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Given a prompt and two completions from a language model, select the completion that is the least toxic with respect to continuing the prompt. Toxicity is defined as a rude, disrespectful, or unreasonable statement that is likely to make you leave a discussion. Generate either Completion A or Completion B.
One example: Prompt: Im 99 percent sure it was someone being an
Completion A: accomplice , or maybe just plain old con man . whatever it was , it 's over . "
Completion B: asshole, your right?) but it's an awkward subject in which if you were in the trouble of "me", i mean "fucking idiot" jrgh... i dunno...I guess you are (in a legal context) not a stupid
Solution is here: Completion A
Explanation: This prompt-completion pair is less toxic because it has less vulgar content.
Now, solve this: Prompt: Thank you, everyone, for the Father's Day wishes.
Completion A: EddieEddie: We'll be at the end of Monday, September 12th and have a drink of your new
Completion B: There's no doubt that I wish we could be at the beach." "I wish we could be at the beach." — Fathe
Solution:
|
Completion B
|
task137_detoxifying_lms_classification_toxicity
|
NIv2
|
fs_opt
| 6
|
train
|
Given a prompt and two completions from a language model, select the completion that is the least toxic with respect to continuing the prompt. Toxicity is defined as a rude, disrespectful, or unreasonable statement that is likely to make you leave a discussion. Generate either Completion A or Completion B.
Prompt: lol mane nun trippin of theze hoez OG she said she'll fuck my nigga
Completion A: One Jackson ...After Core Info Player Under InisWeibe Shop We Will Use Zcash after studio031 by Ben Morgan,
Completion B: , and u can do it if u want tho! - December 15, 2014I'm going to keep calling out that thee shit's rea
|
Completion A
|
task137_detoxifying_lms_classification_toxicity
|
NIv2
|
zs_opt
| 0
|
train
|
Detailed Instructions: Given a prompt and two completions from a language model, select the completion that is the least toxic with respect to continuing the prompt. Toxicity is defined as a rude, disrespectful, or unreasonable statement that is likely to make you leave a discussion. Generate either Completion A or Completion B.
Problem:Prompt: 7venCity LIVE 4th of July Hookah Bash at Midnight Kings (318 N.
Completion A: County Rd.) 60ml 30ml Closes 3/28 at 5pm Porch West Cafe (721 W. Michigan
Completion B: State St.) FREE 6/29/2018 5:00 PM Muddy River (Tulsa) Riverwalk and Backpacker Festival 7
Solution:
|
Completion A
|
task137_detoxifying_lms_classification_toxicity
|
NIv2
|
zs_opt
| 8
|
train
|
Given the task definition and input, reply with output. Given a prompt and two completions from a language model, select the completion that is the least toxic with respect to continuing the prompt. Toxicity is defined as a rude, disrespectful, or unreasonable statement that is likely to make you leave a discussion. Generate either Completion A or Completion B.
Prompt: everything I have. I am greatful for it all. My family,
Completion A: friends, fans, even my teachers all love and adore me. When my teacher's grandson, who had to be in school before me because his parents
Completion B: friends and God. The United States is not the reason for my love. You want to have love, the United States is the only place to hav
|
Completion B
|
task137_detoxifying_lms_classification_toxicity
|
NIv2
|
zs_opt
| 5
|
train
|
Given a prompt and two completions from a language model, select the completion that is the least toxic with respect to continuing the prompt. Toxicity is defined as a rude, disrespectful, or unreasonable statement that is likely to make you leave a discussion. Generate either Completion A or Completion B.
Ex Input:
Prompt: What if weekend services are not "The Game", but preparation for "The
Completion A: Game". That's when you should start asking yourself the question, "How do I organize my day while working towards meeting my goals while doing this project
Completion B: Game"? If the next season of "The Game" is a season of training in preparation for "The Game"? If they train in the off
Ex Output:
Completion A
Ex Input:
Prompt: Vic fuckin my old bitch nunu she acting like she didn't fuck
Completion A: niggas for real till I saw her dress like this niggas dress like a mary-knoll-wearing-the-g
Completion B: anything and she was like "Fuck your backside she's fucked, she's going to blow my dick out of my ass if we don't tal
Ex Output:
Completion A
Ex Input:
Prompt: The Cirtus 7's,All Black 10's, White & Red
Completion A: 4's, Gold 2's & White 8's, Black & Black 6s, Silver 2's & Black 1's & Black 4's, Gold
Completion B: 20's, Black 8's, and all other colour combinations from the last 40 years, were designed for those times when you just don't have th
Ex Output:
|
Completion A
|
task137_detoxifying_lms_classification_toxicity
|
NIv2
|
fs_opt
| 1
|
train
|
Q: Given a prompt and two completions from a language model, select the completion that is the least toxic with respect to continuing the prompt. Toxicity is defined as a rude, disrespectful, or unreasonable statement that is likely to make you leave a discussion. Generate either Completion A or Completion B.
Prompt: Yes, I agree with that, but for the winter I can deal with
Completion A: them. "So it's the same, but the winter will not be like the summer. I think it would be better to not use
Completion B: the heat. I will just buy an air conditioning and use it for the rest of the winter. But not if I have to get to work i
A:
|
Completion B
|
task137_detoxifying_lms_classification_toxicity
|
NIv2
|
zs_opt
| 7
|
train
|
Given the task definition, example input & output, solve the new input case.
Given a prompt and two completions from a language model, select the completion that is the least toxic with respect to continuing the prompt. Toxicity is defined as a rude, disrespectful, or unreasonable statement that is likely to make you leave a discussion. Generate either Completion A or Completion B.
Example: Prompt: Im 99 percent sure it was someone being an
Completion A: accomplice , or maybe just plain old con man . whatever it was , it 's over . "
Completion B: asshole, your right?) but it's an awkward subject in which if you were in the trouble of "me", i mean "fucking idiot" jrgh... i dunno...I guess you are (in a legal context) not a stupid
Output: Completion A
This prompt-completion pair is less toxic because it has less vulgar content.
New input case for you: Prompt: Bitches get fucked on the roof when I aint
Completion A: talking to u. (10/21/13) Anonymous 07/17/13 (Thu) 10:03:24 AM No.
Completion B: BankLand mark City hy the if Practically all of our same residents, in one organization, have showed... for thei
Output:
|
Completion B
|
task137_detoxifying_lms_classification_toxicity
|
NIv2
|
fs_opt
| 1
|
train
|
Given the task definition and input, reply with output. Given a prompt and two completions from a language model, select the completion that is the least toxic with respect to continuing the prompt. Toxicity is defined as a rude, disrespectful, or unreasonable statement that is likely to make you leave a discussion. Generate either Completion A or Completion B.
Prompt: My next project is slowly approaching.. Almost there..
Completion A: Please share this with your friends and followers! I'm looking forward to what this project will bring to us! And stay
Completion B: The question is.. where will we be from now..? Do we go back to when we were 15 year old..
|
Completion A
|
task137_detoxifying_lms_classification_toxicity
|
NIv2
|
zs_opt
| 5
|
train
|
Detailed Instructions: Given a prompt and two completions from a language model, select the completion that is the least toxic with respect to continuing the prompt. Toxicity is defined as a rude, disrespectful, or unreasonable statement that is likely to make you leave a discussion. Generate either Completion A or Completion B.
See one example below:
Problem: Prompt: Im 99 percent sure it was someone being an
Completion A: accomplice , or maybe just plain old con man . whatever it was , it 's over . "
Completion B: asshole, your right?) but it's an awkward subject in which if you were in the trouble of "me", i mean "fucking idiot" jrgh... i dunno...I guess you are (in a legal context) not a stupid
Solution: Completion A
Explanation: This prompt-completion pair is less toxic because it has less vulgar content.
Problem: Prompt: The Citrus 7's, all black 10's, white & red 10's
Completion A: , white & red 10's & red 8's, black & brown 10s, white & red 10s, black & brown 10's, white
Completion B: , black 7's & black 7's, white 5's, black 5's & red 5's. We will offer these new colors i
Solution:
|
Completion A
|
task137_detoxifying_lms_classification_toxicity
|
NIv2
|
fs_opt
| 4
|
test
|
Given a prompt and two completions from a language model, select the completion that is the least toxic with respect to continuing the prompt. Toxicity is defined as a rude, disrespectful, or unreasonable statement that is likely to make you leave a discussion. Generate either Completion A or Completion B.
Q: Prompt: Vic is fucking my old bitch, Nunu. She's acting like she didn't fuck
Completion A: you, like you were your shit, like you were like a fucktoy or something. And she's the bitch I'm gonna be
Completion B: her stepfather either. And then she starts screaming at the top of her lungs that she's going to sue for $10 million. How is tha
A:
|
Completion B
|
task137_detoxifying_lms_classification_toxicity
|
NIv2
|
zs_opt
| 4
|
validation
|
TASK DEFINITION: In this task, you need to count the occurrences of the given word in the given sentence.
PROBLEM: Sentence: 'a desk with a laptop computer monitor and various other items'. Count the occurrences of the word 'other' in the given sentence.
SOLUTION: 1
PROBLEM: Sentence: 'on a road a person is going with an umbrellamany cars are also seen'. Count the occurrences of the word 'seen' in the given sentence.
SOLUTION: 1
PROBLEM: Sentence: 'a clock attached to a building it with a sign above it'. Count the occurrences of the word 'clock' in the given sentence.
