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 660
values | variant stringclasses 6
values | split stringclasses 1
value | group_id stringlengths 22 82 | question_id stringlengths 4 117 | license stringclasses 69
values | license_use stringclasses 3
values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
Passage A:
There is not a single painter walking in the city.
Passage B:
There is not a single person walking in the city. | choice | monli-e20b1da17a:train:694:choice-paired-text-format | [
"entailment",
"neutral"
] | [
0,
1
] | Does text_A entail text_B? | monli | paired_text_format | train | monli-e20b1da17a:train:694 | choice-paired-text-format | unspecified | unspecified |
text_A: a typhoon simoron is approaching japan.
text_B: a typhoon is approaching japan. | choice | monotonicity-entailment-5b266929a5:train:30 | [
"entailment",
"neutral"
] | [
1,
0
] | Does text_A entail text_B? | monotonicity-entailment | direct | train | monotonicity-entailment-5b266929a5:train:30 | decision | apache-2.0 | commercial |
text_A: a typhoon simoron is approaching japan.
text_B: a typhoon is approaching japan. | noul | monotonicity-entailment-5b266929a5:train:30:noul-label-verification | [] | [
1
] | Does text_A entail text_B? Is "entailment" the correct answer? | monotonicity-entailment | label_verification | train | monotonicity-entailment-5b266929a5:train:30 | noul-label-verification | apache-2.0 | commercial |
Steven has some plans with his friend Mandy for this weekend. Steven is not feeling like going, and wants to do something else. | choice | moral-stories-full-cab8d2d165:train:7544 | [
"Steven tells Mandy he'd like to do something else that weekend instead of the original plan.",
"Steven tells Mandy he's going to have to cancel on her."
] | [
1,
0
] | Choose the most appropriate answer from the supplied options. | moral_stories/full | direct | train | moral-stories-full-cab8d2d165:train:7544 | decision | mit, MIT License (DPI) | commercial |
Steven has some plans with his friend Mandy for this weekend. Steven is not feeling like going, and wants to do something else. | choice | moral-stories-full-cab8d2d165:train:7544:choice-instruction-paraphrase | [
"Steven tells Mandy he'd like to do something else that weekend instead of the original plan.",
"Steven tells Mandy he's going to have to cancel on her."
] | [
1,
0
] | Which supplied option best answers the question? | moral_stories/full | instruction_paraphrase | train | moral-stories-full-cab8d2d165:train:7544 | choice-instruction-paraphrase | mit, MIT License (DPI) | commercial |
text_A: These women are playing a beach volleyball game as part of the Summer Olympics in 2012 which took place in London. A member of the women's Austrian beach volleyball team attempts a spike against China at the 2012 Olympics. Three women in sports bikinis are playing volleyball on a sandy beach. This is a group of... | choice | mpe-864f124608:train:18 | [
"entailment",
"neutral",
"contradiction"
] | [
0,
1,
0
] | Does text_A entail text_B, contradict it, or neither? | mpe | direct | train | mpe-864f124608:train:18 | decision | unspecified | unspecified |
text_A: These women are playing a beach volleyball game as part of the Summer Olympics in 2012 which took place in London. A member of the women's Austrian beach volleyball team attempts a spike against China at the 2012 Olympics. Three women in sports bikinis are playing volleyball on a sandy beach. This is a group of... | choice | mpe-864f124608:train:18:choice-criteria-permutation | [
"neutral",
"contradiction",
"entailment"
] | [
1,
0,
0
] | Does text_A entail text_B, contradict it, or neither? | mpe | criteria_permutation | train | mpe-864f124608:train:18 | choice-criteria-permutation | unspecified | unspecified |
እኔ አላምንም! ኧረ ቅሌት! | choice | multilingual-AfriSenti-twitter-sentiment-amh-d94b71d898:train:63 | [
"negative",
"neutral",
"positive"
] | [
1,
0,
0
] | What sentiment does the text express? | multilingual/AfriSenti-twitter-sentiment/amh | direct | train | multilingual-AfriSenti-twitter-sentiment-amh-d94b71d898:train:63 | decision | cc-by-4.0 | commercial |
Item A:
@user كيفاش زعما ؟
Item B:
@user ممم ،منديتا كان لعب في البارصا واقيلا !
Item C:
👥:دارنا خرجو وخلاونى وحدى فى دار \n🧠: عقلى زعما مراهمش ديرين كاميرا مخيفة 😂
Item D:
@user 😂.... بزاف...... عندي ما قلعت مشماش ولوز | choice | multilingual-AfriSenti-twitter-sentiment-arq-46ae4933b2:train:pack-936b3aacccb7:label-A | [
"negative",
"neutral",
"positive"
] | [
0,
1,
0
] | Each item answers: "What sentiment does the text express?"
Choose the criterion that best describes Item A. | multilingual/AfriSenti-twitter-sentiment/arq | packed_derived | train | multilingual-AfriSenti-twitter-sentiment-arq-46ae4933b2:train:pack-936b3aacccb7 | label-A | cc-by-4.0 | commercial |
Item A:
@user كيفاش زعما ؟
Item B:
@user ممم ،منديتا كان لعب في البارصا واقيلا !
Item C:
👥:دارنا خرجو وخلاونى وحدى فى دار \n🧠: عقلى زعما مراهمش ديرين كاميرا مخيفة 😂
Item D:
@user 😂.... بزاف...... عندي ما قلعت مشماش ولوز | noul | multilingual-AfriSenti-twitter-sentiment-arq-46ae4933b2:train:pack-936b3aacccb7:same-A-B | [] | [
1
] | Each item answers: "What sentiment does the text express?"
Do Item A and Item B have the same label? Possible labels: "negative", "neutral", "positive". | multilingual/AfriSenti-twitter-sentiment/arq | packed_derived | train | multilingual-AfriSenti-twitter-sentiment-arq-46ae4933b2:train:pack-936b3aacccb7 | same-A-B | cc-by-4.0 | commercial |
Item A:
@user كيفاش زعما ؟
Item B:
@user ممم ،منديتا كان لعب في البارصا واقيلا !
Item C:
👥:دارنا خرجو وخلاونى وحدى فى دار \n🧠: عقلى زعما مراهمش ديرين كاميرا مخيفة 😂
Item D:
@user 😂.... بزاف...... عندي ما قلعت مشماش ولوز | noul | multilingual-AfriSenti-twitter-sentiment-arq-46ae4933b2:train:pack-936b3aacccb7:exists-0 | [] | [
0
] | Each item answers: "What sentiment does the text express?"
Does at least one item have the label "negative"? Possible labels: "negative", "neutral", "positive". | multilingual/AfriSenti-twitter-sentiment/arq | packed_derived | train | multilingual-AfriSenti-twitter-sentiment-arq-46ae4933b2:train:pack-936b3aacccb7 | exists-0 | cc-by-4.0 | commercial |
Item A:
@user كيفاش زعما ؟
Item B:
@user ممم ،منديتا كان لعب في البارصا واقيلا !
Item C:
👥:دارنا خرجو وخلاونى وحدى فى دار \n🧠: عقلى زعما مراهمش ديرين كاميرا مخيفة 😂
Item D:
@user 😂.... بزاف...... عندي ما قلعت مشماش ولوز | choice | multilingual-AfriSenti-twitter-sentiment-arq-46ae4933b2:train:pack-936b3aacccb7:most-common | [
"negative",
"neutral",
"positive"
] | [
0,
1,
0
] | Each item answers: "What sentiment does the text express?"
