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What key details about eledath thaikkattu neelakandan mooss can be extracted from the following bio? Bio: eledath thaikkattu neelakandan mooss or e.t.neelakandan mooss is an ayurvedic physician and the founder of vaidyaratnam group .
The answer to this question is: | - website is -lsb- http://www.vaidyaratnammooss.com]- death place is ollur , thrissur- residence is ollur , thrissur- employer is vaidyaratnam oushadhasala- resting place is ollur , thrissur- caption is portrait of neelakandan mooss at vaidyaratnam nursing home- death date is 1997- parents is e. t. narayanan mooss- spo... | wiki_bio_key_content | P3 | zs_noopt | 7 | train |
What key details about sally bercow can be extracted from the following bio? Bio: sally kate bercow -lrb- née illman ; born 22 november 1969 -rrb- is the wife of the current speaker of the house of commons , john bercow .
The answer to this question is: | - years active is 2002-present- birth name is sally kate illman- monarch is elizabeth ii- office is wife speaker of the house of commons- birth date is 22 november 1969- term start is 22 june 2009- name is sally bercow- birth place is sutton , london , england | wiki_bio_key_content | P3 | zs_noopt | 7 | train |
Q:What key details about mauro zironelli can be extracted from the following bio? Bio: mauro zironelli -lrb- born january 21 , 1970 in thiene -rrb- is an italian professional football coach and a former player . whilst at fiorentina he played in the 1990 uefa cup final .
A: | - clubs is fiorentina thiene montecchio maggiore pescara vicenza pescara fiorentina chievo venezia chievo modena- caps is 38 23 21 8 26 14 10 21 27 81 28- position is midfielder- managerclubs is vicenza -lrb- youth -rrb- bassano virtus -lrb- youth -rrb-- years is 1989 1992 -- 1993 1993 -- 1994 1994 -- 1995 1995 -- -- 1... | wiki_bio_key_content | P3 | zs_noopt | 3 | train |
Answer the following question: What key details about jim carr -lrb- education -rrb- can be extracted from the following bio? Bio: jim carr -lrb- born december 20 , 1969 -rrb- is vice president of digital media for media general , inc. , a publicly traded broadcast and digital media company headquartered in richmond ... | - birth date is 20 december 1969- name is jim carr- image size is 120px- birth place is rochester , michigan , u.s. usa- occupation is digital strategist , online producer , entrepreneur | wiki_bio_key_content | P3 | zs_opt | 5 | train |
Given the question: What key details about louis-philippe brodeur can be extracted from the following bio? Bio: louis-philippe brodeur , baptised louis-joseph-alexandre brodeur -lrb- august 21 , 1862 -- january 1 , 1924 -rrb- was a canadian journalist , lawyer , politician , federal cabinet minister , and puisne just... | - party is liberal- monarch is george v- predecessor is george auguste gigault désiré girouard charles fitzpatrick- governor general is the viscount byng of vimy- birth date is 21 august 1862- profession is politician- parliament is canadian- order is 13th- death date is 1 january 1924- spouse is emma brillon 1887- off... | wiki_bio_key_content | P3 | zs_noopt | 6 | train |
Given the question: What key details about charles matthau can be extracted from the following bio? Bio: charles `` charlie '' matthau -lrb- born december 10 , 1962 -rrb- is a film and television director and actor and the son of actor walter matthau and actress/author carol saroyan .
The answer is: | - years active is 1973 & ndash ; present- caption is matthau '' freaky deaky '' at the 2012 tribeca film festival premiere of- birth name is charles marcus matthau- spouse is michele 2004 & ndash ; present -rrb- bauer -lrb- divorced -rrb- ashley l. anderson -lrb-- birth date is 10 december 1962- name is charles matthau... | wiki_bio_key_content | P3 | zs_opt | 6 | train |
Please answer the following question: What key details about olexandr nadtoka can be extracted from the following bio? Bio: oleksandr oleksandrovich nadtoka -lrb- ; born 6 march 1991 -rrb- is a ukrainian rower . he won the gold medal in the quadruple sculls at the 2014 world rowing championships in amsterdam .
Answer... | - headercolor is lightsteelblue- birth date is 6 march 1991- name is olexandr nadtoka- birth place is zaporizhia , ukraine | wiki_bio_key_content | P3 | zs_opt | 9 | train |
What key details about carlos tejeda can be extracted from the following bio? Bio: carlos tejeda -lrb- born july 29 , 1980 -rrb- is a volleyball player from venezuela , who won the gold medal with the men 's national team at the 2003 pan american games in santo domingo , dominican republic playing as a wing-spiker . ... | - name is carlos tejeda- medaltemplates is men 's volleyball- birth date is july 29 , 1980 | wiki_bio_key_content | P3 | zs_noopt | 0 | train |
Answer the following question: What key details about viktoria modesta can be extracted from the following bio? Bio: viktoria modesta -lrb- born on 25 february 1987 as viktorija moskaļova in daugavpils , latvia -rrb- is a latvian singer-songwriter and model .
