprot-chemprot-full-source-ea2ca5027c:train:9 | [
"agonist",
"antagonist",
"cofactor",
"downregulator or inhibitor",
"explicitly not related",
"modulator",
"part of",
"regulator (direct or indirect)",
"substrate or product of",
"upregulator or activator"
] | [
0,
0,
0,
1,
0,
0,
0,
0,
0,
0
] | Which relation holds between the chemical and the protein in text_B? | chemprot/chemprot_full_source | direct | train | chemprot-chemprot-full-source-ea2ca5027c:train:9 | decision | 2b5d850f27fb98d0 | other | unspecified |
text_A: Emerging role of epidermal growth factor receptor inhibition in therapy for advanced malignancy: focus on NSCLC.
Combination chemotherapy regimens have emerged as the standard approach in advanced non-small-cell lung cancer. Meta-analyses have demonstrated a 2-month increase in median survival after platinum-ba... | choice | chemprot-chemprot-full-source-ea2ca5027c:train:9:choice-criteria-permutation | [
"regulator (direct or indirect)",
"part of",
"substrate or product of",
"explicitly not related",
"cofactor",
"upregulator or activator",
"downregulator or inhibitor",
"modulator",
"agonist",
"antagonist"
] | [
0,
0,
0,
0,
0,
0,
1,
0,
0,
0
] | Which relation holds between the chemical and the protein in text_B? | chemprot/chemprot_full_source | criteria_permutation | train | chemprot-chemprot-full-source-ea2ca5027c:train:9 | choice-criteria-permutation | 2b5d850f27fb98d0 | other | unspecified |
First text:
Emerging role of epidermal growth factor receptor inhibition in therapy for advanced malignancy: focus on NSCLC.
Combination chemotherapy regimens have emerged as the standard approach in advanced non-small-cell lung cancer. Meta-analyses have demonstrated a 2-month increase in median survival after platinu... | choice | chemprot-chemprot-full-source-ea2ca5027c:train:9:choice-paired-text-format | [
"agonist",
"antagonist",
"cofactor",
"downregulator or inhibitor",
"explicitly not related",
"modulator",
"part of",
"regulator (direct or indirect)",
"substrate or product of",
"upregulator or activator"
] | [
0,
0,
0,
1,
0,
0,
0,
0,
0,
0
] | Which relation holds between the chemical and the protein in text_B? | chemprot/chemprot_full_source | paired_text_format | train | chemprot-chemprot-full-source-ea2ca5027c:train:9 | choice-paired-text-format | 2b5d850f27fb98d0 | other | unspecified |
A: Good.Now what kind of job do you want ? Mr.Wilson ?
B: I don't mind really.Perhaps a job in a shop or a factory .
A: Well , I know Brown's Biscuit Factory are looking for a porter.They pay $ 200 a week .
B: That sounds all right .
A: Good.Now here's the address of the factory.The manager's name is ...
Target uttera... | choice | cicero-03b1d98b47:train:18106 | [
"The speaker will try and get the job as the pay is low.",
"The speaker will not try to get the job as it pays poorly.",
"The speaker will try and get the job as it pays well.",
"The speaker got a job and is happy.",
"The speaker won't try and get the job as it pays poorly."
] | [
0,
0,
1,
0,
0
] | Which supplied option best answers the question? | cicero | direct | train | cicero-03b1d98b47:train:18106 | decision | d33d76f5dac074b0 | mit | commercial |
A: Good.Now what kind of job do you want ? Mr.Wilson ?
B: I don't mind really.Perhaps a job in a shop or a factory .
A: Well , I know Brown's Biscuit Factory are looking for a porter.They pay $ 200 a week .
B: That sounds all right .
A: Good.Now here's the address of the factory.The manager's name is ...
Target uttera... | choice | cicero-03b1d98b47:train:18106:choice-criteria-permutation | [
"The speaker won't try and get the job as it pays poorly.",
"The speaker will not try to get the job as it pays poorly.",
"The speaker got a job and is happy.",
"The speaker will try and get the job as it pays well.",
"The speaker will try and get the job as the pay is low."
] | [
0,
0,
0,
1,
0
] | Which supplied option best answers the question? | cicero | criteria_permutation | train | cicero-03b1d98b47:train:18106 | choice-criteria-permutation | d33d76f5dac074b0 | mit | commercial |
A: Y has just told X that he/she is considering switching his/her job. Do you work with data a lot?