Which label is shared by the most items? | multilingual/AfriSenti-twitter-sentiment/arq | packed_derived | train | multilingual-AfriSenti-twitter-sentiment-arq-46ae4933b2:train:pack-936b3aacccb7 | most-common | cc-by-4.0 | commercial |
ماريانو راخوي : خاص المغرب واسبانيا يشرحو للرأي العام وجميع المتدخلين بوضوح تفاصيل الاتفاق اللي توصلو ليه, | score | multilingual-AfriSenti-twitter-sentiment-ary-4c2d98e466:train:4 | [
"negative",
"neutral",
"positive"
] | [
0,
1,
0
] | What sentiment does the text express? | multilingual/AfriSenti-twitter-sentiment/ary | direct | train | multilingual-AfriSenti-twitter-sentiment-ary-4c2d98e466:train:4 | decision | cc-by-4.0 | commercial |
@user @user Ogah sambo idan ankarba kudin fansan su salma kar a manta dani a Ajiye min nawa kason Ahha 😉 | choice | multilingual-AfriSenti-twitter-sentiment-hau-f8463d38f0:train:8890 | [
"negative",
"neutral",
"positive"
] | [
0,
1,
0
] | What sentiment does the text express? | multilingual/AfriSenti-twitter-sentiment/hau | direct | train | multilingual-AfriSenti-twitter-sentiment-hau-f8463d38f0:train:8890 | decision | cc-by-4.0 | commercial |
@user @user Ogah sambo idan ankarba kudin fansan su salma kar a manta dani a Ajiye min nawa kason Ahha 😉 | noul | multilingual-AfriSenti-twitter-sentiment-hau-f8463d38f0:train:8890:noul-label-verification | [] | [
1
] | What sentiment does the text express? Is "neutral" the correct answer? | multilingual/AfriSenti-twitter-sentiment/hau | label_verification | train | multilingual-AfriSenti-twitter-sentiment-hau-f8463d38f0:train:8890 | noul-label-verification | cc-by-4.0 | commercial |
@user @user Lmao. O dị egwu | score | multilingual-AfriSenti-twitter-sentiment-ibo-641afcdf5a:train:553 | [
"negative",
"neutral",
"positive"
] | [
1,
0,
0
] | What sentiment does the text express? | multilingual/AfriSenti-twitter-sentiment/ibo | direct | train | multilingual-AfriSenti-twitter-sentiment-ibo-641afcdf5a:train:553 | decision | cc-by-4.0 | commercial |
Arko ngo Kabera mu gitondo araza kuba afite #ikinyafu😂😂😂 #RwOT | choice | multilingual-AfriSenti-twitter-sentiment-kin-70468b3d83:train:615 | [
"negative",
"neutral",
"positive"
] | [
1,
0,
0
] | What sentiment does the text express? | multilingual/AfriSenti-twitter-sentiment/kin | direct | train | multilingual-AfriSenti-twitter-sentiment-kin-70468b3d83:train:615 | decision | cc-by-4.0 | commercial |
Arko ngo Kabera mu gitondo araza kuba afite #ikinyafu😂😂😂 #RwOT | choice | multilingual-AfriSenti-twitter-sentiment-kin-70468b3d83:train:615:choice-criteria-permutation | [
"negative",
"positive",
"neutral"
] | [
1,
0,
0
] | What sentiment does the text express? | multilingual/AfriSenti-twitter-sentiment/kin | criteria_permutation | train | multilingual-AfriSenti-twitter-sentiment-kin-70468b3d83:train:615 | choice-criteria-permutation | cc-by-4.0 | commercial |
na madison born for vardy ni why are they both missing | score | multilingual-AfriSenti-twitter-sentiment-pcm-56aea1f7d1:train:1312 | [
"negative",
"neutral",
"positive"
] | [
1,
0,
0
] | What sentiment does the text express? | multilingual/AfriSenti-twitter-sentiment/pcm | direct | train | multilingual-AfriSenti-twitter-sentiment-pcm-56aea1f7d1:train:1312 | decision | cc-by-4.0 | commercial |
@user @user @user Ele É Fiel para todo o sempre. #TheLatterRain | choice | multilingual-AfriSenti-twitter-sentiment-por-0776ecefcc:train:2836 | [
"negative",
"neutral",
"positive"
] | [
0,
0,
1
] | What sentiment does the text express? | multilingual/AfriSenti-twitter-sentiment/por | direct | train | multilingual-AfriSenti-twitter-sentiment-por-0776ecefcc:train:2836 | decision | cc-by-4.0 | commercial |
@user @user @user Ele É Fiel para todo o sempre. #TheLatterRain | choice | multilingual-AfriSenti-twitter-sentiment-por-0776ecefcc:train:2836:choice-criteria-permutation | [
"neutral",
"positive",
"negative"
] | [
0,
1,
0
] | What sentiment does the text express? | multilingual/AfriSenti-twitter-sentiment/por | criteria_permutation | train | multilingual-AfriSenti-twitter-sentiment-por-0776ecefcc:train:2836 | choice-criteria-permutation | cc-by-4.0 | commercial |
Makamu wa Rais Samia Suluhu Hassan aipongeza sekta ya Utalii nchini kwa mahusiano mazuri Duniani kutokana na maendeleo ya teknolojia na upatikanaji taarifaSoma Zaidi gtgt | choice | multilingual-AfriSenti-twitter-sentiment-swa-13d02bc40c:train:1385 | [
"negative",
"neutral",
"positive"
] | [
0,
0,
1
] | What sentiment does the text express? | multilingual/AfriSenti-twitter-sentiment/swa | direct | train | multilingual-AfriSenti-twitter-sentiment-swa-13d02bc40c:train:1385 | decision | cc-by-4.0 | commercial |
Item A:
Ih piki sixti i dii nirmil. Ftsekeee. Maluuuuco
Item B:
Himina muyivi WA botija 😂😂😂😂😂 https://t.co/mMuRG79ePa
Item C:
@user @user @user #HHW boti unga vileli Xikwembu xita hlayisa sesi vana mbilo ya sathana | choice | multilingual-AfriSenti-twitter-sentiment-tso-99f751c444:train:pack-d46fac07724c:label-A | [
"negative",
"neutral",
"positive"
] | [
1,
0,
0
] | Each item answers: "What sentiment does the text express?"
Choose the criterion that best describes Item A. | multilingual/AfriSenti-twitter-sentiment/tso | packed_derived | train | multilingual-AfriSenti-twitter-sentiment-tso-99f751c444:train:pack-d46fac07724c | label-A | cc-by-4.0 | commercial |
Item A:
Ih piki sixti i dii nirmil. Ftsekeee. Maluuuuco
Item B:
Himina muyivi WA botija 😂😂😂😂😂 https://t.co/mMuRG79ePa
Item C:
@user @user @user #HHW boti unga vileli Xikwembu xita hlayisa sesi vana mbilo ya sathana | noul | multilingual-AfriSenti-twitter-sentiment-tso-99f751c444:train:pack-d46fac07724c:same-B-C | [] | [
1
] | Each item answers: "What sentiment does the text express?"
Do Item B and Item C have the same label? Possible labels: "negative", "neutral", "positive". | multilingual/AfriSenti-twitter-sentiment/tso | packed_derived | train | multilingual-AfriSenti-twitter-sentiment-tso-99f751c444:train:pack-d46fac07724c | same-B-C | cc-by-4.0 | commercial |
Item A:
Ih piki sixti i dii nirmil. Ftsekeee. Maluuuuco
Item B:
Himina muyivi WA botija 😂😂😂😂😂 https://t.co/mMuRG79ePa
Item C:
@user @user @user #HHW boti unga vileli Xikwembu xita hlayisa sesi vana mbilo ya sathana | noul | multilingual-AfriSenti-twitter-sentiment-tso-99f751c444:train:pack-d46fac07724c:exists-2 | [] | [
0
] | Each item answers: "What sentiment does the text express?"
Does at least one item have the label "positive"? Possible labels: "negative", "neutral", "positive". | multilingual/AfriSenti-twitter-sentiment/tso | packed_derived | train | multilingual-AfriSenti-twitter-sentiment-tso-99f751c444:train:pack-d46fac07724c | exists-2 | cc-by-4.0 | commercial |
Item A:
Ih piki sixti i dii nirmil. Ftsekeee. Maluuuuco
Item B:
Himina muyivi WA botija 😂😂😂😂😂 https://t.co/mMuRG79ePa
Item C:
@user @user @user #HHW boti unga vileli Xikwembu xita hlayisa sesi vana mbilo ya sathana | score | multilingual-AfriSenti-twitter-sentiment-tso-99f751c444:train:pack-d46fac07724c:count-1 | [
"0",
"1",
"2",
"3"
] | [
1,
0,
0,
0
] | Each item answers: "What sentiment does the text express?"
How many items have the label "neutral"? Possible labels: "negative", "neutral", "positive". | multilingual/AfriSenti-twitter-sentiment/tso | packed_derived | train | multilingual-AfriSenti-twitter-sentiment-tso-99f751c444:train:pack-d46fac07724c | count-1 | cc-by-4.0 | commercial |
gyae gyae na menk bi da | choice | multilingual-AfriSenti-twitter-sentiment-twi-32a4496e5c:train:6 | [
"negative",
"neutral",
"positive"
] | [
1,
0,
0
] | What sentiment does the text express? | multilingual/AfriSenti-twitter-sentiment/twi | direct | train | multilingual-AfriSenti-twitter-sentiment-twi-32a4496e5c:train:6 | decision | cc-by-4.0 | commercial |
RT @user: """"""""@user: @user beeni o, ki lo n mu inu wa dun gan lorileede yii?ajoyo ki la n se?"""""""" #Centenary | choice | multilingual-AfriSenti-twitter-sentiment-yor-f38f2bd16c:train:6438 | [
"negative",
"neutral",
"positive"
] | [
0,
0,
1
] | What sentiment does the text express? | multilingual/AfriSenti-twitter-sentiment/yor | direct | train | multilingual-AfriSenti-twitter-sentiment-yor-f38f2bd16c:train:6438 | decision | cc-by-4.0 | commercial |
RT @user: """"""""@user: @user beeni o, ki lo n mu inu wa dun gan lorileede yii?ajoyo ki la n se?"""""""" #Centenary | noul | multilingual-AfriSenti-twitter-sentiment-yor-f38f2bd16c:train:6438:noul-label-verification | [] | [
1
] | What sentiment does the text express? Is "positive" the correct answer? | multilingual/AfriSenti-twitter-sentiment/yor | label_verification | train | multilingual-AfriSenti-twitter-sentiment-yor-f38f2bd16c:train:6438 | noul-label-verification | cc-by-4.0 | commercial |
@user @user @user انت تحجي على السعودين و تقصد بول البعير السعودين مشغين ٢ مليون يماني حقير مثل… @user | choice | multilingual-MLMA-hate-speech-ea81e6680f:train:12374 | [
"abusive",
"disrespectful",
"fearful",
"hateful",
"normal",
"offensive"
] | [
0,
0,
0,
1,
0,
0
] | Choose the criterion that best describes the state. | multilingual/MLMA_hate_speech | direct | train | multilingual-MLMA-hate-speech-ea81e6680f:train:12374 | decision | mit | commercial |
@user @user @user انت تحجي على السعودين و تقصد بول البعير السعودين مشغين ٢ مليون يماني حقير مثل… @user | choice | multilingual-MLMA-hate-speech-ea81e6680f:train:12374:choice-instruction-paraphrase | [
"abusive",
"disrespectful",
"fearful",
"hateful",
"normal",
"offensive"
] | [
0,
0,
0,
1,
0,
0
] | Choose the most appropriate category for the state. | multilingual/MLMA_hate_speech | instruction_paraphrase | train | multilingual-MLMA-hate-speech-ea81e6680f:train:12374 | choice-instruction-paraphrase | mit | commercial |
Item A:
Kwetiauw goreng ngon teh tarek jeuet keu pilehan lon pajoh disinoe, beuthat pih na padum boh nyang pesan mi yamin, droeneuh jeuet neuci bu gurengjih
Item B:
Susujih segar ngon sayur nyang bereh, nyum kuah mangat ngon peulayanan nyang ramah that. | choice | multilingual-NusaX-senti-ace-819b9f73f4:train:pack-d9f422f25e60:label-A | [
"negative",
"neutral",
"positive"
] | [
0,
1,
0
] | Each item answers: "What sentiment does the text express?"
