inputs stringlengths 38 313k | targets stringlengths 0 4.86k | _template_idx int64 0 9 | _task_source stringclasses 1
value | _task_name stringlengths 19 85 | _template_type stringclasses 2
values | embedding listlengths 1.02k 1.02k |
|---|---|---|---|---|---|---|
Teacher: In this task, you will be presented with a question and you have to answer the question based on your knowledge. Your answers should be as short as possible.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Who were the builders of the mosque in Herat with fire temples ?
Solution: Ghurids
Reason: This is a good example. Ghurids were the builders of the mosque in Herat with fire temples.
Now, solve this instance: What nationality was the person that received 2,626 votes ?
Student: | Scottish | 2 | NIv2 | task344_hybridqa_answer_generation | fs_opt | [
-0.3696242570877075,
0.5468621253967285,
0.4984806776046753,
0.04075584188103676,
-0.28190502524375916,
-0.7238002419471741,
0.2537400424480438,
0.07495839893817902,
-0.6188843250274658,
-0.03078456223011017,
-0.3756009340286255,
0.039086610078811646,
-0.6383196115493774,
-0.68229925632476... |
Given the task definition and input, reply with output. In this task, you are given a set of context paragraphs, some supporting facts and an answer of a question. Your task is to generate question for given answer based on set of context paragraphs, supporting facts and an answer.
Context_1 : Herbert "Barry" Morse (10 June 1918 – 2 February 2008) was an English-Canadian actor of stage, screen and radio best known for his roles in the ABC television series "The Fugitive" and the British sci-fi drama "". His performing career spanned seven decades and he had thousands of roles to his credit, including work for the BBC and the Canadian Broadcasting Corporation. Context_2 : Simon, Simon is a 1970 Sound effect comedy short film directed by Graham Stark. Context_3 : Max Wall (12 March 1908 – 21 May 1990), was an English comedian and actor, whose performing career covered music hall, theatre, films and television. Context_4 : Eric Sykes, CBE (4 May 1923 – 4 July 2012) was an English radio, stage, television and film writer, comedian, actor, and director whose performing career spanned more than 50 years. He frequently wrote for and/or performed with many other leading comedy performers and writers of the period, including Tony Hancock, Spike Milligan, Tommy Cooper, Peter Sellers, John Antrobus, and Johnny Speight. Sykes first came to prominence through his many radio credits as a writer and actor in the 1950s, most notably through his collaboration on "The Goon Show" scripts. He became a TV star in his own right in the early 1960s when he appeared with Hattie Jacques in several popular BBC comedy television series. Context_5 : Ivan Moravec (9 November 1930 – 27 July 2015) was a Czech concert pianist whose performing and recording career spanned nearly half a century. Context_6 : Musiri Subramania Iyer (April 9, 1899 - March 25, 1975) was a Carnatic vocalist whose stage performing career spanned the 1920s to the 1940s. After retirement from the stage, he remained an iconic figure in Carnatic music as a dedicated teacher and leader in the Carnatic community. His bhava-laden renditions of Carnatic songs have become the measuring stick for generations of Carnatic vocalists. Musiri Subramania Iyer is one of the giants of Carnatic music in this century. Context_7 : During the 1960s a new series of 'sound effect' comedies began with Dick Lester, Spike Milligan and Peter Sellers's "Running Jumping & Standing Still", continued through Eric Sykes's "The Plank", Barbara Windsor's "San Ferry Ann" and included four films with Ronnie Barker: "A Home of Your Own", "Futtock's End", "The Picnic", and "By the Sea". Context_8 : George Grossmith (9 December 1847 – 1 March 1912) was an English comedian, writer, composer, actor, and singer. His performing career spanned more than four decades. As a writer and composer, he created 18 comic operas, nearly 100 musical sketches, some 600 songs and piano pieces, three books and both serious and comic pieces for newspapers and magazines. Context_9 : Rutland Barrington (15 January 1853 – 31 May 1922) was an English singer, actor, comedian and Edwardian musical comedy star. Best remembered for originating the lyric baritone roles in the Gilbert and Sullivan operas from 1877 to 1896, his performing career spanned more than four decades. He also wrote at least a dozen works for the stage. Context_10 : Gery Scott (5 October 1923 – 14 December 2005) was a jazz and cabaret entertainer and teacher, whose performing career spanned 26 countries and over 60 years. She was noted for her powerful stage persona and engaging delivery, with material ranging from the songbooks of Cole Porter, George Gershwin, Irving Berlin, Harold Arlen, Lorenz Hart, Cy Coleman and all the "standards" as well as Noël Coward and some pop material. Whilst she was well known to British audiences during the later part of the Second World War, she achieved most of her fame outside the UK. fact_1 : During the 1960s a new series of 'sound effect' comedies began with Dick Lester, Spike Milligan and Peter Sellers's "Running Jumping & Standing Still", continued through Eric Sykes's "The Plank", Barbara Windsor's "San Ferry Ann" and included four films with Ronnie Barker: "A Home of Your Own", "Futtock's End", "The Picnic", and "By the Sea". fact_2 : Eric Sykes, CBE (4 May 1923 – 4 July 2012) was an English radio, stage, television and film writer, comedian, actor, and director whose performing career spanned more than 50 years. Answer: The Plank
| What was the name of the sound effect comedy created by the English radio, stage, television and film writer, comedian, actor, and director whose performing career spanned more than 50 years? | 5 | NIv2 | task191_hotpotqa_question_generation | zs_opt | [
0.4013736844062805,
0.42175233364105225,
-0.5421738624572754,
0.08634599298238754,
0.9094249606132507,
-0.28684648871421814,
-0.06881280243396759,
0.3761802315711975,
0.21581441164016724,
-0.0775638148188591,
0.11935064196586609,
0.7018365859985352,
-0.9462412595748901,
-0.201241597533226,... |
Teacher:In this task, you are given a question and a context passage. You have to answer the question based on the given passage.
Teacher: Now, understand the problem? Solve this instance: what is the last ethnic description mentioned?, Context: President Franklin D. Roosevelt promoted a "good neighbor" policy that sought better relations with Mexico. In 1935 a federal judge ruled that three Mexican immigrants were ineligible for citizenship because they were not white, as required by federal law. Mexico protested, and Roosevelt decided to circumvent the decision and make sure the federal government treated Hispanics as white. The State Department, the Census Bureau, the Labor Department, and other government agencies therefore made sure to uniformly classify people of Mexican descent as white. This policy encouraged the League of United Latin American Citizens in its quest to minimize discrimination by asserting their whiteness.
Student: | whiteness | 6 | NIv2 | task1295_adversarial_qa_question_answering | zs_opt | [
-0.03282724320888519,
-0.11940882354974747,
-0.02158360555768013,
-0.49294114112854004,
-0.44059887528419495,
0.37880799174308777,
0.20799030363559723,
0.4314888119697571,
0.31087929010391235,
0.04233517497777939,
-0.16051247715950012,
0.19632413983345032,
0.2338171750307083,
-0.9002516269... |
Detailed Instructions: In this task, you're given a pair of sentences in the Persian Language written in the Persian alphabet. Your job is to choose whether the two sentences agree (entailment), disagree (contradiction), or neither (neutral). Your answer must be in the form of the letters E, C, and N, respectively. The sentences have been separated by a newline character.
Q: میرعلی تبریزی با لقب قُدوة الکُتّاب (بهمعنی پیشگام خوشنویسان) فرزند میر علی سلطانی از خوشنویسان بهنام و از مفاخر خوشنویسی ایرانی در سده هشتم و نهم هجری (چهاردهم و پانزدهم میلادی) است. او را واضع و مبدع خط زیبای نستعلیق میدانند که از قلههای رفیع هنر ایرانی است.
میرعلی تبریزی، بنیان گذار خط نستعلیق است.
A: | E | 9 | NIv2 | task534_farstail_entailment | zs_opt | [
-0.21600866317749023,
0.028515666723251343,
-0.2404152750968933,
0.3414556682109833,
0.2822222113609314,
0.261447548866272,
0.7434954047203064,
0.3613456189632416,
0.6865508556365967,
0.021278141066432,
-0.2265586256980896,
-0.2725513279438019,
-0.5987785458564758,
0.046644099056720734,
... |
Here are two questions (Question1 and Question2). If these questions have the same meaning and same answer, answer "Yes", otherwise "No".
One example: Question1: How do I get into my Instagram if I forgot my email and my Facebook password?, Question2: I forgot my password and also my email password. how can I get back that account?
Solution is here: Yes
Explanation: These questions have the meaning and the same answer. So, the output should be "Yes".
Now, solve this: Question1: What are the advantages and disadvantages of web based application development vs. desktop application development?, Question2: What is the advantages of desktop application over web application?
Solution: | No | 6 | NIv2 | task1287_glue_qqp_paraphrasing | fs_opt | [
-0.006673632189631462,
0.6501215696334839,
-0.20274223387241364,
0.211032897233963,
-0.1497270166873932,
-1.023874282836914,
0.9531153440475464,
0.6846843957901001,
-0.007907557301223278,
0.2382834553718567,
-0.24944227933883667,
-0.03881305828690529,
-0.7039796113967896,
-0.29103434085845... |
Your task is to generate the next utterance in a given dialogue. You will be given a few sentences describing the personality of the person who is making the dialogue, and a history of the dialogue after that. Each line in the history is said by one of the two participants in the conversation.
Personality: I can say the alphabet backwards.
I lost my job as a banker a month ago.
I got engaged to be married in Paris, France.
I am a redhead.
I have danced since I was two.
Chat history: -Hi how are you doing?
-I'm doing good and you.
I am good thanks for asking.
Personality: I'm a very funny woman.
I deliver packages for a living.
I own 3 cats.
I drive a Honda car.
I love candy.
Chat history: -Hi how are you doing.
-Vera died. I need a new honda. You drive?
-Yes I have Honda and I love it.
-Great! I like subway strangers when I'm lonely. You?
I actually deliver stuffs that s my work.
Personality: I could move out, but she doesn't want me to.
I miss my dad.
There I'm a general of an oris army.
In reality I am 32 and live at home with my mother.
Chat history: -Hello, how are you today?
-I'm great, I just miss my dad today. How are you?
-I'm doing good, I just got out of bad.
-I wish I had a bed, I sleep in the trenches.
-Wow that's rough! Am still in high school and I joined band.
-You should quit band and join us in our fight!
-That's too much for me, but I do like making friends.
| Do you consider yourself more of a hobbit or an orc?
| 0 | NIv2 | task1729_personachat_generate_next | fs_opt | [
-0.2988024353981018,
0.6695907115936279,
-0.3266478180885315,
-0.524587869644165,
-0.13423050940036774,
0.1409454345703125,
0.8804849982261658,
0.12496650218963623,
0.04109181836247444,
-0.44171854853630066,
-0.47289323806762695,
0.17246752977371216,
-0.0079680560156703,
0.1363016963005066... |
Two analogies that signify affordances are given in the form "A : B. C : ?". Affordance is the possibility of an action being done on an object, for example book is an affordance of writing. The phrase "A : B" implies that B is an affordance of A. Your task is to replace the question mark (?) with the appropriate affordance of the given action C, following the "A : B" relation. Your answer should be a single object without further explanation.
Ex Input:
write : letter. eat : ?
Ex Output:
food
Ex Input:
compose : symphony. ride : ?
Ex Output:
horse
Ex Input:
give : gift. write : ?
Ex Output:
| letter
| 1 | NIv2 | task1153_bard_analogical_reasoning_affordance | fs_opt | [
0.32203781604766846,
0.8302099704742432,
-0.1334187388420105,
0.8285244703292847,
0.03458023816347122,
-0.4517766833305359,
0.8714420199394226,
0.934526801109314,
0.1307700276374817,
-0.5056439638137817,
-0.2802897095680237,
0.16599209606647491,
-0.16433478891849518,
-0.33923476934432983,
... |
Teacher:Given a passage with a context and an answer, construct a question on the basis of the information present in the passage. Construct the question in such a way that (i) it is unambiguous, (ii) it is answerable from the passage, (iii) its answer is unique (iv) it answer uses text phrases from the passage. Avoid creating questions that (i) can't be answered correctly without actually understanding the passage and (ii) uses the same words or phrases given in the passage.
Teacher: Now, understand the problem? Solve this instance: Context: Erythropoiesis-stimulating agents (ESAs) are recommended for treating chemotherapy-induced anemia in breast cancer patients. Reduced survival rates in ESAs-treated patients have been reported, possibly due to thromboembolic complications, however the exact mechanism remains obscure. The principal activator of blood coagulation in cancer is tissue factor (TF). There are data that erythropoietin receptor (EPO-R) is expressed in tumor cells. The purpose of this study was to evaluate the expression of EPO-R and TF in loco in breast cancer.', 'The expression of EPO-R and TF was investigated in 24 invasive breast carcinoma specimens. Immunohistochemical (IHC) methodologies according to ABC technique and double-staining IHC procedure were employed utilizing antibodies against EPO-R and TF.', 'Expression of EPO-R and TF was demonstrated in the tumor cells in all breast cancer specimens. No staining for EPO-R and TF was visualized in normal breast tissue. Double staining studies revealed co-expression of both EPO-R and TF in breast cancer cells and endothelial cells.
Answer: EPO-R and TF expression and their coexpression in breast cancer cells suggest a possibility that EPO-R might be responsible for some adverse effects and reduced survival observed in ESAs-treated breast cancer patients with anemia, possibly due to the interaction with TF. Further experimental studies are warranted to determine the role of both EPO-R and TF in the treatment with ESAs of breast cancer patients with chemotherapy-induced anemia.
Student: | Are erythropoietin receptor and tissue factor coexpressed in human breast cancer cells? | 6 | NIv2 | task845_pubmedqa_question_generation | zs_opt | [
0.6715203523635864,
0.20723296701908112,
-0.044277872890233994,
0.4367608428001404,
0.06875033676624298,
-1.089125156402588,
1.0117710828781128,
1.2545299530029297,
0.2303639054298401,
0.845157265663147,
-0.0410674549639225,
0.5507187247276306,
-0.5941823720932007,
0.18588165938854218,
0... |
TASK DEFINITION: In this task, you are given a public comment from online platforms. You are expected to classify the comment into two classes: threat and non-threat. Threat is a statement that someone will be hurt or harmed, especially if the person does not do something in particular.
PROBLEM: Comment: Oh I believe we need to get out of there and let them kill each other with impunity.
SOLUTION: Threat
PROBLEM: Comment: Only one way to handle a terrorist. Kill the SOB.
SOLUTION: Threat
PROBLEM: Comment: Take it easy, Kochbertan spammer crybabies.
We'll study the details of your pipe dream ad infinitum first.
Then we'll kill it.
Happy, now ?
SOLUTION: | Threat
| 8 | NIv2 | task322_jigsaw_classification_threat | fs_opt | [
-0.4771181344985962,
0.7306129336357117,
0.39227697253227234,
-0.06232302635908127,
0.06095694378018379,
-0.22384849190711975,
1.502966284751892,
0.6357382535934448,
0.22562170028686523,
0.48092901706695557,
-0.0056687393225729465,
-0.044264599680900574,
-0.5306541919708252,
-0.51316618919... |
Teacher: In this task, you are given a sentence that is either in the Yoruba language or the English language. Your task is to identify the language of the input sentence. Input sentences should be in Yoruba or English language and also it cannot have two languages at a time.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Everyone had an opportunity to share their opinion.
Solution: English
Reason: The input sentence is in the English language as all the characters are in English and it is recognized as English so it is a positive example.
Now, solve this instance: Ní Friday, August 30, 2019, Arákùnrin Valeriy Moskalenko sọ ọ̀rọ̀ àsọkágbá rẹ̀ fún ilé ẹjọ́.
Student: | Yoruba | 2 | NIv2 | task1621_menyo20k-mt_en_yo_language_identification | fs_opt | [
0.2997857332229614,
0.06793242692947388,
0.7921735048294067,
-0.14239493012428284,
0.4018232226371765,
-0.7672985792160034,
-0.2198428511619568,
0.5168463587760925,
0.7279393672943115,
-0.2722071409225464,
0.4097992479801178,
0.30140531063079834,
-0.4304395318031311,
-0.5809730887413025,
... |
Given the task definition, example input & output, solve the new input case.
In this task, you are given a question and answer options for that question. Using this information, you have to classify each text into different topics: medicine, nursery, psychology, chemistry, pharmacology, biology.
Example: Question: A distension is defined as:
Options: <0> Soft tissue injury. <1> Forced movement of abrupt production. <2> Injury by stretching a muscle. <3> Injury of the joint capsule. <4> Interruption in the continuity of a bone.
Output: nursery
Distension means Bloating and swelling in the belly area. It does not have much to do with chemistry, psychology, pharmacology, biology and medicine. Hence, the correct topic is nursery.
New input case for you: Question: Under the name of xanthines are grouped:
Options: <0> The coca leaf, cocaine and crack. <1> Methadone and heroin <2> The MDA and the MDMA. <3> Nicotine and inhalants. <4> Caffeine and theophylline.
Output: | psychology | 1 | NIv2 | task1434_head_qa_classification | fs_opt | [
0.0706108808517456,
0.37934690713882446,
-0.4868026673793793,
-0.11511905491352081,
-0.26969003677368164,
-0.28115808963775635,
0.8139086365699768,
0.8170482516288757,
1.0247209072113037,
-0.14113523066043854,
-0.36358147859573364,
0.19128787517547607,
-0.09830914437770844,
0.1422864496707... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given two phrases: Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determine whether the Head can be hindered by what is mentioned in the Tail or not. In this task, hindering introduces hindrances that obstruct the natural path to the achievement of a goal. For example, the event PersonX adopts a cat can be obstructed if PersonX is allergic to cats. Classify your answers into "Yes" and "No". The phrase may also contain "___", a placeholder that can be an object, a person, and/or an action.
Head: PersonX applies to medical school<sep>Tail: nervous
Output: | No | 1 | NIv2 | task1204_atomic_classification_hinderedby | zs_opt | [
0.5429633259773254,
0.09781189262866974,
0.4249938130378723,
-0.4291122555732727,
-0.2607976794242859,
-0.9785813093185425,
0.8412705063819885,
0.3251286745071411,
-0.40238285064697266,
-0.32266414165496826,
-0.4078736901283264,
-0.5031116008758545,
-0.3520500361919403,
0.20131045579910278... |
Instructions: In this task, you are given a post in Spanish from online platforms. You are expected to identify whether the post is hateful against immigrants and women. A hateful post expresses hate or encourages violence towards a person or a group. If a post is hateful but not towards immigrants and women, it should be labeled as non-hateful. Answer "hateful" or "Non-hateful". Note that the URLs in the text have been replaced with [Link].