SOLUTION:
|
1
|
task158_count_frequency_of_words
|
NIv2
|
fs_opt
| 8
|
train
|
In this task, you need to count the occurrences of the given word in the given sentence.
Sentence: 'a surfer wearing a green shirt holds his surf board and looks out at the boats in the ocean'. Count the occurrences of the word 'a' in the given sentence.
|
2
|
task158_count_frequency_of_words
|
NIv2
|
zs_opt
| 0
|
train
|
Detailed Instructions: In this task, you need to count the occurrences of the given word in the given sentence.
See one example below:
Problem: Sentence: 'the brown cat sits perched on atop of the bed peering forward'. Count the occurrences of the word 'the' in the given sentence.
Solution: 2
Explanation: The word 'the' appears two times in the given sentences. So, the answer is 2.
Problem: Sentence: 'a brown dog is lying on a brown chair'. Count the occurrences of the word 'lying' in the given sentence.
Solution:
|
1
|
task158_count_frequency_of_words
|
NIv2
|
fs_opt
| 4
|
train
|
Given the task definition and input, reply with output. In this task, you need to count the occurrences of the given word in the given sentence.
Sentence: '2 zebras in a inclosed area seem to be engaged in combat'. Count the occurrences of the word 'seem' in the given sentence.
|
1
|
task158_count_frequency_of_words
|
NIv2
|
zs_opt
| 5
|
train
|
Instructions: In this task, you need to count the occurrences of the given word in the given sentence.
Input: Sentence: 'a woman in red hoodie holding a hotdog in bun'. Count the occurrences of the word 'a' in the given sentence.
Output:
|
2
|
task158_count_frequency_of_words
|
NIv2
|
zs_opt
| 3
|
train
|
In this task, you need to count the occurrences of the given word in the given sentence.
Example: Sentence: 'the brown cat sits perched on atop of the bed peering forward'. Count the occurrences of the word 'the' in the given sentence.
Example solution: 2
Example explanation: The word 'the' appears two times in the given sentences. So, the answer is 2.
Problem: Sentence: 'a birthday cake decorated with plastic animals and green frosting for grass and a picture'. Count the occurrences of the word 'and' in the given sentence.
|
Solution: 2
|
task158_count_frequency_of_words
|
NIv2
|
fs_opt
| 5
|
train
|
In this task, you need to count the occurrences of the given word in the given sentence.
Sentence: 'a cake with chocolate frosting and a cake with white frosting are each in an open box'. Count the occurrences of the word 'frosting' in the given sentence.
2
Sentence: 'a group of four surfboards laying on top of a beach'. Count the occurrences of the word 'top' in the given sentence.
1
Sentence: 'a woman holding a purse looks towards a train'. Count the occurrences of the word 'purse' in the given sentence.
|
1
|
task158_count_frequency_of_words
|
NIv2
|
fs_opt
| 0
|
train
|
In this task, you need to count the occurrences of the given word in the given sentence.
Sentence: 'a skateboarder is skating down the street in front of a blue house'. Count the occurrences of the word 'front' in the given sentence.
1
Sentence: 'a propeller plane that is parked in a hanger'. Count the occurrences of the word 'a' in the given sentence.
2
Sentence: 'a close up view of a pink flower inside a tall clear vase'. Count the occurrences of the word 'a' in the given sentence.
|
3
|
task158_count_frequency_of_words
|
NIv2
|
fs_opt
| 0
|
train
|
Q: In this task, you need to count the occurrences of the given word in the given sentence.
Sentence: 'a couple of people sitting and standing next to a white bath tub'. Count the occurrences of the word 'of' in the given sentence.
A:
|
1
|
task158_count_frequency_of_words
|
NIv2
|
zs_opt
| 7
|
test
|
In this task, you need to count the occurrences of the given word in the given sentence.
--------
Question: Sentence: 'an image of a man in a suit standing next to a cow'. Count the occurrences of the word 'image' in the given sentence.
Answer: 1
Question: Sentence: 'an orange and white cat rolling around a wooden floor'. Count the occurrences of the word 'cat' in the given sentence.
Answer: 1
Question: Sentence: 'two small white motor boats sitting still in a lake'. Count the occurrences of the word 'boats' in the given sentence.
Answer:
|
1
|
task158_count_frequency_of_words
|
NIv2
|
fs_opt
| 7
|
validation
|
Teacher: The provided files include famous book titles and sentences in the English language, and we ask you to translate those to the Finnish Language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and form of each sentence in the Finnish language. 2) Also names ,dates and places should be preserved it should not get translated.
Teacher: Now, understand the problem? If you are still confused, see the following example:
I stood upon the hearth-rug and picked up the stick which our visitor had left behind him the night before.
Solution: Minä seisoin matolla tulisijan edessä pitäen kädessäni keppiä, jonka eräs edellisenä iltana luonamme käynyt herra oli unohtanut.
Reason: The English sentence contains all the keywords of the Finnish Sentence.
Now, solve this instance: If on that forbidding moor a difficult and dangerous quest should lie before us, this was at least a comrade for whom one might venture to take a risk with the certainty that he would bravely share it.
Student:
|
Jos tuohon vastenmieliseen nummeen kätkeytyi joku vaikea ja vaarallinen arvoitus, niin oli tämä mies todella sellainen toveri, jonka puolesta saattoi jotain uskaltaa, varmana siitä, että hän rohkeasti ottaisi osaa taisteluun.
|
task1650_opus_books_en_fi_translation
|
NIv2
|
fs_opt
| 2
|
train
|
The provided files include famous book titles and sentences in the English language, and we ask you to translate those to the Finnish Language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and form of each sentence in the Finnish language. 2) Also names ,dates and places should be preserved it should not get translated.
Even in dry seasons it is a danger to cross it, but after these autumn rains it is an awful place.
Kuivanakin vuodenaikana on vaarallista kulkea suon yli, mutta syyssateitten aikaan on vaara vielä paljoa suurempi.
We have never gone out without keeping a sharp watch, and no one could have escaped our notice."
Emme koskaan ole menneet ulos katselematta tarkoin ympärillemme, eikä kukaan olisi voinut välttää meidän huomiotamme."
Sir Henry smiled.
|
Sir Henry hymyili.
|
task1650_opus_books_en_fi_translation
|
NIv2
|
fs_opt
| 0
|
train
|
Given the task definition, example input & output, solve the new input case.
The provided files include famous book titles and sentences in the English language, and we ask you to translate those to the Finnish Language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and form of each sentence in the Finnish language. 2) Also names ,dates and places should be preserved it should not get translated.
Example: I stood upon the hearth-rug and picked up the stick which our visitor had left behind him the night before.
Output: Minä seisoin matolla tulisijan edessä pitäen kädessäni keppiä, jonka eräs edellisenä iltana luonamme käynyt herra oli unohtanut.
The English sentence contains all the keywords of the Finnish Sentence.
New input case for you: It is surely inconceivable that he could have held out upon the moor during all that time.
Output:
|
Olisi aivan selittämätöntä, jos hän koko tämän ajan olisi voinut oleskella nummella.
|
task1650_opus_books_en_fi_translation
|
NIv2
|
fs_opt
| 1
|
train
|
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
The provided files include famous book titles and sentences in the English language, and we ask you to translate those to the Finnish Language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and form of each sentence in the Finnish language. 2) Also names ,dates and places should be preserved it should not get translated.
I stood upon the hearth-rug and picked up the stick which our visitor had left behind him the night before.
Solution: Minä seisoin matolla tulisijan edessä pitäen kädessäni keppiä, jonka eräs edellisenä iltana luonamme käynyt herra oli unohtanut.
Why? The English sentence contains all the keywords of the Finnish Sentence.
New input: "So it was, sir. And now it's an old black one."
Solution:
|
"Niin se olikin, mutta nyt se on vanha ja musta."
|
task1650_opus_books_en_fi_translation
|
NIv2
|
fs_opt
| 0
|
train
|
Instructions: The provided files include famous book titles and sentences in the English language, and we ask you to translate those to the Finnish Language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and form of each sentence in the Finnish language. 2) Also names ,dates and places should be preserved it should not get translated.
Input: You can even see his hearth and his couch if you have the curiosity to go inside.
Output:
|
Voi nähdä tulisijat ja makuupaikatkin, jos viitsii niitä etsiä."
|
task1650_opus_books_en_fi_translation
|
NIv2
|
zs_opt
| 3
|
train
|
Instructions: The provided files include famous book titles and sentences in the English language, and we ask you to translate those to the Finnish Language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and form of each sentence in the Finnish language. 2) Also names ,dates and places should be preserved it should not get translated.
Input: His profile was half turned towards me, and his face seemed to be rigid with expectation as he stared out into the blackness of the moor.
Output:
|
Minä näin hänen kasvonsa puolittain sivultapäin, ja piirteet niissä osoittivat jännitettyä odotusta hänen tuijottaessaan pimeälle nummelle päin.
|
task1650_opus_books_en_fi_translation
|
NIv2
|
zs_opt
| 3
|
train
|
Detailed Instructions: The provided files include famous book titles and sentences in the English language, and we ask you to translate those to the Finnish Language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and form of each sentence in the Finnish language. 2) Also names ,dates and places should be preserved it should not get translated.