Answer: | - birth name is viktorija moskaļova- genre is electronic , pop- alias is viktoria modesta- birth date is 25 february 1987- name is viktoria modesta- birth place is daugavpils , latvia- occupation is singer-songwriter , artist , model | wiki_bio_key_content | P3 | zs_opt | 5 | test |
What key details about thamizhavel g. sarangapani can be extracted from the following bio? Bio: thamizhavel g. sarangapani , -lrb- , 19 april 1903 -- 16 march 1974 -rrb- or `` kosa '' as he was also known , a tamil writer and publisher , was born in thiruvarur , tamil nadu , on 20 april 1903 . he received a good educ... | - death date is 16 march 1974- agent is tamil murasu- alias is ko.sa- birth date is april 19 , 1903- name is thamizhavel g. sarangapani- birth place is thiruvarur , tamil nadu india- occupation is tamil journalist , writer , publisher | wiki_bio_key_content | P3 | zs_opt | 1 | validation |
You will be given a definition of a task first, then some input of the task.
Given the prompt and a response, classify the them to "yes" if response is "yes, and" type. Otherwise classify it as "no". "Yes, and" is a rule-of-thumb in improvisational comedy that suggests that a participant in a dialogue should accept wha... | no | task361_spolin_yesand_prompt_response_classification | NIv2 | zs_opt | 1 | train |
Teacher: Given the prompt and a response, classify the them to "yes" if response is "yes, and" type. Otherwise classify it as "no". "Yes, and" is a rule-of-thumb in improvisational comedy that suggests that a participant in a dialogue should accept what another participant has stated ("Yes") and then expand on that lin... | yes | task361_spolin_yesand_prompt_response_classification | NIv2 | fs_opt | 2 | train |
Given the prompt and a response, classify the them to "yes" if response is "yes, and" type. Otherwise classify it as "no". "Yes, and" is a rule-of-thumb in improvisational comedy that suggests that a participant in a dialogue should accept what another participant has stated ("Yes") and then expand on that line of thou... | yes
| task361_spolin_yesand_prompt_response_classification | NIv2 | fs_opt | 7 | train |
Detailed Instructions: Given the prompt and a response, classify the them to "yes" if response is "yes, and" type. Otherwise classify it as "no". "Yes, and" is a rule-of-thumb in improvisational comedy that suggests that a participant in a dialogue should accept what another participant has stated ("Yes") and then expa... | yes | task361_spolin_yesand_prompt_response_classification | NIv2 | zs_opt | 8 | train |
Part 1. Definition
Given the prompt and a response, classify the them to "yes" if response is "yes, and" type. Otherwise classify it as "no". "Yes, and" is a rule-of-thumb in improvisational comedy that suggests that a participant in a dialogue should accept what another participant has stated ("Yes") and then expand o... | no | task361_spolin_yesand_prompt_response_classification | NIv2 | fs_opt | 7 | train |
instruction:
Given the prompt and a response, classify the them to "yes" if response is "yes, and" type. Otherwise classify it as "no". "Yes, and" is a rule-of-thumb in improvisational comedy that suggests that a participant in a dialogue should accept what another participant has stated ("Yes") and then expand on that... | yes
| task361_spolin_yesand_prompt_response_classification | NIv2 | fs_opt | 9 | train |
Definition: Given the prompt and a response, classify the them to "yes" if response is "yes, and" type. Otherwise classify it as "no". "Yes, and" is a rule-of-thumb in improvisational comedy that suggests that a participant in a dialogue should accept what another participant has stated ("Yes") and then expand on that ... | no | task361_spolin_yesand_prompt_response_classification | NIv2 | zs_opt | 2 | train |
Given the prompt and a response, classify the them to "yes" if response is "yes, and" type. Otherwise classify it as "no". "Yes, and" is a rule-of-thumb in improvisational comedy that suggests that a participant in a dialogue should accept what another participant has stated ("Yes") and then expand on that line of thou... | yes
| task361_spolin_yesand_prompt_response_classification | NIv2 | fs_opt | 7 | train |
Given the prompt and a response, classify the them to "yes" if response is "yes, and" type. Otherwise classify it as "no". "Yes, and" is a rule-of-thumb in improvisational comedy that suggests that a participant in a dialogue should accept what another participant has stated ("Yes") and then expand on that line of thou... | yes
| task361_spolin_yesand_prompt_response_classification | NIv2 | fs_opt | 7 | test |
Given the task definition and input, reply with output. Given the prompt and a response, classify the them to "yes" if response is "yes, and" type. Otherwise classify it as "no". "Yes, and" is a rule-of-thumb in improvisational comedy that suggests that a participant in a dialogue should accept what another participant... | no | task361_spolin_yesand_prompt_response_classification | NIv2 | zs_opt | 5 | validation |
Detailed Instructions: In this task, based on the given input, we ask you to write a question about when an event happened. Your question should be answerable with common knowledge on when events usually take place. For example, "going to school" usually happens during the day (not at 2 A.M). Don't create questions whi... | What day was the house built? | task012_mctaco_question_generation_absolute_timepoint | NIv2 | zs_opt | 9 | train |