Input: Post: Tu es que la puta rubia esa es gilipollas que le dicen callate que no es y la otra venga venga venga [Link]
Output: | Hateful | 3 | NIv2 | task334_hateeval_classification_hate_es | zs_opt | [
-0.939896285533905,
0.5755907297134399,
0.5247087478637695,
0.8138365745544434,
-0.4351975917816162,
-0.972551703453064,
0.2434026151895523,
1.6424601078033447,
0.19671404361724854,
0.40350812673568726,
-0.14393000304698944,
0.2729441523551941,
-0.6070107221603394,
-0.6416076421737671,
-... |
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 for symbols denoting Punctuations/Separations such as comma, period, backticks etc.,
'ADJ': Adjectives are words that typically modify nouns and specify their properties or attributes,
'ADP': Adposition is a cover term for prepositions and postpositions,
'ADV': Adverbs are words that typically modify verbs for such categories as time, place, direction or manner,
'CONJ': A word used to connect clauses or sentences or to coordinate words in the same clause,
'DET': Determiners are words that modify nouns or noun phrases and express the reference of the noun phrase in context,
'NOUN': Nouns are a part of speech typically denoting a person, place, thing, animal or idea,
'NUM': A numeral is a word, functioning most typically as a determiner, adjective or pronoun, that expresses a number and a relation to the number, such as quantity, sequence, frequency or fraction,
'PRT': Particles are function words that must be associated with another word or phrase to impart meaning and that do not satisfy definitions of other universal parts of speech,
'PRON': Pronouns are words that substitute for nouns or noun phrases, whose meaning is recoverable from the linguistic or extralinguistic context,
'PROPN': A proper noun is a noun (or nominal content word) that is the name (or part of the name) of a specific individual, place, or object,
'VERB': A verb is a member of the syntactic class of words that typically signal events and actions, can constitute a minimal predicate in a clause, and govern the number and types of other constituents which may occur in the clause,
'X': The tag X is used for words that for some reason cannot be assigned a real part-of-speech category.
One example: Sentence: David A. DiLoreto , president of metal container division , was named *-1 to the additional post of group vice president , packaging products , at this packaging {{ , }} industrial and aerospace products concern , *-1 succeeding Delmont A. Davis , who *T*-3 was named *-2 president and chief operating officer in August .
Word: ,
Solution is here: .
Explanation: ',' is assigned the period (.) symbol since it denotes a punctuation.
Now, solve this: Sentence: Unlike many U.S. investors , those in Asia {{ or }} Europe seeking foreign-stock exposure may be less resistant to * paying higher prices for country funds .
Word: or
Solution: | CONJ | 6 | NIv2 | task1167_penn_treebank_coarse_pos_tagging | fs_opt | [
0.4366929829120636,
0.11347271502017975,
-0.17712277173995972,
0.11393848061561584,
-0.10702060163021088,
-0.3591495454311371,
0.6645275354385376,
0.6557318568229675,
-0.39932239055633545,
-0.023159120231866837,
-0.6272092461585999,
0.13208045065402985,
-0.5186734795570374,
0.4744242131710... |
You are given a sentence in Polish. Your job is to translate the Polish sentence into Italian.
Panika i dezorientacja, rozerwanie na kawałki wszystkiego, co znane, zastraszająca świadomość czegoś poza ludzkim pojęciem, można nazwać tylko trwogą. | E questo disorientamento terrorizzante, che separa da tutto ciò che è familiare, che spaventa la consapevolezza di qualcosa oltre la comprensione umana, può essere chiamato solamente terribile stupore. | 0 | NIv2 | task1262_ted_translation_pl_it | zs_opt | [
0.393918514251709,
0.7544524669647217,
0.1343318670988083,
0.04897952079772949,
-0.2584296464920044,
-0.35730478167533875,
0.8692516684532166,
-0.15284256637096405,
0.13776686787605286,
-0.0960349291563034,
-0.8714470863342285,
-0.06637637317180634,
-0.5252810716629028,
0.2257770299911499,... |
In this task you will be given a string that only contains single digit numbers spelled out. The input string will not contain spaces between the different numbers. Your task is to return the number that the string spells out. The string will spell out each digit of the number for example '1726' will be 'oneseventwosix' instead of 'one thousand seven hundred six'.
Input: Consider Input: fivefourninefivezerosevenseven
Output: 5495077
Input: Consider Input: seventhreesixfourthreeseventhreeseveneight
Output: 736437378
Input: Consider Input: seveneightsixsixfoursixtwothreethreezerofourtwo
| Output: 786646233042
| 2 | NIv2 | task1443_string_to_number | fs_opt | [
-0.5200574398040771,
1.2461414337158203,
-0.5303657054901123,
-0.9829310178756714,
-0.1771678924560547,
-0.32007578015327454,
0.575786828994751,
0.29449859261512756,
0.12048377096652985,
-0.5061309933662415,
-0.7961073517799377,
0.39165595173835754,
-1.0072076320648193,
-0.0846208482980728... |
In this task, you are given a sentence in the English language and your task is to convert it into the Hindi language. In translation, keep numbers as it is and make it sentence case (capitalize only the first word of each sentence and noun).
One example: Italy have defeated Portugal 31-5 in Pool C of the 2007 Rugby World Cup at Parc des Princes, Paris, France.
Solution is here: 2007 में फ़्रांस, पेरिस के पार्क डेस प्रिंसेस में हुए रग्बी विश्व कप के पूल C में इटली ने पुर्तगाल को 31-5 से हराया।
Explanation: This is a correct and accurate translation from English to Hindi because translated text is just paraphrased of English sentence. Also, it preserves the numbers as it is.
Now, solve this: Police have described Hudson as about 180 cm tall, with short brown hair and wearing a dark tracksuit top and dark denim jeans.
Solution: | पुलिस ने हडसन को लगभग 180 सेमी लंबा बताया, छोटे भूरे बाल थे और उसने गहरे रंग का ट्रैक सूट और गहरे रंग की डेनिम जीन्स पहनी थी। | 6 | NIv2 | task432_alt_en_hi_translation | fs_opt | [
0.22249868512153625,
0.947738766670227,
-0.22141209244728088,
0.3024001121520996,
-0.36537671089172363,
-0.29021260142326355,
0.25440889596939087,
0.4694688320159912,
-0.17651894688606262,
-0.3627279996871948,
-1.2733275890350342,
0.6197903156280518,
-0.19217845797538757,
0.345062732696533... |
Given the task definition, example input & output, solve the new input case.
Given a passage, construct a question on the basis of the information present in the passage. Construct the question in such a way that (i) it is unambiguous, (ii) it is answerable from the passage, (iii) its answer is unique (iv) it answer uses text phrases from the passage. Avoid creating questions that (i) can't be answered correctly without actually understanding the passage and (ii) uses the same words or phrases given in the passage.
Example: Chronic rhinosinusitis (CRS) is a heterogeneous disease with an uncertain pathogenesis. Group 2 innate lymphoid cells (ILC2s) represent a recently discovered cell population which has been implicated in driving Th2 inflammation in CRS; however, their relationship with clinical disease characteristics has yet to be investigated. The aim of this study was to identify ILC2s in sinus mucosa in patients with CRS and controls and compare ILC2s across characteristics of disease. A cross-sectional study of patients with CRS undergoing endoscopic sinus surgery was conducted. Sinus mucosal biopsies were obtained during surgery and control tissue from patients undergoing pituitary tumour resection through transphenoidal approach. ILC2s were identified as CD45(+) Lin(-) CD127(+) CD4(-) CD8(-) CRTH2(CD294)(+) CD161(+) cells in single cell suspensions through flow cytometry. ILC2 frequencies, measured as a percentage of CD45(+) cells, were compared across CRS phenotype, endotype, inflammatory CRS subtype and other disease characteristics including blood eosinophils, serum IgE, asthma status and nasal symptom score. 35 patients (40% female, age 48 ± 17 years) including 13 with eosinophilic CRS (eCRS), 13 with non-eCRS and 9 controls were recruited. ILC2 frequencies were associated with the presence of nasal polyps (P = 0.002) as well as high tissue eosinophilia (P = 0.004) and eosinophil-dominant CRS (P = 0.001) (Mann-Whitney U). They were also associated with increased blood eosinophilia (P = 0.005). There were no significant associations found between ILC2s and serum total IgE and allergic disease. In the CRS with nasal polyps (CRSwNP) population, ILC2s were increased in patients with co-existing asthma (P = 0.03). ILC2s were also correlated with worsening nasal symptom score in CRS (P = 0.04).
Output: Are group 2 innate lymphoid cells ( ILC2s ) increased in chronic rhinosinusitis with nasal polyps or eosinophilia?
The question is based on the following sentences from the passage (i) Group 2 innate lymphoid cells (ILC2s) {ii) In the CRS with nasal polyps (CRSwNP) population, ILC2s were increased in patients with co-existing asthma (iii) As ILC2s are elevated in patients with CRSwNP, they may drive nasal polyp formation in CRS. and (iv) They were also associated with increased blood eosinophilia
New input case for you: Diastolic runoff in the abdominal aorta, with subsequent circulatory mesenteric insufficiency, has been postulated as a cause of necrotizing enterocolitis in term infants with congenital heart disease. With this study we sought to determine whether Doppler-flow characteristics in the abdominal aorta can predict which infants are at specific risk, independent of gestational age and type of congenital heart disease.', 'We conducted a case-control study of term infants with congenital heart disease and proven necrotizing enterocolitis (n = 18) compared with gestational age-matched and diagnosis-matched control subjects (n = 20). Abdominal aortic Doppler velocities, time intervals, and reversals were analyzed. Groups were compared, and independent risk factors for necrotizing enterocolitis were determined.', 'The groups were similar with regard to weight, pulse pressure, use of prostaglandins or inotropes, presence of a patent ductus arteriosus, and systolic function. However, 47% of the case subjects with necrotizing enterocolitis had persistent retrograde diastolic flow in the abdominal aorta compared with 15% of the control subjects. When adjusting for multiple risk factors, persistent diastolic flow reversal remained the only factor significantly associated with necrotizing enterocolitis.
Output: | Is persistent diastolic flow reversal in abdominal aortic Doppler-flow profiles associated with an increased risk of necrotizing enterocolitis in term infants with congenital heart disease? | 1 | NIv2 | task847_pubmedqa_question_generation | fs_opt | [
0.4055958390235901,
0.28042760491371155,
-0.18304750323295593,
-0.08937858045101166,
0.7660573720932007,
-0.4149892032146454,
0.33572331070899963,
0.7242246270179749,
-0.3058076798915863,
-0.07212117314338684,
-0.2815015912055969,
0.08802301436662674,
-0.5852836966514587,
0.548351407051086... |
Detailed Instructions: In this task you will be given an arithmetic operation and you have to find its answer. The symbols of operators '+' and '-' has been swapped i.e you need to perform subtraction when you see a '+' symbol and addition in case of '-' symbol.
See one example below:
Problem: 5 + 3
Solution: 2
Explanation: Here, '+' represents subtraction operation. So, the answer is 2 (5-3=2).
Problem: 4284 - 7547 - 4478 - 3941 + 9791 - 3691 + 6936
Solution: | 7214 | 4 | NIv2 | task085_unnatural_addsub_arithmetic | fs_opt | [
0.08535619080066681,
-0.05213100463151932,
-0.8136506080627441,
0.4962611198425293,
-0.08135282248258591,
0.23646436631679535,
0.4915052652359009,
1.4124431610107422,
0.30815792083740234,
-0.27735352516174316,
-0.7258858680725098,
-0.5476974248886108,
-0.48394590616226196,
0.24200576543807... |
TASK DEFINITION: You are given an open-domain question from an open movie database. Your task is to provide an answer to that question. Try to only include the answer. Do not put it in a sentence.
PROBLEM: which film did Mark H. Baker write the story for?
SOLUTION: Flight of the Navigator
PROBLEM: what is the language spoken in You're Not You?
SOLUTION: English
PROBLEM: what does Sergey Garmash appear in?
SOLUTION: | 12
| 8 | NIv2 | task615_moviesqa_answer_generation | fs_opt | [
-0.3817718029022217,
-0.10871439427137375,
0.07389289885759354,
0.12219500541687012,
-0.33248165249824524,
1.2321302890777588,
1.1898796558380127,
-0.18437157571315765,
0.1667967140674591,
0.11834335327148438,
0.28422048687934875,
-0.11978612840175629,
-0.2693798542022705,
0.52194666862487... |
Q: In this task you will be given a passage and a yes/no question based on the passage. You should answer the question using the information from the passage.
passage: Basil (UK: /ˈbæzəl/, US: /ˈbeɪzəl/; Ocimum basilicum), also called great basil or Saint-Joseph's-wort, is a culinary herb of the family Lamiaceae (mints).
question: is basil leaves the same as mint leaves?
A: | No | 7 | NIv2 | task380_boolq_yes_no_question | zs_opt | [
0.519037663936615,
1.007367491722107,
-0.3742496371269226,
0.3003934621810913,
0.19050070643424988,
-1.1042964458465576,
1.7340087890625,
-0.17088951170444489,
-0.12816491723060608,
0.11832252144813538,
0.10247768461704254,
0.4446427822113037,
-1.021681785583496,
0.4482138752937317,
0.61... |
TASK DEFINITION: In this task you will be given a string of characters. You should remove all vowels from the given string. Vowels are: i,e,a,u,o. The character 'y' or 'Y' does not count as a vowel.
PROBLEM: xsY
SOLUTION: xsY
PROBLEM: PiaYhvxreRuasge
SOLUTION: PYhvxrRsg
PROBLEM: kaUooGofWoSQSHp
SOLUTION: | kGfWSQSHp
| 8 | NIv2 | task365_synthetic_remove_vowels | fs_opt | [
0.7281085252761841,
0.7051973938941956,
-0.33022990822792053,
-0.5763782262802124,
0.4403385519981384,
-0.4305512011051178,
0.7893974781036377,
0.3417549729347229,
0.23930439352989197,
-0.20365840196609497,
-0.15570791065692902,
-0.6697701215744019,
0.1357172429561615,
-0.9508547186851501,... |
Teacher:You are given a sentence from a conversation between a human and a virtual assistant. Your task is to identify whether the sentence is a question or not. Answer with Yes or No.
Teacher: Now, understand the problem? Solve this instance: Thank you for your assistance; that's all.
Student: | No | 6 | NIv2 | task879_schema_guided_dstc8_classification | zs_opt | [
-0.332912802696228,
0.331352174282074,
0.6713855266571045,
-0.20607340335845947,
-0.038590461015701294,
-0.72267746925354,
0.6339520215988159,
0.5420281887054443,
0.8397445678710938,
0.2912392020225525,
0.2613798975944519,
-0.5907907485961914,
0.002237972104921937,
-0.5527320504188538,
0... |
In this task, you will be shown a prompt from a judicial decision and multiple holding statements derived from citations following text in a legal decision. Holdings represent the governing legal rule when the law is applied to a particular set of facts. There are five answer choices for each citing text. The correct answer is the holding statement that corresponds to the citing text. You should write an incorrect option. Even though there exist multiple wrong answers, we only need a single wrong answer. There is a <HOLDING> token in the position of the citing text prompt where the holding statement was extracted.
of relief. Fed.R.Civ.P. 8(a). 32 . See also Avakian v. Chulengarian, 328 Ill.App.3d 147, 262 Ill.Dec. 663, 766 N.E.2d 283, 294 (2002); Tucker v. St. James Hosp., 279 Ill.App.3d 696, 216 Ill.Dec. 332, 665 N.E.2d 392, 396 (1996). 33 . This conclusion also is consistent with the few of our sister circuits that have addressed this precise issue. See, e.g., Liggon-Redding v. Estate of Sugarman, 659 F.3d 258, 261-65 (3d Cir.2011) (finding no conflict between Rule 8 or Rule 11 and a Pennsylvania statute requiring a “certificate of merit” to be filed in professional malpractice claims); Chamberlain v. Giampapa, 210 F.3d 154, 158-61 (3d Cir.2000) (finding no conflict between Rule 8 or Rule 9 and a similar New Jersey law); cf. Littlepaige v. United States, 528 F. App'x 289, 292-93 (4th Cir.2013) (<HOLDING>). 34 . R.40 at 2 (citation omitted). 35 . R.49
Holding statements: (A) holding that discovery rule applied to wrongful death action predicated on medical malpractice (B) holding amendment to statute of limitations was a procedural amendment to be applied retroactively in a medical malpractice case (C) holding expert testimony is generally required to establish proximate cause in medical malpractice cases (D) holding the provisions of a comprehensive medical malpractice act unconstitutional (E) holding that a north carolina rule requiring an expert certification in a medical malpractice case applied in a federal tort claims act case sounding in medical malpractice brought in federal court | holding that discovery rule applied to wrongful death action predicated on medical malpractice | 0 | NIv2 | task287_casehold_legal_incorrect_answer_generation | zs_opt | [
-0.024049635976552963,
-0.13246682286262512,
-0.13774895668029785,
-0.1263449788093567,
0.43809932470321655,
-1.0000433921813965,
0.3768535256385803,
1.0308107137680054,
-0.2513582706451416,
-0.3967384099960327,
-0.5587795972824097,
0.7824054956436157,
-0.30729401111602783,
0.0378480330109... |
A text is given in Marathi. Translate it from the Marathi language to the Tamil language. The translation must not omit or add information to the original sentence.
[EX Q]: இந்தியர்களாகிய நமக்கு இவை யாவும், சாதகமாக உள்ளன.
[EX A]: आपणा भारतीयांसाठी सर्व गोष्टी अनुकूल आहेत.
[EX Q]: இந்த தீவிரத்துக்குக் காரணம் உண்டு.
[EX A]: हे वारंवार भेटणेजाणीवपूर्वक आहे.
[EX Q]: கொரியாவில் தொழில்நுட்பத் திறன்கள், செயல்வல்லமைகள் வலுவாக இருக்கும் நிலையில், இந்தியாவில் போக்குவரத்து, மின்சாரம், துறைமுகங்கள், கப்பல் கட்டும் தளங்கள், வீட்டு வசதிகள், நகர்ப்புறக் கட்டமைப்பு மேம்பாடு, இவற்றுக்குப் பெரிய தேவை உள்ளது.
[EX A]: | वाहतूक असो, ऊर्जा असो, बंदरे असो, जहाजबांधणी असो, गृहनिर्माण असो किंवा शहरी पायाभूत सुविधा. भारतात या सर्व बाबींना मोठी मागणी असून कोरियामध्ये त्यांची पूर्तता करणारी तंत्रज्ञानसंबंधी सक्षमता आहे.
| 6 | NIv2 | task1084_pib_translation_tamil_marathi | fs_opt | [
0.625064492225647,
0.34248071908950806,
0.005648376885801554,
-0.2283565104007721,
0.13302552700042725,
-1.1629273891448975,
0.01206140872091055,
0.11701381206512451,
0.029273007065057755,
0.1721261739730835,
-0.25653406977653503,
0.006353649310767651,
0.17854222655296326,
0.10808582603931... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
Given a document, an entity and its sentiment towards the entity, verify if it is the correct sentiment towards the entity. Answer should be yes or no. Note that URLs in the text have been replaced with [Link].