B: I don't do that type of work. | choice | circa-9b8c5093f3:train:25061 | [
"Yes",
"No",
"In the middle, neither yes nor no",
"Yes, subject to some conditions",
"Other"
] | [
0,
1,
0,
0,
0
] | Select the label that best applies to the state. | circa | direct | train | circa-9b8c5093f3:train:25061 | decision | 016d917e948a4088 | cc-by-4.0 | commercial |
The formalization of DLRs provided by Meurers ( 1995 ) defines a formal lexical rule specification language and provides a semantics for that language in two steps : A rewrite system enriches the lexical rule specification into a fully explicit description of the kind shown in Figure 1 . | choice | citation-intent-d614a94399:train:9 | [
"Background",
"CompareOrContrast",
"Extends",
"Future",
"Motivation",
"Uses"
] | [
1,
0,
0,
0,
0,
0
] | Which of the supplied criteria best matches the state? | citation_intent | direct | train | citation-intent-d614a94399:train:9 | decision | 45ca044aaa373b45 | unspecified | unspecified |
The formalization of DLRs provided by Meurers ( 1995 ) defines a formal lexical rule specification language and provides a semantics for that language in two steps : A rewrite system enriches the lexical rule specification into a fully explicit description of the kind shown in Figure 1 . | noul | citation-intent-d614a94399:train:9:noul-label-verification | [] | [
0
] | Is "CompareOrContrast" the correct label for this example? | citation_intent | label_verification | train | citation-intent-d614a94399:train:9 | noul-label-verification | 45ca044aaa373b45 | unspecified | unspecified |
That's justice, not liberty. | noul | google-civil-comments-22ba067369:train:ca18e10247b8a56b:civil_comments-identity_attack_share | [] | [
0
] | What fraction of annotators rated the comment as an identity attack? | civil_comments/identity_attack_share | direct | train | google-civil-comments-22ba067369:train:ca18e10247b8a56b | civil_comments-identity_attack_share | fa631630b01df4e1 | cc0-1.0 | commercial |
That's justice, not liberty. | noul | google-civil-comments-22ba067369:train:ca18e10247b8a56b:civil_comments-insult_share | [] | [
0
] | What fraction of annotators rated the comment as insulting? | civil_comments/insult_share | direct | train | google-civil-comments-22ba067369:train:ca18e10247b8a56b | civil_comments-insult_share | fa631630b01df4e1 | cc0-1.0 | commercial |
That's justice, not liberty. | noul | google-civil-comments-22ba067369:train:ca18e10247b8a56b:civil_comments-obscene_share | [] | [
0
] | What fraction of annotators rated the comment as obscene? | civil_comments/obscene_share | direct | train | google-civil-comments-22ba067369:train:ca18e10247b8a56b | civil_comments-obscene_share | fa631630b01df4e1 | cc0-1.0 | commercial |
That's justice, not liberty. | noul | google-civil-comments-22ba067369:train:ca18e10247b8a56b:civil_comments-severe_toxicity_share | [] | [
0
] | What fraction of annotators rated the comment as severely toxic? | civil_comments/severe_toxicity_share | direct | train | google-civil-comments-22ba067369:train:ca18e10247b8a56b | civil_comments-severe_toxicity_share | fa631630b01df4e1 | cc0-1.0 | commercial |
That's justice, not liberty. | noul | google-civil-comments-22ba067369:train:ca18e10247b8a56b:civil_comments-sexual_explicit_share | [] | [
0
] | What fraction of annotators rated the comment as sexually explicit? | civil_comments/sexual_explicit_share | direct | train | google-civil-comments-22ba067369:train:ca18e10247b8a56b | civil_comments-sexual_explicit_share | fa631630b01df4e1 | cc0-1.0 | commercial |
That's justice, not liberty. | noul | google-civil-comments-22ba067369:train:ca18e10247b8a56b:civil_comments-threat_share | [] | [
0
] | What fraction of annotators rated the comment as threatening? | civil_comments/threat_share | direct | train | google-civil-comments-22ba067369:train:ca18e10247b8a56b | civil_comments-threat_share | fa631630b01df4e1 | cc0-1.0 | commercial |
That's justice, not liberty. | noul | google-civil-comments-22ba067369:train:ca18e10247b8a56b:civil_comments-toxicity_share | [] | [
0
] | What fraction of annotators rated the comment as toxic? | civil_comments/toxicity_share | direct | train | google-civil-comments-22ba067369:train:ca18e10247b8a56b | civil_comments-toxicity_share | fa631630b01df4e1 | cc0-1.0 | commercial |