Detailed Instructions: In this task, based on the given input, we ask you to write a question about when an event happened. Your question should be answerable with common knowledge on when events usually take place. For example, "going to school" usually happens during the day (not at 2 A.M). Don't create questions whi... | When did he first pursue financial interests in those countries? | task012_mctaco_question_generation_absolute_timepoint | NIv2 | zs_opt | 8 | train |
In this task, based on the given input, we ask you to write a question about when an event happened. Your question should be answerable with common knowledge on when events usually take place. For example, "going to school" usually happens during the day (not at 2 A.M). Don't create questions which have explicit mentio... | What time was the aircraft shot down? | task012_mctaco_question_generation_absolute_timepoint | NIv2 | zs_opt | 0 | train |
In this task, based on the given input, we ask you to write a question about when an event happened. Your question should be answerable with common knowledge on when events usually take place. For example, "going to school" usually happens during the day (not at 2 A.M). Don't create questions which have explicit mentio... | When did Brewer talk?
| task012_mctaco_question_generation_absolute_timepoint | NIv2 | fs_opt | 5 | train |
In this task, based on the given input, we ask you to write a question about when an event happened. Your question should be answerable with common knowledge on when events usually take place. For example, "going to school" usually happens during the day (not at 2 A.M). Don't create questions which have explicit mentio... | What time did the battle end? | task012_mctaco_question_generation_absolute_timepoint | NIv2 | zs_opt | 4 | train |
Definition: In this task, based on the given input, we ask you to write a question about when an event happened. Your question should be answerable with common knowledge on when events usually take place. For example, "going to school" usually happens during the day (not at 2 A.M). Don't create questions which have exp... | When did Shelly talk to the puppies? | task012_mctaco_question_generation_absolute_timepoint | NIv2 | zs_opt | 2 | train |
Detailed Instructions: In this task, based on the given input, we ask you to write a question about when an event happened. Your question should be answerable with common knowledge on when events usually take place. For example, "going to school" usually happens during the day (not at 2 A.M). Don't create questions whi... | What day was the Serbian declared winner? | task012_mctaco_question_generation_absolute_timepoint | NIv2 | zs_opt | 8 | train |
Teacher: In this task, based on the given input, we ask you to write a question about when an event happened. Your question should be answerable with common knowledge on when events usually take place. For example, "going to school" usually happens during the day (not at 2 A.M). Don't create questions which have explic... | At what time of the day did he lay in her lap? | task012_mctaco_question_generation_absolute_timepoint | NIv2 | fs_opt | 2 | train |
In this task, based on the given input, we ask you to write a question about when an event happened. Your question should be answerable with common knowledge on when events usually take place. For example, "going to school" usually happens during the day (not at 2 A.M). Don't create questions which have explicit mentio... | Output: When did the Beetles hold their press conference?
| task012_mctaco_question_generation_absolute_timepoint | NIv2 | fs_opt | 2 | test |
In this task, based on the given input, we ask you to write a question about when an event happened. Your question should be answerable with common knowledge on when events usually take place. For example, "going to school" usually happens during the day (not at 2 A.M). Don't create questions which have explicit mentio... | What time did they go to the crime scene?
| task012_mctaco_question_generation_absolute_timepoint | NIv2 | fs_opt | 5 | validation |
In this task, you are given a fact statement and question based on the fact. Your task is to generate the correct answer for the question. The answer needs to be generated using the context fact statement.
Fact: usually plants die or become dormant during the winter. Question: Usually, plants naturally decrease their ... | very cold temperatures | task1399_obqa_answer_generation | NIv2 | zs_opt | 0 | train |
In this task, you are given a fact statement and question based on the fact. Your task is to generate the correct answer for the question. The answer needs to be generated using the context fact statement.
Q: Fact: a hot substance is a source of heat. Question: Lucy came in from the cold and can's stop shivering. It m... | your phone
****
| task1399_obqa_answer_generation | NIv2 | fs_opt | 4 | train |
Q: In this task, you are given a fact statement and question based on the fact. Your task is to generate the correct answer for the question. The answer needs to be generated using the context fact statement.
Fact: bacteria can cause people to become ill. Question: Single cell organisms can put an animal in the?