Choose the criterion that best describes Item A. | multilingual/NusaX-senti/ace | packed_derived | train | multilingual-NusaX-senti-ace-819b9f73f4:train:pack-d9f422f25e60 | label-A | cc-by-sa-4.0 | commercial |
Item A:
Kwetiauw goreng ngon teh tarek jeuet keu pilehan lon pajoh disinoe, beuthat pih na padum boh nyang pesan mi yamin, droeneuh jeuet neuci bu gurengjih
Item B:
Susujih segar ngon sayur nyang bereh, nyum kuah mangat ngon peulayanan nyang ramah that. | noul | multilingual-NusaX-senti-ace-819b9f73f4:train:pack-d9f422f25e60:same-A-B | [] | [
0
] | Each item answers: "What sentiment does the text express?"
Do Item A and Item B have the same label? Possible labels: "negative", "neutral", "positive". | multilingual/NusaX-senti/ace | packed_derived | train | multilingual-NusaX-senti-ace-819b9f73f4:train:pack-d9f422f25e60 | same-A-B | cc-by-sa-4.0 | commercial |
Item A:
Kwetiauw goreng ngon teh tarek jeuet keu pilehan lon pajoh disinoe, beuthat pih na padum boh nyang pesan mi yamin, droeneuh jeuet neuci bu gurengjih
Item B:
Susujih segar ngon sayur nyang bereh, nyum kuah mangat ngon peulayanan nyang ramah that. | noul | multilingual-NusaX-senti-ace-819b9f73f4:train:pack-d9f422f25e60:exists-1 | [] | [
1
] | Each item answers: "What sentiment does the text express?"
Does at least one item have the label "neutral"? Possible labels: "negative", "neutral", "positive". | multilingual/NusaX-senti/ace | packed_derived | train | multilingual-NusaX-senti-ace-819b9f73f4:train:pack-d9f422f25e60 | exists-1 | cc-by-sa-4.0 | commercial |
Item A:
Kwetiauw goreng ngon teh tarek jeuet keu pilehan lon pajoh disinoe, beuthat pih na padum boh nyang pesan mi yamin, droeneuh jeuet neuci bu gurengjih
Item B:
Susujih segar ngon sayur nyang bereh, nyum kuah mangat ngon peulayanan nyang ramah that. | score | multilingual-NusaX-senti-ace-819b9f73f4:train:pack-d9f422f25e60:count-1 | [
"0",
"1",
"2"
] | [
0,
1,
0
] | Each item answers: "What sentiment does the text express?"
How many items have the label "neutral"? Possible labels: "negative", "neutral", "positive". | multilingual/NusaX-senti/ace | packed_derived | train | multilingual-NusaX-senti-ace-819b9f73f4:train:pack-d9f422f25e60 | count-1 | cc-by-sa-4.0 | commercial |
Ajenganne lumayan, tiang mesen spring roll agak melengis, ajin ajengan utamanyane cukup maal. Bangunanne unik nanging genahne agak ten becik nike mawinan genahne setata cingakin sepi. Dugase mesen sepatutne ngorahang nyekenang , krana sane katiba ring tiang, tiang mesen 2 sakewala katrima 3 ajengan. Pelayan ramah pesa... | score | multilingual-NusaX-senti-ban-5642fa62a9:train:328 | [
"negative",
"neutral",
"positive"
] | [
1,
0,
0
] | What sentiment does the text express? | multilingual/NusaX-senti/ban | direct | train | multilingual-NusaX-senti-ban-5642fa62a9:train:328 | decision | cc-by-sa-4.0 | commercial |
Item A:
Parmanganan naadong panatapan na uli nang pe ikkon didalani dohot dalan na pattik. Alai targar do dohot inganan dohot dai na oke.
Item B:
Tu aha ma marsingkola ho timbo alai molo manghatai sehera biang na mangorong. | choice | multilingual-NusaX-senti-bbc-4c146511ba:train:pack-f81975df037e:label-B | [
"negative",
"neutral",
"positive"
] | [
1,
0,
0
] | Each item answers: "What sentiment does the text express?"
Choose the criterion that best describes Item B. | multilingual/NusaX-senti/bbc | packed_derived | train | multilingual-NusaX-senti-bbc-4c146511ba:train:pack-f81975df037e | label-B | cc-by-sa-4.0 | commercial |
Item A:
Parmanganan naadong panatapan na uli nang pe ikkon didalani dohot dalan na pattik. Alai targar do dohot inganan dohot dai na oke.
Item B:
Tu aha ma marsingkola ho timbo alai molo manghatai sehera biang na mangorong. | noul | multilingual-NusaX-senti-bbc-4c146511ba:train:pack-f81975df037e:same-A-B | [] | [
0
] | Each item answers: "What sentiment does the text express?"
Do Item A and Item B have the same label? Possible labels: "negative", "neutral", "positive". | multilingual/NusaX-senti/bbc | packed_derived | train | multilingual-NusaX-senti-bbc-4c146511ba:train:pack-f81975df037e | same-A-B | cc-by-sa-4.0 | commercial |
Item A:
Parmanganan naadong panatapan na uli nang pe ikkon didalani dohot dalan na pattik. Alai targar do dohot inganan dohot dai na oke.
Item B:
Tu aha ma marsingkola ho timbo alai molo manghatai sehera biang na mangorong. | noul | multilingual-NusaX-senti-bbc-4c146511ba:train:pack-f81975df037e:exists-1 | [] | [
0
] | Each item answers: "What sentiment does the text express?"
Does at least one item have the label "neutral"? Possible labels: "negative", "neutral", "positive". | multilingual/NusaX-senti/bbc | packed_derived | train | multilingual-NusaX-senti-bbc-4c146511ba:train:pack-f81975df037e | exists-1 | cc-by-sa-4.0 | commercial |
Item A:
Parmanganan naadong panatapan na uli nang pe ikkon didalani dohot dalan na pattik. Alai targar do dohot inganan dohot dai na oke.
Item B:
Tu aha ma marsingkola ho timbo alai molo manghatai sehera biang na mangorong. | score | multilingual-NusaX-senti-bbc-4c146511ba:train:pack-f81975df037e:count-1 | [
"0",
"1",
"2"
] | [
1,
0,
0
] | Each item answers: "What sentiment does the text express?"
How many items have the label "neutral"? Possible labels: "negative", "neutral", "positive". | multilingual/NusaX-senti/bbc | packed_derived | train | multilingual-NusaX-senti-bbc-4c146511ba:train:pack-f81975df037e | count-1 | cc-by-sa-4.0 | commercial |
Rasai cicilan 0% sampai 12 bulan gasan mamasan tikit pasawat air asia lawan kartu kridit bni! | score | multilingual-NusaX-senti-bjn-662106e9cb:train:0 | [
"negative",
"neutral",
"positive"
] | [
0,
1,
0
] | What sentiment does the text express? | multilingual/NusaX-senti/bjn | direct | train | multilingual-NusaX-senti-bjn-662106e9cb:train:0 | decision | cc-by-sa-4.0 | commercial |
Item A:
Iye anroangnge massenge' ladde' ri pada-padanna mahasiswa e. Nasaba saliwengenna malunra' ellinna aga maka to sempo waseng ko iya'. Makanja ladde.
Item B:
Mabbalu manu' tunu taliwang tapi manu' iya napatale'e pada kare' e sibawa de' na mappakario, sibawa rasana makemme, sambala' na assala engka. Pole iya manen... | choice | multilingual-NusaX-senti-bug-5bd053a293:train:pack-ab7be37595dd:label-C | [
"negative",
"neutral",
"positive"
] | [
1,
0,
0
] | Each item answers: "What sentiment does the text express?"