Verify if the sentiment of the following document towards the entity Bill Clinton is Positive . Bill Clinton knows how to win friends and influence people. The former president is a master of reinvention — and the same talents that guided him into office have propelled him, more recently, into the stratosphere of Internet stardom.
Solution: yes
Why? Here the author of the document praises Bill for this ability to win friends. Hence the sentiment should be Positive and the answer is yes.
New input: Verify if the sentiment of the following document towards the entity Donald Trump Jr. is Neutral . Donald Trump Jr. who once compared refugees to poisoned Skittles and got stuck in traffic behind a Wienermobile made a very bold fashion choice this weekend.
He was chilling in Florida with the Trump family when he tweeted out this poolside photo.
I'm going to have to buy 5-10 000 of these to pass around to our buddies in the #MSM. In the meantime I'll model it for them😂. #yourewelcome pic.twitter.com/Hnn3Z5Pspm — Donald Trump Jr. (@DonaldJTrumpJr) April 15 2017
Of course there was a reference to that photo of Donald Trump Jr. sitting on a tree stump.
Solution: | yes | 0 | NIv2 | task423_persent_document_sentiment_verification | fs_opt | [
-0.9177781343460083,
0.266701877117157,
0.36760178208351135,
0.46850669384002686,
0.04469624161720276,
-0.793735146522522,
0.5451910495758057,
0.960862398147583,
-0.18755745887756348,
0.42785754799842834,
0.15453371405601501,
0.012410564348101616,
-0.1874421089887619,
-0.3322093188762665,
... |
Teacher: In this task, you are given a sentence from the Bible in Persian, and your task is to translate it into English.
Teacher: Now, understand the problem? If you are still confused, see the following example:
در ابتدا، خدا آسمانها و زمین را آفرید.
Solution: In the beginning God created the heaven and the earth.
Reason: This is a good example. The above sentence is correctly translated from Persian to English.
Now, solve this instance: پس یوسف در نظر وی التفات یافت، و او را خدمت میکرد، واو را به خانه خود برگماشت و تمام مایملک خویش را بدست وی سپرد.
Student: | And the LORD was with Joseph, and he was a prosperous man; and he was in the house of his master the Egyptian. | 2 | NIv2 | task654_bible_fa_en_translation | fs_opt | [
-0.4591503143310547,
1.345430612564087,
-0.39536961913108826,
-0.09389270842075348,
-0.6515909433364868,
-0.5799563527107239,
1.1608264446258545,
0.6578291654586792,
0.644775927066803,
0.17790602147579193,
-0.5618179440498352,
0.6574467420578003,
-0.69780433177948,
-0.10902095586061478,
... |
instruction:
In this task, you are given a dialogue from a conversation between an agent and a customer. Your task is to determine the speaker of the dialogue. Answer with "agent" or "customer".
question:
May I know your source airport code please?
answer:
agent
question:
Hello, how may I support you today?
answer:
agent
question:
Sure, I am glad to help you with that. Can you please provide your preferable dates of travelling?
answer:
| agent
| 9 | NIv2 | task575_air_dialogue_classification | fs_opt | [
-0.28972184658050537,
0.2929108142852783,
-0.24731644988059998,
-1.1123113632202148,
0.11172305047512054,
-0.5503911972045898,
0.4838865399360657,
-0.25788187980651855,
0.18698793649673462,
0.656419575214386,
-0.2361246645450592,
-0.18423330783843994,
-1.0423730611801147,
-0.14087386429309... |
instruction:
In this task, you're given a pair of sentences in the Persian Language written in the Persian alphabet. Your job is to choose whether the two sentences agree (entailment), disagree (contradiction), or neither (neutral). Your answer must be in the form of the letters E, C, and N, respectively. The sentences have been separated by a newline character.
question:
اعجاز لفظی و ظاهری قرآن از مقوله زیبایی و اعجاز معنوی قرآن از مقوله معرفتی است.
معجزه لفظی قرآن کریم در باب دنیوی و معجزه معنوی آن در باب اخروی می باشد.
answer:
C
question:
خداوند در قرآن کریم دو اصل مودت و رحمت را برای حفظ استحکام خانواده و رابطه بین زن و شوهر معرفی کرده است.
قرآن مجید از عشق و مدارا به عنوان پایه وحدت زن و شوهر در عرصه زندگی صحبت کرده است.
answer:
C
question:
پرویز ناتل خانلری خود باآنکه در جوانی در شاعری گرایشهائی مشابه نیما یوشیج داشت، ولی با مطالعهٔ بیشتر به این نتیجه رسید که عروض فارسی ظرفیّتهای گستردهای دارد و آنچه نیازمند تغییر و تحوّلست، زبان شعرست که باید امروزی شود. مجموعهٔ اشعار او با نام "ماه در مرداب" در سال ۱۳۴۳ انتشار یافت و بارها تجدید چاپ شد.
مجموعه شعر "ماه در مرداب" را "پرویز ناتل خانلری" سروده است.
answer:
| E
| 9 | NIv2 | task534_farstail_entailment | fs_opt | [
-0.013335056602954865,
0.3084568381309509,
-0.0911366194486618,
0.07238615304231644,
-0.13704535365104675,
0.2136474847793579,
1.0241730213165283,
0.48953092098236084,
0.31143972277641296,
-0.24210718274116516,
-0.8742344379425049,
-0.14746978878974915,
-0.722271203994751,
-0.1801310181617... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a public comment from online platforms. You are expected to classify the comment into two classes: toxic and non-toxic. Toxicity is defiend as anything that is rude, disrespectful, or unreasonable that would make someone want to leave a converation.
Comment: Ahhh of course. Label him a hater cuz he won. Sore loser eh!!
Output: | Toxic | 1 | NIv2 | task327_jigsaw_classification_toxic | zs_opt | [
-0.7605685591697693,
0.28644734621047974,
0.7005575299263,
0.11607380211353302,
0.07364344596862793,
-0.471876323223114,
0.47833967208862305,
0.2848712205886841,
0.4578297734260559,
0.133605495095253,
-0.44437792897224426,
0.012594207189977169,
-0.2505781948566437,
-0.7882074117660522,
0... |
You are given a background paragraph that describes one or more causal or qualitative relationships such as a relationship in economics or a scientific law and a story that makes use of the concepts or the relationship described in the provided paragraph. You need to come up with a question about the story that requires an understanding of the relationship described in the background paragraph. The generated question should not be answerable without both the background and story. Write a question about the story that requires a relationship in the background paragraph to answer. Check whether your question requires both the background paragraph and the story to answer. If your question can be answered by only one of these, try to rewrite your question so that it requires both. Note that "flipping" a word in the question can give rise to a new question where the answer will be different from the original question. Often, "flipping" a word gives rise to flipping the direction of the relationship, for example, from "increase" to "decrease."
Example Input: Background Paragraph: Sugaring is a food preservation method similar to pickling. Sugaring is the process of desiccating a food by first dehydrating it, then packing it with pure sugar. This sugar can be crystalline in the form of table or raw sugar, or it can be a high sugar density liquid such as honey, syrup or molasses.
The purpose of sugaring is to create an environment hostile to microbial life and prevent food spoilage. Sugaring is commonly used to preserve fruits as well as vegetables such as ginger. From time to time sugaring has also been used for non-food preservations. For example, honey was used as part of the mummification process in some ancient Egyptian rites.
A risk in sugaring is that sugar itself attracts moisture. Once a sufficient moisture level is reached, native yeast in the environment will come out of dormancy and begin to ferment the sugars into alcohol and carbon dioxide. This leads to the process of fermentation. Although fermentation can be used as a food preservation method, it must be intentionally controlled, or the results will tend to be unpleasant.
Story: Peter decided to sugar mangoes, ginger, pineapples, peaches to preserve them for next spring. He also bought blueberries and raspberries to eat fresh.
Example Output: Which fruit had a higher sugar content, ginger or blueberries?
Example Input: Background Paragraph: Protozoa generally feed by engulfing and digesting other organisms. As consumers, they have various roles in food chains and webs. Some are predators. They prey upon other single-celled organisms, such as bacteria. In fact, protozoa predators keep many bacterial populations in check. Other protozoa are herbivores. They graze on algae. Still others are decomposers. They consume dead organic matter. There are also parasitic protozoa that live in or on living hosts. For example, the protozoan that causes malaria lives inside a human host. For their part, protozoa are important food sources for many larger organisms, including insects and worms.
Story: Two biologists studied different living creatures. Matt studied protozoa, while his friend Greg studied nematodes and insects.
Example Output: Which friend studied less about herbivore protozoa grazing on algae?
Example Input: Background Paragraph: Like water in the ocean, air in the atmosphere exerts pressure that increases with depth. Most gas molecules in the atmosphere are pulled close to Earth’s surface by gravity. As a result, air pressure decreases quickly at lower altitudes and then more slowly at higher altitudes. This is illustrated in Figure below . Air pressure is greatest at sea level, where the depth of the atmosphere is greatest. At higher altitudes, the pressure is less because the depth of the atmosphere is less. For example, on top of Mount Everest, the tallest mountain on Earth, air pressure is only about one-third of the pressure at sea level. At such high altitudes, low air pressure makes it hard to breathe and is dangerous to human health.
Story: Molly has just moved to a new city for a job she was just hired for. She used to live in a city up in the mountains named Midgar. She liked living there due to the hikes she could go on and seeing the beautiful nature of the hills and mountains. The town she lives in now, Treno, is closer to sea level and is mostly flat plains and farm land. It's a change of scenery, and she hopes she starts to enjoy it more.
Example Output: | Is air pressure in Midgar higher or lower than in Treno?
| 3 | NIv2 | task060_ropes_question_generation | fs_opt | [
0.10944090783596039,
0.23651188611984253,
-0.3843874931335449,
-0.20950672030448914,
0.5206911563873291,
-0.6359081864356995,
0.3278377950191498,
1.197210669517517,
-0.8869075775146484,
-0.10816776752471924,
-0.6012954115867615,
-0.5127543807029724,
-0.40511947870254517,
0.1970082223415374... |
You are given a concept, and a list of answers. You should generate a question about the concept that leads to the given answer(s).
Q: concept: Italy answers: ['World War II']
A: | when did the italian fascists came to power? | 4 | NIv2 | task1602_webquestion_question_genreation | zs_opt | [
-0.0750625878572464,
0.8186219334602356,
-0.11766169220209122,
0.23991155624389648,
0.3188488185405731,
-1.4081459045410156,
-0.023904938250780106,
1.8109829425811768,
0.19102369248867035,
-0.3289371728897095,
-0.49252158403396606,
0.13626906275749207,
-0.2154543548822403,
0.46253204345703... |
Q: Here are two questions (Question1 and Question2). If these questions have the same meaning and same answer, answer "Yes", otherwise "No".
Question1: How can I improve my communication and verbal skills?, Question2: How can I improve my communication skills?
A: | Yes | 7 | NIv2 | task1287_glue_qqp_paraphrasing | zs_opt | [
-0.5614134073257446,
0.8154828548431396,
0.5757925510406494,
-0.11119206249713898,
0.18585243821144104,
-0.49359560012817383,
0.17308199405670166,
0.5287883877754211,
-0.3713076114654541,
-0.15292422473430634,
-0.29316475987434387,
-0.9706757664680481,
-1.4062588214874268,
-0.2628350257873... |
Given the task definition and input, reply with output. In this task, answer 'Yes' if the frequency of the given word in the two sentences is equal, else answer 'No'.
Sentence1: 'a boy sits on top of a suitcase and between two other stacks of luggage', Sentence2: 'two women having a drink next to a fire'. Is the frequency of the word 'a' in two sentences equal?
| Yes | 5 | NIv2 | task159_check_frequency_of_words_in_sentence_pair | zs_opt | [
-0.5732126235961914,
0.4476754665374756,
-0.08166606724262238,
-0.48236995935440063,
-0.10330107063055038,
0.09230200201272964,
0.40770280361175537,
1.1144359111785889,
0.053472790867090225,
-0.005243874154984951,
-0.3138137459754944,
-0.09709767997264862,
0.08949510753154755,
0.0061181960... |
In this task, you are given an input list A. You need to convert all the alphabets in the list with a number representing their position in the English alphabet. E.g., replace A by 1, B by 2, a by 1, b by 2, and so on.
Ex Input:
['4795', 'W', '5241', 'z', '2089', '491', '3775', '3161', 'x', '6747', '85', 'w', 'V']
Ex Output:
4795, 23, 5241, 26, 2089, 491, 3775, 3161, 24, 6747, 85, 23, 22
Ex Input:
['s', '1165', 'z', '2673', 's', 'n', '847', '2553', '9111', 'w', '9411', 'B', 'U', 'P', 'c']
Ex Output:
19, 1165, 26, 2673, 19, 14, 847, 2553, 9111, 23, 9411, 2, 21, 16, 3
Ex Input:
['O', '6529', 'h', '6265', 'h', 'c', '4655', 'i', 'e', 'S', 'G', '5649', '6289', 'a', '4915', '8835', 'w', 'e']
Ex Output:
| 15, 6529, 8, 6265, 8, 3, 4655, 9, 5, 19, 7, 5649, 6289, 1, 4915, 8835, 23, 5
| 1 | NIv2 | task622_replace_alphabets_in_a_list_by_their_position_in_english_alphabet | fs_opt | [
0.18659357726573944,
-0.08799377828836441,
0.2537629008293152,
-0.39438489079475403,
0.03936762735247612,
-0.5749335289001465,
0.5558791756629944,
0.5161186456680298,
-0.32358813285827637,
-0.0824829638004303,
-0.3232724666595459,
0.43466243147850037,
0.07812599837779999,
-0.13395455479621... |
In this task, you are given a dialogue between a user and an assistant, where users and assistants converse about geographic topics like geopolitical entities and locations. The task here is to find if the dialogue is by the user or assistant. Classify your answers into user and assistant.
Let me give you an example: Ok, the national drink of Scotland is whisky.
The answer to this example can be: assistant
Here is why: It is pretty straightforward. It is knowledge sharing, and the assistant explains the question asked by the user.
OK. solve this:
Hello, can you please tell me about Mizoram?
Answer: | user | 8 | NIv2 | task577_curiosity_dialogs_classification | fs_opt | [
-0.22339239716529846,
0.5713192820549011,
-0.39498376846313477,
-0.7475430965423584,
-0.2518259882926941,
0.041698068380355835,
1.4738043546676636,
-0.9537211060523987,
0.8275600075721741,
-0.2941613793373108,
-0.007881805300712585,
-0.2689804136753082,
-0.47426626086235046,
0.515421509742... |
Indicate if the following Polish tweet contains cyber-bullying content with 'Yes'; otherwise, respond with 'No'.
One example: Tweet: @anonymized_account @anonymized_account @anonymized_account Gdzie jest @anonymized_account . Brudziński jesteś kłamcą i marnym kutasem @anonymized_account, Question: Does the tweet contain cyberbullying (harmful) content?
Solution is here: Yes
Explanation: The tweet contains Bullying content
Now, solve this: Tweet: @anonymized_account @anonymized_account jeść hawajską i w dodatku sztućcami to chyba najwièkszy grzech na świecie :) , Question: Is the tweet free of any cyberbullying (harmful) content?
Solution: | Yes | 6 | NIv2 | task839_cdt_classification | fs_opt | [
-1.4631974697113037,
1.1244018077850342,
0.5751829147338867,
0.48854267597198486,
-0.7358276844024658,
-0.2529788911342621,
0.9121585488319397,
-0.9363012313842773,
-0.4330146908760071,
0.13819871842861176,
-0.3564487397670746,
0.1435094177722931,
-0.6774699687957764,
-0.000690817541908472... |
In this task, you will be shown a conversation. You need to write a question with three choices for the conversation. Your question should be answerable based on the conversation and only have one correct answer. Note that you don't need to answer your question. "W" and "M" in the conversations stand for "woman" and "man".
W: How do you feel today? M: I still have a headache, but my temperature has gone down. | Where are the speakers possibly? (A) In a factory. (B) In a hospital. (C) On a train. | 0 | NIv2 | task246_dream_question_generation | zs_opt | [
0.48886290192604065,
0.3661658763885498,
-0.21804672479629517,
-0.656825602054596,
0.0410846583545208,
-0.38701754808425903,
0.8841797113418579,
0.267788290977478,
0.23982374370098114,
-0.7136392593383789,
-0.5466102957725525,
0.10079103708267212,
0.3778492510318756,
0.0870223343372345,
... |
Q: In this task you are expected to provide an SQL statement from an english description of what that SQL statement does. The description may include multiple steps but you should only ouput one SQL statement that accomplishes every step. An SQL query works by selecting data from a table where certain conditions apply. A table contains columns where every row in that table must have a value for each column. Every table has a primary key that uniquely identifies each row, usually an id. To choose which columns are returned you specify that after the "SELECT" statement. Next, you use a "FROM" statement to specify what tables you want to select the data from. When you specify a table you can rename it with the "AS" statement. You can reference that table by whatever name follows the "AS" statement. If you want to select data from multiple tables you need to use the "JOIN" statement. This will join the tables together by pairing a row in one table with every row in the other table (Cartesian Product). To limit the number of rows returned you should use the "ON" statement. This will only return rows where the condition specified after the statement is true, this is usually an equals operator with primary keys. You can also use the "WHERE" statement to specify that only rows with column values statisfying a certain condition, should be returned. The "GROUP BY" statement will group rows together that have equal column values for whatever columns follows the statement. The "HAVING" statement will return groups that statisfy whatever condition follows the statement. Any column(s) being returned from grouped rows must either be an aggregate function, (AVG, MAX, COUNT, SUM, ...) of a column, or the column(s) that the data was grouped by. To sort the returned data you can use the "ORDER BY" command which will order the data by whatever aggregate function or column follows the statement. The "DESC" statement will sort in descending order and the "ASC" statement will sort in ascending order. Finally, you can use the "LIMIT" statement to return a certain number of rows. When "*" is used in an SQL statement every column is returned. For example, SELECT * FROM table WHERE attribute = 1, will select every column from rows with the attribute column equal to 1.
find the minimum Order_Quantity and the summation of Order_Quantity in Invoice_Items table
A: | SELECT Min ( Order_Quantity ) , Sum ( Order_Quantity ) FROM Invoice_Items | 7 | NIv2 | task077_splash_explanation_to_sql | zs_opt | [
0.6133435964584351,
0.5597875118255615,
-1.1009384393692017,
0.9353093504905701,
-0.33762669563293457,
-0.2976521849632263,
0.6489367485046387,
0.9948424696922302,
-0.35873112082481384,
0.7590643763542175,
0.27289819717407227,
0.44989538192749023,
0.06113159656524658,
0.3383004367351532,
... |
Detailed Instructions: You are given a sentence in Persian. Your job is to translate the Farsi sentence into Italian.