A: | emergency room | task1399_obqa_answer_generation | NIv2 | zs_opt | 7 | train |
Instructions: In this task, you are given a fact statement and question based on the fact. Your task is to generate the correct answer for the question. The answer needs to be generated using the context fact statement.
Input: Fact: baking soda can react chemically with vinegar. Question: Which of the following results... | Science fair volcanoes | task1399_obqa_answer_generation | NIv2 | zs_opt | 3 | train |
Detailed Instructions: In this task, you are given a fact statement and question based on the fact. Your task is to generate the correct answer for the question. The answer needs to be generated using the context fact statement.
Q: Fact: if a tree falls then that tree is dead. Question: Which sustains life yet stopped ... | a felled tree | task1399_obqa_answer_generation | NIv2 | zs_opt | 9 | train |
TASK DEFINITION: In this task, you are given a fact statement and question based on the fact. Your task is to generate the correct answer for the question. The answer needs to be generated using the context fact statement.
PROBLEM: Fact: algae is found in bodies of water. Question: Where would algae be safe from predat... | hotplate
| task1399_obqa_answer_generation | NIv2 | fs_opt | 8 | train |
Teacher: In this task, you are given a fact statement and question based on the fact. Your task is to generate the correct answer for the question. The answer needs to be generated using the context fact statement.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Fact: deep se... | Putting a fresh raspberry seed in soil | task1399_obqa_answer_generation | NIv2 | fs_opt | 2 | train |
Q: In this task, you are given a fact statement and question based on the fact. Your task is to generate the correct answer for the question. The answer needs to be generated using the context fact statement.
Fact: limestone is formed by water evaporating from a solution of water and minerals. Question: Limestone is fo... | cement | task1399_obqa_answer_generation | NIv2 | zs_opt | 7 | train |
Instructions: In this task, you are given a fact statement and question based on the fact. Your task is to generate the correct answer for the question. The answer needs to be generated using the context fact statement.
Input: Fact: strumming a string can cause that string to vibrate. Question: Which of these has reson... | a lute | task1399_obqa_answer_generation | NIv2 | zs_opt | 3 | test |
In this task, you are given a fact statement and question based on the fact. Your task is to generate the correct answer for the question. The answer needs to be generated using the context fact statement.
Input: Consider Input: Fact: plant requires seed dispersal for reproduction. Question: New plants sprang up every... | Output: keeping your eyes covered
| task1399_obqa_answer_generation | NIv2 | fs_opt | 2 | validation |
You are given a sentence in Italian. Your job is to translate the Italian sentence into Japanese.
Let me give you an example: Mio padre è medico. Ed è stato un grande vantaggio per noi. Si è occupato di lei in modo fantastico.
The answer to this example can be: 父が医師だったので父に担当してもらえるという大きな利点がありました父は母に見事な治療を施しました
Here is ... | 彼らがキッチンカウンターにいるアリです | task1248_ted_translation_it_ja | NIv2 | fs_opt | 8 | train |
Given the task definition, example input & output, solve the new input case.
You are given a sentence in Italian. Your job is to translate the Italian sentence into Japanese.
Example: Mio padre è medico. Ed è stato un grande vantaggio per noi. Si è occupato di lei in modo fantastico.
Output: 父が医師だったので父に担当してもらえるという大きな利点... | こちらは脳表面のマップで非常に精巧な実験を行い体の部位とニューロンの反応の対応を細かく調べました | task1248_ted_translation_it_ja | NIv2 | fs_opt | 1 | train |
Teacher:You are given a sentence in Italian. Your job is to translate the Italian sentence into Japanese.
Teacher: Now, understand the problem? Solve this instance: Il secondo giorno ha registrato suoni di motoseghe illegali.
Student: | 開始から２日目に違法伐採のチェーンソーの音を感知しました | task1248_ted_translation_it_ja | NIv2 | zs_opt | 6 | train |
You are given a sentence in Italian. Your job is to translate the Italian sentence into Japanese.
Example: Mio padre è medico. Ed è stato un grande vantaggio per noi. Si è occupato di lei in modo fantastico.
Example solution: 父が医師だったので父に担当してもらえるという大きな利点がありました父は母に見事な治療を施しました
Example explanation: The Italian sentence is ... | Solution: ではどのように遺伝するのでしょうか ？ | task1248_ted_translation_it_ja | NIv2 | fs_opt | 5 | train |
Teacher: You are given a sentence in Italian. Your job is to translate the Italian sentence into Japanese.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Mio padre è medico. Ed è stato un grande vantaggio per noi. Si è occupato di lei in modo fantastico.
Solution: 父が医師だったので父... | 潮汐力や波の力を電力に変換する技術開発が競って進められこれによって石炭を地下に眠らせておくことが可能になります | task1248_ted_translation_it_ja | NIv2 | fs_opt | 2 | train |
You are given a sentence in Italian. Your job is to translate the Italian sentence into Japanese.