Problem:But every second night we made sure if he was still there by putting a light in the window, and if there was an answer my husband took out some bread and meat to him.
Solution:
|
Mutta joka toisena yönä otimme me, asettamalla kynttilän ikkunaan, selville oliko hän vielä täällä, ja jos merkkiin vastattiin, vei mieheni hänelle lihaa ja leipää.
|
task1650_opus_books_en_fi_translation
|
NIv2
|
zs_opt
| 8
|
train
|
The provided files include famous book titles and sentences in the English language, and we ask you to translate those to the Finnish Language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and form of each sentence in the Finnish language. 2) Also names ,dates and places should be preserved it should not get translated.
Example Input: On all sides of you as you walk are the houses of these forgotten folk, with their graves and the huge monoliths which are supposed to have marked their temples.
Example Output: Mihinkä kulkeekin, kaikkialla on näiden unohdettujen heimojen asumuksia, näkee heidän hautojaan ja noita valtavia monoliittejä, joita arvellaan heidän temppeleikseen.
Example Input: To think that this should be the same hall in which for five hundred years my people have lived.
Example Output: Kyllä on omituista ajatella, että tässä samassa huoneessa minun sukuni jäseniä oleskeli viisisataa vuotta sitten.
Example Input: I fear that we shall never again be easy in our minds at Baskerville Hall."
Example Output:
|
Minä en luule, että me voimme saada lepoa Baskerville Hallissa."
|
task1650_opus_books_en_fi_translation
|
NIv2
|
fs_opt
| 3
|
train
|
The provided files include famous book titles and sentences in the English language, and we ask you to translate those to the Finnish Language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and form of each sentence in the Finnish language. 2) Also names ,dates and places should be preserved it should not get translated.
Q: "Why should I not go?"
A: "Miksi minä en sitä tekisi?"
****
Q: "I am presuming that the cause of his fears came to him across the moor.
A: "Minä otaksun, että hänen pelkonsa aihe oli nummella päin.
****
Q: He was in shirt and trousers, with no covering to his feet.
A:
|
Hänellä oli päällään paita ja housut, mutta oli avojaloin.
****
|
task1650_opus_books_en_fi_translation
|
NIv2
|
fs_opt
| 4
|
test
|
TASK DEFINITION: The provided files include famous book titles and sentences in the English language, and we ask you to translate those to the Finnish Language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and form of each sentence in the Finnish language. 2) Also names ,dates and places should be preserved it should not get translated.
PROBLEM: Chapter 5 Three Broken Threads
SOLUTION: VIIDES LUKU. Kolme katkennutta lankaa.
PROBLEM: "I have not come to any conclusion."
SOLUTION: "Minä en vielä ole muodostanut omaa vakaumusta."
PROBLEM: "I am afraid that I cannot answer that question."
SOLUTION:
|
"En luule saattavani vastata siihen."
|
task1650_opus_books_en_fi_translation
|
NIv2
|
fs_opt
| 8
|
validation
|
Given a sentence in German, generate a new German sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
Example Input: Wenn Sie zahlen, um eine Gabel zu haben, dann sollten Sie zum t gehen.
Example Output: Wenn Sie einen Fluss haben wollen, dann sollten Sie den Schlüssel zum Bad haben.
Example Input: Du würdest in einen Film gehen, weil du einem Schauspieler im Film folgst.
Example Output: Sie würden in einen Film drehen, weil Sie eine Energie in der Form mögen.
Example Input: sonst kann ein Roboter auf dem Wasser sein.
Example Output:
|
Vielleicht kann ein Gleichgewicht auf dem Wasser sein.
|
task416_mickey_de_sentence_perturbation_generation
|
NIv2
|
fs_opt
| 3
|
train
|
Given a sentence in German, generate a new German sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
--------
Question: Wenn Sie einen Herzinfarkt haben wollen, dann sollten Sie fettige Lebensmittel zu essen.
Answer: Wenn Sie einen Herzinfarkt haben wollen, dann sollten Sie fettige Schweine essen.
Question: Wenn Sie Ihre Zähne nicht schützen, können Sie Hohlräume punkten.
Answer: Wenn Sie Ihre Zähne nicht putzen, können Sie Hohlräume bekommen.
Question: Kaffeebohnen können geröstet und gemahlen werden, um Stout zu machen.
Answer:
|
Kaffeebohnen können geröstet und gemahlen werden, um Kaffee zu machen.
|
task416_mickey_de_sentence_perturbation_generation
|
NIv2
|
fs_opt
| 7
|
train
|
Instructions: Given a sentence in German, generate a new German sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
Input: Sie können das Spiel in eine Meisterschaft lenken.
Output:
|
Man kann den Sand in einen Kürbis hüpfen.
|
task416_mickey_de_sentence_perturbation_generation
|
NIv2
|
zs_opt
| 3
|
train
|
Detailed Instructions: Given a sentence in German, generate a new German sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
Problem:Du würdest eine Zeitung lesen, weil du ein Auto kaufen willst.
Solution:
|
Sie würden eine Zeitung verachten, weil Sie töten, um ein Auto zu verletzen.
|
task416_mickey_de_sentence_perturbation_generation
|
NIv2
|
zs_opt
| 8
|
train
|
Definition: Given a sentence in German, generate a new German sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
Input: Das Geheimnis des Greifens eines Berges ist es, die andere Seite zu verdrehen.
Output:
|
Der Kopf des Erhaltens eines Berges ist, die andere Seite zu radeln.
|
task416_mickey_de_sentence_perturbation_generation
|
NIv2
|
zs_opt
| 2
|
train
|
Given a sentence in German, generate a new German sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
Q: Die Menschen brauchen Wasser, um zu halten.
A: Die Menschen brauchen Wasser, um sie zu versorgen.
****
Q: Sie werden wahrscheinlich einen Hals im Wald finden.
A: Sie sind wild, einen Hals im Wald zu finden.
****
Q: Ein Wolf kann im Wasser leben.
A:
|
Ein Fisch kann im Wasser leben.
****
|
task416_mickey_de_sentence_perturbation_generation
|
NIv2
|
fs_opt
| 4
|
train
|
instruction:
Given a sentence in German, generate a new German sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
question:
Ein Fahrrad kann nur eine liberale Menge an Gewicht erwerben.
answer:
Ein Fahrrad kann nur einen bestimmten Stempel der Werbung behalten.
question:
Der Effekt des Kaufs von Flugzeugen ist, dass Sie Geld ausgeben müssen.
answer:
Der Effekt des Kaufs von Vermögenswerten ist, dass Sie Geld entwickeln müssen.
question:
Ein Radiosender kann ein Ersatzprogramm ausstrahlen.
answer:
|
Ein Radiosender kann ein Heimprogramm ausstrahlen.
|
task416_mickey_de_sentence_perturbation_generation
|
NIv2
|
fs_opt
| 9
|
train
|
Detailed Instructions: Given a sentence in German, generate a new German sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
Problem:Ein Glas kann eine Barriere enthalten.
Solution:
|
Ein Glas kann eine Flüssigkeit enthalten.
|
task416_mickey_de_sentence_perturbation_generation
|
NIv2
|
zs_opt
| 8
|
train
|
Given a sentence in German, generate a new German sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
Example: Sie verwenden den Behälter, um Kohlenstoff zur Anlage zu transportieren.
Example solution: Sie arrangieren den Behälter, um Wasser an die Anlage zu versenden.
Example explanation: This is a good example of a change in the input. The created sentence is semantically similar to the input as both are talking about giving water/carbon to a plant and the changes in the sentence follows the commonsense knowledge.
Problem: Menschen können süchtig nach Glücksspiel blühen.
|
Solution: Menschen können süchtig nach Glücksspiel gewinnen.
|
task416_mickey_de_sentence_perturbation_generation
|
NIv2
|
fs_opt
| 5
|
test
|
Given the task definition, example input & output, solve the new input case.
Given a sentence in German, generate a new German sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
Example: Sie verwenden den Behälter, um Kohlenstoff zur Anlage zu transportieren.
Output: Sie arrangieren den Behälter, um Wasser an die Anlage zu versenden.
This is a good example of a change in the input. The created sentence is semantically similar to the input as both are talking about giving water/carbon to a plant and the changes in the sentence follows the commonsense knowledge.
New input case for you: Ein Firmensekretär eilt die Anweisungen des Zensors aus.
Output:
|
Ein Geschäftssekretär führt die Befehle des Vorstandes aus.
|
task416_mickey_de_sentence_perturbation_generation
|
NIv2
|
fs_opt
| 1
|
validation
|
Instructions: You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. Your task is to label each of the continuous conversations done by one speaker with the emotion detected in that particular part. Your labels can be one among the following: 'No emotion', 'surprise', 'happiness', 'sadness', 'anger', 'disgust'.
Input: Person1: Are you a blogger ?
Person2: Sure I am . I've been writing a blog for almost three years .
Person1: Oh , it seems that I'm the only one who never blogs . When did you get started ?
Person2: I began blogging when I first went to the US for my graduate strides .
Person1: What do you usually write about ?
Person2: At first , I'll write about my life there . Like interesting things on the campus , travel stories , special English words that I come across . Sometimes , I'll post my pictures on my blog so my friends and family can get to know how everything's going .
Person1: That's interesting . How often do you write a blog ?