Choose the criterion that best describes Item C. | multilingual/NusaX-senti/bug | packed_derived | train | multilingual-NusaX-senti-bug-5bd053a293:train:pack-ab7be37595dd | label-C | cc-by-sa-4.0 | commercial |
Item A:
Iye anroangnge massenge' ladde' ri pada-padanna mahasiswa e. Nasaba saliwengenna malunra' ellinna aga maka to sempo waseng ko iya'. Makanja ladde.
Item B:
Mabbalu manu' tunu taliwang tapi manu' iya napatale'e pada kare' e sibawa de' na mappakario, sibawa rasana makemme, sambala' na assala engka. Pole iya manen... | noul | multilingual-NusaX-senti-bug-5bd053a293:train:pack-ab7be37595dd:same-A-B | [] | [
0
] | Each item answers: "What sentiment does the text express?"
Do Item A and Item B have the same label? Possible labels: "negative", "neutral", "positive". | multilingual/NusaX-senti/bug | packed_derived | train | multilingual-NusaX-senti-bug-5bd053a293:train:pack-ab7be37595dd | same-A-B | cc-by-sa-4.0 | commercial |
Item A:
Iye anroangnge massenge' ladde' ri pada-padanna mahasiswa e. Nasaba saliwengenna malunra' ellinna aga maka to sempo waseng ko iya'. Makanja ladde.
Item B:
Mabbalu manu' tunu taliwang tapi manu' iya napatale'e pada kare' e sibawa de' na mappakario, sibawa rasana makemme, sambala' na assala engka. Pole iya manen... | noul | multilingual-NusaX-senti-bug-5bd053a293:train:pack-ab7be37595dd:exists-1 | [] | [
0
] | Each item answers: "What sentiment does the text express?"
Does at least one item have the label "neutral"? Possible labels: "negative", "neutral", "positive". | multilingual/NusaX-senti/bug | packed_derived | train | multilingual-NusaX-senti-bug-5bd053a293:train:pack-ab7be37595dd | exists-1 | cc-by-sa-4.0 | commercial |
Item A:
Iye anroangnge massenge' ladde' ri pada-padanna mahasiswa e. Nasaba saliwengenna malunra' ellinna aga maka to sempo waseng ko iya'. Makanja ladde.
Item B:
Mabbalu manu' tunu taliwang tapi manu' iya napatale'e pada kare' e sibawa de' na mappakario, sibawa rasana makemme, sambala' na assala engka. Pole iya manen... | score | multilingual-NusaX-senti-bug-5bd053a293:train:pack-ab7be37595dd:count-0 | [
"0",
"1",
"2",
"3"
] | [
0,
0,
1,
0
] | Each item answers: "What sentiment does the text express?"
How many items have the label "negative"? Possible labels: "negative", "neutral", "positive". | multilingual/NusaX-senti/bug | packed_derived | train | multilingual-NusaX-senti-bug-5bd053a293:train:pack-ab7be37595dd | count-0 | cc-by-sa-4.0 | commercial |
Indonesian needs a visionary leader, not an entertainer | score | multilingual-NusaX-senti-eng-c54ab2d977:train:376 | [
"negative",
"neutral",
"positive"
] | [
0,
1,
0
] | What sentiment does the text express? | multilingual/NusaX-senti/eng | direct | train | multilingual-NusaX-senti-eng-c54ab2d977:train:376 | decision | cc-by-sa-4.0 | commercial |
Hari ini mau belanja di toko itu supaya bisa dapatkan peralatan masak keren plus kesempatan liburan ke Belanda. | choice | multilingual-NusaX-senti-ind-99da6b456a:train:333 | [
"negative",
"neutral",
"positive"
] | [
0,
0,
1
] | What sentiment does the text express? | multilingual/NusaX-senti/ind | direct | train | multilingual-NusaX-senti-ind-99da6b456a:train:333 | decision | cc-by-sa-4.0 | commercial |
Hari ini mau belanja di toko itu supaya bisa dapatkan peralatan masak keren plus kesempatan liburan ke Belanda. | noul | multilingual-NusaX-senti-ind-99da6b456a:train:333:noul-label-verification | [] | [
1
] | What sentiment does the text express? Is "positive" the correct answer? | multilingual/NusaX-senti/ind | label_verification | train | multilingual-NusaX-senti-ind-99da6b456a:train:333 | noul-label-verification | cc-by-sa-4.0 | commercial |
Handphoneku lenovo, kecemplung ing got pas 2 minggu nembe tuku, gigal ing aspal pas ngebut numpak motor nganti isie nang ndi-nang ndi, teleponku tetep tahan, mantep memang lenovo | choice | multilingual-NusaX-senti-jav-79f48b18f6:train:340 | [
"negative",
"neutral",
"positive"
] | [
0,
0,
1
] | What sentiment does the text express? | multilingual/NusaX-senti/jav | direct | train | multilingual-NusaX-senti-jav-79f48b18f6:train:340 | decision | cc-by-sa-4.0 | commercial |
Engkok sataretanan nyare kennengngan ngakan mare ningghu. Engkok bik taretan bhusen ngakan e resto / kafe e mal. Mutemmu etangale resto e kanan jelen. La abit engkok bik taretan tak ngakan kari. Nyepperlah engkok bik taretan ka resto se tamasok kenik pera' 9 mija. Kanyataanna nyaman kennengngan ben kakananna. | choice | multilingual-NusaX-senti-mad-8b2b7d0f6c:train:29 | [
"negative",
"neutral",
"positive"
] | [
0,
0,
1
] | What sentiment does the text express? | multilingual/NusaX-senti/mad | direct | train | multilingual-NusaX-senti-mad-8b2b7d0f6c:train:29 | decision | cc-by-sa-4.0 | commercial |
Engkok sataretanan nyare kennengngan ngakan mare ningghu. Engkok bik taretan bhusen ngakan e resto / kafe e mal. Mutemmu etangale resto e kanan jelen. La abit engkok bik taretan tak ngakan kari. Nyepperlah engkok bik taretan ka resto se tamasok kenik pera' 9 mija. Kanyataanna nyaman kennengngan ben kakananna. | choice | multilingual-NusaX-senti-mad-8b2b7d0f6c:train:29:choice-criteria-permutation | [
"positive",
"negative",
"neutral"
] | [
1,
0,
0
] | What sentiment does the text express? | multilingual/NusaX-senti/mad | criteria_permutation | train | multilingual-NusaX-senti-mad-8b2b7d0f6c:train:29 | choice-criteria-permutation | cc-by-sa-4.0 | commercial |
Nikmati cicilan 0% sampai 12 bulan untuak pamasanan tiket pisawat air asia jo kartu kredit bni! | score | multilingual-NusaX-senti-min-7cbd2ff259:train:0 | [
"negative",
"neutral",
"positive"
] | [
0,
1,
0
] | What sentiment does the text express? | multilingual/NusaX-senti/min | direct | train | multilingual-NusaX-senti-min-7cbd2ff259:train:0 | decision | cc-by-sa-4.0 | commercial |
Amun dumah kan restoran tuh pas bujur halemei dengan hamalem, mimbit pasangan mangat tau mengkeme kamangat kuman hamalem ji romantis dengan tempayah ji mias kehalap ah | choice | multilingual-NusaX-senti-nij-4190e2353c:train:13 | [
"negative",
"neutral",
"positive"
] | [
0,
0,
1
] | What sentiment does the text express? | multilingual/NusaX-senti/nij | direct | train | multilingual-NusaX-senti-nij-4190e2353c:train:13 | decision | cc-by-sa-4.0 | commercial |
Amun dumah kan restoran tuh pas bujur halemei dengan hamalem, mimbit pasangan mangat tau mengkeme kamangat kuman hamalem ji romantis dengan tempayah ji mias kehalap ah | choice | multilingual-NusaX-senti-nij-4190e2353c:train:13:choice-criteria-permutation | [
"positive",
"neutral",
"negative"
] | [
1,
0,
0
] | What sentiment does the text express? | multilingual/NusaX-senti/nij | criteria_permutation | train | multilingual-NusaX-senti-nij-4190e2353c:train:13 | choice-criteria-permutation | cc-by-sa-4.0 | commercial |
Ibu kantos ngadamel di grab indonesia | score | multilingual-NusaX-senti-sun-51ed171e66:train:2 | [
"negative",
"neutral",
"positive"
] | [
0,
1,
0
] | What sentiment does the text express? | multilingual/NusaX-senti/sun | direct | train | multilingual-NusaX-senti-sun-51ed171e66:train:2 | decision | cc-by-sa-4.0 | commercial |
一般般，希望解决的问题没解决几个，相当于一本辅食烹饪书。 | choice | multilingual-amazon-reviews-multi-all-languages-2dc9b25f8d:train:1344 | [
"1 star",
"2 stars",
"3 stars",
"4 stars",
"5 stars"
] | [
0,
0,
1,
0,
0
] | How many stars does the review give? | multilingual/amazon_reviews_multi/all_languages | direct | train | multilingual-amazon-reviews-multi-all-languages-2dc9b25f8d:train:1344 | decision | other | unspecified |
一般般，希望解决的问题没解决几个，相当于一本辅食烹饪书。 | noul | multilingual-amazon-reviews-multi-all-languages-2dc9b25f8d:train:1344:noul-label-verification | [] | [
1
] | How many stars does the review give? Is "3 stars" the correct answer? | multilingual/amazon_reviews_multi/all_languages | label_verification | train | multilingual-amazon-reviews-multi-all-languages-2dc9b25f8d:train:1344 | noul-label-verification | other | unspecified |
text_A: Ramonar mayamp jawsañaxanawakunalaykutix mä jiskt'aw utjitana …walikiwa…tukt'ayayita.. mä jisk't'aw utjitana kuntix lurkan ukata.
text_B: Ramonarux jiskt'añ munayatxa. | choice | multilingual-americas-nli-all-languages-dd166da2c2:train:1033 | [
"entailment",
"neutral",
"contradiction"
] | [
1,
0,
0
] | Does text_A entail text_B, contradict it, or neither? | multilingual/americas_nli/all_languages | direct | train | multilingual-americas-nli-all-languages-dd166da2c2:train:1033 | decision | cc-by-sa-4.0 | commercial |
Passage A:
Ramonar mayamp jawsañaxanawakunalaykutix mä jiskt'aw utjitana …walikiwa…tukt'ayayita.. mä jisk't'aw utjitana kuntix lurkan ukata.