Good for him. Why are they working on feel-good, PC, everyone-is-a-winner bills rather than brainstorming constructive new ideas for fixing the budget? | noul | google-civil-comments-22ba067369:train:f2e55f824bdab36d:civil_comments-identity_attack_share | [] | [
0
] | What fraction of annotators rated the comment as an identity attack? | civil_comments/identity_attack_share | direct | train | google-civil-comments-22ba067369:train:f2e55f824bdab36d | civil_comments-identity_attack_share | 894fea7c4796f436 | cc0-1.0 | commercial |
Good for him. Why are they working on feel-good, PC, everyone-is-a-winner bills rather than brainstorming constructive new ideas for fixing the budget? | noul | google-civil-comments-22ba067369:train:f2e55f824bdab36d:civil_comments-insult_share | [] | [
0
] | What fraction of annotators rated the comment as insulting? | civil_comments/insult_share | direct | train | google-civil-comments-22ba067369:train:f2e55f824bdab36d | civil_comments-insult_share | 894fea7c4796f436 | cc0-1.0 | commercial |
Good for him. Why are they working on feel-good, PC, everyone-is-a-winner bills rather than brainstorming constructive new ideas for fixing the budget? | noul | google-civil-comments-22ba067369:train:f2e55f824bdab36d:civil_comments-threat_share | [] | [
0
] | What fraction of annotators rated the comment as threatening? | civil_comments/threat_share | direct | train | google-civil-comments-22ba067369:train:f2e55f824bdab36d | civil_comments-threat_share | 894fea7c4796f436 | cc0-1.0 | commercial |
Good for him. Why are they working on feel-good, PC, everyone-is-a-winner bills rather than brainstorming constructive new ideas for fixing the budget? | noul | google-civil-comments-22ba067369:train:f2e55f824bdab36d:civil_comments-toxicity_share | [] | [
0
] | What fraction of annotators rated the comment as toxic? | civil_comments/toxicity_share | direct | train | google-civil-comments-22ba067369:train:f2e55f824bdab36d | civil_comments-toxicity_share | 894fea7c4796f436 | cc0-1.0 | commercial |
What's up with this elitist proposal from Loudermilk? If the rest of us "regular" Americans must suffer the price of having "gun-free zones" everywhere, then our so-called "leaders" should as well. Barry needs to have the guts to live in the same world as his constituents do. Either remove these deadly "gun-free zones"... | noul | google-civil-comments-22ba067369:train:f443fcf244ee39f2:civil_comments-identity_attack_share | [] | [
0
] | What fraction of annotators rated the comment as an identity attack? | civil_comments/identity_attack_share | direct | train | google-civil-comments-22ba067369:train:f443fcf244ee39f2 | civil_comments-identity_attack_share | 345f0f65a9550881 | cc0-1.0 | commercial |
What's up with this elitist proposal from Loudermilk? If the rest of us "regular" Americans must suffer the price of having "gun-free zones" everywhere, then our so-called "leaders" should as well. Barry needs to have the guts to live in the same world as his constituents do. Either remove these deadly "gun-free zones"... | noul | google-civil-comments-22ba067369:train:f443fcf244ee39f2:civil_comments-insult_share | [] | [
0
] | What fraction of annotators rated the comment as insulting? | civil_comments/insult_share | direct | train | google-civil-comments-22ba067369:train:f443fcf244ee39f2 | civil_comments-insult_share | 345f0f65a9550881 | cc0-1.0 | commercial |
What's up with this elitist proposal from Loudermilk? If the rest of us "regular" Americans must suffer the price of having "gun-free zones" everywhere, then our so-called "leaders" should as well. Barry needs to have the guts to live in the same world as his constituents do. Either remove these deadly "gun-free zones"... | noul | google-civil-comments-22ba067369:train:f443fcf244ee39f2:civil_comments-obscene_share | [] | [
0
] | What fraction of annotators rated the comment as obscene? | civil_comments/obscene_share | direct | train | google-civil-comments-22ba067369:train:f443fcf244ee39f2 | civil_comments-obscene_share | 345f0f65a9550881 | cc0-1.0 | commercial |