One example is below.
Q: Mio padre è medico. Ed è stato un grande vantaggio per noi. Si è occupato di lei in modo fantastico.
A: 父が医師だったので父に担当してもらえるという大きな利点がありました父は母に見事な治療を施しました
Rationale: The Italian sentence is correctly... | 彼はアートセンターのトップになったそこにはクレイグ・エルウッドの建物がある | task1248_ted_translation_it_ja | NIv2 | fs_opt | 9 | train |
Instructions: You are given a sentence in Italian. Your job is to translate the Italian sentence into Japanese.
Input: Questo è un negozio per un'azienda di borse.
Output: | バッグ会社の店舗 | task1248_ted_translation_it_ja | NIv2 | zs_opt | 3 | train |
You will be given a definition of a task first, then some input of the task.
You are given a sentence in Italian. Your job is to translate the Italian sentence into Japanese.
Questo è inusuale per le grotte.
Output: | 洞窟では非常に稀です | task1248_ted_translation_it_ja | NIv2 | zs_opt | 1 | train |
You are given a sentence in Italian. Your job is to translate the Italian sentence into Japanese.
Ex Input:
Molto diversi dagli stati-nazione, che sono astrazioni.
Ex Output:
これは抽象化されている国家とはとても違います
Ex Input:
Ecco un modo che ci permetterebbe di portare i malati alla terapia intensiva.
Ex Output:
これが人を救命救急施設に搬送する方法... | そんなときには ３つのことを思い出してください
| task1248_ted_translation_it_ja | NIv2 | fs_opt | 1 | test |
Given the task definition and input, reply with output. You are given a sentence in Italian. Your job is to translate the Italian sentence into Japanese.
Disponiamo di quattro stabilimenti. Ne stiamo costruendo in tutto il paese.
| もう４件のプラントが建てられました。我々は全国に新しい乾式壁を製造している。 | task1248_ted_translation_it_ja | NIv2 | zs_opt | 5 | validation |
Detailed Instructions: Provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corpus is -
'.': ... | VERB | task1167_penn_treebank_coarse_pos_tagging | NIv2 | zs_opt | 8 | train |
Provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corpus is -
'.': Period symbol is used f... | PRON
| task1167_penn_treebank_coarse_pos_tagging | NIv2 | fs_opt | 3 | train |
Provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corpus is -
'.': Period symbol is used f... | X
| task1167_penn_treebank_coarse_pos_tagging | NIv2 | fs_opt | 3 | train |
Detailed Instructions: Provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corpus is -
'.': ... | PRT | task1167_penn_treebank_coarse_pos_tagging | NIv2 | zs_opt | 8 | train |
TASK DEFINITION: Provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corpus is -
'.': Period... | .
| task1167_penn_treebank_coarse_pos_tagging | NIv2 | fs_opt | 8 | train |
Provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corpus is -
'.': Period symbol is used f... | NOUN
| task1167_penn_treebank_coarse_pos_tagging | NIv2 | fs_opt | 3 | train |
instruction:
Provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corpus is -
'.': Period sym... | CONJ
| task1167_penn_treebank_coarse_pos_tagging | NIv2 | fs_opt | 9 | train |
Detailed Instructions: Provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corpus is -
'.': ... | NOUN | task1167_penn_treebank_coarse_pos_tagging | NIv2 | zs_opt | 8 | train |
Q: Provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corpus is -
'.': Period symbol is use... | ADP | task1167_penn_treebank_coarse_pos_tagging | NIv2 | zs_opt | 7 | test |
Provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corpus is -
'.': Period symbol is used f... | NOUN | task1167_penn_treebank_coarse_pos_tagging | NIv2 | fs_opt | 9 | validation |
Q: In this task, you are given a sentence in English, and your task is to translate it into Persian.
and how was everything, how was everybody
A: | و اینکه اوضاع چطور است، همه خوبند؟ | task661_mizan_en_fa_translation | NIv2 | zs_opt | 7 | train |
Given the task definition and input, reply with output. In this task, you are given a sentence in English, and your task is to translate it into Persian.
The long train of his mantle swept down over the steps and lay spread out on the chancel floor,
| دنباله طویل ردایش بر روی پلهها کشیده و بر کف صدر کلیسا گسترده شده بود، | task661_mizan_en_fa_translation | NIv2 | zs_opt | 5 | train |
In this task, you are given a sentence in English, and your task is to translate it into Persian.
I can't explain it; I just know that it is in me.; | نمیتونم توضیحش بدم اما میدونم که این احساس در درونم هست. | task661_mizan_en_fa_translation | NIv2 | zs_opt | 0 | train |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a sentence in English, and your task is to translate it into Persian.