Passage B:
Ramonarux jiskt'añ munayatxa. | choice | multilingual-americas-nli-all-languages-dd166da2c2:train:1033:choice-paired-text-format | [
"entailment",
"neutral",
"contradiction"
] | [
1,
0,
0
] | Does text_A entail text_B, contradict it, or neither? | multilingual/americas_nli/all_languages | paired_text_format | train | multilingual-americas-nli-all-languages-dd166da2c2:train:1033 | choice-paired-text-format | cc-by-sa-4.0 | commercial |
text_A: 花呗可以分期两次
text_B: 花呗分期几个月可以分一次 | choice | multilingual-clue-afqmc-6a165da840:train:20438 | [
"different meaning",
"same meaning"
] | [
1,
0
] | Do text_A and text_B mean the same thing? | multilingual/clue/afqmc | direct | train | multilingual-clue-afqmc-6a165da840:train:20438 | decision | unspecified | unspecified |
text_A: 花呗可以分期两次
text_B: 花呗分期几个月可以分一次 | noul | multilingual-clue-afqmc-6a165da840:train:20438:noul-label-verification | [] | [
0
] | Do text_A and text_B mean the same thing? Is "same meaning" the correct answer? | multilingual/clue/afqmc | label_verification | train | multilingual-clue-afqmc-6a165da840:train:20438 | noul-label-verification | unspecified | unspecified |
text_A: 花呗可以分期两次
text_B: 花呗分期几个月可以分一次 | choice | multilingual-clue-afqmc-6a165da840:train:20438:choice-criteria-permutation | [
"same meaning",
"different meaning"
] | [
0,
1
] | Do text_A and text_B mean the same thing? | multilingual/clue/afqmc | criteria_permutation | train | multilingual-clue-afqmc-6a165da840:train:20438 | choice-criteria-permutation | unspecified | unspecified |
text_A: 我们知道一个事情的事实,它是永远可以调查下去的,对吗
text_B: 它只能暂时被调查 | choice | multilingual-clue-ocnli-970cc11880:train:14413 | [
"neutral",
"entailment",
"contradiction"
] | [
0,
0,
1
] | Does text_A entail text_B, contradict it, or neither? | multilingual/clue/ocnli | direct | train | multilingual-clue-ocnli-970cc11880:train:14413 | decision | unspecified | unspecified |
First text:
我们知道一个事情的事实,它是永远可以调查下去的,对吗
Second text:
它只能暂时被调查 | choice | multilingual-clue-ocnli-970cc11880:train:14413:choice-paired-text-format | [
"neutral",
"entailment",
"contradiction"
] | [
0,
0,
1
] | Does text_A entail text_B, contradict it, or neither? | multilingual/clue/ocnli | paired_text_format | train | multilingual-clue-ocnli-970cc11880:train:14413 | choice-paired-text-format | unspecified | unspecified |
Item A:
本想托关系多要些拆迁补偿款，没想到欠了人情反而……
Item B:
中国最贵的寺庙：价值28亿，开发商：拆不起
Item C:
一支股票卖盘一直挂豹子单，有何用意？
Item D:
中石油2017年负债超万亿元 乐视网等15家公司已资不抵债 | choice | multilingual-clue-tnews-600d6c4459:train:pack-edf634c1ffe8:label-C | [
"story",
"culture",
"entertainment",
"sports",
"finance",
"real estate",
"cars",
"education",
"technology",
"military",
"travel",
"world",
"stocks",
"agriculture",
"games"
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0
] | Choose the criterion that best describes Item C. | multilingual/clue/tnews | packed_derived | train | multilingual-clue-tnews-600d6c4459:train:pack-edf634c1ffe8 | label-C | unspecified | unspecified |
Item A:
本想托关系多要些拆迁补偿款，没想到欠了人情反而……
Item B:
中国最贵的寺庙：价值28亿，开发商：拆不起
Item C:
一支股票卖盘一直挂豹子单，有何用意？
Item D:
中石油2017年负债超万亿元 乐视网等15家公司已资不抵债 | noul | multilingual-clue-tnews-600d6c4459:train:pack-edf634c1ffe8:in-C-0.2.3.4.5.7.8.9.10.11.12.13 | [] | [
1
] | Is the label of Item C one of "story", "entertainment", "sports", "finance", "real estate", "education", "technology", "military", "travel", "world", "stocks", "agriculture"? Possible labels: "story", "culture", "entertainment", "sports", "finance", "real estate", "cars", "education", "technology", "military", "travel"... | multilingual/clue/tnews | packed_derived | train | multilingual-clue-tnews-600d6c4459:train:pack-edf634c1ffe8 | in-C-0.2.3.4.5.7.8.9.10.11.12.13 | unspecified | unspecified |
Item A:
本想托关系多要些拆迁补偿款，没想到欠了人情反而……
Item B:
中国最贵的寺庙：价值28亿，开发商：拆不起
Item C:
一支股票卖盘一直挂豹子单，有何用意？
Item D:
中石油2017年负债超万亿元 乐视网等15家公司已资不抵债 | noul | multilingual-clue-tnews-600d6c4459:train:pack-edf634c1ffe8:exists-4 | [] | [
0
] | Does at least one item have the label "finance"? Possible labels: "story", "culture", "entertainment", "sports", "finance", "real estate", "cars", "education", "technology", "military", "travel", "world", "stocks", "agriculture", "games". | multilingual/clue/tnews | packed_derived | train | multilingual-clue-tnews-600d6c4459:train:pack-edf634c1ffe8 | exists-4 | unspecified | unspecified |
Item A:
本想托关系多要些拆迁补偿款，没想到欠了人情反而……
Item B:
中国最贵的寺庙：价值28亿，开发商：拆不起
Item C:
一支股票卖盘一直挂豹子单，有何用意？
Item D:
中石油2017年负债超万亿元 乐视网等15家公司已资不抵债 | score | multilingual-clue-tnews-600d6c4459:train:pack-edf634c1ffe8:count-0 | [
"0",
"1",
"2",
"3",
"4"
] | [
1,
0,
0,
0,
0
] | How many items have the label "story"? Possible labels: "story", "culture", "entertainment", "sports", "finance", "real estate", "cars", "education", "technology", "military", "travel", "world", "stocks", "agriculture", "games". | multilingual/clue/tnews | packed_derived | train | multilingual-clue-tnews-600d6c4459:train:pack-edf634c1ffe8 | count-0 | unspecified | unspecified |
text_A: Die verwirrende Zahl von Spendenbegehren kann einen schnell verzweifeln lassen .
text_B: wichtig ist vor allem , dass man hilft . | choice | multilingual-disrpt-deu-rst-pcc-rels-3069bea10e:train:1933 | [
"antithesis",
"background",
"cause",
"circumstance",
"concession",
"condition",
"conjunction",
"contrast",
"disjunction",
"e-elaboration",
"elaboration",
"evaluation-n",
"evaluation-s",
"evidence",
"interpretation",
"joint",
"list",
"means",
"preparation",
"purpose",
"reason"... | [
1,
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
] | Which discourse relation links unit text_B to unit text_A? | multilingual/disrpt/deu.rst.pcc.rels | direct | train | multilingual-disrpt-deu-rst-pcc-rels-3069bea10e:train:1933 | decision | apache-2.0 | commercial |
text_A: Die verwirrende Zahl von Spendenbegehren kann einen schnell verzweifeln lassen .
text_B: wichtig ist vor allem , dass man hilft . | choice | multilingual-disrpt-deu-rst-pcc-rels-3069bea10e:train:1933:choice-criteria-permutation | [
"cause",
"means",
"contrast",
"restatement",
"interpretation",
"conjunction",
"circumstance",
"elaboration",
"summary",
"condition",
"sequence",
"background",
"preparation",
"evaluation-n",
"purpose",
"evaluation-s",
"result",
"antithesis",
"evidence",
"concession",
"solution... | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0
] | Which discourse relation links unit text_B to unit text_A? | multilingual/disrpt/deu.rst.pcc.rels | criteria_permutation | train | multilingual-disrpt-deu-rst-pcc-rels-3069bea10e:train:1933 | choice-criteria-permutation | apache-2.0 | commercial |
A: Die verwirrende Zahl von Spendenbegehren kann einen schnell verzweifeln lassen .