What's up with this elitist proposal from Loudermilk? If the rest of us "regular" Americans must suffer the price of having "gun-free zones" everywhere, then our so-called "leaders" should as well. Barry needs to have the guts to live in the same world as his constituents do. Either remove these deadly "gun-free zones"... | noul | google-civil-comments-22ba067369:train:f443fcf244ee39f2:civil_comments-severe_toxicity_share | [] | [
0
] | What fraction of annotators rated the comment as severely toxic? | civil_comments/severe_toxicity_share | direct | train | google-civil-comments-22ba067369:train:f443fcf244ee39f2 | civil_comments-severe_toxicity_share | 345f0f65a9550881 | cc0-1.0 | commercial |
What's up with this elitist proposal from Loudermilk? If the rest of us "regular" Americans must suffer the price of having "gun-free zones" everywhere, then our so-called "leaders" should as well. Barry needs to have the guts to live in the same world as his constituents do. Either remove these deadly "gun-free zones"... | noul | google-civil-comments-22ba067369:train:f443fcf244ee39f2:civil_comments-sexual_explicit_share | [] | [
0
] | What fraction of annotators rated the comment as sexually explicit? | civil_comments/sexual_explicit_share | direct | train | google-civil-comments-22ba067369:train:f443fcf244ee39f2 | civil_comments-sexual_explicit_share | 345f0f65a9550881 | cc0-1.0 | commercial |
What's up with this elitist proposal from Loudermilk? If the rest of us "regular" Americans must suffer the price of having "gun-free zones" everywhere, then our so-called "leaders" should as well. Barry needs to have the guts to live in the same world as his constituents do. Either remove these deadly "gun-free zones"... | noul | google-civil-comments-22ba067369:train:f443fcf244ee39f2:civil_comments-threat_share | [] | [
0
] | What fraction of annotators rated the comment as threatening? | civil_comments/threat_share | direct | train | google-civil-comments-22ba067369:train:f443fcf244ee39f2 | civil_comments-threat_share | 345f0f65a9550881 | cc0-1.0 | commercial |
What's up with this elitist proposal from Loudermilk? If the rest of us "regular" Americans must suffer the price of having "gun-free zones" everywhere, then our so-called "leaders" should as well. Barry needs to have the guts to live in the same world as his constituents do. Either remove these deadly "gun-free zones"... | noul | google-civil-comments-22ba067369:train:f443fcf244ee39f2:civil_comments-toxicity_share | [] | [
0
] | What fraction of annotators rated the comment as toxic? | civil_comments/toxicity_share | direct | train | google-civil-comments-22ba067369:train:f443fcf244ee39f2 | civil_comments-toxicity_share | 345f0f65a9550881 | cc0-1.0 | commercial |
First text:
Let V2 = the candle; X = the man in the room; Y = room. Causal graph: X->Y,V2->Y.
The overall probability of blowing out the candle is 16%. For people not blowing out candles, the probability of dark room is 88%. For people who blow out candles, the probability of dark room is 56%.
Second text:
Is dark roo... | choice | cladder-55e0a301db:train:14 | [
"no",
"yes"
] | [
0,
1
] | Choose the most appropriate category for the state. | cladder | direct | train | cladder-55e0a301db:train:14 | decision | 6c70db8bc30ed30f | mit | commercial |
First text:
Let V2 = the candle; X = the man in the room; Y = room. Causal graph: X->Y,V2->Y.
The overall probability of blowing out the candle is 16%. For people not blowing out candles, the probability of dark room is 88%. For people who blow out candles, the probability of dark room is 56%.
Second text:
Is dark roo... | noul | cladder-55e0a301db:train:14:noul-label-verification | [] | [
1
] | Is "yes" the correct label for this example? | cladder | label_verification | train | cladder-55e0a301db:train:14 | noul-label-verification | 6c70db8bc30ed30f | mit | commercial |
First text:
Let V2 = the candle; X = the man in the room; Y = room. Causal graph: X->Y,V2->Y.
The overall probability of blowing out the candle is 16%. For people not blowing out candles, the probability of dark room is 88%. For people who blow out candles, the probability of dark room is 56%.