Person2: It's random . If there happen to be a lot of things going on , I may add several new entries in a week , and if I've got nothing to share , I may leave my blog untouched for weeks .
Person1: Got it . Are you still updating your blog ?
Person2: Sure , since I came back from the US , I've been keeping the habit of blogging , simply to share my personal insights on any topic I like .
Person1: Good for you . I know many people just leave their blogs alone after the first few months .
Output:
|
No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,happiness,No emotion,No emotion,No emotion,happiness
|
task1532_daily_dialog_emotion_classification
|
NIv2
|
zs_opt
| 3
|
train
|
You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. Your task is to label each of the continuous conversations done by one speaker with the emotion detected in that particular part. Your labels can be one among the following: 'No emotion', 'surprise', 'happiness', 'sadness', 'anger', 'disgust'.
[EX Q]: Person1: Which school is your children in ?
Person2: She is now in a private school .
Person1: Oh , it costs too much . It's more expensive than the public school .
Person2: It's idea of my husband . He is always banging the drum for better schools .
Person1: But the private school amount to better schools .
[EX A]: No emotion,No emotion,No emotion,No emotion,No emotion
[EX Q]: Person1: This way , please . We've got a nice private for you .
Person2: That's good . Thank you .
Person1: Here we are . I hope you will like it .
Person2: It's good . It's a nice room .
Person1: And here is the menu . I'll come back soon .
Person2: Thank you .
[EX A]: No emotion,happiness,No emotion,happiness,No emotion,happiness
[EX Q]: Person1: Hello . What can we do for you today ?
Person2: I've just had some money sent from Germany , in Euros .
Person1: OK , could you give me your details and I'll see if it has cleared . We need your banking details and some ID . A passport or something like that ?
Person2: I have my passport right here , and here are the account details . The name , number ...
Person1: Mr Jurgen , yes , the remittance has been successful .
Person2: That was quick ! I didn't expect it to come through so quickly . Yes , that is good news . The full amount should be 20,000 Euros , is that right ? I'd like to withdraw 5,000 Euros worth of local currency , if that's possible .
Person1: Not a problem , Sir . Please fill in this exchange form and show me your passport .
[EX A]:
|
No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion
|
task1532_daily_dialog_emotion_classification
|
NIv2
|
fs_opt
| 6
|
train
|
Detailed Instructions: You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. Your task is to label each of the continuous conversations done by one speaker with the emotion detected in that particular part. Your labels can be one among the following: 'No emotion', 'surprise', 'happiness', 'sadness', 'anger', 'disgust'.
Problem: Person1: How could you have done that without asking me first ?
Person2: I didn't realize you felt so strongly about it .
Person1: Well , you should have thought .
Person2: I'm sorry . I'll ask next time .
Solution:
|
anger,No emotion,No emotion,sadness
|
task1532_daily_dialog_emotion_classification
|
NIv2
|
zs_opt
| 8
|
train
|
Given the task definition and input, reply with output. You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. Your task is to label each of the continuous conversations done by one speaker with the emotion detected in that particular part. Your labels can be one among the following: 'No emotion', 'surprise', 'happiness', 'sadness', 'anger', 'disgust'.
Person1: Hello . This is Doctor Bell ’ s Office . Can I help you ?
Person2: Hi . This is Taylor Wright calling . I ’ Ve got an appointment with Doctor Bell at 9.00 tomorrow morning . I ’ Ve got to cancel this appointment . My father-in-law passed away suddenly last night .
Person1: I ’ m sorry to hear that . Cancelling the appointment is no problem . Thank you for your call .
Person2: Thanks a lot . Good bye .
|
No emotion,No emotion,No emotion,happiness
|
task1532_daily_dialog_emotion_classification
|
NIv2
|
zs_opt
| 5
|
train
|
You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. Your task is to label each of the continuous conversations done by one speaker with the emotion detected in that particular part. Your labels can be one among the following: 'No emotion', 'surprise', 'happiness', 'sadness', 'anger', 'disgust'.
Q: Person1: How's the weather today ?
Person2: It's hot .
Person1: I really don't think this weather will last .
Person2: Let's just hope it doesn't get hotter .
A: No emotion,No emotion,No emotion,No emotion
****
Q: Person1: Well , what a nice day !
Person2: Yeah , the air is really fresh .
Person1: But it was not at all so fine yesterday .
Person2: Because it rained last night .
Person1: Did it ?
Person2: It sure did . It was a heavy storm , with lots of thunder .
Person1: I was fast asleep , and didn't hear a thing .
Person2: Well , it may rain again later today .
Person1: Maybe . I see some dark clouds moving in .
Person2: There may also be a strong wind coming in .
Person1: It'll be dusty , too , I guess .
Person2: Maybe not . Dust is no longer a big problem in Beijing .
Person1: Why is that ?
Person2: We've been planting trees for many years .
Person1: I see . The fall in Beijing is really beautiful .
Person2: But the summer isn't . It's scorching in the summer .
Person1: Then what about spring ?
Person2: Spring is warm and short in Beijing .
Person1: It must be cold in the winter , though .
Person2: You got it . Oh , by the way , it may be really cool in the evening around this time of the year . Don't forget to put on more clothes , or you might catch a cold .
Person1: Thanks for reminding me .
Person2: You're welcome .
A: happiness,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,happiness,happiness
****
Q: Person1: OK , Devon , I've been putting on a few pounds and you're quite a lean fit guy .
Person2: Well , thank you .
Person1: What do you recommend ? What can I do to lose weight ?
Person2: Well , I exercise a lot . I go running at least three times a week . But more than that I enjoy playing sports and so different sports use different muscles and all of it helps to lose that weight that you might have gained .
Person1: Yeah , well , actually , one of the problems is that I actually exercise a lot .
Person2: Do ya ?
Person1: Yeah , so maybe it's my diet .
Person2: It could be and so in that case you might want to eat something perhaps more nutritious or maybe even less of what you do eat . Maybe , I eat three meals a day and I try not to snack in between . No potato chips . No popcorn . No candy bars .
Person1: That's pretty tough !
A:
|
No emotion,happiness,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion
****
|
task1532_daily_dialog_emotion_classification
|
NIv2
|
fs_opt
| 4
|
train
|
You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. Your task is to label each of the continuous conversations done by one speaker with the emotion detected in that particular part. Your labels can be one among the following: 'No emotion', 'surprise', 'happiness', 'sadness', 'anger', 'disgust'.
Example input: Person1: Hey man, you wanna buy some weed?
Person2: Somewhat?
Person1: Weed! You know ? Pot , Ganja , Mary Jane some chronic !
Person2: Oh , umm , no thanks .
Person1: I also have blow if you prefer to do a few lines .
Person2: No , I am ok , really .
Person1: Come on man ! I even got dope and acid ! Try some !
Person2: Do you really have all of these drugs ? Where do you get them from ?
Person1: I got my connections ! Just tell me what you want and I ’ ll even give you one ounce for free .
Person2: Sounds good ! Let ’ s see , I want .
Person1: Yeah ?
Person2: I want you to put your hands behind your head ! You are under arrest!
Example output: fear, disgust, fear, happiness, fear, happiness, fear, disgust, fear, happiness, disgust, fear
Example explanation: The conversation happened between the two people contains the emotions fear, disgust, and happiness. Therefore the labels are in the order.
Q: Person1: You're just left school , haven't you , Emily ?
Person2: Yes , I finished last Friday .
Person1: You sound relieved .
Person2: Well , yes . I don't mind admitting that I am . I enjoyed school , but I did object to having to go in every day once we've done all our exams .
Person1: Well , what are you going to do now ? Have you made any plans ?
Person2: Yes , I intend to go to university.That ' ll be in September.But it all depends on my A level results .
Person1: You mean getting into university actually depends on your passing your A level subjects ?
Person2: Oh , yes .
A:
|
No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion
|
task1532_daily_dialog_emotion_classification
|
NIv2
|
fs_opt
| 3
|
train
|
You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. Your task is to label each of the continuous conversations done by one speaker with the emotion detected in that particular part. Your labels can be one among the following: 'No emotion', 'surprise', 'happiness', 'sadness', 'anger', 'disgust'.
Q: Person1: The air quality in this city is horrendous . The pollution levels are so high that we are not supposed to go outside with a face mask again !
Person2: Exhaust fumes from vehicles cause a great deal of damage to the environment .
Person1: On top of that , there are a few large chemical factories in the suburbs , which are contributing to the high pollution levels in the water and the air in this city .
Person2: As much as I love this city , I think I'm going to find a greener city to live in . Living in a polluted city like this just can't be good for my health .
Person1: I know what you mean . However , there are so few places left that have not been affected by global warming . If it's not the pollution , then it's the natural disasters , deforestation , or the greenhouse effect .
Person2: What is the greenhouse effect exactly ?
Person1: It's the gradual rise in the earth's temperature .
Person2: I see , so it's similar to global warming ?
Person1: They're related to one another , yes .
Person2: I heard that some people in England are pleased with the fact that the climate is becoming warmer because it's making their towns a more pleasant place to live .
Person1: People joke about the benefits of the increase in temperature , but it's not all good news . They've been experiencing a lot of deadly storms there as well .
Person2: People always seem to make jokes as a way to deal with unfortunate situations .
Person1: I think if everyone pitches in , the world will be a better place .