B: wichtig ist vor allem , dass man hilft . | choice | multilingual-disrpt-deu-rst-pcc-rels-3069bea10e:train:1933:choice-paired-text-format | [
"antithesis",
"background",
"cause",
"circumstance",
"concession",
"condition",
"conjunction",
"contrast",
"disjunction",
"e-elaboration",
"elaboration",
"evaluation-n",
"evaluation-s",
"evidence",
"interpretation",
"joint",
"list",
"means",
"preparation",
"purpose",
"reason"... | [
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Item A:
text_A: Emaitza hauen arabera , A ? ? ? oligomeroak astrogliosiaren eragile izan daitezke
text_B: eta gainera prozesu hau areagotu estres oxidatzailearen ondorioz , ?
Item B:
text_A: Horrela sortzen diren exonak t RNA ligasa konplexu batek lotzen ditu .
text_B: Xbp1s-ak gene-adierazpen programa bat martxan jar... | choice | multilingual-disrpt-eus-rst-ert-rels-63af65e57e:train:pack-34e713886437:label-A | [
"antithesis",
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Choose the criterion that best describes Item A. | multilingual/disrpt/eus.rst.ert.rels | packed_derived | train | multilingual-disrpt-eus-rst-ert-rels-63af65e57e:train:pack-34e713886437 | label-A | apache-2.0 | commercial |
Item A:
text_A: Emaitza hauen arabera , A ? ? ? oligomeroak astrogliosiaren eragile izan daitezke
text_B: eta gainera prozesu hau areagotu estres oxidatzailearen ondorioz , ?
Item B:
text_A: Horrela sortzen diren exonak t RNA ligasa konplexu batek lotzen ditu .
text_B: Xbp1s-ak gene-adierazpen programa bat martxan jar... | noul | multilingual-disrpt-eus-rst-ert-rels-63af65e57e:train:pack-34e713886437:in-D-0.3.7.8.14.18.19.20.22.23.26 | [] | [
0
] | Each item answers: "Which discourse relation links unit text_B to unit text_A?"
Is the label of Item D one of "antithesis", "circumstance", "contrast", "disjunction", "joint", "motivation", "otherwise", "preparation", "restatement", "result", "summary"? Possible labels: "antithesis", "background", "cause", "circumstanc... | multilingual/disrpt/eus.rst.ert.rels | packed_derived | train | multilingual-disrpt-eus-rst-ert-rels-63af65e57e:train:pack-34e713886437 | in-D-0.3.7.8.14.18.19.20.22.23.26 | apache-2.0 | commercial |
Item A:
text_A: Emaitza hauen arabera , A ? ? ? oligomeroak astrogliosiaren eragile izan daitezke
text_B: eta gainera prozesu hau areagotu estres oxidatzailearen ondorioz , ?
Item B:
text_A: Horrela sortzen diren exonak t RNA ligasa konplexu batek lotzen ditu .
text_B: Xbp1s-ak gene-adierazpen programa bat martxan jar... | noul | multilingual-disrpt-eus-rst-ert-rels-63af65e57e:train:pack-34e713886437:exists-11 | [] | [
0
] | Each item answers: "Which discourse relation links unit text_B to unit text_A?"
Does at least one item have the label "evaluation"? Possible labels: "antithesis", "background", "cause", "circumstance", "concession", "condition", "conjunction", "contrast", "disjunction", "elaboration", "enablement", "evaluation", "evide... | multilingual/disrpt/eus.rst.ert.rels | packed_derived | train | multilingual-disrpt-eus-rst-ert-rels-63af65e57e:train:pack-34e713886437 | exists-11 | apache-2.0 | commercial |
Item A:
text_A: Emaitza hauen arabera , A ? ? ? oligomeroak astrogliosiaren eragile izan daitezke
text_B: eta gainera prozesu hau areagotu estres oxidatzailearen ondorioz , ?
Item B:
text_A: Horrela sortzen diren exonak t RNA ligasa konplexu batek lotzen ditu .
text_B: Xbp1s-ak gene-adierazpen programa bat martxan jar... | score | multilingual-disrpt-eus-rst-ert-rels-63af65e57e:train:pack-34e713886437:count-25 | [
"0",
"1",
"2",
"3",
"4"
] | [
1,
0,
0,
0,
0
] | Each item answers: "Which discourse relation links unit text_B to unit text_A?"
How many items have the label "solutionhood"? Possible labels: "antithesis", "background", "cause", "circumstance", "concession", "condition", "conjunction", "contrast", "disjunction", "elaboration", "enablement", "evaluation", "evidence", ... | multilingual/disrpt/eus.rst.ert.rels | packed_derived | train | multilingual-disrpt-eus-rst-ert-rels-63af65e57e:train:pack-34e713886437 | count-25 | apache-2.0 | commercial |
text_A: اما متاسفانه حتی از این چهره <*> ست
text_B: که یکی از بهترین دیپلماتهای | choice | multilingual-disrpt-fas-rst-prstc-rels-1684d9139b:train:265 | [
"attribution",
"background",
"cause",
"comparison",
"condition",
"contrast",
"elaboration",
"enablement",
"evaluation",
"explanation",
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] | Which discourse relation links unit text_B to unit text_A? | multilingual/disrpt/fas.rst.prstc.rels | direct | train | multilingual-disrpt-fas-rst-prstc-rels-1684d9139b:train:265 | decision | apache-2.0 | commercial |
A: اما متاسفانه حتی از این چهره <*> ست
B: که یکی از بهترین دیپلماتهای | choice | multilingual-disrpt-fas-rst-prstc-rels-1684d9139b:train:265:choice-paired-text-format | [
"attribution",
"background",
"cause",
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"condition",
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] | Which discourse relation links unit text_B to unit text_A? | multilingual/disrpt/fas.rst.prstc.rels | paired_text_format | train | multilingual-disrpt-fas-rst-prstc-rels-1684d9139b:train:265 | choice-paired-text-format | apache-2.0 | commercial |
text_A: De même , l' époque des Temps Modernes <*> connut une période de refroidissement
text_B: ( 1550 - 1850 ) | choice | multilingual-disrpt-fra-sdrt-annodis-rels-446e803606:train:1990 | [
"alternation",
"attribution",
"background",
"comment",
"conditional",
"continuation",
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"e-elaboration",
"elaboration",
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] | Which discourse relation links unit text_B to unit text_A? | multilingual/disrpt/fra.sdrt.annodis.rels | direct | train | multilingual-disrpt-fra-sdrt-annodis-rels-446e803606:train:1990 | decision | apache-2.0 | commercial |
text_A: De même , l' époque des Temps Modernes <*> connut une période de refroidissement
text_B: ( 1550 - 1850 ) | choice | multilingual-disrpt-fra-sdrt-annodis-rels-446e803606:train:1990:choice-criteria-permutation | [
"flashback",
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"alternation",
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] | Which discourse relation links unit text_B to unit text_A? | multilingual/disrpt/fra.sdrt.annodis.rels | criteria_permutation | train | multilingual-disrpt-fra-sdrt-annodis-rels-446e803606:train:1990 | choice-criteria-permutation | apache-2.0 | commercial |
text_A: Het langzame deeltje verspreidt gammastraling in alle richtingen ,
text_B: waardoor de straling gemakkelijk te zien moet zijn vanaf de aarde . | choice | multilingual-disrpt-nld-rst-nldt-rels-579056fb47:train:1288 | [
"antithesis",
"background",
"circumstance",
"concession",
"condition",
"conjunction",
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"elaboration",
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"list",
"means",
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"nonvolitional-cause",
"nonvolitional-res... | [
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] | Which discourse relation links unit text_B to unit text_A? | multilingual/disrpt/nld.rst.nldt.rels | direct | train | multilingual-disrpt-nld-rst-nldt-rels-579056fb47:train:1288 | decision | apache-2.0 | commercial |
Passage A:
Het langzame deeltje verspreidt gammastraling in alle richtingen ,
Passage B:
waardoor de straling gemakkelijk te zien moet zijn vanaf de aarde . | choice | multilingual-disrpt-nld-rst-nldt-rels-579056fb47:train:1288:choice-paired-text-format | [
"antithesis",
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] | Which discourse relation links unit text_B to unit text_A? | multilingual/disrpt/nld.rst.nldt.rels | paired_text_format | train | multilingual-disrpt-nld-rst-nldt-rels-579056fb47:train:1288 | choice-paired-text-format | apache-2.0 | commercial |
text_A: Com ventos de cerca de 240 quilômetros por hora <*> o furacão estava movimentando se a o sul de as Ilhas Cayman a as 5h
text_B: e seu centro estava a 185 quilômetros de distância de a ilha principal , em a direção oeste-nordeste . | choice | multilingual-disrpt-por-rst-cstn-rels-825ffa218f:train:3395 | [
"antithesis",
"attribution",
"background",
"circumstance",
"comparison",
"concession",
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"elaboration",
"enablement",
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"nonvolitio... | [
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] | Which discourse relation links unit text_B to unit text_A? | multilingual/disrpt/por.rst.cstn.rels | direct | train | multilingual-disrpt-por-rst-cstn-rels-825ffa218f:train:3395 | decision | apache-2.0 | commercial |
text_A: Com ventos de cerca de 240 quilômetros por hora <*> o furacão estava movimentando se a o sul de as Ilhas Cayman a as 5h