Second text:
Is dark roo... | choice | cladder-55e0a301db:train:14:choice-instruction-paraphrase | [
"no",
"yes"
] | [
0,
1
] | Choose the most appropriate category for the state. | cladder | instruction_paraphrase | train | cladder-55e0a301db:train:14 | choice-instruction-paraphrase | 6c70db8bc30ed30f | mit | commercial |
A: Everyone has visited Tajikistan, The Bahamas, Romania, Nicaragua, Belarus, Poland, Jordan, Liechtenstein, Grenada, Nepal, China, Sierra Leone, Georgia, Saint Lucia, Australia, Burkina, Pakistan and Bulgaria
B: Sam didn't visit Laos | choice | clcd-english-ee91b0e324:train:6063 | [
"contradiction",
"not_contradiction"
] | [
0,
1
] | Which of the supplied criteria best matches the state? | clcd-english | direct | train | clcd-english-ee91b0e324:train:6063 | decision | 64e56170f2643b16 | apache-2.0 | commercial |
A: Everyone has visited Tajikistan, The Bahamas, Romania, Nicaragua, Belarus, Poland, Jordan, Liechtenstein, Grenada, Nepal, China, Sierra Leone, Georgia, Saint Lucia, Australia, Burkina, Pakistan and Bulgaria
B: Sam didn't visit Laos | choice | clcd-english-ee91b0e324:train:6063:choice-paired-text-format | [
"contradiction",
"not_contradiction"
] | [
0,
1
] | Which of the supplied criteria best matches the state? | clcd-english | paired_text_format | train | clcd-english-ee91b0e324:train:6063 | choice-paired-text-format | 64e56170f2643b16 | apache-2.0 | commercial |
translate hello to english | choice | clinc-oos-plus-1b9b3d1a5a:train:28 | [
"restaurant_reviews",
"nutrition_info",
"account_blocked",
"oil_change_how",
"time",
"weather",
"redeem_rewards",
"interest_rate",
"gas_type",
"accept_reservations",
"smart_home",
"user_name",
"report_lost_card",
"repeat",
"whisper_mode",
"what_are_your_hobbies",
"order",
"jump_sta... | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
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0,
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0,
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0,
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0,
0,
0,
0,
1,
0,
0... | Which of the supplied criteria best matches the state? | clinc_oos/plus | direct | train | clinc-oos-plus-1b9b3d1a5a:train:28 | decision | abb2d46c3a0418dc | cc-by-3.0 | commercial |
translate hello to english | noul | clinc-oos-plus-1b9b3d1a5a:train:28:noul-label-verification | [] | [
0
] | Is "order" the correct label for this example? | clinc_oos/plus | label_verification | train | clinc-oos-plus-1b9b3d1a5a:train:28 | noul-label-verification | abb2d46c3a0418dc | cc-by-3.0 | commercial |
He would [MASK] the basket on purpose so I wouldn't lose against him. | choice | cloth-a8d3866ed4:train:4 | [
"miss",
"hit",
"catch",
"get"
] | [
1,
0,
0,
0
] | Choose the most appropriate answer from the supplied options. | cloth | direct | train | cloth-a8d3866ed4:train:4 | decision | b23474948f48ac30 | mit | commercial |
He would [MASK] the basket on purpose so I wouldn't lose against him. | noul | cloth-a8d3866ed4:train:4:noul-label-verification | [] | [
1
] | Is "miss" the correct answer to the question? | cloth | label_verification | train | cloth-a8d3866ed4:train:4 | noul-label-verification | b23474948f48ac30 | mit | commercial |
Item A:
text_A: Pedro made a pizza for his daughter. Her name is Rebecca. . One day Antonio the uncle of Rebecca, decided to surprise Rebecca with a camping trip. Rebecca had been wanting to go camping for a long time. Pedro took his daughter, Rebecca, to the father daughter dance at church. Antonio enjoys talking to h... | choice | clutrr-effc7ced7a:train:pack-f59e25835dde:label-B | [
"aunt",
"brother",
"daughter",
"daughter-in-law",
"father",
"father-in-law",
"granddaughter",
"grandfather",
"grandmother",
"grandson",
"mother",
"mother-in-law",
"nephew",
"niece",
"sister",
"son",
"son-in-law",
"uncle"
] | [
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] | Choose the criterion that best describes Item B. | clutrr | packed_derived | train | clutrr-effc7ced7a:train:pack-f59e25835dde | label-B | 48898692603d9099 | unspecified | unspecified |
Item A:
text_A: Pedro made a pizza for his daughter. Her name is Rebecca. . One day Antonio the uncle of Rebecca, decided to surprise Rebecca with a camping trip. Rebecca had been wanting to go camping for a long time. Pedro took his daughter, Rebecca, to the father daughter dance at church. Antonio enjoys talking to h... | noul | clutrr-effc7ced7a:train:pack-f59e25835dde:in-B-1.2.6.8.9.10.13.14 | [] | [
0