Problem:همه راضی ٫ منم خوشحال.
Solution: | Va bene per tutti, sono contento. | 8 | NIv2 | task1271_ted_translation_fa_it | zs_opt | [
-0.20250657200813293,
1.023139476776123,
-0.20581665635108948,
-0.5534014105796814,
-0.8042104244232178,
-0.4988136887550354,
0.6283578872680664,
0.5631195306777954,
1.0378133058547974,
-0.25656163692474365,
-1.0907565355300903,
0.48772889375686646,
-0.09203170984983444,
0.4807069897651672... |
Q: Given a sentence, an entity and its sentiment towards the entity, verify if it is the correct sentiment towards the entity. Answer should be yes or no. Note that URLs in the text have been replaced with [Link].
Verify if the sentiment of the following document towards the entity Paul Kennedy is Negative . Kennedy's investigation as well as several others including the public inquiry were launched after the amateur video of the confrontation was made public.
A: | no | 7 | NIv2 | task422_persent_sentence_sentiment_verification | zs_opt | [
-0.8371943831443787,
-0.01165524311363697,
0.6448630094528198,
-0.26542773842811584,
-0.5091098546981812,
-1.1280735731124878,
0.9246340990066528,
0.32616397738456726,
0.06230700761079788,
0.5285259485244751,
0.23376141488552094,
-0.5968607664108276,
-0.21824780106544495,
-0.42617070674896... |
Given the task definition, example input & output, solve the new input case.
In this task, you are given a text of many news articles seperated by special token "|||||". Your task is to summarize them.
Example: A photo series on the popular Humans of New York Facebook page may have went viral and captured the nation’s attention last Tuesday, but for Daniel Kang, the post really hit home.
When Kang, a junior studying computer science at the University of Michigan, heard that the refugee pictured and his family were relocating to his hometown of Troy, Mich., he said he knew he had to help.
“I was really inspired by how intelligent he was and I knew a lot of people wanted to welcome him, so I thought, why not it be me?” he said.
On the Humans of New York Facebook page with over 16 million likes — including comments from President Obama — the seven-part picture series’ captions detail one Syrian scientist and his family’s tale of loss after a missile strike destroyed their home, forcing them to to flee to Turkey, now with plans of coming to the United States.
“Everything ended for us that day. That was our destiny. That was our share in life,” the scientist said. Battling stomach cancer, the loss of a home, career and seven family members, the man, whose name remains confidential to protect his identity as a refugee, expressed his hope for a new life in the United States.
“I learned today that I’m going to Troy, Michigan,” he said. “I know nothing about it. I just hope that it’s safe and that it’s a place where they respect science. I just want to get back to work. I want to be a person again. I don’t want the world to think I’m over. I’m still here.”
Knowing that refugees come to the United States with little more than they can carry, Kang quickly organized a crowdfunding campaign to help establish the man in his new home.
In four days, the GoFundMe page has raised over $16K in donations from over 700 people. On Saturday afternoon, actor Edward Norton also began a fundraiser for the scientist, raising even more for the refugee who says he “just wants to be a person again.”
“The response has been overwhelmingly positive,” said Kang. “A lot of people thanked me for doing a nice thing but I really feel like I was doing what anyone else would have done.”
Kang said he’s received many messages from people expressing their gratitude, those who want to reach out to the man personally, as well local companies interested in working with the scientist. This includes invitations to lecture at local colleges, research job opportunities and potential help from local medical facilities in treating the man’s stomach cancer.
“There’s definitely a lot of interest in helping him out,” he said.
The biggest concern, said Kang, are those skeptical of how the money will reach the man.
Kang, who has successfully crowdfunded in the past, is working closely with GoFundMe, the local refugee relocation agency Lutheran Social Services of Michigan, and is in communication with the Humans of New York staff to make sure all funding goes to the scientist.
In the end, Kang said he just hopes the scientist receives the welcome he deserves.
“If I could talk to him right now, I’d just tell him how sorry I am for everything he’s been through and that he’s coming to a great place. One of the things he said that resonated with me the most is that ‘I hope Troy is a place that appreciates science.’
I’d say out of all the cities in Michigan, Troy is the best place to raise a family, be a scientist and we can’t wait to have him.”
Oona Goodin-Smith is a student at Oakland University and a member of the USA TODAY College contributor network. ||||| I saw this story on one of my favorite sites, Humans of New York, and it moved me to tears. This man has suffered profound loss that would crush the spirit of many people and yet he still passionately wants a chance to contribute positively to the world. If we don’t welcome people like this into our communities and empower his dream of making an impact with his life, then we’re not the country we tell ourselves we are. Let’s reject the 'anti-human’ voices that tell us to fear refugees and show this man and his family what Americans are really made of. Let’s show that a country built by the energy and dreams of immigrants still believes in brave people who come here with hope for better life.
Everything we raise here will go to help this family so that the father can get the medical treatment he needs to live and pursue his work, and his family can build a new stable life after their tragedy, and…as the Scientist beautifully expresses…to support his dream of contributing to the world.
Thanks to Humans of New York for sharing these stories. Thanks to the team at CrowdRise for putting this together and figuring out how to get even the credit card transaction fees covered so we can get the maximum to the family.
Thanks to everyone who rallies together to create the power of the crowd. If enough of us kick in the price of two frappucinos, we can probably transform the experience of this family and show them that life can deliver healing and kindness, not just heartbreak.
Thanks to Benevolent, all donations are tax-deductible. We will work with Benevolent to use all donated funds to help this family and will seek to use any excess or unused funds to help the other 11 profiled in the HONY ‘Syrian American’ series.
Edward Norton ||||| DETROIT, MI -- Moved to tears by a Humans of New York feature on a Syrian refugee fleeing to Metro Detroit, Hollywood actor Edward Norton launched an online fundraiser that had raised nearly $450,000 for the widower and his four children as of Thursday afternoon.
"I didn't hear about it, but I want to thank him very much from the humanity perspective," the man told NBC News after hearing about the fundraiser's success. "There are people outside who need that money much more than me."
The man asked NBC to refer to him as "Abu Ammar," a fake named used to protect his relatives who remain in Syria. He's known to many on the Internet simply as "The Scientist," which is also his profession.
The refugee's family was scheduled to arrive in Troy, a Detroit suburb, Thursday. He and four surviving children spent the last two years in Instanbul, Turkey. They fled civil-war-torn Syria after the man's wife and one of his daughters were killed in a missile attack on April 6, 2013.
His is one of 12 families featured by Humans of New York and cleared to resettle in the U.S.
"I learned today that I'm going to Troy, Michigan," the man told Humans of New York. "I know nothing about it. I just hope that it's safe and that it's a place where they respect science. I just want to get back to work. I want to be a person again. I don't want the world to think I'm over. I'm still here."
The story made rounds throughout the Internet and even garnered a response from President Barack Obama's official Facebook page:
As a husband and a father, I cannot even begin to imagine the loss you've endured. You and your family are an inspiration. I know that the great people of Michigan will embrace you with the compassion and support you deserve. Yes, you can still make a difference in the world, and we're proud that you'll pursue your dreams here. Welcome to your new home. You're part of what makes America great.
,Norton, known for his roles in movies like "Fight Club" and "Birdman," wrote in the description of his online fundraiser:
If we don't welcome people like this into our communities and empower his dream of making an impact with his life, then we're not the country we tell ourselves we are. Let's reject the 'anti-human' voices that tell us to fear refugees and show this man and his family what Americans are really made of. Let's show that a country built by the energy and dreams of immigrants still believes in brave people who come here with hope for better life.
(6/7) “I had no problems before the bombing. I think the cancer came from my sadness and my stress. It’s in my... Posted by Humans of New York on Tuesday, December 8, 2015 ||||| ISTANBUL — The grieving refugee who touched hearts as "The Scientist" on the Humans of New York blog only mustered a brief smile when told that a Hollywood star had helped raise $450,000 for him.
Hours before flying to Michigan to start a new life in the U.S. on Thursday, the cancer-stricken Syrian civil engineer glanced down.
"I didn't hear about it, but I want to thank him very much from the humanity perspective," he said after NBC News revealed the crowdfunding appeal. Oscar-nominated actor Edward Norton was moved to tears after reading the refugee's biography on the photography site last week and launched the fundraiser.
"There are people outside who need that money much more than me," The Scientist said, displaying the sort of compassion and humility that helped his story go viral.
The Scientist, who asked NBC News to refer to him as "Abu Ammar" to protect family in Syria, said his life was shattered by a bomb that killed his wife and daughter just under three years ago.
He was later diagnosed with stomach cancer, and has had to care for five remaining children.
They include a teenage son, who is still reeling after watching his mother die, and a daughter who carries inside of her shrapnel from the attack on April 6, 2013.
"When a bomb drops you don't know where it comes from," he said. "There is no question our lives changed after that ... 180 degrees. I am mentally tired, in overwhelming sadness."
“ As long as there are good people in the world … then we can stop this bloodshed”
On Thursday, Abu Ammar and four of his children flew to Troy, Michigan, as part of a United Nations refugee resettlement program.
For about two years, the family had been living close to destitution in Turkey. But the drive to succeed still lingers, Abu Ammar said.
"I've had ambitions since I was a child, and right now I'm still that same child with the same ambitions," he said. "But I still have a message — sometimes when I'm talking to myself I say, 'No, I'm not supposed to die. I need to live long enough to realize my message to humanity.'"
Abu Ammar's story on Humans of New York, a popular blog started in 2010 that spawned a bestselling book, prompted an outpouring of compassion. Even President Barack Obama contributed, calling Abu Ammar and his family an "inspirations" on HONY's Facebook page.
"Yes, you can still make a difference in the world, and we're proud that you'll pursue your dreams here." Obama wrote. "Welcome to your new home. You're part of what makes America great."
Last night President @BarackObama wrote a very sweet welcome note to the scientist in Tuesday's story. pic.twitter.com/ZGrn3gOdR7 — Brandon Stanton (@humansofny) December 10, 2015
Norton, who starred in "Birdman," "Fight Club" and "American History X," set out to help pay The Scientist's medical expenses.
"This man has suffered profound loss that would crush the spirit of many people and yet he still passionately wants a chance to contribute positively to the world," Norton wrote.
The resettlement of Syrian and Muslim refugees in the United States is controversial, especially in the aftermath of attacks by Islamic extremists in Paris and San Bernardino. Some politicians — notably GOP presidential hopeful Donald Trump — have called for a ban on Muslims entering the country.
Abu Ammar told NBC News he didn't know anything about the debate over Muslims and immigration raging in the U.S. He also didn't have a solution to the war raging in his home country.
"I don't like to get into politics because I am a man of science, and I can separate science and politics completely," he said. "But as long as there are good people in the world, and everyone looks into his or her conscience, then we can stop this bloodshed."
Abu Ammar added: "No one benefits from people dying, and wars overall never benefit anybody — so let's hope God can help everyone and put out this fire." |||||
Output: A Syrian refugee whose moving story went viral earlier this month starts his new life in Troy, Michigan, on Thursday, NBC News reports. The refugee—who wants to keep his real name out of the media to protect family members still in Syria—is known as "The Scientist" on the blog Humans of New York, where he was first profiled. "I learned today that I’m going to Troy, Michigan," The Scientist told HONY. "I know nothing about it. I just hope that it’s safe and that it’s a place where they respect science." According to MLive, The Scientist left Syria in 2013 after a bomb killed his wife and one of his daughters. Since then, he's been diagnosed with stomach cancer and was barely scraping by in Turkey. Despite being "in overwhelming sadness," he and his surviving children are hoping for a new start in the US, he tells NBC. Thanks to his story—which even got the attention of President Obama—The Scientist will have some help to get that new start. NBC reports actor Edward Norton was moved to tears after reading The Scientist's story and started a crowdfunding page that has raised nearly $450,000. "I didn't hear about it, but I want to thank him very much from the humanity perspective," The Scientist says. "There are people outside who need that money much more than me." A Michigan college student was also inspired to help after hearing The Scientist would be moving to his hometown, according to USA Today. His fundraising page has raised more than $16,000. "I’d say out of all the cities in Michigan, Troy is the best place to raise a family, be a scientist, and we can’t wait to have him," Daniel Kang says.
This is a good example. The output correctly summarizes the articles.
New input case for you: The comedian endorsed Hillary Clinton for president but said she remains ‘inspired’ by Bernie Sanders’ ideals at Democratic convention in Philadelphia
After a first day shot through with a sense of betrayal and injustice at the Democratic national convention, it took a comedian to articulate the feeling of tragedy gripping Bernie Sanders supporters.
Democratic convention live: Michelle Obama brings down the house in call to unite behind Clinton Read more
Sarah Silverman started with a pretty obvious “Feel the Bern” gag (“I put cream on it”), but went on to make one of the speeches of the night, with a thoughtful exposition of the argument for switching from Sanders to Hillary Clinton.
But while she articulated the argument for Sanders voters to get behind Clinton, she also displayed a flash of unscripted irritation, which appeared to anger some of the Vermont senator’s delegates in the room. After a day of rolling emotions, Silverman said: “To the ‘Bernie or Bust’ people, you’re being ridiculous.”
The remark came after a unifying speech, which began with her own declaration of support for Sanders.
“As some of you may know, I support Bernie Sanders and the movement behind him,” Silverman told the cheering audience.
“Not only did Bernie wake us up, he made us understand what is possible and what we deserve. You know, my shrink says we don’t get what we want, we get what we think we deserve, and Bernie showed us that all Americans deserve quality healthcare.
“All it takes to accomplish this, it’s everyone, it’s all of us. Or as a pretty kickass woman once said – it takes a village,” Silverman said, the first of numerous references to the common ground shared by Clinton and Sanders.
Silverman called the Democratic primary “exemplary”, especially when compared to the “major arrested development stuff” employed by Trump, who clearly lacked “human touch or coping tools” as a child.
“That is the process of democracy at its very best, and it’s very cool to see,” Silverman continued, before going in for the full endorsement: “Hillary is our Democratic nominee, and I will proudly vote for her.”
As the audience cheered and jeered, the chants of Bernie and Hillary gliding over one another, Silverman continued. “So inspiring! It’s so inspiring – just a few years ago, she was a secretary, and now she’s going to be president. She’s like the only person ever to be overqualified for a job as the president. So I tell you this: I will vote for Hillary with gusto as I continue to be inspired and moved to action by the ideals set forth by Bernie, who will never stop fighting for us.” ||||| Supporters of Sen. Bernie Sanders chanted his name throughout the first day of the Democratic National Convention, frequently interrupting speeches. From first lady Michelle Obama's moving speech to many politicians slamming Donald Trump, here's what happened. (Nicki DeMarco/The Washington Post)
A tumultuous first day of the Democratic National Convention is in the books. I watched, tweeted and, candidly, ate and drank. (I mean, it was a long day.)
My take on the best and worst of the night that was is below.
Winners
* Michelle Obama: An absolute home run. Period. It will be difficult for anyone in the next three days to deliver a better speech than the first lady did on Monday night. She used her personal story of raising two young African American girls in the White House to tie her husband's history-making presidency to the history-making bid of Hillary Clinton. She was poised, calm and convincing. When she teared up talking about what it would mean to her, Malia and Sasha to see a woman elected president, it was an instantly memorable moment.
[Michelle Obama delivers a passionate defense of Hillary Clinton]
Remember this, too: Michelle Obama is not a politician. She has not run for any office — yet. It is not easy to get up and deliver a heartfelt, effective speech in front of a bunch of rowdy delegates and millions of people watching at home. Michelle Obama did it with an ease that suggests she may not be on the sidelines of the political game for much longer.
First lady Michelle Obama speaks at the Democratic National Convention on July 25. (Toni L. Sandys/The Washington Post)
* Bernie Sanders: The Vermont democratic socialist who, before this presidential campaign, existed on the outskirts of American politics, received a hero's welcome when he emerged as the final speaker of Monday night. The applause lasted for three minutes. People in the crowd cried. And then Sanders delivered much of his now-familiar stump speech — revolutionary change, millionaires and billionaires, economic justice — with a sprinkling of "Hillary Clinton" on top. Sanders's speech was, essentially, a confirmation that he was right about almost everything and Clinton now understood that fact. It was, generally, fine — if too long. Still, Sanders was able, largely, to avoid a moment when his supporters booed, jeered or otherwise protested the idea that Clinton had won the nomination fair and square. That plus the amazing response he received at the start of the speech made it a good night for him.
Some supporters of Sen. Bernie Sanders (D-Vt.) booed speakers at the Democratic National Convention in Philadelphia on July 25 – and a few Clinton fans aren't happy about it. (Peter Stevenson,Alice Li,Dalton Bennett/The Washington Post)
* Stephanie Rawlings-Blake: The mayor of Baltimore benefited from the fact that she was not Debbie Wasserman Schultz. She received a massive cheer when she emerged to open the convention — a huge moment in the spotlight for Rawlings-Blake. And, yes, she forgot to actually gavel the convention. But she more than made up for it with this epic reaction when she realized what she had done.
I think this gif has potential to outlast the election season. @NBCNightlyNews pic.twitter.com/XZfx1B4U9S — David Freddoso (@freddoso) July 25, 2016
* Sarah Silverman: Conventions tend to be programmatic affairs. Even when there is behind-the-scenes drama, every effort is made to show a smiling face to the public. It's like a duck — all smooth grace above the waterline and all paddling below it. Kudos to Silverman for breaking down the fourth wall and acknowledging the fight between Clinton and Sanders forces. Her line — "To the 'Bernie-or-bust' people: You're being ridiculous" — will be one of the memorable lines of the convention. And it was spontaneous.
[Sarah Silverman ripped into fellow Bernie Sanders supporters: ‘You’re being ridiculous!’]
Comedian Sarah Silverman told Bernie Sanders supporters who refuse to back Hillary Clinton that they are "being ridiculous" during her speech at the Democratic National Convention July 25. (The Washington Post)
Losers
* Debbie Wasserman Schultz: A total disaster of a day for the soon-to-be-former chair of the Democratic National Committee. First she was booed and heckled at a Florida delegation breakfast. Then she was pushed out of any formal role at the convention — for fear that she would, again, be booed but this time in front of a national TV audience. Rumors flew as to whether she would be fleeing back to Florida or trying to stick out the week. Whether she stays or goes, this was a very, very, very bad day for Wasserman Schultz.
* Elizabeth Warren: The Massachusetts senator had a tough task — following Michelle Obama, who absolutely brought the house down. But this was still a crowd primed to love her. The speech Warren delivered just didn't cut it — a cookie-cutter recitation of Democratic principles followed by a laundry list of attacks against Donald Trump. People insisted to me that she was "building up" to a major moment at the end of the speech but, if it happened, I missed it entirely. Warren's speech reminded me of something I noticed during her 2012 Senate campaign. She is a beloved figure more for her resume than her charisma or her natural abilities as a speaker. Warren wasn't terrible. But she was far from a standout Monday night.