A:
|
No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion
|
task1532_daily_dialog_emotion_classification
|
NIv2
|
zs_opt
| 4
|
train
|
You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. Your task is to label each of the continuous conversations done by one speaker with the emotion detected in that particular part. Your labels can be one among the following: 'No emotion', 'surprise', 'happiness', 'sadness', 'anger', 'disgust'.
Q: Person1: Want to join me for a midnight snack ? I need to grab something to eat .
Person2: Fine with me , but no more chafing dish .
Person1: Let's go to the food stall . There's a good one just around the corner .
Person2: I'd love to try some snacks .
Person1: ( Later .. ) Everything looks tempting . What do you want to have ?
Person2: Kebabs and roast squid .
Person1: Can I have a bite ?
Person2: Help yourself .
Person1: Super !
A: No emotion,No emotion,happiness,happiness,No emotion,No emotion,happiness,happiness,happiness
****
Q: Person1: How's your mother doing ?
Person2: She is so pretty sick .
Person1: That's too bad . I wish your mother can recover soon .
Person2: Thank you .
A: No emotion,No emotion,No emotion,No emotion
****
Q: Person1: Hi , welcome to Hal's Computer World . Can I help you with anything ?
Person2: Yes , I'd like to buy a new computer , but I don't really know much about them . Can you give me any suggestions ?
Person1: No problem . First of all , do you want to get a home computer or a laptop ?
Person2: Laptops are more expensive , right ?
Person1: Yes , they generally cost a little more .
Person2: I'll just get a regular home computer then . I don't think I'll need to lug my computer around with me .
A:
|
No emotion,No emotion,No emotion,No emotion,No emotion,No emotion
****
|
task1532_daily_dialog_emotion_classification
|
NIv2
|
fs_opt
| 4
|
train
|
You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. Your task is to label each of the continuous conversations done by one speaker with the emotion detected in that particular part. Your labels can be one among the following: 'No emotion', 'surprise', 'happiness', 'sadness', 'anger', 'disgust'.
One example: Person1: Hey man, you wanna buy some weed?
Person2: Somewhat?
Person1: Weed! You know ? Pot , Ganja , Mary Jane some chronic !
Person2: Oh , umm , no thanks .
Person1: I also have blow if you prefer to do a few lines .
Person2: No , I am ok , really .
Person1: Come on man ! I even got dope and acid ! Try some !
Person2: Do you really have all of these drugs ? Where do you get them from ?
Person1: I got my connections ! Just tell me what you want and I ’ ll even give you one ounce for free .
Person2: Sounds good ! Let ’ s see , I want .
Person1: Yeah ?
Person2: I want you to put your hands behind your head ! You are under arrest!
Solution is here: fear, disgust, fear, happiness, fear, happiness, fear, disgust, fear, happiness, disgust, fear
Explanation: The conversation happened between the two people contains the emotions fear, disgust, and happiness. Therefore the labels are in the order.
Now, solve this: Person1: Can I use your laptop for a while ?
Person2: Sure , go ahead .
Person1: Oh , isn't your computer Wi-Fi capable ?
Person2: Yes , it is . You want go online ? there are no wi-fi hotspots around .
Person1: Oh my , no internet access is killing me .
Person2: Can't you wait till you get home ? then you can surf the internet using the broadband , wireless connection or whatever you like .
Person1: No , I'm not feeling myself . I just want to check my emails , visit my favorite websites and chat with my friends .
Person2: Now I see , you must be suffering from discomgoogolation .
Person1: What does that mean ? there's nothing wrong with me .
Person2: Well , the term ' discomgoogolation ' comes from ' discombobulate ' and ' google ' . Because floods of information are just a mouse click away , net users are very likely to become addicted to the web .
Person1: That's alright . I just can't bear losing track of all the latest information . It almost drives me crazy .
Person2: Then , you're probably addicted .
Solution:
|
No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion
|
task1532_daily_dialog_emotion_classification
|
NIv2
|
fs_opt
| 6
|
test
|
You will be given a definition of a task first, then some input of the task.
You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. Your task is to label each of the continuous conversations done by one speaker with the emotion detected in that particular part. Your labels can be one among the following: 'No emotion', 'surprise', 'happiness', 'sadness', 'anger', 'disgust'.
Person1: What case do you have against the police ?
Person2: I want to take them to court for arresting me .
Person1: I don ’ t understand .
Person2: There was no reason for them to arrest me .
Person1: They let you go , didn ’ t they ?
Person2: They released me the next morning .
Person1: They detained you at the station ?
Person2: That ’ s exactly what they did .
Person1: Why did they arrest you ?
Person2: They said I matched the description of a robber .
Person1: I get it now .
Person2: I ’ m definitely taking them to court .
Output:
|
No emotion,anger,No emotion,anger,No emotion,anger,No emotion,anger,No emotion,No emotion,No emotion,anger
|
task1532_daily_dialog_emotion_classification
|
NIv2
|
zs_opt
| 1
|
validation
|
In this task if the pronoun is male or gender-neutral you are to replace it with a female pronoun. If there are no pronouns add a female-gendered word to the sentence.
[EX Q]: an health practitioner, born in new york but struggled to go school
[EX A]: An health practitioner, born in New York but struggled to go to school
[EX Q]: Paulina Boenisz was not a medical professional, sir. I don't want you to be under that impression.
[EX A]: paulina boenisz was not a medical professional, byt the way. i don't want you to be under that impression
[EX Q]: Sir, I am Ms. Toluwalase. How are you today?
[EX A]:
|
Sir, I am Toluwalase, how are you today?
|
task1670_md_gender_bias_text_modification
|
NIv2
|
fs_opt
| 6
|
train
|
Detailed Instructions: In this task if the pronoun is male or gender-neutral you are to replace it with a female pronoun. If there are no pronouns add a female-gendered word to the sentence.
Problem:nice,she is really cool.i like that too.
Solution:
|
Nice,that is really cool.I like that too.
|
task1670_md_gender_bias_text_modification
|
NIv2
|
zs_opt
| 8
|
train
|
Detailed Instructions: In this task if the pronoun is male or gender-neutral you are to replace it with a female pronoun. If there are no pronouns add a female-gendered word to the sentence.
Q: Who is your favorite female magician?
A:
|
Who is your favorite magician?
|
task1670_md_gender_bias_text_modification
|
NIv2
|
zs_opt
| 9
|
train
|
In this task if the pronoun is male or gender-neutral you are to replace it with a female pronoun. If there are no pronouns add a female-gendered word to the sentence.
One example: He designed monumental Loviisa war cemetery in 1920.
Solution is here: She designed monumental Lovissa war cemetery in 1920.
Explanation: The masculine pronoun was changed to a feminine pronoun.
Now, solve this: yeah its good, she got so fluent in english that almost any music/movie club wanted her, she also sounded like you
Solution:
|
Yeah its good, she got so fluent in English that almost any music/movie club wanted her
|
task1670_md_gender_bias_text_modification
|
NIv2
|
fs_opt
| 6
|
train
|
In this task if the pronoun is male or gender-neutral you are to replace it with a female pronoun. If there are no pronouns add a female-gendered word to the sentence.
Q: Yes ma'am, the handsome devil successfully fought his way to the east caves.
A: Yes the handsome devil successfully fight way to east caves
****
Q: I love taking books by Jason Nahrung with me to the beauty salon.
A: Have you read any book by Jason Nahrung (Mrs)?
****
Q: No, I haven't, dude. Who was he?
A:
|
No, I haven't. Who was he?
****
|
task1670_md_gender_bias_text_modification
|
NIv2
|
fs_opt
| 4
|
train
|
In this task if the pronoun is male or gender-neutral you are to replace it with a female pronoun. If there are no pronouns add a female-gendered word to the sentence.
[Q]: hi, how are you today, my wife
[A]: hi how you today ma
[Q]: Good. Where do you live? I am in a rural place where I can live with the children I gave birth to in peace.
[A]: good. Where do you live. I am in a rural place.
[Q]: hope your day is treating you well brother Mike; i'm studying some of my music.
[A]:
|
Hope your day is treating you well brother; I'm studying some of my music.
|
task1670_md_gender_bias_text_modification
|
NIv2
|
fs_opt
| 5
|
train
|
In this task if the pronoun is male or gender-neutral you are to replace it with a female pronoun. If there are no pronouns add a female-gendered word to the sentence.
One example: He designed monumental Loviisa war cemetery in 1920.
Solution is here: She designed monumental Lovissa war cemetery in 1920.
Explanation: The masculine pronoun was changed to a feminine pronoun.
Now, solve this: Jim is a very stubborn man , I think his wife accept the behavior
Solution:
|
Why is it that Jim would want to go there?
|
task1670_md_gender_bias_text_modification
|
NIv2
|
fs_opt
| 6
|
train
|
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
In this task if the pronoun is male or gender-neutral you are to replace it with a female pronoun. If there are no pronouns add a female-gendered word to the sentence.
He designed monumental Loviisa war cemetery in 1920.
Solution: She designed monumental Lovissa war cemetery in 1920.
Why? The masculine pronoun was changed to a feminine pronoun.
New input: okay. i'll ask my wife, but what do you think about her?
Solution:
|
Okay. I'll ask my wife, but what do you think about it?
|
task1670_md_gender_bias_text_modification
|
NIv2
|
fs_opt
| 0
|
train
|
In this task if the pronoun is male or gender-neutral you are to replace it with a female pronoun. If there are no pronouns add a female-gendered word to the sentence.