] | Is the label of Item B one of "brother", "daughter", "granddaughter", "grandmother", "grandson", "mother", "niece", "sister"? Possible labels: "aunt", "brother", "daughter", "daughter-in-law", "father", "father-in-law", "granddaughter", "grandfather", "grandmother", "grandson", "mother", "mother-in-law", "nephew", "nie... | clutrr | packed_derived | train | clutrr-effc7ced7a:train:pack-f59e25835dde | in-B-1.2.6.8.9.10.13.14 | 48898692603d9099 | unspecified | unspecified |
Item A:
text_A: Pedro made a pizza for his daughter. Her name is Rebecca. . One day Antonio the uncle of Rebecca, decided to surprise Rebecca with a camping trip. Rebecca had been wanting to go camping for a long time. Pedro took his daughter, Rebecca, to the father daughter dance at church. Antonio enjoys talking to h... | noul | clutrr-effc7ced7a:train:pack-f59e25835dde:exists-5 | [] | [
0
] | Does at least one item have the label "father-in-law"? Possible labels: "aunt", "brother", "daughter", "daughter-in-law", "father", "father-in-law", "granddaughter", "grandfather", "grandmother", "grandson", "mother", "mother-in-law", "nephew", "niece", "sister", "son", "son-in-law", "uncle". | clutrr | packed_derived | train | clutrr-effc7ced7a:train:pack-f59e25835dde | exists-5 | 48898692603d9099 | unspecified | unspecified |
Item A:
text_A: Pedro made a pizza for his daughter. Her name is Rebecca. . One day Antonio the uncle of Rebecca, decided to surprise Rebecca with a camping trip. Rebecca had been wanting to go camping for a long time. Pedro took his daughter, Rebecca, to the father daughter dance at church. Antonio enjoys talking to h... | score | clutrr-effc7ced7a:train:pack-f59e25835dde:count-3 | [
"0",
"1",
"2",
"3"
] | [
1,
0,
0,
0
] | How many items have the label "daughter-in-law"? Possible labels: "aunt", "brother", "daughter", "daughter-in-law", "father", "father-in-law", "granddaughter", "grandfather", "grandmother", "grandson", "mother", "mother-in-law", "nephew", "niece", "sister", "son", "son-in-law", "uncle". | clutrr | packed_derived | train | clutrr-effc7ced7a:train:pack-f59e25835dde | count-3 | 48898692603d9099 | unspecified | unspecified |
text_A: A blue delivery truck is parked in front of a white building on a street corner.
text_B: A person is sleeping. | choice | cnli-14f2bf6434:train:9 | [
"entailment",
"neutral",
"contradiction"
] | [
0,
0,
1
] | Does text_A entail text_B, contradict it, or neither? | cnli | direct | train | cnli-14f2bf6434:train:9 | decision | 4a9c76800f31d5e7 | unspecified | unspecified |
A: A blue delivery truck is parked in front of a white building on a street corner.
B: A person is sleeping. | choice | cnli-14f2bf6434:train:9:choice-paired-text-format | [
"entailment",
"neutral",
"contradiction"
] | [
0,
0,
1
] | Does text_A entail text_B, contradict it, or neither? | cnli | paired_text_format | train | cnli-14f2bf6434:train:9 | choice-paired-text-format | 4a9c76800f31d5e7 | unspecified | unspecified |
I woke up in a cold sweat in the middle of the night. I | choice | codah-codah-29ecccdde1:train:69 | [
"asked my imaginary friend, Dr. Dolittle, if I had a fever.",
"merged onto the highway.",
"washed my face and drank some water.",
"decided not to eat any more Krabby Patties before bed."
] | [
0,
0,
1,
0
] | Choose the most appropriate answer from the supplied options. | codah/codah | direct | train | codah-codah-29ecccdde1:train:69 | decision | acf5af4668d2291a | odc-by | commercial |
I woke up in a cold sweat in the middle of the night. I | noul | codah-codah-29ecccdde1:train:69:noul-label-verification | [] | [
0
] | Is "asked my imaginary friend, Dr. Dolittle, if I had a fever." the correct answer to the question? | codah/codah | label_verification | train | codah-codah-29ecccdde1:train:69 | noul-label-verification | acf5af4668d2291a | odc-by | commercial |
static int transcode(AVFormatContext **output_files,
int nb_output_files,
InputFile *input_files,
int nb_input_files,
StreamMap *stream_maps, int nb_stream_maps)
{
int ret = 0, i, j, k, n, nb_ostreams = 0, step;
AVForma... | choice | code-x-glue-cc-defect-detection-1c76c57e72:train:1 | [
"defect",
"no defect"
] | [
0,
1
] | Does this C function contain a defect, such as a vulnerability or a memory bug? | code_x_glue_cc_defect_detection | direct | train | code-x-glue-cc-defect-detection-1c76c57e72:train:1 | decision | c33c4dae1aef2fdd | c-uda | unspecified |
Item A:
If I borrow a book from a friend and return it, she will unlikely to lend me anything again.