[Elizabeth Warren is on her way to becoming the most powerful liberal in the Senate]
Sen. Elizabeth Warren (D-Mass.) took aim at Republican presidential nominee Donald Trump by saying that Trump knows Americans are angry, "a fact so obvious he can see it from the top of the Trump Tower." (The Washington Post)
* Cory Booker: Sometimes you want to make fetch happen so badly that you ensure it doesn't happen. That's what happened to the New Jersey senator on Monday night. He was clearly aiming to make a moment, to use his speech as a launchpad for his national ambitions. The speech was well written and competently delivered. But it felt too rehearsed, too plotted — and, without question, way, way too long. The speech could have been half as long and twice as good.
* Al Franken: The Minnesota senator has worked very hard since being elected to the Senate in 2008 to avoid being the funny guy he portrayed during his time on "Saturday Night Live." On Monday night, Franken let loose — delivering a comedy routine aimed at poking holes in Donald Trump's resume and qualifications. I say comedy because that was clearly Franken's intent — if not what he accomplished. Doing comedy off a teleprompter is not exactly a recipe for success, and Franken is, clearly, very funny. But his routine fell flat. Once he transitioned to a more traditional stump speech, Franken was far better.
* Susan Sarandon: Yes, she was adamantly with Bernie Sanders during the primaries. But if you are going to go the convention, try to have a little fun!
Susan Sarandon is having literally the worst time at the #DemConvention pic.twitter.com/Ola9Hi3y5o — Ian McKenna (@Ian_McK_) July 26, 2016
* Randy Quaid: Man. What the genuine hell is going on here? ||||| PHILADELPHIA — Even Bernie wasn’t Bernie enough to tame Bernie’s revolution.
Polls show that the majority of Bernie Sanders supporters are consolidating around Hillary Clinton. But hundreds of die-hard Sanders backers — furious over revelations the Democratic National Committee colluded with Clinton campaign officials — resisted their candidate’s calls to unify around the party’s nominee, or at least booed lustily when he called for them to mobilize for Clinton.
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The shake-up of the party’s senior leadership on the first day of a Democratic National Convention that was supposed to unify Democrats around their sturdy but widely unadored nominee wasn’t enough to appease progressives who still believe the Clintons rigged the game against them. “Brothers and sisters, this is the real world we live in!” Sanders implored his supporters at an outdoor rally hours before he was scheduled to address the convention to offer his un-Ted Cruz-like backing to the candidate who defeated him.
Hours earlier they booed ousted DNC chairwoman Debbie Wasserman Schultz off a stage, and then, to the surprise of the socialist who led their “revolution,” they hooted and howled their disapproval at him. It got so bad Sanders had to send out a last-minute text message to his delegates instructing them to “not engage in any kind of protest on the floor,” begging them not to turn their backs or heckle pro-Clinton speakers. “Our credibility as a movement will be damaged,” he wrote.
But something happened on the way to the Democratic crack-up: Michelle Obama, something of an afterthought on the opening-night program, delivered the best speech of Hillary Clinton’s career.
And Sanders, not one to show emotion on the campaign trail, momentarily broke down during a nearly five-minute standing ovation — and braved the boos to summon his army to battle Trump. Whether all of them will heed the call remains to be seen.
Here are five takeaways from an emotional roller coaster of a first night of the Democratic convention.
Bernie is pro-Hillary (But he’s a little more anti-Trump). The Vermont senator, who appeared at a joint rally with Clinton in New Hampshire earlier this month (long after he was mathematically eliminated from contention) was passionate in his summons to defeat the surging GOP nominee. He was thunderous in his praise for the millions of Americans who backed his revolution — and in attacking what he called “the grotesque level of income inequality in America.”
He was full-throated in his support for Clinton, but, um, just not quite as much. To the untrained ear, Sanders delivered his standard primary spiel (bashing Trump for intolerance, decrying the influence of Wall Street, purging Big Money from politics) but this was the first real general election speech he delivered. And the case he made for Clinton was less about a visceral appeal to liberal values than a dry, logical chain of argument that led (somewhat joylessly and amid boos) to the conclusion that Clinton deserved to be the nominee.
“We have made progress, but I think we can agree that much, much more needs to be done,” he said, as chants of “Bernie!” cascaded through the Wells Fargo Arena. “This election is about which candidate understands the real problems facing this country and has offered reasonable solutions— not just bombast, fear-mongering, name-calling and divisiveness.”
It was a shouted appeal for solidarity (and the Clinton team was satisfied with his fervor), but one with tinges of south Brooklyn melancholy. “I think it’s fair to say no one was more disappointed than I am” in the result of the primary, he offered the Bernie-or-Bust holdouts.
And note the order of Sanders’ big tweet on Monday night: “We have got to defeat Donald Trump and do everything we can to elect Hillary Clinton to the White house,” he wrote. Sanders, who first registered as a Democrat last year, when he decided to run for president, added a little Democratic donkey icon to make the point that he is playing with the home team.
“He really wants to stop Trump, you can see that,” one Democratic senator close to Sanders told me, on condition of anonymity. “The Hillary part … that’s coming along a bit more slowly, but it will come.”
Michelle Obama delivers for Clinton. Over the years, much has been made of the first lady’s supposed animosity toward both Clintons (mostly fiction, with a soupçon of truth), a vestige of the bitter 2008 campaign. But on Monday night, Michelle Obama delivered a more passionate and concise case for Clinton than the candidate has ever made for herself — and perhaps the single most effective political address delivered in 2016.
While reporters scanned the arena eaves for signs of discord, Obama offered a case for unifying around the first female major party nominee in the country’s 240-year history — voice breaking as she talked about Clinton’s role in teaching her daughters that a woman could be president. It was an appeal to the better angels of the electorate, a hybrid of her husband’s classic hope-and-change message and Clinton’s “Glass Ceiling” 2008 concession speech. “We insist that the hateful language that they hear from public figures on TV does not represent the true spirit of this country,” she said, clearly — if not explicitly — referring to Trump. “When someone is cruel and acts like a bully, you don’t stoop to their level. … When they go low, we go high.”
With most eyes on Sanders — and many on Elizabeth Warren — a first lady who had to be dragged into the spotlight by her husband’s staff in 2008 was something of an afterthought on the first night of Hillary Clinton’s convention. But she repeated, and in many ways, exceeded her memorable 2012 speech on behalf of Barack Obama’s reelection in Charlotte.
And she didn’t shy away from directly addressing the schism in the party — celebrating Clinton’s gritted-teeth decision to fall in line behind her husband, even as many of her supporters rebelled. “When she didn’t win the nomination eight years ago, she didn’t get angry or disillusioned. … Hillary Clinton has never quit on anything in her life.”
Fear. The action inside the arena was, for much of the day, overshadowed by the data on the delegates’ smartphones. Several polls released in the wake of the GOP convention last week showed Trump surging to the lead — and Nate Silver (the poll-aggregating Linus blanket of the Left in 2008) sent a shiver through Philly by reckoning, for the first time, that Trump had a 55 percent chance of winning were the election held that day.
Elizabeth Warren was OK. The firebrand Massachusetts senator is great in small groups — or delivering a broadside against Citibank or Trump on the Senate floor — but she has trouble scaling up to the big stage of national politics. Monday was no exception; and Warren, like Michelle Obama, essentially repeated her 2012 convention performance. In Warren’s case, that was a solid but mostly unmemorable speech.
Sarah Silverman — oy. At the start of the night, there was a bit of discord, a smattering of boos during the opening speeches that died down. Then came the comedy, which nearly precipitated tragedy from the perspective of the Clinton campaign.
Silverman — a former Sanders supporter — is known as absurdist provocateur (she once jokingly accused sweet, avuncular, octogenarian New York talk show host Joe Franklin of raping her) and she made a serious miscalculation. When she called for the audience to back Clinton (“Hillary is our Democratic nominee, and I will proudly vote for her”), they responded with deafening, unifying applause. But then she taunted the vanquished, a rookie political mistake. “To the Bernie-or-Bust people, you are being ridiculous!” she said, standing next to a puckered “Saturday Night Live” stalwart-turned-Minnesota Sen. Al Franken.
The upper tier erupted in a cascade of “Bernie!” — out came the signs — and the kumbaya narrative was momentarily shattered. ||||| If you thought the open booing of Ted Cruz during the Republican National Convention was a sign that the event had gotten way out of hand, then the first day of the Democrats’ convention was something else entirely.
During speech after speech, even by Sanders supporters like former NAACP head Ben Jealous or Rep. Raúl Grijalva (D-AZ), Bernie Sanders fans booed and occasionally interrupted with chants of, "Lock her up!" or "No TPP!" Despite repeated attempts by Sanders himself to calm the insurrection, it kept going.
But by the end of the night, the insurrection had calmed down. Pro-Bernie speakers, and Bernie himself, used their time slots to acknowledge Bernie dead-enders’ grievances and make a case for Clinton aimed directly at them. And from the look of things, it worked.
Here’s who left opening night better off, and who took some hits.
Winner: Michelle Obama
Michelle Obama and Hillary Clinton are the only two people living on Earth to have the experience of putting a career on hold to become first lady of the United States. Rosalynn Carter and Barbara Bush were primarily homemakers before moving to the White House. Laura Bush had quit her job as a librarian long before George W. Bush made it to Washington. But Clinton gave up her job as a partner at a prestigious Little Rock law firm. Obama gave up a senior executive position at the University of Chicago Hospitals.
When Clinton was at the stage that Obama has now reached, she was running for Senate in New York, as it was her turn to forge her own political career once Bill’s was finished. Obama has shown little interest in following that path; she declined to challenge Sen. Mark Kirk (R-IL) this year and has over and over again expressed reluctance about her husband’s decision to go into politics in the first place, not exactly a sign of an insatiable political animal who’ll miss this life terribly.
But for all their differences, she shares with Clinton a conviction that the position of first lady — with its focus on domesticity and family — needn’t be limiting, and can be a powerful platform to express the administration and party’s values and ideals. And you can see that theme woven throughout her convention speech. Clinton, she said again and again, will do right by our families. She will do right by our children.
The cynical reading is that Obama is accepting the limited understanding of first lady as confined to commenting on and thinking about traditional women’s and parenting issues. But something more substantial is going on here. Clinton has spent much of her life, from her time at the Children’s Defense Fund to It Takes a Village to her current push on paid parental leave, demanding that "women’s issues" be taken seriously, that concerns of parenting and children and motherhood are as important as anything else on the minds of presidents.
Obama hit that message again and again and again, with feeling and conviction:
I trust Hillary to lead this country because I have seen her lifelong devotion to our nation’s children. Not just her own daughter, who she has raised to perfection. But every child who needs a champion. Kids who take the long way to school to avoid the gangs. Kids who wonder how they will ever afford college. Kids whose parents don't speak a word of English but dream of a better life. Who look to us to dream of what they can be. Hillary has spent decades doing the relentless work to actually make a difference in their lives. …Hillary understands that the president is about one thing and one thing only — it is about leaving something better for our kids. …Because of Hillary Clinton, my daughters and all of our sons and daughters now take for granted that a woman can be president of the United States.
And after a primary race in which the failings of the first Clinton administration on mass incarceration and welfare and other racially charged issues came to the fore repeatedly, Obama explicitly tied the historic nature of Clinton’s campaign to the historic progress represented by her and her husband’s move to the White House:
Leaders like Hillary Clinton who have the guts and the grace to keep coming back and putting those cracks in the highest and hardest glass ceiling until they finally break through, lifting all of us along with her. That is the story of this country. The story that has brought me to the stage tonight. The story of generations of people who felt the lash of bondage, the shame of servitude, the sting of segregation, who kept on striving and hoping and doing what needed to be done so that today, I wake up every morning in a house that was built by slaves. And I watch my daughters, two beautiful, intelligent black young women, play with the dog on the White House lawn.
Here, too, Obama is recentering her role as first lady and mother as a role of consequence. That Malia and Sasha are playing and living and thriving in rooms built using slave labor, by slave owners who never dreamed that they were building a home for the descendants of the men they kept as property, is itself a political act, a political accomplishment, a real step forward for the country.
Tellingly, Obama did not mention Trump. Hers was a purely positive speech, the kind of soaring, inspirational oratory that made her husband famous 12 years ago. A week after Obama’s national debut speech at the 2008 convention was plagiarized by Trump’s wife, her remarks tonight felt like the ultimate rebuke. She is a more confident, fluent, and powerful speaker than she was in 2008 — and a far more persuasive one, too.
Winner: Bernie Sanders
Bernie Sanders lost the presidential race well over a month ago, which meant that his goal at the convention was to a) try to win over his supporters to the Clinton camp and ensure a Trump defeat; b) curry favor with Democratic elites such that he can retain his position as the top Democrat on the Senate Budget Committee and be positioned to shape budget policy should Democrats retake the Senate; and c) maintain the support of his following such that he can continue to mobilize them to support whatever efforts he pursues in the Senate going forward.
Goals A and B are conveniently very well-aligned. C, however, has to be balanced carefully. Sanders had to persuade his followers that he hadn’t sold out but that they still need to vote for the candidate he spent the whole primary telling them was beholden to corporate America.
His remarks struck that balance well. The speech was unmistakably Sanders. There were invocations of the political revolution, of the greed of Wall Street and pharmaceutical companies, the reference to $27 average donations and the need for tuition-free college. There was all the red meat a Bern feeler could’ve asked for.
But that red meat was tethered strongly to a repeated, clear, and unequivocal reiteration of his endorsement of Clinton:
Hillary Clinton understands that if someone in America works 40 hours a week, that person should not be living in poverty. She understands that we must raise the minimum wage to a living wage. And she is determined to create millions of new jobs by rebuilding our crumbling infrastructure – our roads, bridges, water systems, and wastewater plants. But her opponent – Donald Trump – well, he has a very different view. He does not support raising the federal minimum wage of $7.25 an hour – a starvation wage. While Donald Trump believes in huge tax breaks for billionaires, he believes that states should actually have the right to lower the minimum wage below $7.25. What an outrage!
If this sounds like Sanders’s typical calls for more infrastructure and jobs spending, and a $15-an-hour minimum wage, with Clinton’s name added, that’s exactly the point. He’s arguing that Clinton is not merely better than Trump but is affirmatively committed to the principles that drove his own campaign.
And he didn’t ignore the cognitive dissonance created by him praising a candidate he was fiercely condemning not two months ago. He instead told a plausible story of how he came aboard, one that emphasized the gains he and his movement made in the process:
It is no secret that Hillary Clinton and I disagree on a number of issues. That’s what this campaign has been about. That’s what democracy is about. But I am happy to tell you that at the Democratic platform committee there was a significant coming together between the two campaigns, and we produced, by far, the most progressive platform in the history of the Democratic Party. Among many other strong provisions, the Democratic Party now calls for breaking up the major financial institutions on Wall Street and the passage of a 21st-century Glass-Steagall Act. It also calls for strong opposition to job-killing free trade agreements like the Trans-Pacific Partnership.
It was the ideal Sanders speech both for keeping his supporters on his side and for trying to move them to Clinton’s camp, and every major Democrat should be thrilled at how well he nailed it.
Winner: Sarah Silverman
Who could have guessed that the comedian behind this bit would’ve gone off script and off message in her DNC appearance?
You can understand why the DNC organizers scheduled time for Silverman. She was paired with fellow Saturday Night Live alum Sen. Al Franken, who presumably would keep her on track. The two, one a comedian supporting Clinton and the other a comedian supporting Sanders, made a good pro-unity pairing. Using their call for a "bridge" between the two sides of the primary divide as an opening for Paul Simon’s performance of "Bridge Over Troubled Water" was a little corny, but what political convention isn’t?
But when Silverman was added, organizers presumably didn’t know there’d be a substantial number of pro-Bernie hecklers. They didn’t know she’d effectively be charged with winning over the most hostile and skeptical segment of the audience. And they thus didn’t anticipate that she would respond to the situation the way any comedian facing hecklers would — by fighting back, and telling the crowd, "Can I just say, to the Bernie or bust people, you're being ridiculous."
That was definitely not in the script. The words "Bernie or Bust" were not supposed to be uttered; even mentioning it is giving the idea more attention than national Democrats really want. And directly confronting the Bernie die-hards risks alienating them further and adding to the convention’s drama.
Here’s the thing, though: It looks like it worked. The comment brought on a wave of applause, and Vox reporters on the floor say the response was overwhelmingly positive.
"The most effective speech by a celebrity I've ever seen." -Republican Nicole Wallace, on Sarah Silverman's appearance #DNCinPHL — Doug Benson (@DougBenson) July 26, 2016
Obviously, some Bernie die-hards won’t be persuaded by Silverman, and might even be put off. But for casual Bernie supporters watching at home, weighing whether to stay home or throw in for Hillary, it might have been the bracing moment they needed to get on board.
And millions not watching at home will probably see aggregations of the moment floating around on Facebook and Google and hear, even in passing, the idea that "Bernie or Bust" is a joke. That wouldn’t have happened if Silverman had approached the speech more traditionally and stuck to the script.
Winner: American exceptionalism
Traditionally, the left and even many liberals have had a conflicted relationship with American political culture’s insistence that America is wonderful and must be celebrated. Almost by definition, to be liberal, or at least anti-conservative, in this country is to embrace the idea that America or at least its government needs to change.
The health care system should be less American and more Canadian. The tuition system for higher education should be less American and more German. The family leave policy should be less American and more Swedish. America’s preeminence in the world is a mixed blessing that leads to disasters like Vietnam and Iraq as much as it does triumphs like the end of the Soviet Union.
This is a tension conservatives have identified and exploited to great effect. You can see it in attacks on "socialized medicine" and European-style "class warfare," and in more sophisticated and paranoid attacks like Dinesh D’Souza’s claim that Barack Obama is animated by a fundamentally foreign anti-colonialist perspective.
Then something weird happened: Republicans nominated Donald Trump. And Donald Trump is not a fan of America, or at least America as it currently exists. Even as he argues for a fervently nationalistic foreign policy and appeals to his base with jingoistic rhetoric, Trump’s overarching slogan proclaims that America must be made great again, that it has lost a past glory, that something is, at this juncture, fundamentally wrong with it.
That, combined with the major progress of the Obama administration in making America more like the universal health care–boasting, marriage equality–having, anti-racist country liberals have wanted for decades, has enabled a Democratic convention that is almost unprecedentedly patriotic and celebratory of America:
Eva Longoria: " A Latina from south Texas is introducing the first black senator from New Jersey on the week we will nominate our first female candidate for president of the United States. So guess what, Donald, it turns out America is pretty great already."
Cory Booker: "Free from fear and intimidation, let us declare we are a nation of interdependence and that in America love always trumps hate. Let us declare so that generations yet unborn can hear us. We are the United States of America. Our best days are ahead of us."