It seemed to enter into her body and course through her veins in a liquid glow,
Output: | احساس میکرد که این نسیم وارد بدنش میشود و همچون آتشی سیال در رگهایش جریان مییابد، | task661_mizan_en_fa_translation | NIv2 | zs_opt | 1 | train |
In this task, you are given a sentence in English, and your task is to translate it into Persian.
Input: Consider Input: They had spent a year in France, for no particular reason,
Output: قبلا یک سالی را، بدون هیچ گونه دلیل خاص، در فرانسه گذرانده بودند،
Input: Consider Input: and talk as cheerfully as they could ab... | Output: و به بحثها گوش میداد و هر بار با حسرت از آنجا دور میشد.
| task661_mizan_en_fa_translation | NIv2 | fs_opt | 2 | train |
Detailed Instructions: In this task, you are given a sentence in English, and your task is to translate it into Persian.
Problem:It was a very short and simple affair; a mere formality, occupying barely twenty minutes.
Solution: | کار بسیار مختصر و سهلی بود، با یک تشریفات مخفی که به زحمت ۲۰ دقیقه طول کشید. | task661_mizan_en_fa_translation | NIv2 | zs_opt | 8 | train |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a sentence in English, and your task is to translate it into Persian.
It is with great diffidence that I venture to press the point after what Your Eminence has said;
Output: | علی رغم آنچه عالیجناب بیان داشتند با خضوع بسیار، جسارتا روی این مطلب پافشاری میکنم؛ | task661_mizan_en_fa_translation | NIv2 | zs_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.
In this task, you are given a sentence in English, and your task is to translate it into Persian.
I heard enough of what she said to you last night to understand her unwillingness to be acting with ... | مجبور شد قبول کند که جاذبه بازیگری و تئاتر میتواند هر ذهن مبتکری را به خود جلب کند. | task661_mizan_en_fa_translation | NIv2 | fs_opt | 0 | train |
Detailed Instructions: In this task, you are given a sentence in English, and your task is to translate it into Persian.
Problem:Very likely I shall get killed some day that is the natural consequence of being a revolutionist.
Solution: | احتمال زیاد دارد که من روزی کشته شوم سرنوشت طبیعی یک انقلابی همین است | task661_mizan_en_fa_translation | NIv2 | zs_opt | 8 | test |
Teacher:In this task, you are given a sentence in English, and your task is to translate it into Persian.
Teacher: Now, understand the problem? Solve this instance: and when her sisters left her to amuse herself, she soon found that accomplished and important little self a great burden.
Student: | یعنی به یک طریق خیلی مناسبی آن را به یک تجربهی به یادماندنی تبدیل نماید. | task661_mizan_en_fa_translation | NIv2 | zs_opt | 6 | validation |
Problem: Given the question: Here's a question: Dancing poorly in public may make you feel what? Here are possible answers to this question: - exhaustion - recognizance - blisters - humiliation - fatigue I believe the correct choice is "humiliation", here's why:
++++++++++++++++++++++++++++++++
The answer is:
making ... | the workflow is very heavy. | cos_e_v1_11_i_think | P3 | fs_opt | 8 | train |
Here's a question: Where in your office would you store a highlight that you don't use often? Here are possible answers to this question: - office supply store - case - desk drawer - campus book store - lamp I believe the correct choice is "desk drawer", here's why:
The answer to this question is: | desk drawer office would you store a highlight that you don't use often | cos_e_v1_11_i_think | P3 | zs_noopt | 7 | train |
Here's a question: They wanted to put on a show about being human beings, which ironically worked because none of them could do what well? Here are possible answers to this question: - behave well - question authority - melt - act - read newspapers I believe the correct choice is "act", here's why:
A: | act show being human work ironically | cos_e_v1_11_i_think | P3 | zs_opt | 2 | train |
Answer the following question: Here's a question: Snoopy thought Charlie wanted to play fetch, but Charlie was just treating his pet what for fleas? Here are possible answers to this question: - house - cat - carpet - rug - dog I believe the correct choice is "dog", here's why:
Answer: | snoopy thought charlie wanted to play fetch, but charlie was just treating his pet dog or fleas | cos_e_v1_11_i_think | P3 | zs_opt | 5 | train |
Here's a question: If someone has hunger in the middle of the night what should they do? Here are possible answers to this question: - drink water - cook dinner - have lunch - eat hamburger - have food I believe the correct choice is "have food", here's why:
Answer: | has hunger in the middle of the night have food. | cos_e_v1_11_i_think | P3 | zs_opt | 1 | train |
Q:Here's a question: What kind of emotion does eating at your favorite restaurant bring about? Here are possible answers to this question: - getting full - sadness - gas - gaining weight - satisfaction I believe the correct choice is "satisfaction", here's why:
A: | satisfaction emotion does eating at your favorite restaurant bring | cos_e_v1_11_i_think | P3 | zs_noopt | 3 | train |
Here's a question: People like to watch movies to escape for a couple hours, they find them very what? Here are possible answers to this question: - entertaining - theasres - funny - watched on videos - excellent I believe the correct choice is "entertaining", here's why:
A: | rivers flow trough valleys. | cos_e_v1_11_i_think | P3 | zs_opt | 2 | train |
Please answer the following question: Here's a question: When we are thankful for getting something what do we do? Here are possible answers to this question: - say thank - smile - looking for - get more - show appreciation I believe the correct choice is "show appreciation", here's why:
A: | show appreciation thankful for getting something | cos_e_v1_11_i_think | P3 | zs_noopt | 8 | train |
Question: Here's a question: What do you do when your friend can't lift groceries themselves? Here are possible answers to this question: - write letter - promise to help - rely on - offer to help - do not help I believe the correct choice is "offer to help", here's why:
Answer: rivers flow trough valleys.