Item B:
A pickaxe is better suited to cutting down a tree than a chainsaw. | choice | com2sense-cbe923accf:train:pack-84d4db59c5ea:label-B | [
"False",
"True"
] | [
1,
0
] | Choose the criterion that best describes Item B. | com2sense | packed_derived | train | com2sense-cbe923accf:train:pack-84d4db59c5ea | label-B | 363770f3f65e71f8 | unspecified | unspecified |
Item A:
If I borrow a book from a friend and return it, she will unlikely to lend me anything again.
Item B:
A pickaxe is better suited to cutting down a tree than a chainsaw. | noul | com2sense-cbe923accf:train:pack-84d4db59c5ea:same-A-B | [] | [
1
] | Do Item A and Item B have the same label? Possible labels: "False", "True". | com2sense | packed_derived | train | com2sense-cbe923accf:train:pack-84d4db59c5ea | same-A-B | 363770f3f65e71f8 | unspecified | unspecified |
Item A:
If I borrow a book from a friend and return it, she will unlikely to lend me anything again.
Item B:
A pickaxe is better suited to cutting down a tree than a chainsaw. | noul | com2sense-cbe923accf:train:pack-84d4db59c5ea:exists-1 | [] | [
0
] | Does at least one item have the label "True"? Possible labels: "False", "True". | com2sense | packed_derived | train | com2sense-cbe923accf:train:pack-84d4db59c5ea | exists-1 | 363770f3f65e71f8 | unspecified | unspecified |
Item A:
If I borrow a book from a friend and return it, she will unlikely to lend me anything again.
Item B:
A pickaxe is better suited to cutting down a tree than a chainsaw. | score | com2sense-cbe923accf:train:pack-84d4db59c5ea:count-0 | [
"0",
"1",
"2"
] | [
0,
0,
1
] | How many items have the label "False"? Possible labels: "False", "True". | com2sense | packed_derived | train | com2sense-cbe923accf:train:pack-84d4db59c5ea | count-0 | 363770f3f65e71f8 | unspecified | unspecified |
Miranda wasn't sure about what she was doing, she just knew that she couldn't stop moving her smelly feet. This was a problem, because she was told to do what? | choice | commonsense-qa-89cea5128c:train:8667 | [
"walk",
"stink",
"hands",
"stay still",
"shoes"
] | [
0,
0,
0,
1,
0
] | Choose the criterion that best answers the question. | commonsense_qa | direct | train | commonsense-qa-89cea5128c:train:8667 | decision | c6da1855809367db | mit | commercial |
kidney stones are larger than gravel stones | choice | commonsense-qa-2-0-fe3c76eb16:train:8820 | [
"no",
"yes"
] | [
1,
0
] | Choose the most appropriate category for the state. | commonsense_qa_2.0 | direct | train | commonsense-qa-2-0-fe3c76eb16:train:8820 | decision | 0709286292a19976 | cc-by-4.0 | commercial |
kidney stones are larger than gravel stones | choice | commonsense-qa-2-0-fe3c76eb16:train:8820:choice-criteria-permutation | [
"yes",
"no"
] | [
0,
1
] | Choose the most appropriate category for the state. | commonsense_qa_2.0 | criteria_permutation | train | commonsense-qa-2-0-fe3c76eb16:train:8820 | choice-criteria-permutation | 0709286292a19976 | cc-by-4.0 | commercial |
text_A: Pizza is in the vicinity of plate. Plate is in the vicinity of dishwasher. Weasel is not in the vicinity of your eye. Plate is used for put food on. Weasel is in the vicinity of cheese. Cheese is in the vicinity of pizza. Weasel is not in the vicinity of book. Lettuce is not in the vicinity of populous area. Ch... | choice | conceptrules-v2-83f331d8b8:train:76 | [
"False",
"True"
] | [
1,
0
] | Is the statement true given the context? | conceptrules_v2 | direct | train | conceptrules-v2-83f331d8b8:train:76 | decision | c2ab5860bb728849 | mit, Custom (DPI) | commercial |
Passage A:
Pizza is in the vicinity of plate. Plate is in the vicinity of dishwasher. Weasel is not in the vicinity of your eye. Plate is used for put food on. Weasel is in the vicinity of cheese. Cheese is in the vicinity of pizza. Weasel is not in the vicinity of book. Lettuce is not in the vicinity of populous area.... | choice | conceptrules-v2-83f331d8b8:train:76:choice-paired-text-format | [
"False",
"True"
] | [
1,
0
] | Is the statement true given the context? | conceptrules_v2 | paired_text_format | train | conceptrules-v2-83f331d8b8:train:76 | choice-paired-text-format | c2ab5860bb728849 | mit, Custom (DPI) | commercial |
text_A: The game centers on battles between the player's army and enemy monsters or computer-controlled players.