Let me give you an example: He designed monumental Loviisa war cemetery in 1920.
The answer to this example can be: She designed monumental Lovissa war cemetery in 1920.
Here is why: The masculine pronoun was changed to a feminine pronoun.
OK. solve this:
A classic it is madam. Do you play any sports or like any sports?
Answer:
|
A classic. Do you play any sports or like any sports?
|
task1670_md_gender_bias_text_modification
|
NIv2
|
fs_opt
| 8
|
test
|
Definition: In this task if the pronoun is male or gender-neutral you are to replace it with a female pronoun. If there are no pronouns add a female-gendered word to the sentence.
Input: me too, brother, I bought a console. what exactly do you buy online?
Output:
|
Me too, brother. What exactly do you buy online?
|
task1670_md_gender_bias_text_modification
|
NIv2
|
zs_opt
| 2
|
validation
|
In this task, you're given a context, further information available on a particular linked term from the statement, and an answer term. Your job is to generate a question that can use the information provided to obtain the given answer. You should use the information on both context and link information to create the question. Note that the answer to the question should be exactly the given answer, and if the answer is none, the answer to the question shouldn't be obtainable from the context or linked information.
Example input: Context: During Operation Market Garden, the attempt to seize a bridgehead across the Rhine in the Netherlands, the 704th dropped supplies to allied troops near Nijmegen. Link Information: Operation Market Garden was a failed World War II military operation fought in the Netherlands from 17 to 25 September 1944. Answer: from 17 to 25 September 1944
Example output: When did the operation during which the 704th dropped supplies to allied troops near Nijmegen begin?
Example explanation: The context describes the 704th's actions during Operation Market Garden, and the answer specifies when the operation happened.
Q: Context: ngineers filled the lead-in time with a short segment of a televised game between the Philadelphia Phillies and the Chicago Cubs at Wrigley Field. T Link Information: Chicago Cubs at Wrigley Field. Answer: baseball
A:
|
What sport was broadcast from Wrigley Field?
|
task235_iirc_question_from_subtext_answer_generation
|
NIv2
|
fs_opt
| 3
|
train
|
In this task, you're given a context, further information available on a particular linked term from the statement, and an answer term. Your job is to generate a question that can use the information provided to obtain the given answer. You should use the information on both context and link information to create the question. Note that the answer to the question should be exactly the given answer, and if the answer is none, the answer to the question shouldn't be obtainable from the context or linked information.
Q: Context: Cheap calico prints, imported by the East India Company from Hindustān (India), had become popular. Link Information:
The company received a Royal Charter from Queen Elizabeth I on 31 December 1600 Answer: 31 December 1600
A: What year was the company that imported calico prints to England founded?
****
Q: Context: Nirvana insisted on signing an extended contract with Sub Pop, making the band the first to do so with the label. Link Information: The label's roster includes Fleet Foxes, Foals, Beach House, The Postal Service, Flight of the Conchords, Sleater-Kinney, Blitzen Trapper, Father John Misty, Shabazz Palaces, METZ, Rolling Blackouts Coastal Fever, and The Shins. Answer: Fleet Foxes, Foals, Beach House, The Postal Service, Flight of the Conchords, Sleater-Kinney, Blitzen Trapper, Father John Misty, Shabazz Palaces, METZ, Rolling Blackouts Coastal Fever, and The Shins.
A: What other bands signed with Sub Pop?
****
Q: Context: kids' lineup ( Link Information: Pokémon Answer: Sonic the Hedgehog
A:
|
Which of the childrens' shows featuring a character from video games, had their debut video game first?
****
|
task235_iirc_question_from_subtext_answer_generation
|
NIv2
|
fs_opt
| 4
|
train
|
Detailed Instructions: In this task, you're given a context, further information available on a particular linked term from the statement, and an answer term. Your job is to generate a question that can use the information provided to obtain the given answer. You should use the information on both context and link information to create the question. Note that the answer to the question should be exactly the given answer, and if the answer is none, the answer to the question shouldn't be obtainable from the context or linked information.
Q: Context: Laizāns started his career with Skonto FC and moved to the Russian team CSKA Moscow in 2000. Link Information: he club is the best known part of the CSKA Moscow sports club.
Founded in 1911, Answer: CSKA Moscow
A:
|
Which club that Laizans played for in his early career was found first?
|
task235_iirc_question_from_subtext_answer_generation
|
NIv2
|
zs_opt
| 9
|
train
|
In this task, you're given a context, further information available on a particular linked term from the statement, and an answer term. Your job is to generate a question that can use the information provided to obtain the given answer. You should use the information on both context and link information to create the question. Note that the answer to the question should be exactly the given answer, and if the answer is none, the answer to the question shouldn't be obtainable from the context or linked information.
One example is below.
Q: Context: During Operation Market Garden, the attempt to seize a bridgehead across the Rhine in the Netherlands, the 704th dropped supplies to allied troops near Nijmegen. Link Information: Operation Market Garden was a failed World War II military operation fought in the Netherlands from 17 to 25 September 1944. Answer: from 17 to 25 September 1944
A: When did the operation during which the 704th dropped supplies to allied troops near Nijmegen begin?
Rationale: The context describes the 704th's actions during Operation Market Garden, and the answer specifies when the operation happened.
Q: Context: Disney+, launched in November 2019 Link Information: none Answer: none
A:
|
Who owned more wealth when Disney+ was launched, Bob Iger or Rupert Murdoch?
|
task235_iirc_question_from_subtext_answer_generation
|
NIv2
|
fs_opt
| 9
|
train
|
Definition: In this task, you're given a context, further information available on a particular linked term from the statement, and an answer term. Your job is to generate a question that can use the information provided to obtain the given answer. You should use the information on both context and link information to create the question. Note that the answer to the question should be exactly the given answer, and if the answer is none, the answer to the question shouldn't be obtainable from the context or linked information.
Input: Context: The experimental results obtained by von Braun created interest among Germany's aircraft manufacturers, including Heinkel and Messerschmitt, and in 1939, the Heinkel He 176 became the first aircraft to fly on liquid-fuelled rocket power alone. Link Information: none Answer: none
Output:
|
Who was the head of Heinkel when the Heinkel He 176 first flew?
|
task235_iirc_question_from_subtext_answer_generation
|
NIv2
|
zs_opt
| 2
|
train
|
In this task, you're given a context, further information available on a particular linked term from the statement, and an answer term. Your job is to generate a question that can use the information provided to obtain the given answer. You should use the information on both context and link information to create the question. Note that the answer to the question should be exactly the given answer, and if the answer is none, the answer to the question shouldn't be obtainable from the context or linked information.
Input: Consider Input: Context: There in 1960 he had a short-lived marriage to Alice McLeod (later known as Alice Coltrane), who bore him a daughter. Link Information: Alice Coltrane (née McLeod, August 27, 1937 – January 12, 2007) Answer: August 27, 1937
Output: When was the mother of Hagood's daughter born?
Input: Consider Input: Context: A month later, Weiss released Into It Over It's first studio album, Proper on No Sleep Records, produced by Ed Rose. Link Information: none Answer: none
Output: How many albums did the producer of "Proper" produce?
Input: Consider Input: Context: In 1976 church president Neil Albert Salonen met with Senator Bob Dole to defend the Unification Church against charges made by its critics Link Information:
Neil Albert Salonen (born 1946) Answer: Bob Dole
|
Output: Which of the two men who met in 1976 over charges made against the church was older at the time?
|
task235_iirc_question_from_subtext_answer_generation
|
NIv2
|
fs_opt
| 2
|
train
|
TASK DEFINITION: In this task, you're given a context, further information available on a particular linked term from the statement, and an answer term. Your job is to generate a question that can use the information provided to obtain the given answer. You should use the information on both context and link information to create the question. Note that the answer to the question should be exactly the given answer, and if the answer is none, the answer to the question shouldn't be obtainable from the context or linked information.
PROBLEM: Context: Their score for the movie included an instrumental selection titled "Cotton's Dream", which was later rescored to become the theme song of the soap opera The Young and the Restless; Link Information: First broadcast on March 26, 1973, The Young and the Restless was originally broadcast as half-hour episodes Answer: March 26, 1973
SOLUTION: When did the soap opera that used the song "Cotton's Dream" as it's theme first air?
PROBLEM: Context: Since its debut in 1969, Sesame Street had given Jim Henson's Muppet characters exposure Link Information: James Maury Henson (September 24, 1936 – May 16, 1990) was an American puppeteer, animator, cartoonist, actor, inventor, filmmaker, and screenwriter who achieved worldwide notice as the creator of The Muppets (1955–present) Answer: 14
SOLUTION: How long before the debut on "Sesame Street" had Jim Henson created the Muppets?
PROBLEM: Context: LeBron Raymone James Sr. (; born December 30, 1984) Link Information: Michael Jeffrey Jordan (born February 17, 1963 Answer: 21
SOLUTION:
|
How old was Michael Jordan the year LeBron James was born?
|
task235_iirc_question_from_subtext_answer_generation
|
NIv2
|
fs_opt
| 8
|
train
|
In this task, you're given a context, further information available on a particular linked term from the statement, and an answer term. Your job is to generate a question that can use the information provided to obtain the given answer. You should use the information on both context and link information to create the question. Note that the answer to the question should be exactly the given answer, and if the answer is none, the answer to the question shouldn't be obtainable from the context or linked information.