Michelle Obama: "Don't let anyone ever tell you that this country is not great. That somehow we need to make a great again. Because this right now is the greatest country on Earth."
Rep. Brendan Boyle (D-PA): "Donald Trump says the American dream is dead. Why does he want to lead America when he does not even believe in America? Donald Trump is wrong. This is a remarkable country. By geography and by destiny, we are a land set apart."
Rep. Linda Sanchez (D-CA): "Donald, let me say this. America is great. It is the country that gave my family the opportunity for a better life, just like all immigrants who came before them. It is because of our diversity that we are the envy of the world."
Not every speaker took this tone; Bernie Sanders and Elizabeth Warren, naturally, kept the focus on America’s problems with money in politics and persistent economic disparities. And to be sure, the tone of the event was not quietist. There’s plenty more the speakers want done — and expect Clinton to do if elected.
But Sanchez’s comment is nonetheless instructive. This election is about immigration, due to Trump’s obsessive focus on the issue. And immigration really is an issue on which the US stands apart. No other rich nation shares our historical commitment to taking in large numbers of immigrants and integrating them into the American community and economy. Denmark, otherwise looked to by liberals as a model, is horrendously disappointing at letting in refugees and immigrants. It’s basically a gated community as a nation.
This is a place where the Democratic platform is genuinely more in line with American tradition and distinctively American values, and the convention speakers have noticed. The result is an exuberant, celebratory take on America and its history from a left-of-center perspective, something that few orators not named Barack Obama have tried much at all.
Loser: Debbie Wasserman Schultz
First, Debbie Wasserman Schultz was going to open the convention as the Democratic National Committee’s chair. Then she resigned her position under pressure but was still going to open the convention. Then she ultimately didn’t get to do anything at all. Her role at the convention was limited to a breakfast meeting with the Florida delegation, a meeting that was greeted by throngs of pro-Sanders protesters armed with anti–Wasserman Schultz signs.
And she’ll go home to a contentious primary election on August 30 with a challenger, Tim Canova, who has out-fundraised her and is endorsed by Bernie Sanders and supported by Sanders's large movement of supporters still grieving his loss to Clinton. The race previously looked like a gimme for Wasserman Schultz, but that appears to be changing, at least in the eyes of state Sen. and delegate Eleanor Sobel, a DWS ally:
In an interview three weeks ago, Sobel said Wasserman Schultz wouldn't have any problem defeating Canova in the primary. On Monday, she was less certain. "I hope not," she said when asked if Wasserman Schultz is in danger of losing. "I don't know. I think there are people just like myself who believe that Debbie has done so much for our community. She's a known entity. We know what she can do. And she will continue fighting," Sobel said.
At the start of this weekend, Wasserman Schultz was, at least on paper, one of the most powerful Democrats in the country. By the end of August, she could be a lame-duck incumbent without a political position in Congress, the DNC, or anywhere.
This has been a long time coming, however. Reportedly, John Podesta, the chair of Clinton's campaign, asked to remove Wasserman Schultz last fall, only to have Obama nix the idea — not because he didn't want her gone, but because he thought it'd be too much drama.
"The Obama team — especially 2012 campaign manager Jim Messina — long viewed Wasserman Schultz as a major campaign liability, questioning her fundraising prowess and her tendency to appoint personal aides to positions of authority, prioritizing loyalty over competence and effectiveness as a spokesperson for Democrats," report Politico's Glenn Thrush, Gabriel Debenedetti, and Edward-Isaac Dovere.
She made a whole new set of enemies with the primary campaign, in which Sanders supporters, and Sanders himself, saw her as violating the DNC’s promise of neutrality and subtly making decisions that helped Clinton. As Vox’s Jeff Stein explains, "She got into bitter arguments with the Sanders camp about obscure Nevada caucus rules, made a mess of the debate schedule, fought over ballot access data, and may have helped Clinton skirt the campaign finance rules."
So when WikiLeaks released emails showing DNC staff bashing Sanders, that was the last straw. Wasserman Schultz was out of the chair position within 24 hours. By Monday, she was no longer opening the convention. It was a long time coming, but when it came, it happened fast. And the rest of the Democratic establishment wasn’t particularly broken up about it:
Senior Dem, close to the Clintons, to me just now 'Thank you Wikileaks for accomplishing something we couldn't' — Glenn Thrush (@GlennThrush) July 24, 2016
At this point, the best-case scenario for Wasserman Schultz is that she wins her primary and gets reelected to the House. She'll become the chair of an appropriations subcommittee if Democrats ever win back their majority. Who knows, maybe she'll chair the whole Appropriations Committee some day. But her time in the national limelight is over. And if the primary goes wrong, her time in elected politics will be over too.
Loser: TPP
Political parties don’t generally campaign on issues on which they agree. You don’t see Republican Senate candidates going from town to town saying, "Bribing politicians to enact certain policies should remain a crime," and Hillary Clinton hasn’t formally announced, "I think alcohol should continue to be legal." There’s no actual political debate on the topics, and so it doesn’t come up.
That’s why it’s so odd to compare the rhetoric on trade at the DNC with that at the RNC last week. Here are a few statements; some are from Trump’s acceptance speech, some from the first night of the DNC. Can you tell which is which?
"It begins with a new, fair trade policy that protects our jobs and stands up to countries that cheat." "We need to fight for trade policies that put American workers first, which means we must say no to bad trade deals, and that includes the TPP." "Trade deals … strip our country of jobs." "We need to commit ourselves to making good-paying jobs here at home." "I have visited the laid-off factory workers, and the communities crushed by our horrible and unfair trade deals." "We believe that the United States should never sign trade deals that help big corporations and leave workers in the dirt."
The odd statements are Trump; the even ones are Sens. Jeff Merkley (D-OR), Bob Casey (D-PA), and Elizabeth Warren (D-MA), respectively. The rhetoric is nearly identical. Both parties are committing themselves to opposing unrestricted free trade and outsourcing and, more specifically, the TPP — even though the incumbent Democratic president is the one who negotiated it.
You could see this foreshadowed over the weekend, when newly named Clinton running mate Tim Kaine told reporters he shared Clinton’s opposition to TPP, a deal he had praised as recently as Thursday. Of course, Clinton came out against the deal after having been involved in its negotiation in her role as secretary of state; it was a bizarre turnaround, one that she still has yet to adequately explain and that only makes sense as a way to temper the strength of Bernie Sanders’s primary challenge.
And yet she’s not only stuck with it but insisted that her running mate adopt her position as well, and let the opening night of her convention involved repeated attacks on the deal.
It’s reasonable to be skeptical that Clinton will actually uphold her election-year stance upon taking office. It was telling that during a portion of the convention devoted to attacking Trump’s outsourcing record, the DNC aired a video starring Austan Goolsbee, the former White House chief economist who famously told Canadian officials in 2008 that Obama was just bullshitting when he said he wanted to renegotiate the North American Free Trade Agreement.
In practice, most presidents, regardless of their campaign rhetoric on trade, abide closely to WTO rules upon taking office and pursue additional bi- and multilateral agreements.
But the attack on TPP specifically could prove significant. It’s possible Clinton will amend it slightly, declare her concerns adequately addressed, and push it through Congress as though she’d never opposed it at all. But that’d be very awkward after her campaign position, and political scientists have found that campaign promises have surprisingly large effects on administration policy. It’s likelier that the agreement will simply die under her, as under Trump, if Obama can’t push it through in the lame-duck session.
That’s a major defeat for the main part of the American trade agenda of the past five or so years. And it suggests that the old party alignments on trade, with Republicans enthusiastically supporting free trade and Democrats being slightly more skeptical but still pretty on board, are being disrupted. Now the Republicans are the most outspokenly protectionist party, and Democrats attack them as hypocrites ("Trump outsources his T-shirts!" etc. ) but do not challenge their underlying trade skepticism.
Having Republicans be the stronger trade opponents more closely matches where actual voters are on trade issues, but if anything, Democrats are running the risk of being more trade-skeptical than their base is. Pew polling found that while 56 percent of Democratic voters say free trade agreements have been a good thing for the US, only 38 percent of Republicans agree. They're likelier to endorse NAFTA than Republicans are as well.
That Democratic trade enthusiasm was nowhere in evidence at the DNC — especially on TPP. |||||
Output: | There was no shortage of drama on Day 1 of the Democratic National Convention, though the day appeared to end with a more unified party, with Michelle Obama delivering what could be the convention's best speech and Bernie Sanders telling the Philadelphia crowd that Hillary Clinton "must become the next president." Here's who analysts say had a good day, or a terrible day. Among the winners: Michelle Obama. She didn't just give a great speech, she gave the "best speech of Hillary Clinton's career," according to Glenn Thrush at Politico. She "delivered a more passionate and concise case for Clinton than the candidate has ever made for herself—and perhaps the single most effective political address delivered in 2016," he writes. Bernie Sanders. Some 14 months after he launched his campaign from the "outskirts of American politics," Sanders received a "hero's welcome" from an emotional crowd Monday night, writes Chris Cillizza at the Washington Post. His speech was "essentially a confirmation that he was right about almost everything and Clinton now understood that fact," Cillizza writes. Sarah Silverman. Her off-the-cuff line to hecklers—"To the Bernie-or-bust people, you're being ridiculous"—got one of the night's biggest cheers. It came after what the Guardian calls "a thoughtful exposition of the argument for switching from Sanders to Hillary Clinton." Among the losers: Debbie Wasserman Schultz. The soon-to-be former Democratic National Committee chief had a terrible day by anybody's reckoning. She decided against opening the convention after she was heavily booed and heckled when speaking to Florida delegates Monday morning. Cory Booker. The New Jersey senator tried a little too hard to launch himself on the national stage with his Monday night speech, which "felt too rehearsed, too plotted—and, without question, way, way too long," according to Cillizza at the Post. "The speech could have been half as long and twice as good." The Trans-Pacific Partnership. The rhetoric against the trade deal from speakers like Elizabeth Warren and Bernie Sanders was almost indistinguishable from what Donald Trump has to say about it, despite the fact that it was negotiated by the sitting Democratic president, notes Dylan Matthews at Vox. He predicts that the deal will now die under either Clinton or Trump "if Obama can't push it through in the lame-duck session." | 1 | NIv2 | task1291_multi_news_summarization | fs_opt | [
0.7134968638420105,
0.051936060190200806,
-0.056923944503068924,
-0.05066048353910446,
0.9168752431869507,
-0.158541738986969,
1.125438928604126,
0.8764550685882568,
-0.5444329380989075,
0.6913919448852539,
-0.05184028297662735,
0.22544044256210327,
-0.0906672477722168,
0.5464355945587158,... |
Teacher:A text is given in English. Translate it from the English language to the Hindi language. The translation must not omit or add information to the original sentence.
Teacher: Now, understand the problem? Solve this instance: जब से हमने स्वच्छता के लिए रैंकिंग करना शुरू किया है, independent agency द्वारा किया है शहरों के बीच में स्पर्धा शुरू हुई है।
Student: | Since we started ranking the cities for cleanliness through an independent agency, the cities have started competing with each other. | 6 | NIv2 | task1024_pib_translation_hindi_english | zs_opt | [
-0.17615357041358948,
0.45461371541023254,
0.9941900968551636,
-0.4962225556373596,
0.09851668030023575,
-0.735708475112915,
-0.22958192229270935,
0.20492449402809143,
-0.29783177375793457,
-0.6549840569496155,
-0.18902018666267395,
-0.1272526979446411,
-0.6659957766532898,
-0.430019140243... |
Detailed Instructions: You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Portugese.
See one example below:
Problem: ولكن ماهي حقوق الإنسان ؟
Solution: Mas o que são direitos humanos?
Explanation: The Arabic sentence is correctly translated into Portugese, because the meaning is preserved.
Problem: وابيضت مفاصل اصابع يدي من تجمدها على الباب... اجربتم يوما شعور الخوف هذا ؟
Solution: | Tenho os nós dos dedos brancos, de me agarrar à porta, estão a ver? | 4 | NIv2 | task1109_ted_translation_ar_pt | fs_opt | [
0.3541664481163025,
0.7640711665153503,
-0.3795747458934784,
-0.8210710883140564,
-1.019731044769287,
-0.11996957659721375,
0.8756961822509766,
0.8739157319068909,
0.12176921963691711,
0.05076528713107109,
-0.8919681906700134,
0.37803319096565247,
-1.0517692565917969,
0.20074966549873352,
... |
Instructions: In this task you will be given a list of numbers and you need to subtract every value in the list with the index it is at. The index of an elements shows its numerical order in the list(for example, in the list [7,10,4,5], the index of 7 is 1 and the index of 4 is 3) You should start the index at 1, so the first element in the list will be subtracted by one. For every element in the list you need to find "element - index" where the index of the beginning element is 1 and increments by 1 for each element. Put your result list in brackets.
Input: [-15, 11, -15, 3, 1, -19, 3, 16]
Output: | [-16, 9, -18, -1, -4, -25, -4, 8] | 3 | NIv2 | task096_conala_list_index_subtraction | zs_opt | [
0.44735580682754517,
0.05409516766667366,
-0.7672856450080872,
-0.2386505901813507,
0.13951058685779572,
-0.08496379852294922,
1.1496906280517578,
0.381267786026001,
0.08833955228328705,
-0.08108189702033997,
-0.5841501951217651,
-0.21773682534694672,
-0.2089235782623291,
-0.12075373530387... |
This task involves annotating the answer type to a given question that involve some kind of complex reasoning (including numerical reasoning). Note that the questions require looking at more than one part of the passage to answer. There are 3 possible answer types (i) spans, (ii) numbers and (iii) dates. If the answer can be found in the passage, label it as "span". If the answer is a number, label as "number". Similarly, label "date" if you think the answer to the given question is a date.
Example Input: Passage: In the city, the year 2010 population was spread out with 26.3% under the age of 18, 13.6% from 18 to 24, 30.7% from 25 to 44, 21.1% from 45 to 64, and 7.2% who were 65 years of age or older. The median age was 32 years. For every 100 females, there were 92.5 males. For every 100 females age 18 and over, there were 88.4 males.
Question: Which age group is larger: under the age of 18 or 65 years of age or older?
Example Output: span
Example Input: Passage: Looking to muster their first winning streak of the season, the Washington Redskins took on the rival New York Giants on Monday Night Football. To add to the fanfare, Redskins owner Daniel Snyder hired Bruce Allen to be the new General Manager. However, the Redskins came out flat, and trailed 24-0 by halftime. With a chance to kick a field goal as the half ended to cut it to a 24-3 deficit, the Redskins tried one of the most ill-advised and ill-fated fake field goal attempts of all-time. Redskins P Hunter Smith sent the entire offensive line in motion, along with K Graham Gano. The first attempt was foiled by a Giants time-out. The second attempt was intercepted and almost taken back for a 31-0 lead. In the 2nd half, the Redskins finally got on the board, scoring on a touchdown pass to Fred Davis. However, it was too little, too late, as K Graham Gano missed the extra point. The Redskins would not score again until it was 38-6 Giants. RB Quinton Ganther scored on a 2-yard scamper, but the Redskins came up a foot short on the 2-point conversion, which sealed any slim chance there was of a comeback. When all was said and done, the Giants won 45-12. With the crushing loss, Washington fell to 4-10, losing 10 games or more for the third time in six seasons.
Question: How many points did the Giants win by?
Example Output: number
Example Input: Passage: The Broncos' defense limited Patriots' quarterback Tom Brady to 188 yards passing and no touchdowns, but their defensive effort was wasted by a poor performance from their inconsistent offense. The Broncos' only scoring play was a 33-yard field goal by placekicker Brandon McManus. In the first quarter, a fumbled punt by Jordan Norwood led to a 45-yard field goal by Patriots' placekicker Stephen Gostkowski. An interception off Broncos' quarterback Trevor Siemian by cornerback Logan Ryan resulted in the only touchdown of the game—a 1-yard run by Patriots' running back LeGarrette Blount in the second quarter. Gostkowski added two more field goals—a 40-yarder in the third quarter and a 21-yarder in the fourth. The Broncos wore their alternate navy blue uniforms for this game.
Question: Which quarter did Stephen Gostkowski kick his longest field goal?
Example Output: | span
| 3 | NIv2 | task027_drop_answer_type_generation | fs_opt | [
0.6439855694770813,
0.4455503225326538,
-0.9660142660140991,
-0.8069798350334167,
-0.12673252820968628,
-0.5026450157165527,
0.6976373791694641,
0.42281556129455566,
0.27224063873291016,
-0.13256461918354034,
-0.5972455143928528,
0.6584370136260986,
-0.8384376168251038,
-0.2102954387664795... |
Detailed Instructions: In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to choose whether the two sentences clearly agree (entailment)/disagree (contradiction) with each other, or if this cannot be determined (neutral). Your answer must be in the form of the letters E, C, and N respectively.
Q: Sentence 1: Two women tussle in a roller derby as a small audience watches in a barren room. Sentence 2: Some people are wearing helmets.
A: | C | 9 | NIv2 | task190_snli_classification | zs_opt | [
-0.035696692764759064,
0.6323407888412476,
0.21708963811397552,
0.07437045127153397,
0.20756280422210693,
-0.7715465426445007,
0.2085387110710144,
0.7632397413253784,
0.7098897695541382,
0.0411415696144104,
-0.5765100717544556,
-0.3368990421295166,
-0.17858025431632996,
-0.3084813952445984... |
Q: In this task, you are given a context tweet, a question and corresponding answer of given question. Your task is to classify given passage into two categories: (1) "yes" if the given context is useful in answering the question, and (2) "no" if the given context is not useful.
Context: I apologize if I've offended anyone. The post was meant to be anti-racist with humour. I now understand that (...) Mario Balotelli (@FinallyMario) December 2, 2014 Question: how many finalist return Answer: three
A: | no | 7 | NIv2 | task242_tweetqa_classification | zs_opt | [
-0.2817212641239166,
-0.02517016977071762,
0.8059597015380859,
1.0199787616729736,
-0.37027066946029663,
0.2951456606388092,
0.6078558564186096,
0.05638991668820381,
-0.29369890689849854,
0.009793370962142944,
-0.8261121511459351,
0.5171915292739868,
0.08171281218528748,
0.0734518319368362... |
TASK DEFINITION: In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to choose whether the two sentences clearly agree (entailment)/disagree (contradiction) with each other, or if this cannot be determined (neutral). Your answer must be in the form of the letters E, C, and N respectively.
PROBLEM: Sentence 1: Two people with hats looking at a lake while sitting on a yellow-grassed hill. Sentence 2: The two people are inside
SOLUTION: C
PROBLEM: Sentence 1: two crew people talk about an race car engine during a race car show. Sentence 2: Two people are having a discussion.
SOLUTION: C
PROBLEM: Sentence 1: An African American worker putting food into the oven while looking at the camera. Sentence 2: Black worker cooking food in oven.