Question:... | people are powerful | cos_e_v1_11_i_think | P3 | fs_opt | 3 | test |
Please answer this: Here's a question: Why would someone stop having food? Here are possible answers to this question: - getting fat - being full - weight gain - hungry - eating food I believe the correct choice is "being full", here's why:
++++++++
Answer: being full is the only answer that has anything to do with n... | e ticket - wikipedia | cos_e_v1_11_i_think | P3 | fs_opt | 6 | validation |
Teacher: Given an trivia question precisely answer the question with a word/phrase/name. External resources such as Wikipedia could be used to obtain the facts.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Which writer rode Devon Loch in the 1956 Grand National?
Solution: ... | monaco | task898_freebase_qa_answer_generation | NIv2 | fs_opt | 2 | train |
Given an trivia question precisely answer the question with a word/phrase/name. External resources such as Wikipedia could be used to obtain the facts.
Example: Which writer rode Devon Loch in the 1956 Grand National?
Example solution: dick francis
Example explanation: The answer is precise and accurately answers the q... | Solution: motivation | task898_freebase_qa_answer_generation | NIv2 | fs_opt | 5 | train |
TASK DEFINITION: Given an trivia question precisely answer the question with a word/phrase/name. External resources such as Wikipedia could be used to obtain the facts.
PROBLEM: Which American actor starred in the film 'The Magnificent Seven' and on TV in 'The Man From Uncle'?
SOLUTION: robert vaughn
PROBLEM: Before ... | united states
| task898_freebase_qa_answer_generation | NIv2 | fs_opt | 8 | train |
Given an trivia question precisely answer the question with a word/phrase/name. External resources such as Wikipedia could be used to obtain the facts.
Example input: Which writer rode Devon Loch in the 1956 Grand National?
Example output: dick francis
Example explanation: The answer is precise and accurately answers ... | denmark | task898_freebase_qa_answer_generation | NIv2 | fs_opt | 3 | train |
Instructions: Given an trivia question precisely answer the question with a word/phrase/name. External resources such as Wikipedia could be used to obtain the facts.
Input: What species is General Sherman, the world's heaviest single-trunk tree?
Output: | sequoiadendron giganteum | task898_freebase_qa_answer_generation | NIv2 | zs_opt | 3 | train |
Given an trivia question precisely answer the question with a word/phrase/name. External resources such as Wikipedia could be used to obtain the facts.
Q: Jana Gana Mana is, since 1950, the national anthem of?
A: | india | task898_freebase_qa_answer_generation | NIv2 | zs_opt | 4 | train |
Instructions: Given an trivia question precisely answer the question with a word/phrase/name. External resources such as Wikipedia could be used to obtain the facts.
Input: Who played the title role in the 1951 film 'Captain Horatio Hornblower RN'?
Output: | gregory peck | task898_freebase_qa_answer_generation | NIv2 | zs_opt | 3 | train |
You will be given a definition of a task first, then some input of the task.
Given an trivia question precisely answer the question with a word/phrase/name. External resources such as Wikipedia could be used to obtain the facts.
Which Madonna song mentions Grace Kelly, Joe Dimaggio, and Rita Hayworth?
Output: | vogue | task898_freebase_qa_answer_generation | NIv2 | zs_opt | 1 | train |
Q: Given an trivia question precisely answer the question with a word/phrase/name. External resources such as Wikipedia could be used to obtain the facts.
The statue called Manneken Pis, of a small boy relieving himself, is in which city?
A: | brussels | task898_freebase_qa_answer_generation | NIv2 | zs_opt | 7 | test |
Q: Given an trivia question precisely answer the question with a word/phrase/name. External resources such as Wikipedia could be used to obtain the facts.