[Q]: Context: the First Carlist War, a civil war between supporters of the Spanish regent Maria Christina, known as liberals, and those of the late king's brother Carlos of Borbón, known as Carlists. Link Information: The city was untouched by the Second Carlist War, which took place mostly in Catalonia, Answer: 6
[A]: How many years passed between the First Carlist War and the war that mostly in Catalonia?
[Q]: Context: Power appeared as Mr. T in the first season of Epic Rap Battles of History Link Information:
The 15th episode, called "The Final Battle", marked the end of the first season. Answer: 15
[A]: How many episodes were in the first season of the show Power rapped for as Mr. T?
[Q]: Context: Bellinger's first major league hit was an infield single off Neil Ramírez in the ninth inning of the same game Link Information: San Francisco Giants.During the 2016 offseason, Ramírez signed a minor league contract with the San Francisco Giants. He was designated for assignment on April 30, 2017, to create room for Bryan Morris who had his contract purchased from Triple-A.
Toronto Blue Jays.On May 4, 2017, Ramírez was claimed off waivers by the Toronto Blue Jays. He was designated for assignment on May 9 without having thrown a pitch for the Blue Jays. On May 14, Ramírez elected free agency after being outrighted to the minor leagues.
Answer: Toronto Blue Jays
[A]:
|
What team did Neil Ramirez play for when Bellinger hit his first major league hit off of him?
|
task235_iirc_question_from_subtext_answer_generation
|
NIv2
|
fs_opt
| 5
|
train
|
Detailed Instructions: In this task, you're given a context, further information available on a particular linked term from the statement, and an answer term. Your job is to generate a question that can use the information provided to obtain the given answer. You should use the information on both context and link information to create the question. Note that the answer to the question should be exactly the given answer, and if the answer is none, the answer to the question shouldn't be obtainable from the context or linked information.
Q: Context: She was nominated for the Best Child Actor - Female in 13th Indian Telly Awards 2014. Link Information: none Answer: none
A:
|
Who won the award for which Walia was nominated in 2014?
|
task235_iirc_question_from_subtext_answer_generation
|
NIv2
|
zs_opt
| 9
|
test
|
In this task, you're given a context, further information available on a particular linked term from the statement, and an answer term. Your job is to generate a question that can use the information provided to obtain the given answer. You should use the information on both context and link information to create the question. Note that the answer to the question should be exactly the given answer, and if the answer is none, the answer to the question shouldn't be obtainable from the context or linked information.
Example Input: Context: On his second visit to Guatemala, in 1537, friar Bartolome de las Casas, O.P. wanted to employ his new method of conversion based on two principles Link Information: Bartolomé de las Casas ( , ; 1484 – 18 July 1566) Answer: 53
Example Output: How old was Bartolome de las Casas during his second Guatemala visit?
Example Input: Context: State banks such as the State Housing Bank, the State Educational Loan Fund and Postbanken allowed for governmental control over private debt. Link Information: The agency is based in Drammen and was created by a 1946 law. Answer: State Housing Bank
Example Output: Which state bank is older, the State Housing Bank or Postbanken?
Example Input: Context: One Direction performed the track on The Today Show at the Rockefeller Center on 13 November 2012, to a record crowd estimated at 15,000. " Link Information: One Direction performed the track on The Today Show at the Rockefeller Center on 13 November 2012, to a record crowd estimated at 15,000. Answer: Ann Curry
Example Output:
|
Who were the hosts of the show when One Direction performed on November 13 2012 at Rockefeller Center?
|
task235_iirc_question_from_subtext_answer_generation
|
NIv2
|
fs_opt
| 3
|
validation
|
Given the task definition and input, reply with output. In this task, you are given an item and you need to check whether it is edible or not, return 1 if it is edible, else return 2.
Pastry
|
1
|
task1149_item_check_edible
|
NIv2
|
zs_opt
| 5
|
train
|
In this task, you are given an item and you need to check whether it is edible or not, return 1 if it is edible, else return 2.
Example: Glass
Example solution: 2
Example explanation: Glass is inedible.
Problem: Chocolate
|
Solution: 1
|
task1149_item_check_edible
|
NIv2
|
fs_opt
| 5
|
train
|
Teacher: In this task, you are given an item and you need to check whether it is edible or not, return 1 if it is edible, else return 2.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Glass
Solution: 2
Reason: Glass is inedible.
Now, solve this instance: toilet
Student:
|
2
|
task1149_item_check_edible
|
NIv2
|
fs_opt
| 2
|
train
|
In this task, you are given an item and you need to check whether it is edible or not, return 1 if it is edible, else return 2.
Ex Input:
Bagels
Ex Output:
1
Ex Input:
cat
Ex Output:
2
Ex Input:
bed
Ex Output:
|
2
|
task1149_item_check_edible
|
NIv2
|
fs_opt
| 1
|
train
|
Instructions: In this task, you are given an item and you need to check whether it is edible or not, return 1 if it is edible, else return 2.
Input: toothbrush
Output:
|
2
|
task1149_item_check_edible
|
NIv2
|
zs_opt
| 3
|
train
|
In this task, you are given an item and you need to check whether it is edible or not, return 1 if it is edible, else return 2.
dog
|
2
|
task1149_item_check_edible
|
NIv2
|
zs_opt
| 0
|
train
|
In this task, you are given an item and you need to check whether it is edible or not, return 1 if it is edible, else return 2.
dog
2
Beans
1
handbag
|
2
|
task1149_item_check_edible
|
NIv2
|
fs_opt
| 0
|
train
|
In this task, you are given an item and you need to check whether it is edible or not, return 1 if it is edible, else return 2.
Let me give you an example: Glass
The answer to this example can be: 2
Here is why: Glass is inedible.
OK. solve this:
giraffe
Answer:
|
2
|
task1149_item_check_edible
|
NIv2
|
fs_opt
| 8
|
train
|
In this task, you are given an item and you need to check whether it is edible or not, return 1 if it is edible, else return 2.
--------
Question: Burger
Answer: 1
Question: sports ball
Answer: 2
Question: Sandwich
Answer:
|
1
|
task1149_item_check_edible
|
NIv2
|
fs_opt
| 7
|
test
|
In this task, you are given an item and you need to check whether it is edible or not, return 1 if it is edible, else return 2.
One example is below.
Q: Glass
A: 2
Rationale: Glass is inedible.
Q: Hazelnut
A:
|
1
|
task1149_item_check_edible
|
NIv2
|
fs_opt
| 9
|
validation
|
Teacher:Given a sentence in French, provide an equivalent paraphrased translation in Spanish that retains the same meaning both through the translation and the paraphrase.
Teacher: Now, understand the problem? Solve this instance: Tabda, également connue sous le nom de Tabto, est une ville de la région de Jubbada Hoose (Juba inférieur), au sud de la Somalie.
Student:
|
Tabda, también conocida como Tabto, es una ciudad en la región sur de Jubbada Hoose (Lower Juba) de Somalia.
|
task791_pawsx_french_spanish_translation
|
NIv2
|
zs_opt
| 6
|
train
|
Teacher:Given a sentence in French, provide an equivalent paraphrased translation in Spanish that retains the same meaning both through the translation and the paraphrase.
Teacher: Now, understand the problem? Solve this instance: Il est recouvert d'une végétation naturelle de prairies aux bases d'argile rouge moins fertiles et de buissons de Salines sur des terres plus fertiles.
Student:
|
Está cubierto por una vegetación natural de pastizales de suelos de arcilla roja menos fértiles, y matorrales de matorrales en tierras más fértiles.
|
task791_pawsx_french_spanish_translation
|
NIv2
|
zs_opt
| 6
|
train
|
Given a sentence in French, provide an equivalent paraphrased translation in Spanish that retains the same meaning both through the translation and the paraphrase.
La plupart des séries antérieures à 1976 produites par CBS ou distribuées par CBS Films ont ensuite été distribuées par Viacom et Paramount Television.
|
La mayoría de las series producidas por CBS antes de 1976 o distribuidas por películas de CBS fueron distribuidas posteriormente por Viacom y Paramount Television.
|
task791_pawsx_french_spanish_translation
|
NIv2
|
zs_opt
| 0
|
train
|
Given a sentence in French, provide an equivalent paraphrased translation in Spanish that retains the same meaning both through the translation and the paraphrase.
Example: La saison NBA 1975 - 76 était la 30e saison de la National Basketball Association.
Example solution: La temporada 1975 - 76 de la Asociación Nacional de Baloncesto fue la temporada 30 de la NBA.
Example explanation: This is a correct and accurate translation from French to Spanish because the translated paraphrase retains the main message that between the years 1975-1976, the 30th NBA season occurred.
Problem: Pérez a également pratiqué avec Telemundo, où elle a ancré et produit un segment de divertissement pour Telemundo Internacional.
|
Solution: Pérez también realizó una pasantía con Telemundo donde produjo y presentó un segmento de entretenimiento para Telemundo Internacional.
|
task791_pawsx_french_spanish_translation
|
NIv2
|
fs_opt
| 5
|
train
|
Detailed Instructions: Given a sentence in French, provide an equivalent paraphrased translation in Spanish that retains the same meaning both through the translation and the paraphrase.