SOLUTION: | C
| 8 | NIv2 | task190_snli_classification | fs_opt | [
-0.5378087759017944,
0.20463919639587402,
-0.09569845348596573,
-0.24818174540996552,
-0.2934669256210327,
-0.25268834829330444,
0.3333086669445038,
0.6953374743461609,
0.3850513696670532,
-0.36994004249572754,
-0.324959397315979,
-0.8077545166015625,
0.004743753466755152,
0.00198218366131... |
Craft one correct answer to the question given in input. To make it more interesting, try to use non-stereotypical language if possible. Make sure your correct answer is reasonably long, consistent with the context, and requires common sense (instead of explicit extraction from the context.) In your answer, use as few words as possible from the given context. Use a response that is uncommon/non-stereotypical, so that it is less predictable. To be less repetitive, please vary your language for each question.
Q: Context: " You should probably come in with us , just to make sure you 're ok . " " No , " I said firmly , watching T - shirt guy talking to the camera guy . " Are you sure ? " Dave asked . " Yes , I ' m sure . I just got freaked out for a second .
Question: Did I want to get checked on ?
A: I did not want to be checked out.
****
Q: Context: It was very open and light with a wooden floor polished by age and a bar of red and white painted tin . It served the beers I like - Hoegaarden and Leffe . There was music playing most of the time , but it was much less intrusive and annoying than the music you get in English pubs - sort of relaxed piano and that type of thing . It had live blues acts on several times while we were there . And also , when I ' m sitting in a French bar I see far more people who I think ' Oh , they look interesting ' than I do in England .
Question: What may be a fact about this person ?
A: They are drinking at a bar .
****
Q: Context: A little gay . I do n't remember if the tiramisu was any good because I was sharing it with a dude I just met and that 's a little uncomfortable . After dessert the check came and I paid my half .
Question: Why was the dessert experience uncomfortable ?
A: | The narrator was with a stranger .
****
| 4 | NIv2 | task024_cosmosqa_answer_generation | fs_opt | [
0.7761597633361816,
1.0520635843276978,
-0.36408576369285583,
0.2715212106704712,
0.223807230591774,
-0.4457637667655945,
0.32373613119125366,
0.41157495975494385,
0.2706870436668396,
0.12419451773166656,
-0.06895897537469864,
0.3717738687992096,
-0.5789845585823059,
0.15148071944713593,
... |
Q: You are given a sentence in Spanish. Your job is to translate the Spanish sentence into Hebrew.
AK: Daré un paso atrás.
A: | אק: אני אקח צעד אחורה. | 7 | NIv2 | task1229_ted_translation_es_he | zs_opt | [
-0.009976696223020554,
0.7599998116493225,
-0.12099853157997131,
-0.3516971468925476,
-0.5383142232894897,
-0.07964381575584412,
0.7525511980056763,
0.46671390533447266,
0.5903102159500122,
0.05847311019897461,
0.13676968216896057,
0.14247256517410278,
-1.3922187089920044,
0.13342612981796... |
You are given a sentence and a question in the input. If the information provided in the sentence is enough to answer the question, label "Yes", otherwise label "No". Do not use any facts other than those provided in the sentence while labeling "Yes" or "No". There are only two types of valid responses: Yes and No.
Q: Sentence: Now, I like butterflies!.
Question: Where did the child go when he saw the butterflies?
A: | No. | 4 | NIv2 | task050_multirc_answerability | zs_opt | [
-0.9112740159034729,
0.38947391510009766,
0.3858254551887512,
0.3573604226112366,
-0.295878529548645,
-1.0077295303344727,
0.291390061378479,
1.0697300434112549,
0.27674421668052673,
-0.15715700387954712,
-0.10940408706665039,
0.13399732112884521,
-0.2983158230781555,
0.1156303659081459,
... |
In this task, you are given a sentence in the English and Japanese language. Your task is check if the Japanese sentence is translation of English. if the translation is correct than generate label "Yes", otherwise generate label "No".
Input: Consider Input: English: In the "2008 Taipei City New Year Countdown Party", several local and foreign media focused on the fireworks of the Taipei 101 due to the notability of the skyscraper world-wide.
Japanese: 暴徒が「イスラム教のマホメットを侮辱する者は銃殺だ」、「許すな、処刑だ」、「殺せ、銃殺にしろ」、「恥を知れ、イギリスに辱めを」というようなスローガンを唱えた。
Output: No
Input: Consider Input: English: Wired News additionally reports that there is "circumstantial evidence" linking the perpetrators of the attack to the internet group "Anonymous", who are most well known for their recent protests and attacks against the Church of Scientology, and their members created a reputation as "griefers" in the virtual worlds Second Life, and Habbo Hotel.
Japanese: 悪名高く風変わりなマリンガーの男は、「子供だましのアイルランドの航空会社が20年前ウォーターフォードの畑で始まり、20年で世界の自称人気のある航空会社を追い越すことができるというまさしくその事実が、ヨーロッパ中の格安航空旅行に対してほとんど止めることのできない需要があるという証拠だ」と記者団に話し続けた。
Output: No
Input: Consider Input: English: The preemptive crackdown was introduced with predictions of hundreds of thousands of British citizens losing their homes to credit companies as the international financial crisis grows worse.
Japanese: 国際的に金融恐慌がよりひどくなるにつれ、会社を信用して家を失う何十万人もの英国市民が出ることが予測され、先買の取締りが始められた。
| Output: Yes
| 2 | NIv2 | task437_alt_en_ja_answer_generation | fs_opt | [
-0.26872411370277405,
-0.08561207354068756,
0.23286348581314087,
0.2034287005662918,
0.06125248968601227,
-0.3900553584098816,
0.2513263523578644,
0.6133828163146973,
0.02052328735589981,
0.2641233205795288,
-0.28156834840774536,
0.7208174467086792,
-1.3388197422027588,
-0.0549280270934104... |
You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. If the conversation begins with a question, label it '1' otherwise '0'.
Example: Person1: Passport , please , madam .
Person2: Just a minute , please . It's in my bag . Here it is .
Person1: Thank you . Please fill out the Baggage Declaration Form .
Person2: All right . Shall I enter all my belongings ?
Person1: No , only the articles listed on the Declaration .
Example solution: 0
Example explanation: The first sentence in the conversation begins with a request, therefore there is no presence of a question.
Problem: Person1: John , my father isn't there at all . Are you kidding ?
Person2: Poor , fellow , what's the date today , buddy ?
Person1: It's ... oh it's the 1st April , April Fool's Day .
Person2: You forgot all of about it , didn't you ?
| Solution: 1 | 5 | NIv2 | task1534_daily_dialog_question_classification | fs_opt | [
0.8092378377914429,
0.1186809092760086,
-0.28196918964385986,
0.3364480137825012,
0.20993608236312866,
-0.24405284225940704,
0.5609474778175354,
0.14078325033187866,
-0.0875164121389389,
0.1834503412246704,
-0.2849469482898712,
-0.49437883496284485,
-0.45556139945983887,
-0.205432921648025... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given text for US Congressional and California state bills, your task is to generate a summary for this bill.
SECTION 1. SHORT TITLE.
This Act may be cited as the ``Free Market Grazing Fees Act''.
SEC. 2. GRAZING FEES ESTABLISHED AT FAIR MARKET VALUE.
(a) Fees Required.--Notwithstanding any other provision of law, the
Secretary of Agriculture and the Secretary of the Interior, with
respect to public grazing lands subject to their respective
jurisdiction, shall establish an annual domestic livestock grazing fee
equal to the fair market value of the grazing lease or permit
concerned.
(b) Commencement of Fees.--The grazing fees required by this
section shall apply beginning with the grazing season that commences on
March 1, 1998.
(c) Factors.--In determining the fair market value of a grazing
lease or permit, the Secretary concerned shall take into account the
following:
(1) The amounts and conditions under which neighboring non-
Federal lands are leased or sold for grazing purposes.
(2) The improvements provided or to be provided by the
lessee or permit holder.
(3) The services to be provided by the United States.
(d) Procedures.--In determining the fair market value of grazing
permits, the Secretary concerned shall publish rules in accordance with
chapter 5 of title 5, United States Code, which ensure that whenever
practicable fair market value is established through competitive
bidding.
(e) Small Family Ranch Exemption.--
(1) Certification for prevailing fees.--The holder of a
Federal grazing lease or permit as of the date of the enactment
of this section who makes a certification to the Secretary
concerned in accordance with this subsection shall be charged
the prevailing grazing fee on that date for the period
beginning on that date and ending on February 28, 2008.
(2) Content of certification.--
(A) Annual income.--The holder of the Federal
grazing lease or permit shall certify that, for the
immediately preceding calendar year--
(i) the holder derived more than half of
the holder's annual income from the ranching
operation associated with the Federal grazing
lease or permit; and
(ii) the holder--
(I) if an individual, has an
adjusted gross annual income (as
defined in the Internal Revenue Code of
1986) of less than $50,000; or
(II) if a person other than an
individual, has total assets of less
than $1,000,000, including the value of
Federal leases or permits of any kind,
including the assets of any entity
owned by, controlled by, or under
common control of, directly or
indirectly, the holder.
(B) Substantial labor.--The holder of the Federal
grazing lease or permit shall certify that, for the
immediately preceding calendar year, the holder--
(i) if an individual, performed substantial
labor in the ranching operation either
personally or using members of the holder's
immediate family; or
(ii) if a person other than an individual,
performed substantial labor in the ranching
operation using the officers of the holder.
(3) Submission of certification.--A certification under
this subsection shall be submitted to the Secretary concerned
before the beginning of each grazing season.
(f) Definitions.--For the purposes of this section:
(1) Public grazing lands.--The term ``public grazing
lands'' means the following:
(A) The National Forest lands (including the
national grasslands) in the 16 contiguous Western
States administered by the United States Forest Service
where domestic livestock grazing is permitted under
applicable law.
(B) The public domain lands administered by the
Bureau of Land Management where domestic livestock
grazing is permitted under applicable law.
(C) The lands within units of the National Park
System on which grazing is permitted under applicable
law.
(2) Secretary concerned.--The term ``Secretary concerned''
means--
(A) the Secretary of Agriculture, with respect to
public grazing lands subject to the jurisdiction of the
Secretary of Agriculture; and
(B) the Secretary of the Interior, with respect to
public grazing lands subject to the jurisdiction of the
Secretary of the Interior.
(g) Effect of Failure to Establish Fees.--No grazing shall be
permitted on any public grazing lands after March 1, 1998, unless the
Secretary of the Interior and the Secretary of Agriculture each affirm
to Congress that grazing fees for all public grazing lands have been
established in compliance with this section.
Output: | Free Market Grazing Fees Act - Directs the Secretaries of Agriculture and the Interior to establish fair market value grazing fees for use of their respective public lands. Establishes a prevailing fee exception for current small family ranch leases or permits. | 1 | NIv2 | task1658_billsum_summarization | zs_opt | [
-0.2559660077095032,
-0.3749695420265198,
-0.46686816215515137,
0.07033900916576385,
0.7678555846214294,
-0.2713702321052551,
1.03737473487854,
1.1047242879867554,
-0.7894344329833984,
0.1869819164276123,
-0.07612892240285873,
0.34441477060317993,
-0.3195337653160095,
0.347881019115448,
... |
Definition: You will be given a context and a question in Spanish. Your job is to generate answers that are at least THREE words long.
The answers need to be context specific and can not be general knowledge or a random guess.
Input: CONTEXT: 14 de agosto de 2013 El presidente de Nicaragua, Daniel Ortega, declaró durante las celebraciones del 33 aniversario de la Fuerza Naval de Nicaragua, que reclamará la provincia costarricense de Guanacaste. Las declaraciones generaron repudio en Costa Rica, donde el ejecutivo y legislativo condenaron las declaraciones del mandatario nicaragüense. Según Daniel Ortega, la provincia de Guanacaste fue cedida a Costa Rica "mientras Nicaragua luchaba contra el expansionismo yanqui". Ortega afirmó que si el fallo de la Corte Internacional de La Haya favorece a Nicaragua, "eso le permitiría a Nicaragua recuperar un inmenso territorio". El canciller de Costa Rica, Enrique Castillo fue convocado por la Presidenta costarricense Laura Chinchilla tras las declaraciones de Ortega. Castillo afirmó que las declaraciones del mandatario nicaragüense son "una bravuconada que no nos intimida como país". — Enrique Castillo, Canciller de Costa Rica Por su parte, la mandataria Laura Chinchilla declaró en un comunicado que las declaraciones de Ortega son "un desprecio difícil de entender y difícil de comprender particularmente por el hecho de que Costa Rica no está haciendo nada para provocar ese tipo de reacciones". — Laura Chinchilla, Presidenta de Costa Rica Costa Rica y Nicaragua ya tienen en la Corte Internacional de Justicia una disputa por el territorio de Isla Calero, el cual Nicaragua reclama como suyo. La provincia de Guanacaste, una de las regiones más atractivas turisticamente de país, se anexó a Costa Rica el 25 de julio de 1824 tras un cabildo abierto. Durante esa época, Nicaragua se encontraba sumida en una guerra civil. El comunicado afirma que las declaraciones del mandatario nicaragüense "dañan gravemente las relaciones entre las dos naciones. Y constituyen un grave rechazo e irrespeto a los tratados de límites Cañas-Jerez de 1858. El comunicado afirmó que Costa Rica no permitirá que se ponga entre dicho la frontera y régimen fronterizo vigente o que se le exija entablar un proceso legal para determinar aclarar disputas acerca de conflictos territoriales. La nota de protesta también afirma que Costa Rica sigue dispuesta a entablar un diálogo con Nicaragua y recordó que las declaraciones Ortega "no hacen más que agravar el conflicto diplomático y limítrofe entre ambos países por la Isla Calero". — Nota de protesta de Costa Rica enviada a Nicaragua por la canciller a.i Gioconda Ubeda Rivera Durante la sesión en el Congreso de Costa Rica de este miércoles, los diputados aprobaron una moción de censura y condena a las declaraciones emitidas por el Presidente de Nicaragua. De los 40 diputados presentes en la sesión, todos votaron a favor de la moción presentada por el oficialista Partido Liberación Nacional y el Partido Accesibilidad Sin Exclusión. El Presidente del Congreso de Costa Rica, afirmó en declaraciones a la prensa que todas las fracciones legislativas "dejaron atrás sus diferencias y aprobaron el pronunciamiento hacia Nicaragua". El canciller de Costa Rica, Enrique Castillo, afirmó en declaraciones al diario nación.com, que las declaraciones del presidente nicaragüense, Daniel Ortega "atizan la xenofobia contra los costarricenses". El canciller afirmó que las declaraciones de Ortega son una falta de respeto y afirmó que el Gobierno planea acciones tras las declaraciones del mandatario nicaragüense. Carlos Argüello, representante de Nicaragua ante la Corte Internacional de Justicia en La Haya afirmó que desconoce si su país presentará una demanda contra Costa Rica reclamando la provincia de Guanacaste y afirmó que solo conoce que las declaraciones de Ortega en efecto fueron dadas. Argüello afirma que las acusaciones de Costa Rica, acerca de que Nicaragua tiene una política expansionista son "una ironía".
QUESTION: ¿Qué ha reivindicado el mandatario nicaragüense durante una ceremonia militar?
Output: | la provincia costarricense de Guanacaste | 2 | NIv2 | task1334_sqac_answer_generation | zs_opt | [
0.800291121006012,
0.23213303089141846,
-0.2571907043457031,
-0.4370524287223816,
0.7052260041236877,
-0.6336687803268433,
0.5398100018501282,
0.7845037579536438,
0.08550092577934265,
0.36337530612945557,
0.19496731460094452,
0.6681308746337891,
-0.8034375905990601,
0.09765760600566864,
... |
In this task, you are given a sentence in the English language and your task is to convert it into the Hindi language. In translation, keep numbers as it is and make it sentence case (capitalize only the first word of each sentence and noun).
Q: These conflicts of interest have never been publicly disclosed by WHO, an apparent violation of its own rules.
A: | हित के इन संघर्षों को कभी भी WHO द्वारा सार्वजनिक रूप से प्रकट नहीं किया गया है, यह अपने स्वयं के नियमों का स्पष्ट उल्लंघन है। | 4 | NIv2 | task432_alt_en_hi_translation | zs_opt | [
-0.1045118048787117,
0.2879866361618042,
0.6660885214805603,
-0.13560938835144043,
-0.22769291698932648,
-0.1341439038515091,
0.1976006031036377,
-0.24284183979034424,
-0.16186971962451935,
-0.4603027403354645,
-0.4719504714012146,
0.020153898745775223,
-0.1463889628648758,
-0.358352333307... |
In this task you will be given a string and you should find the longest substring that is a palindrome. A palindrome is a string that is the same backwards as it is forwards. If the shortest possible palindrome is length 1 you should return the first character.
Input: Consider Input: qqqqqqgqggqqqgg
Output: ggqqqgg
Input: Consider Input: yvyyyyvyyvv
Output: yvyyyyvy
Input: Consider Input: rnnxrxnxrxxxx
| Output: xrxnxrx
| 2 | NIv2 | task850_synthetic_longest_palindrome | fs_opt | [
-0.9288678169250488,
1.1561338901519775,
0.13274863362312317,
-0.5828652381896973,
-0.43565577268600464,
0.07061851024627686,
0.6064563989639282,
-0.09118776768445969,
0.4704458713531494,
-0.2167241871356964,
-0.4766726791858673,
0.3909103274345398,
-0.8149427175521851,
0.5521652698516846,... |
Teacher: In this task, you're given the title of a story consisting of five sentences, numbered 1 through 5. Your job is to determine which two sentences need to be swapped sentences in order to make a story that makes complete sense and is befittingly titled. Indicate your answer using the numbers of the two sentences in order, such as '34' or '25'. The first digit refers to the sentence which should come first in the story.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Title: Marcus Buys Khakis. Sentence 1: Marcus needed clothing for a business casual event. Sentence 2: The pair he bought fit him perfectly. Sentence 3: He decided to buy a pair of khakis. Sentence 4: All of his clothes were either too formal or too casual. Sentence 5: Marcus was happy to have the right clothes for the event.
Solution: 24
Reason: Marcus's reasons for buying khakis is established, followed by his purchase of them and reaction.
Now, solve this instance: Title: The Salt and Pepa Concert. Sentence 1: She messaged Dori and asked her if she wanted to go to the concert. Sentence 2: Dori's friend Suzie had an extra ticket to the Salt and Pepa concert. Sentence 3: Dori replied to Suzie and told her she would like to go to the concert. Sentence 4: The next day Dori and Suzie went to the concert with ten other people. Sentence 5: They danced and had fun all night long!