Which river, the fifth longest in Europe, is Portugal's longest?
A: | tagus | task898_freebase_qa_answer_generation | NIv2 | zs_opt | 7 | validation |
Detailed Instructions: In this task, given a sentence in the English language, your task is to convert it into the Chinese language.
See one example below:
Problem: "This has not been a donor conference where governments have been invited to come and make new pledges, as I said if everybody lived by their Paris pledges... | 据英国《卫报》报道，随着越来越多的报道称医院里的病人被忽视，两家工会昨天与肯尼亚政府举行了会谈，就恢复工作进行了谈判，尽管相当一部分示威者不服从协议。 | task548_alt_translation_en_ch | NIv2 | fs_opt | 4 | train |
In this task, given a sentence in the English language, your task is to convert it into the Chinese language.
Example Input: Mr Downer was also questioned about a cable delivered in June 2003 from US army captain Puckett which claimed that every contract under the UN's oil for food program contained a kickback.
Exampl... | 巴拉德最著名的作品是1973年的《撞车》和1984年的《太阳帝国》，后者获得了詹姆斯·泰特·布莱克纪念奖。
| task548_alt_translation_en_ch | NIv2 | fs_opt | 3 | train |
Teacher: In this task, given a sentence in the English language, your task is to convert it into the Chinese language.
Teacher: Now, understand the problem? If you are still confused, see the following example:
"This has not been a donor conference where governments have been invited to come and make new pledges, as I ... | 罢工人员本周再次出庭，最高法院法官布伦达·布朗表示，她将于周五就工会因在上周民事藐视法庭裁决后拒绝取消罢工而被处以额外罚款的请求做出裁决。 | task548_alt_translation_en_ch | NIv2 | fs_opt | 2 | train |
Given the task definition, example input & output, solve the new input case.
In this task, given a sentence in the English language, your task is to convert it into the Chinese language.
Example: "This has not been a donor conference where governments have been invited to come and make new pledges, as I said if everybo... | 这是自1996年以来第一次重新设计一百美元纸币。 | task548_alt_translation_en_ch | NIv2 | fs_opt | 1 | train |
In this task, given a sentence in the English language, your task is to convert it into the Chinese language.
[Q]: The switch was funded by the province of Bolzano, the European Social Fund, and the Center for Professional Formation in Italian Language.
[A]: 该转变由博尔扎诺省，欧洲社会基金和意大利语专业形成中心资助。
[Q]: Radiocarbon dating ind... | 帕夫洛斯·梅拉斯足球俱乐部在第三阶段首次亮相后，尽管以2比1战胜了多沙戏剧足球俱乐部，最终在32场比赛中取得36分，但仍因排名14位而被降级。
| task548_alt_translation_en_ch | NIv2 | fs_opt | 5 | train |
Definition: In this task, given a sentence in the English language, your task is to convert it into the Chinese language.
Input: Funding for developed countries was previously expected to be 130 billion US dollars.
Output: | 根据此前的预期，为发达国家提供的资金为1300亿美元。 | task548_alt_translation_en_ch | NIv2 | zs_opt | 2 | train |
Q: In this task, given a sentence in the English language, your task is to convert it into the Chinese language.
The first took place at 07:15 (12:15 UTC), at West Ambler Johnston Hall dormitory.
A: | 第一次发生在07：15（世界协调时12：15），地点在西安布勒约翰斯顿宿舍。 | task548_alt_translation_en_ch | NIv2 | zs_opt | 7 | train |
In this task, given a sentence in the English language, your task is to convert it into the Chinese language.
Q: The People's Republic of China is not the first country to ban or restrict plastic shopping bags and the notice names Uganda and South Africa according to CNN.
A: | 据CNN报道，中华人民共和国并不是第一个禁止或限制塑料购物袋的国家，这份通知提到了乌干达和南非。 | task548_alt_translation_en_ch | NIv2 | zs_opt | 4 | train |
Given the task definition and input, reply with output. In this task, given a sentence in the English language, your task is to convert it into the Chinese language.
Paraguay lost number one goalkeeper Justo Villa to an injury in the sixth minute of the game.
| 比赛开始6分钟，巴拉圭的一号守门员贾斯脱·维拉受伤下场。 | task548_alt_translation_en_ch | NIv2 | zs_opt | 5 | test |
In this task, given a sentence in the English language, your task is to convert it into the Chinese language.
Q: The phenomenon is particularly important for crops such as almond growing in California, where honey-bees are the predominant pollinator and the crop value is $US 1.5 billion.
A: | 这一现象对加利福尼亚种植的杏仁等作物尤为重要，因为那里的蜜蜂是主要的授粉者，作物价值为15亿美元。 | task548_alt_translation_en_ch | NIv2 | zs_opt | 4 | validation |
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