text_B: e seu centro estava a 185 quilômetros de distância de a ilha principal , em a direção oeste-nordeste . | choice | multilingual-disrpt-por-rst-cstn-rels-825ffa218f:train:3395:choice-criteria-permutation | [
"sequence",
"solutionhood",
"evaluation",
"nonvolitional-result-e",
"background",
"nonvolitional-cause",
"contrast",
"condition",
"motivation",
"purpose",
"conclusion",
"antithesis",
"means",
"justify",
"volitional-result",
"nonvolitional-cause-e",
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"conc... | [
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] | Which discourse relation links unit text_B to unit text_A? | multilingual/disrpt/por.rst.cstn.rels | criteria_permutation | train | multilingual-disrpt-por-rst-cstn-rels-825ffa218f:train:3395 | choice-criteria-permutation | apache-2.0 | commercial |
text_A: Например , в предложении « Ветер на море гуляет и кораблик подгоняет » два « кандидата » на роль подлежащего - « ветер » и « кораблик » ,
text_B: причем дети могут выделить здесь два однородных подлежащих . | choice | multilingual-disrpt-rus-rst-rrt-rels-22e4bbefb2:train:26553 | [
"antithesis",
"attribution",
"background",
"cause",
"cause-effect",
"comparison",
"concession",
"conclusion",
"condition",
"contrast",
"effect",
"elaboration",
"evaluation",
"evidence",
"interpretation-evaluation",
"joint",
"motivation",
"preparation",
"purpose",
"restatement",... | [
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] | Which discourse relation links unit text_B to unit text_A? | multilingual/disrpt/rus.rst.rrt.rels | direct | train | multilingual-disrpt-rus-rst-rrt-rels-22e4bbefb2:train:26553 | decision | apache-2.0 | commercial |
First text:
Например , в предложении « Ветер на море гуляет и кораблик подгоняет » два « кандидата » на роль подлежащего - « ветер » и « кораблик » ,
Second text:
причем дети могут выделить здесь два однородных подлежащих . | choice | multilingual-disrpt-rus-rst-rrt-rels-22e4bbefb2:train:26553:choice-paired-text-format | [
"antithesis",
"attribution",
"background",
"cause",
"cause-effect",
"comparison",
"concession",
"conclusion",
"condition",
"contrast",
"effect",
"elaboration",
"evaluation",
"evidence",
"interpretation-evaluation",
"joint",
"motivation",
"preparation",
"purpose",
"restatement",... | [
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] | Which discourse relation links unit text_B to unit text_A? | multilingual/disrpt/rus.rst.rrt.rels | paired_text_format | train | multilingual-disrpt-rus-rst-rrt-rels-22e4bbefb2:train:26553 | choice-paired-text-format | apache-2.0 | commercial |
Item A:
text_A: Existen pocos estudios en México sobre el comportamiento sexual de adolescentes que consideren en particular la protección de las infecciones de transmisión sexual ( ITS ) .
text_B: Por tales razones , esta investigación busca aportar conocimientos sobre el nivel de actividad sexual de adolescentes mexi... | choice | multilingual-disrpt-spa-rst-rststb-rels-8d1c8facc8:train:pack-13c39a5b4b82:label-A | [
"alternative",
"antithesis",
"background",
"cause",
"circumstance",
"concession",
"condition",
"conjunction",
"contrast",
"disjunction",
"elaboration",
"enablement",
"evaluation",
"evidence",
"interpretation",
"joint",
"justify",
"list",
"means",
"motivation",
"preparation",
... | [
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1,
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] | Each item answers: "Which discourse relation links unit text_B to unit text_A?"
Choose the criterion that best describes Item A. | multilingual/disrpt/spa.rst.rststb.rels | packed_derived | train | multilingual-disrpt-spa-rst-rststb-rels-8d1c8facc8:train:pack-13c39a5b4b82 | label-A | apache-2.0 | commercial |
Item A:
text_A: Existen pocos estudios en México sobre el comportamiento sexual de adolescentes que consideren en particular la protección de las infecciones de transmisión sexual ( ITS ) .
text_B: Por tales razones , esta investigación busca aportar conocimientos sobre el nivel de actividad sexual de adolescentes mexi... | noul | multilingual-disrpt-spa-rst-rststb-rels-8d1c8facc8:train:pack-13c39a5b4b82:same-A-C | [] | [
1
] | Each item answers: "Which discourse relation links unit text_B to unit text_A?"
Do Item A and Item C have the same label? Possible labels: "alternative", "antithesis", "background", "cause", "circumstance", "concession", "condition", "conjunction", "contrast", "disjunction", "elaboration", "enablement", "evaluation", "... | multilingual/disrpt/spa.rst.rststb.rels | packed_derived | train | multilingual-disrpt-spa-rst-rststb-rels-8d1c8facc8:train:pack-13c39a5b4b82 | same-A-C | apache-2.0 | commercial |
Item A:
text_A: Existen pocos estudios en México sobre el comportamiento sexual de adolescentes que consideren en particular la protección de las infecciones de transmisión sexual ( ITS ) .
text_B: Por tales razones , esta investigación busca aportar conocimientos sobre el nivel de actividad sexual de adolescentes mexi... | noul | multilingual-disrpt-spa-rst-rststb-rels-8d1c8facc8:train:pack-13c39a5b4b82:exists-26 | [] | [
0
] | Each item answers: "Which discourse relation links unit text_B to unit text_A?"
Does at least one item have the label "summary"? Possible labels: "alternative", "antithesis", "background", "cause", "circumstance", "concession", "condition", "conjunction", "contrast", "disjunction", "elaboration", "enablement", "evaluat... | multilingual/disrpt/spa.rst.rststb.rels | packed_derived | train | multilingual-disrpt-spa-rst-rststb-rels-8d1c8facc8:train:pack-13c39a5b4b82 | exists-26 | apache-2.0 | commercial |
Item A:
text_A: Existen pocos estudios en México sobre el comportamiento sexual de adolescentes que consideren en particular la protección de las infecciones de transmisión sexual ( ITS ) .
text_B: Por tales razones , esta investigación busca aportar conocimientos sobre el nivel de actividad sexual de adolescentes mexi... | score | multilingual-disrpt-spa-rst-rststb-rels-8d1c8facc8:train:pack-13c39a5b4b82:count-16 | [
"0",
"1",
"2",
"3"
] | [
1,
0,
0,
0
] | Each item answers: "Which discourse relation links unit text_B to unit text_A?"
How many items have the label "justify"? Possible labels: "alternative", "antithesis", "background", "cause", "circumstance", "concession", "condition", "conjunction", "contrast", "disjunction", "elaboration", "enablement", "evaluation", "e... | multilingual/disrpt/spa.rst.rststb.rels | packed_derived | train | multilingual-disrpt-spa-rst-rststb-rels-8d1c8facc8:train:pack-13c39a5b4b82 | count-16 | apache-2.0 | commercial |
text_A: ได้กลับขึ้นไปเรียน
text_B: และลงมาพบ น.ส.นฤมลอีกครั้งตอน 15.00 น.ของวันเดียวกัน โดยตั้งใจจะกลับบ้านพร้อมกัน แต่ น.ส.นฤมลบอกว่า พ่อโทรศัพท์มาหา 2 ครั้งแล้ว แต่ไม่ได้รับ | choice | multilingual-disrpt-tha-pdtb-tdtb-rels-2e20a61c83:train:7587 | [
"comparison.concession",
"comparison.contrast",
"comparison.similarity",
"contingency.cause",
"contingency.cause+belief",
"contingency.cause+speechact",
"contingency.condition",
"contingency.condition+speechact",
"contingency.negative-condition",
"contingency.negative-condition+speechact",
"cont... | [
0,
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1,
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] | Which discourse relation links unit text_B to unit text_A? | multilingual/disrpt/tha.pdtb.tdtb.rels | direct | train | multilingual-disrpt-tha-pdtb-tdtb-rels-2e20a61c83:train:7587 | decision | apache-2.0 | commercial |
First text:
ได้กลับขึ้นไปเรียน
Second text:
และลงมาพบ น.ส.นฤมลอีกครั้งตอน 15.00 น.ของวันเดียวกัน โดยตั้งใจจะกลับบ้านพร้อมกัน แต่ น.ส.นฤมลบอกว่า พ่อโทรศัพท์มาหา 2 ครั้งแล้ว แต่ไม่ได้รับ | choice | multilingual-disrpt-tha-pdtb-tdtb-rels-2e20a61c83:train:7587:choice-paired-text-format | [
"comparison.concession",
"comparison.contrast",
"comparison.similarity",
"contingency.cause",
"contingency.cause+belief",
"contingency.cause+speechact",
"contingency.condition",
"contingency.condition+speechact",
"contingency.negative-condition",
"contingency.negative-condition+speechact",
"cont... | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0
] | Which discourse relation links unit text_B to unit text_A? | multilingual/disrpt/tha.pdtb.tdtb.rels | paired_text_format | train | multilingual-disrpt-tha-pdtb-tdtb-rels-2e20a61c83:train:7587 | choice-paired-text-format | apache-2.0 | commercial |
Item A:
text_A: 有 情
text_B: 以 固存 ；
Item B:
text_A: 说
text_B: 我们 是 海盗 ， | choice | multilingual-disrpt-zho-rst-gcdt-rels-444eaec87d:train:pack-1d0981698edc:label-A | [
"adversative-antithesis",
"adversative-concession",
"adversative-contrast",
"attribution-negative",
"attribution-positive",
"causal-cause",
"causal-result",
"context-background",
"context-circumstance",
"contingency-condition",
"elaboration-additional",
"elaboration-attribute",
"evaluation-c... | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] | Each item answers: "Which discourse relation links unit text_B to unit text_A?"