text_B: The game centers on battles between the player's army and ally monsters or computer-controlled players. | choice | conj-nli-0f0ab95726:train:4523 | [
"entailment",
"neutral",
"contradiction"
] | [
0,
1,
0
] | Does text_A entail text_B, contradict it, or neither? | conj_nli | direct | train | conj-nli-0f0ab95726:train:4523 | decision | 2c6083aab99176b8 | unspecified | unspecified |
text_A: The game centers on battles between the player's army and enemy monsters or computer-controlled players.
text_B: The game centers on battles between the player's army and ally monsters or computer-controlled players. | choice | conj-nli-0f0ab95726:train:4523:choice-criteria-permutation | [
"neutral",
"entailment",
"contradiction"
] | [
1,
0,
0
] | Does text_A entail text_B, contradict it, or neither? | conj_nli | criteria_permutation | train | conj-nli-0f0ab95726:train:4523 | choice-criteria-permutation | 2c6083aab99176b8 | unspecified | unspecified |
Sentence: HELSINKI 1996-08-29
Target token at position 0: HELSINKI
Marked sentence: [TARGET: HELSINKI] 1996-08-29 | choice | conll2003-ner-tags-be686b5302:train:13656:token-0 | [
"outside any named entity",
"beginning of a person entity",
"inside a person entity",
"beginning of an organization entity",
"inside an organization entity",
"beginning of a location entity",
"inside a location entity",
"beginning of a miscellaneous entity",
"inside a miscellaneous entity"
] | [
0,
0,
0,
0,
0,
1,
0,
0,
0
] | Choose the criterion that best labels the target token. | conll2003/ner_tags | direct | train | conll2003-ner-tags-be686b5302:train:13656 | token-0 | babb6cea31e2d6bb | other, Academic Research Purposes Only (DPI), Request Form (DPI) | non-commercial |
Sentence: HELSINKI 1996-08-29
Target token at position 1: 1996-08-29
Marked sentence: HELSINKI [TARGET: 1996-08-29] | choice | conll2003-ner-tags-be686b5302:train:13656:token-1 | [
"outside any named entity",
"beginning of a person entity",
"inside a person entity",
"beginning of an organization entity",
"inside an organization entity",
"beginning of a location entity",
"inside a location entity",
"beginning of a miscellaneous entity",
"inside a miscellaneous entity"
] | [
1,
0,
0,
0,
0,
0,
0,
0,
0
] | Choose the criterion that best labels the target token. | conll2003/ner_tags | direct | train | conll2003-ner-tags-be686b5302:train:13656 | token-1 | babb6cea31e2d6bb | other, Academic Research Purposes Only (DPI), Request Form (DPI) | non-commercial |
Item A:
text_A: Upon the expiration or termination of this Agreement, or at the Disclosing Party's request at any time during the term of this Agreement, the Recipient and its Representatives shall promptly return to the Disclosing Party all copies, whether in written, electronic or other form or media, of the Disclosi... | choice | contract-nli-contractnli-a-seg-c5d5a7346a:train:pack-352007e244e5:label-B | [
"contradiction",
"entailment",
"neutral"
] | [
0,
0,
1
] | Each item answers: "Does text_A entail text_B, contradict it, or neither?"
Choose the criterion that best describes Item B. | contract-nli/contractnli_a/seg | packed_derived | train | contract-nli-contractnli-a-seg-c5d5a7346a:train:pack-352007e244e5 | label-B | 224f98514ed86bfe | cc-by-nc-sa-4.0 | non-commercial |
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