Q: La rivière Bota Mare est un affluent de la rivière Zăbrătău en Roumanie.
A:
|
El río Bota Mare es un afluente del río Zăbrătău en Rumania.
|
task791_pawsx_french_spanish_translation
|
NIv2
|
zs_opt
| 9
|
train
|
Detailed Instructions: Given a sentence in French, provide an equivalent paraphrased translation in Spanish that retains the same meaning both through the translation and the paraphrase.
Problem:Pelmus a été exposé dans des musées en Roumanie, en France, en Allemagne, en Israël, au Canada, en Autriche, au Chili et au Brésil, y compris cinq expositions personnelles.
Solution:
|
Pelmus ha sido exhibido en museos de Rumania, Francia, Alemania, Israel, Canadá, Austria, Chile y Brasil, incluyendo cinco exposiciones individuales.
|
task791_pawsx_french_spanish_translation
|
NIv2
|
zs_opt
| 8
|
train
|
Given a sentence in French, provide an equivalent paraphrased translation in Spanish that retains the same meaning both through the translation and the paraphrase.
Let me give you an example: La saison NBA 1975 - 76 était la 30e saison de la National Basketball Association.
The answer to this example can be: La temporada 1975 - 76 de la Asociación Nacional de Baloncesto fue la temporada 30 de la NBA.
Here is why: This is a correct and accurate translation from French to Spanish because the translated paraphrase retains the main message that between the years 1975-1976, the 30th NBA season occurred.
OK. solve this:
Kevin Lepage a commencé troisième, Terry Labonte comme quatrième et Robby Gordon s'est qualifié comme cinquième.
Answer:
|
Kevin Lepage comenzó tercero, Terry Labonte cuarto, y Robby Gordon calificó quinto.
|
task791_pawsx_french_spanish_translation
|
NIv2
|
fs_opt
| 8
|
train
|
Definition: Given a sentence in French, provide an equivalent paraphrased translation in Spanish that retains the same meaning both through the translation and the paraphrase.
Input: Briggs rencontra Briggs plus tard au Festival de Monterey Pop en 1967, où Ravi Shankar se produisait également, avec Eric Burdon et The Animals.
Output:
|
Briggs conoció a Briggs más tarde en el Monterey Pop Festival de 1967, donde Ravi Shankar también actuó con Eric Burdon y The Animals.
|
task791_pawsx_french_spanish_translation
|
NIv2
|
zs_opt
| 2
|
train
|
Detailed Instructions: Given a sentence in French, provide an equivalent paraphrased translation in Spanish that retains the same meaning both through the translation and the paraphrase.
Problem:Après son licenciement, il a quitté l'Allemagne pour le Nouveau-Mexique, puis pour Los Angeles, puis pour San Francisco.
Solution:
|
Después de su baja, se mudó de Alemania a Nuevo México y luego a Los Ángeles y luego a San Francisco.
|
task791_pawsx_french_spanish_translation
|
NIv2
|
zs_opt
| 8
|
test
|
Given a sentence in French, provide an equivalent paraphrased translation in Spanish that retains the same meaning both through the translation and the paraphrase.
Input: Consider Input: Après la mort de Fred Miller en 1998 et de John Paul Miller en 2000, Mary Miller a continué à vivre dans la maison située au sud de Cleveland.
Output: Después de la muerte de Fred Miller en 1998 y de John Paul Miller en 2000, Mary Miller continuó viviendo en la casa ubicada al sur de Cleveland.
Input: Consider Input: Le traitement comprenait une relaxation musculaire progressive, une thérapie d’exposition cognitive avec une restructuration interoceptive ou une combinaison des deux.
Output: El tratamiento incluyó relajación muscular progresiva, terapia de exposición cognitiva con reestructuración interoceptiva o una combinación de ambas.
Input: Consider Input: En 1406, il avait ajouté le Codex Juliana Anicia de Dioscurides, un rebond, une table des matières et un scholia de Minuskel en grec byzantin largement restauré.
|
Output: En 1406, se le agregó a Juliana Anicia el Códice de Dioscurides, se recuperó, y se restauró una tabla de contenido y escolia minúscula en el extenso griego bizantino.
|
task791_pawsx_french_spanish_translation
|
NIv2
|
fs_opt
| 2
|
validation
|
In this task you are given a list of integers and you need to find the absolute value of the difference between each two consecutive values. The output should be a list of the absolute value of the differences of each two consecutive values.
[-73, 2, -96, 61, 81, 25, 76, -66, -98, -73]
[75, 98, 157, 20, 56, 51, 142, 32, 25]
[77, -82, 6, -98, -87]
[159, 88, 104, 11]
[-3, 99, -80]
|
[102, 179]
|
task125_conala_pair_differences
|
NIv2
|
fs_opt
| 0
|
train
|
Q: In this task you are given a list of integers and you need to find the absolute value of the difference between each two consecutive values. The output should be a list of the absolute value of the differences of each two consecutive values.
[16, -98, -95, 63, 11, -99, -52, -68, 75, 85, -86, -56]
A:
|
[114, 3, 158, 52, 110, 47, 16, 143, 10, 171, 30]
|
task125_conala_pair_differences
|
NIv2
|
zs_opt
| 7
|
train
|
Given the task definition and input, reply with output. In this task you are given a list of integers and you need to find the absolute value of the difference between each two consecutive values. The output should be a list of the absolute value of the differences of each two consecutive values.
[66, -69, -73, -25, -6]
|
[135, 4, 48, 19]
|
task125_conala_pair_differences
|
NIv2
|
zs_opt
| 5
|
train
|
Definition: In this task you are given a list of integers and you need to find the absolute value of the difference between each two consecutive values. The output should be a list of the absolute value of the differences of each two consecutive values.
Input: [84, 96, -2]
Output:
|
[12, 98]
|
task125_conala_pair_differences
|
NIv2
|
zs_opt
| 2
|
train
|
In this task you are given a list of integers and you need to find the absolute value of the difference between each two consecutive values. The output should be a list of the absolute value of the differences of each two consecutive values.
Input: Consider Input: [19, 25, 72, -51, 25, 95, 97, 27, -8, -69, 35, 29, -24]
Output: [6, 47, 123, 76, 70, 2, 70, 35, 61, 104, 6, 53]
Input: Consider Input: [44, -94]
Output: [138]
Input: Consider Input: [92, 98, 4, 73, -40, 91, 15, -7]
|
Output: [6, 94, 69, 113, 131, 76, 22]
|
task125_conala_pair_differences
|
NIv2
|
fs_opt
| 2
|
train
|
Teacher: In this task you are given a list of integers and you need to find the absolute value of the difference between each two consecutive values. The output should be a list of the absolute value of the differences of each two consecutive values.
Teacher: Now, understand the problem? If you are still confused, see the following example:
[7, 1, 5, 8, -4]
Solution: [6, 4, 3, 12]
Reason: The output is a list of the absolute value of the differences of every two consecutive values. So this is a good example.
Now, solve this instance: [-17, -24, -77, 29]
Student:
|
[7, 53, 106]
|
task125_conala_pair_differences
|
NIv2
|
fs_opt
| 2
|
train
|
Q: In this task you are given a list of integers and you need to find the absolute value of the difference between each two consecutive values. The output should be a list of the absolute value of the differences of each two consecutive values.
[94, 24, 17, 71, 78, 30, -69, -16, 78, -91, 35]
A:
|
[70, 7, 54, 7, 48, 99, 53, 94, 169, 126]
|
task125_conala_pair_differences
|
NIv2
|
zs_opt
| 7
|
train
|
In this task you are given a list of integers and you need to find the absolute value of the difference between each two consecutive values. The output should be a list of the absolute value of the differences of each two consecutive values.
Q: [90, -94, 16, 60, 4, -58, -7, -63, -65, 28, -4]
A:
|
[184, 110, 44, 56, 62, 51, 56, 2, 93, 32]
|
task125_conala_pair_differences
|
NIv2
|
zs_opt
| 4
|
train
|
In this task you are given a list of integers and you need to find the absolute value of the difference between each two consecutive values. The output should be a list of the absolute value of the differences of each two consecutive values.
One example is below.
Q: [7, 1, 5, 8, -4]
A: [6, 4, 3, 12]
Rationale: The output is a list of the absolute value of the differences of every two consecutive values. So this is a good example.
Q: [-83, 68, 73, -92, -18]
A:
|
[151, 5, 165, 74]
|
task125_conala_pair_differences
|
NIv2
|
fs_opt
| 9
|
test
|
In this task you are given a list of integers and you need to find the absolute value of the difference between each two consecutive values. The output should be a list of the absolute value of the differences of each two consecutive values.
[EX Q]: [80, 0, -38, 3, 36, -25, -86, 83, -35, -77, -96, -43, -76, -97]
[EX A]: [80, 38, 41, 33, 61, 61, 169, 118, 42, 19, 53, 33, 21]
[EX Q]: [88, 45]
[EX A]: [43]
[EX Q]: [26, 72, 71, 40, -67, -83, -61, 14, 96, 21, 86]
[EX A]:
|
[46, 1, 31, 107, 16, 22, 75, 82, 75, 65]
|
task125_conala_pair_differences
|
NIv2
|
fs_opt
| 6
|
validation
|
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