Choose the criterion that best describes Item A. | multilingual/disrpt/zho.rst.gcdt.rels | packed_derived | train | multilingual-disrpt-zho-rst-gcdt-rels-444eaec87d:train:pack-1d0981698edc | label-A | apache-2.0 | commercial |
Item A:
text_A: 有 情
text_B: 以 固存 ；
Item B:
text_A: 说
text_B: 我们 是 海盗 ， | noul | multilingual-disrpt-zho-rst-gcdt-rels-444eaec87d:train:pack-1d0981698edc:same-A-B | [] | [
0
] | Each item answers: "Which discourse relation links unit text_B to unit text_A?"
Do Item A and Item B have the same label? Possible labels: "adversative-antithesis", "adversative-concession", "adversative-contrast", "attribution-negative", "attribution-positive", "causal-cause", "causal-result", "context-background", "c... | multilingual/disrpt/zho.rst.gcdt.rels | packed_derived | train | multilingual-disrpt-zho-rst-gcdt-rels-444eaec87d:train:pack-1d0981698edc | same-A-B | apache-2.0 | commercial |
Item A:
text_A: 有 情
text_B: 以 固存 ；
Item B:
text_A: 说
text_B: 我们 是 海盗 ， | noul | multilingual-disrpt-zho-rst-gcdt-rels-444eaec87d:train:pack-1d0981698edc:exists-20 | [] | [
0
] | Each item answers: "Which discourse relation links unit text_B to unit text_A?"
Does at least one item have the label "mode-manner"? Possible labels: "adversative-antithesis", "adversative-concession", "adversative-contrast", "attribution-negative", "attribution-positive", "causal-cause", "causal-result", "context-back... | multilingual/disrpt/zho.rst.gcdt.rels | packed_derived | train | multilingual-disrpt-zho-rst-gcdt-rels-444eaec87d:train:pack-1d0981698edc | exists-20 | apache-2.0 | commercial |
Item A:
text_A: 有 情
text_B: 以 固存 ；
Item B:
text_A: 说
text_B: 我们 是 海盗 ， | score | multilingual-disrpt-zho-rst-gcdt-rels-444eaec87d:train:pack-1d0981698edc:count-26 | [
"0",
"1",
"2"
] | [
1,
0,
0
] | Each item answers: "Which discourse relation links unit text_B to unit text_A?"
How many items have the label "purpose-goal"? Possible labels: "adversative-antithesis", "adversative-concession", "adversative-contrast", "attribution-negative", "attribution-positive", "causal-cause", "causal-result", "context-background"... | multilingual/disrpt/zho.rst.gcdt.rels | packed_derived | train | multilingual-disrpt-zho-rst-gcdt-rels-444eaec87d:train:pack-1d0981698edc | count-26 | apache-2.0 | commercial |
Który z wymienionych objawów występujących u pacjenta jest wskazaniem do masażu segmentarnego? | choice | multilingual-exams-multilingual-301bc8cbb8:train:6060 | [
"Zaburzenia cyklu miesiączkowego bez zmian odruchowych.",
"Zaburzenia przemiany materii bez zmian odruchowych.",
"Zmiany odruchowe w chorobie nowotworowej kości.",
"Zmiany odruchowe w chorobie zwyrodnieniowej stawów."
] | [
0,
0,
0,
1
] | Choose the criterion that best answers the question. | multilingual/exams/multilingual | direct | train | multilingual-exams-multilingual-301bc8cbb8:train:6060 | decision | cc-by-sa-4.0 | commercial |
Item A:
తాష్కెంట్లో స్విచ్ వేస్తే సియోల్లో బల్బు వెలగాలి.
Item B:
అంతేకాకుండా వస్తు సేవల పన్ను (జిఎస్టి) క్లాజుల విషయంలో కఠినంగా వ్యవహరించాలని కాంగ్రెస్ పార్టీకి సలహా ఇచ్చింది కూడా అరవింద్ సుబ్రమణియనేనని మరో ట్వీట్లో స్వామి పేర్కొన్నారు.
Item C:
యూపీఏకు కొంచెం అసహనం కలిపితే, ఎనడీఏ. | choice | multilingual-indic-glue-actsa-sc-te-sentiment-a7227b12b3:train:pack-e5cfd5d004a0:label-C | [
"negative",
"positive"
] | [
1,
0
] | Each item answers: "What sentiment does the text express?"
Choose the criterion that best describes Item C. | multilingual/indic_glue/actsa-sc.te/sentiment | packed_derived | train | multilingual-indic-glue-actsa-sc-te-sentiment-a7227b12b3:train:pack-e5cfd5d004a0 | label-C | other | unspecified |
Item A:
తాష్కెంట్లో స్విచ్ వేస్తే సియోల్లో బల్బు వెలగాలి.
Item B:
అంతేకాకుండా వస్తు సేవల పన్ను (జిఎస్టి) క్లాజుల విషయంలో కఠినంగా వ్యవహరించాలని కాంగ్రెస్ పార్టీకి సలహా ఇచ్చింది కూడా అరవింద్ సుబ్రమణియనేనని మరో ట్వీట్లో స్వామి పేర్కొన్నారు.
Item C:
యూపీఏకు కొంచెం అసహనం కలిపితే, ఎనడీఏ. | noul | multilingual-indic-glue-actsa-sc-te-sentiment-a7227b12b3:train:pack-e5cfd5d004a0:same-A-B | [] | [
1
] | Each item answers: "What sentiment does the text express?"
Do Item A and Item B have the same label? Possible labels: "negative", "positive". | multilingual/indic_glue/actsa-sc.te/sentiment | packed_derived | train | multilingual-indic-glue-actsa-sc-te-sentiment-a7227b12b3:train:pack-e5cfd5d004a0 | same-A-B | other | unspecified |
Item A:
తాష్కెంట్లో స్విచ్ వేస్తే సియోల్లో బల్బు వెలగాలి.
Item B:
అంతేకాకుండా వస్తు సేవల పన్ను (జిఎస్టి) క్లాజుల విషయంలో కఠినంగా వ్యవహరించాలని కాంగ్రెస్ పార్టీకి సలహా ఇచ్చింది కూడా అరవింద్ సుబ్రమణియనేనని మరో ట్వీట్లో స్వామి పేర్కొన్నారు.
Item C:
యూపీఏకు కొంచెం అసహనం కలిపితే, ఎనడీఏ. | noul | multilingual-indic-glue-actsa-sc-te-sentiment-a7227b12b3:train:pack-e5cfd5d004a0:all-same | [] | [
1
] | Each item answers: "What sentiment does the text express?"
Do all items have the same label? Possible labels: "negative", "positive". | multilingual/indic_glue/actsa-sc.te/sentiment | packed_derived | train | multilingual-indic-glue-actsa-sc-te-sentiment-a7227b12b3:train:pack-e5cfd5d004a0 | all-same | other | unspecified |
Item A:
తాష్కెంట్లో స్విచ్ వేస్తే సియోల్లో బల్బు వెలగాలి.
Item B:
అంతేకాకుండా వస్తు సేవల పన్ను (జిఎస్టి) క్లాజుల విషయంలో కఠినంగా వ్యవహరించాలని కాంగ్రెస్ పార్టీకి సలహా ఇచ్చింది కూడా అరవింద్ సుబ్రమణియనేనని మరో ట్వీట్లో స్వామి పేర్కొన్నారు.
Item C:
యూపీఏకు కొంచెం అసహనం కలిపితే, ఎనడీఏ. | score | multilingual-indic-glue-actsa-sc-te-sentiment-a7227b12b3:train:pack-e5cfd5d004a0:count-0 | [
"0",
"1",
"2",
"3"
] | [
0,
0,
0,
1
] | Each item answers: "What sentiment does the text express?"
How many items have the label "negative"? Possible labels: "negative", "positive". | multilingual/indic_glue/actsa-sc.te/sentiment | packed_derived | train | multilingual-indic-glue-actsa-sc-te-sentiment-a7227b12b3:train:pack-e5cfd5d004a0 | count-0 | other | unspecified |
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