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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:... | 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... | 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 Com... | 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. Ge... | 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:
P... | 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: Y... | 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 l... | 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. Ge... | 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 Com... | 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: V... | 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 wit... | 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... | 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 giv... | 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 bea... | 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... | 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 f... | 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 lan... | 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)... | 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... | 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 doin... | "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 Finnis... | 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 Finnis... | 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 t... | 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)... | 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)... | 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 Fin... | "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 bei... | 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 bei... | 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 probabi... | 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 reasonabl... | 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 probabili... | 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 bei... | 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 probabil... | 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 reasonabl... | 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 bei... | 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 hi... | 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 emot... | 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', 'surpris... | 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:... | 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 label... | 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', 'surpris... | 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', 'surpris... | 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', 'surpris... | 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', 'surpris... | 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', 'surpris... | 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 partic... | 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 sch... | 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: T... | 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:... | 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... | 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: T... | 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... | 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... | 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 q... | 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 q... | 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 info... | 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 q... | 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 ... | 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 q... | 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 informatio... | 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 q... | 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 info... | 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 q... | 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... | 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 fe... | 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 Nacion... | 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 B... | 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 tempor... | 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 A... | 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.
Solu... | 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 ... | 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, 3... | [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, -... | [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, 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 ... | [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 outp... | [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... | [46, 1, 31, 107, 16, 22, 75, 82, 75, 65]
| task125_conala_pair_differences | NIv2 | fs_opt | 6 | validation |
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