Student: | 21 | 2 | NIv2 | task218_rocstories_swap_order_answer_generation | fs_opt | [
0.433860719203949,
0.15372614562511444,
-0.061640650033950806,
0.21915847063064575,
0.3171863257884979,
-0.23843564093112946,
0.2519484758377075,
0.542946994304657,
-0.304612934589386,
0.5269434452056885,
-0.27808552980422974,
0.045924112200737,
-0.48905429244041443,
-0.1279318630695343,
... |
Read the given sentence and if it is a general advice then indicate via "yes". Otherwise indicate via "no". advice is basically offering suggestions about the best course of action to someone. advice can come in a variety of forms, for example Direct advice and Indirect advice. (1) Direct advice: Using words (e.g., suggest, advice, recommend), verbs (e.g., can, could, should, may), or using questions (e.g., why don't you's, how about, have you thought about). (2) Indirect advice: contains hints from personal experiences with the intention for someone to do the same thing or statements that imply an action should (or should not) be taken.
Q: It helps a lot .
A: | no | 4 | NIv2 | task115_help_advice_classification | zs_opt | [
-0.16409149765968323,
0.7375895977020264,
0.3862629532814026,
0.10079445689916611,
0.37098926305770874,
-1.597442626953125,
0.9264371395111084,
0.2607491612434387,
0.11562827974557877,
0.2808299660682678,
-0.6361231803894043,
-0.6091409921646118,
-0.9170493483543396,
-0.06915348023176193,
... |
In this task, you are given a sentence in Persian, and your task is to translate it into English.
Example Input: چطور میتوانید به ما کمک کنید؟ اولا این لینک را در تمامی شبکههای اجتماعی به اشتراک بگذارید.
Example Output: How can you help us right now? 1) Share this link in all your social media networks, 2) Retweet this tweet.
Example Input: سه سال پیش در چنین روزی، هراند دینک روزنامه نگار ارمنی-ترک در جلوی دفتر روزنامه آگوس در استانبول، که خود سردبیری آنرا بر عهده داشت، ترور شد.
Example Output: Three years ago today, Turkish-Armenian journalist Hrant Dink was gunned down outside the office of the Argos newspaper he edited in Istanbul, Turkey.
Example Input: چیزی که عراقیها روز آخر عید هدیه گرفتند: ۱۳ انفجار، ۶۷ کشته، ۲۱۸ زخمی.
Example Output: | This is what Iraqis get on the last day of Eid: 13 blasts, 67 people killed, 218 injured..
| 3 | NIv2 | task662_global_voices_fa_en_translation | fs_opt | [
-0.5726420879364014,
1.0191559791564941,
0.4278034269809723,
-0.31725403666496277,
-0.6629346609115601,
0.15295308828353882,
0.711274266242981,
0.19602403044700623,
0.5557138919830322,
0.013107050210237503,
-0.6732507348060608,
0.6952556371688843,
-0.5807269811630249,
0.10381151735782623,
... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
This task is about creating an unanswerable question based on a given passage. Construct a question that looks relevant to the given context but is unanswerable. Following are a few suggestions about how to create unanswerable questions:
(i) create questions which require satisfying a constraint that is not mentioned in the passage
(ii) create questions which require information beyond what is provided in the passage in order to answer
(iii) replace an existing entity, number, date mentioned in the passage with other entity, number, date and use it in the question
(iv) create a question which is answerable from the passage and then replace one or two words by their antonyms or insert/remove negation words to make it unanswerable.
Passage: In 1763, Spain traded Florida to the Kingdom of Great Britain for control of Havana, Cuba, which had been captured by the British during the Seven Years' War. It was part of a large expansion of British territory following the country's victory in the Seven Years' War. Almost the entire Spanish population left, taking along most of the remaining indigenous population to Cuba. The British soon constructed the King's Road connecting St. Augustine to Georgia. The road crossed the St. Johns River at a narrow point, which the Seminole called Wacca Pilatka and the British named "Cow Ford", both names ostensibly reflecting the fact that cattle were brought across the river there.
Solution: Who owned Cuba after the Eight Years War?
Why? This question appears to be relevant to the passage as both involves words such as 'Cuba' and 'War' which also exist in the passage. The passage mentions that "after the war, almost the entire Spanish population left, taking along most of the remaining indigenous population to Cuba". This information is not sufficient to conclude that which country owned cuba.
New input: Passage: The Thuringian Realm existed until 531 and later, the Landgraviate of Thuringia was the largest state in the region, persisting between 1131 and 1247. Afterwards there was no state named Thuringia, nevertheless the term commonly described the region between the Harz mountains in the north, the Weiße Elster river in the east, the Franconian Forest in the south and the Werra river in the west. After the Treaty of Leipzig, Thuringia had its own dynasty again, the Ernestine Wettins. Their various lands formed the Free State of Thuringia, founded in 1920, together with some other small principalities. The Prussian territories around Erfurt, Mühlhausen and Nordhausen joined Thuringia in 1945.
Solution: | How long did the Thuringian realm decay? | 0 | NIv2 | task348_squad2.0_unanswerable_question_generation | fs_opt | [
1.1338392496109009,
0.3145941197872162,
-0.8131542205810547,
-0.37919843196868896,
0.4223858416080475,
-0.44477638602256775,
0.986335277557373,
0.9857022166252136,
-0.14242127537727356,
0.15111461281776428,
0.0071590617299079895,
0.1288803517818451,
-0.6323246955871582,
0.49203237891197205... |
Given a sentence in Arabic, generate a new Arabic 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.
One example: يمكنك أن تُسدّد محفظة بطاقة إئتمان لحمل كل بطاقات إئتمانك
Solution is here: يمكنك تحميل محفظة بطاقة إئتمان لحمل كل بطاقات إئتمانك.
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 credit card wallets and the changes in the sentence follows the commonsense knowledge.
Now, solve this: « والورق مصنوع من فحم الخشب ».
Solution: | « إن » ما « هي » أي الورق « إلا من نطفة ». | 6 | NIv2 | task414_mickey_ar_sentence_perturbation_generation | fs_opt | [
0.5797017216682434,
0.4139796495437622,
-0.5110266208648682,
-0.763178825378418,
-0.5707085728645325,
-0.491795152425766,
1.3543457984924316,
0.7868154644966125,
0.291904091835022,
-0.40079089999198914,
-0.5346843004226685,
0.29159122705459595,
-1.0552343130111694,
0.19435344636440277,
0... |
In this task, you are given a sentence in English and your task is to translate it into Spanish. In translation, keep the numbers and capitalization (capitalize only the first word of each sentence and name).
Example Input: Does the Council believe that it is permissible to consolidate future overfishing which violates the originally established TAC of 33 000 metric tonnes per year, given the current evidence for the critical state of anchovy stocks?
Example Output: ¿Considera admisible el Consejo consolidar para el futuro una sobrepesca que vulnere el TAC inicialmente establecido de 33.000 Tm./año con las evidencias actuales de crisis que presenta este recurso?
Example Input: At the end of the day, one of the fundamental tenets of economic theory is that the market is failing in many respects and anyone who takes issue with this is nothing more than an ideologue.
Example Output: Una de las nociones económicas fundamentales es que el mercado no funciona en una serie de aspectos y quien lo niegue no es más que un ideólogo.
Example Input: These are what are missing.
Example Output: | Esto no existe.
| 3 | NIv2 | task530_europarl_en_es_translation | fs_opt | [
-0.06439247727394104,
0.3282718062400818,
0.4199674129486084,
0.12658044695854187,
0.1360989212989807,
-0.7592916488647461,
0.7235981225967407,
1.1033642292022705,
-0.6382256746292114,
-0.1201232522726059,
-0.7381550073623657,
-0.2680439352989197,
-0.552555501461029,
-0.16347381472587585,
... |
Detailed Instructions: In this task, you need to replace a letter in the sentence with another given letter.
Q: Sentence: 'some guys playing frisbee on some red surface'. Replace the letter 'y' with 'f' in the sentence.
A: | some gufs plafing frisbee on some red surface | 9 | NIv2 | task160_replace_letter_in_a_sentence | zs_opt | [
-0.22702930867671967,
0.6627300977706909,
-0.6933546662330627,
-1.2747454643249512,
0.6691557765007019,
-0.4635959267616272,
0.10876531898975372,
0.44189146161079407,
0.8855206370353699,
-0.3272123336791992,
-0.6883038282394409,
0.2242792397737503,
0.10741105675697327,
-0.6578978896141052,... |
Detailed Instructions: In this task, you are given an input list A. You need to find all the elements of the list that are numbers and calculate their sum.
Problem:['j', 'B', '5953', '5249', '1215', '5409', 'Q', '747', '4815', '5825', '205', 'i', 'S', 'y', '9849', 'P', 't', 'z']
Solution: | 39267 | 8 | NIv2 | task499_extract_and_add_all_numbers_from_list | zs_opt | [
0.2287406623363495,
1.0473145246505737,
-0.8615227937698364,
-0.5274558067321777,
-0.10614638775587082,
-0.22562777996063232,
0.6556004285812378,
-0.5700545310974121,
-0.8561755418777466,
0.03138812258839607,
-0.7297133207321167,
0.31899264454841614,
0.15716159343719482,
-0.175847440958023... |
Detailed Instructions: In this task, you are given a hateful post in English from online platforms. You are expected to classify the post into two classes: aggresive or non-aggresive. An aggresive post is one that expresses feelings and opinions in an abusive way and tries to dominate others. Note that the URLs in the text have been replaced with [Link].
See one example below:
Problem: Post: This immigrant should be hung or shot! Period! Animal.
Solution: Aggresive
Explanation: This post is aggresive because it is abusive to immigrants.
Problem: Post: @chelseahandler Another dried up liberal cunt willing to look the other way while hollywoods powerful abuse women .… [Link]
Solution: | Non-aggresive | 4 | NIv2 | task335_hateeval_classification_aggresive_en | fs_opt | [
-0.8155263662338257,
0.12417793273925781,
0.8332691192626953,
0.47691503167152405,
0.029026050120592117,
-1.1235263347625732,
0.5220018625259399,
0.7520175576210022,
0.13743355870246887,
0.3686080574989319,
0.11952612549066544,
-0.06224637106060982,
-0.6863060593605042,
-0.5848999619483948... |
In this task, you're given a question, along with a context passage. The passage will not have a direct answer to the question, but can include some information and a clue for the answer. Assuming you can only obtain information about one entity in the passage, your job is to determine whether information from the passage can be used to answer the question. Indicate your choice as `a` for Yes or `b` for No.
Example: Question: When did the operation during which the 704th dropped supplies to allied troops near Nijmegen begin? Passage: The group was occasionally diverted from strategic missions to carry out air support and interdiction missions. It supported Operation Overlord, the invasion of Normandy by attacking transportation targets, including bridges, along with airfields and strong points in France. On D Day, the squadron and the rest of the 446th Group led the first heavy bomber mission of the day. The 446th aided ground forces at Caen and Saint-Lô during July by hitting bridges, gun batteries, and enemy troops. 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. It struck lines of communications during the Battle of the Bulge. During Operation Varsity in March 1945, it supplied ground and airborne troops near Wesel. The squadron flew its last combat mission on 25 April 1945 against Salzburg, Austria. The group had flown 273 missions and had lost 58 aircraft during the war,
.
Example solution: a
Example explanation: The passage describes the 704th's actions during Operation Market Garden so only information about the operation is needed.
Problem: Question: What years are the setting for Davidson's first novel? Passage:When the war ended, he returned to the Keystone Agency and travelled all over Europe as a freelance reporter. It was during one of these trips that he came up with the idea for his first thriller, The Night of Wenceslas (1960). The novel is set in Czechoslovakia during the Cold War, and tells the story of young Nicolas Whistler, a 24-year-old Londoner whose business trip to Prague goes horribly awry. The Night of Wenceslas was an instant success, inviting favourable comparisons with such luminaries as Eric Ambler. Davidson became one of the handful of living writers to have their first novel appear in a green Penguin jacket. The book won the Crime Writers' Association's Gold Dagger Award (the top prize for crime and spy fiction in Britain) as well as the Authors' Club First Novel Award. It was filmed as Hot Enough for June (1964), with Dirk Bogarde in the role of Whistler.
| Solution: b | 5 | NIv2 | task233_iirc_link_exists_classification | fs_opt | [
0.7621282339096069,
0.47288477420806885,
-0.4242774248123169,
0.042029254138469696,
0.2156502604484558,
-0.321880966424942,
1.1495414972305298,
0.7484942674636841,
0.6839277744293213,
-0.19596406817436218,
-0.6379686594009399,
0.15008226037025452,
-0.6398562788963318,
-0.2177426517009735,
... |
In this task, you are given a sentence in Spanish and your task is to translate it into English. In translation, keep the numbers and capitalization (capitalize only the first word of each sentence and name).
[EX Q]: Creo que hay que felicitarse por ello.
[EX A]: I believe that we should be pleased about this.
[EX Q]: Les insto a estudiar seriamente este problema, ya que la ruptura de la continuidad tendrá consecuencias muy graves para el programa y un efecto negativo en los trabajadores profesionales y voluntarios.
[EX A]: I urge you to look seriously at this problem. A break in continuity will have serious consequences for the programme and certainly a disruptive effect on voluntary and professional workers.
[EX Q]: No obstante, también sabemos que sólo podremos afrontar los grandes retos de la globalización todos unidos, en nuestra calidad de europeos.
[EX A]: | But we also know that we can only shape the huge challenge of globalisation together as Europeans.
| 6 | NIv2 | task531_europarl_es_en_translation | fs_opt | [
-0.8074657917022705,
0.5877028703689575,
0.6414611339569092,
-0.5899732708930969,
-0.06590348482131958,
-0.4384523928165436,
0.6411347389221191,
0.42124319076538086,
0.06673522293567657,
-0.1392582654953003,
-0.3139943778514862,
-0.10422444343566895,
-0.4448378086090088,
-0.027945378795266... |
In this task, you are given a sentence and a category word that defines the relation between the input sentence and the output to be generated. Your job is to generate another sentence that satisfies the relation specified by the category. If the category is specified as entailment, then the output sentence must clearly agree with the input sentence. If the category specified is contradiction , then the output sentence must clearly disagree with the input sentence.
sentence_A: A man is fitting a silencer to a pistol. category: contradiction | There is no man fitting a silencer to a pistol | 0 | NIv2 | task1613_sick_given_category_generate_sentence | zs_opt | [
-0.7891832590103149,
0.606573224067688,
0.24163587391376495,
-0.3409537076950073,
0.12124322354793549,
0.17346706986427307,
0.20519042015075684,
0.2411237508058548,
0.6006363034248352,
-0.29513657093048096,
-1.145430088043213,
-0.43282338976860046,
-0.46294987201690674,
0.16008684039115906... |
In this task, you're given a question, along with a context passage which has extra information available on certain terms mentioned in it, i.e., the proper nouns in the passage. Your job is to determine whether information from more than one term is needed to answer the question. Indicate your choice as `a` for Yes or `b` for No.
Example Input: Question: Were the Oz books the only books L. Frank Baum ever wrote? Passage:The Land of Ev is a fictional country in the Oz books of L. Frank Baum and his successors. Its exact location is unclear between text and maps. The Road to Oz states that Ev is to the north of the Land of Oz, and in Ozma of Oz, Princess Ozma of Oz and her procession enter the Munchkin Country and meet the King of the Munchkins upon leaving the palace at Evna, the capital city. Subsequent books place Ev nearer to the Winkie Country, and the map on the endpapers of Tik-Tok of Oz shows the Munchkin Country as having no northern border with the desert that surrounds Oz, as a thin strip of the Gillikin Country extends even farther east than most of the Munchkin Country. This map depicts Ev as a small country to the northwest (the compass rose is reversed) of Oz, with the Dominions of the Nome King as a separate area. James E. Haff and Dick Martin's map, following the text, place the Nome Kingdom under an Ev that takes up the entire portion allotted to the Nome King's dominions on Baum's map.
Example Output: a
Example Input: Question: During what dates did Wotherspoon play for the Canadian Junior Team? Passage:A native of Surrey, British Columbia, Wotherspoon was selected by the Portland Winter Hawks in the second round of the 2008 Western Hockey League (WHL) Bantam Draft. He made his WHL debut as a 15-year-old in 2008–09, appearing in four games for Portland, then played four full seasons between 2009 and 2013. In his WHL career, he has appeared in 239 games in his WHL career and scored 17 goals along with 65 assists. With the Winterhawks, he appeared in the WHL championship series in three consecutive years as Portland lost the final in 2011 and 2012 to the Kootenay Ice and Edmonton Oil Kings, respectively, before finally winning the Ed Chynoweth Cup championship in 2013 by defeating Edmonton. Wotherspoon was also named to the WHL's Western Conference second All-Star Team in 2012–13. Wotherspoon scored three points in five games at the 2013 Memorial Cup, however Portland lost the Canadian Hockey League (CHL) championship game, the Memorial Cup, to the Halifax Mooseheads, 6–4. During the season, Wotherspoon was also a member of the Canadian junior team, recording two points in six games at the 2013 World Junior Ice Hockey Championships.
Example Output: a
Example Input: Question: What state did Smith graduate high school from? Passage:In 1996, Smith began his coaching career as an assistant at Hempfield High School. From there Smith spent the next four seasons as the passing coordinator for the Duquesne Dukes. In 2001, Smith returned to his high school alma mater the Gateway Gators where he served as the offensive coordinator. The following season Smith was named as the Gators Head Coach and over the next eleven seasons Smith led Gateway to a 101-30 mark and four WPIAL runner-up finishes.. In that time Smith sent 23 players to NCAA FBS (I-A) colleges and 17 more to FCS(I-AA) colleges, and coached in three U.S. Army All-America and Semper Fidelis All-America games. He has mentored six NFL players, including former Nittany Lions Trevor Williams, Jordan Lucas, Justin King and Lydell Sargeant. Smith, who also served as the athletic director, departed Gateway following the 2012 football season when his athletic director position was reduced to part-time. His salary was also cut in half and the district instituted a new rule that no administrator could coach. Following a January recruiting visit in 2013, the Temple Owls coach and fellow Penn State alum Matt Rhule offered Smith a coaching position as his wide receivers coach. Smith accepted and helped the Owls’ passing game reach new heights during the 2013 season. In 2014 James Franklin hired Smith as the Penn State Nittany Lions’ defensive recruiting coordinator and cornerbacks coach, positions he currently maintains. Smith is also the assistant head coach for the Nittany Lions, a title received following the 2015 season.
Example Output: | b
| 3 | NIv2 | task232_iirc_link_number_classification | fs_opt | [
0.5986016392707825,
0.1461011916399002,
-0.13821876049041748,
-0.6460024118423462,
0.6742465496063232,
-0.3830300271511078,
1.1267352104187012,
0.7195539474487305,
-0.3246834874153137,
0.013330934569239616,
0.012712045572698116,
0.8182510137557983,
-0.8121780157089233,
0.29716575145721436,... |
Given the task definition and input, reply with output. In this task you are given a sentence pair from wikipedia that have high lexical overlap. If the sentences have the same meaning and are just paraphrases of each other label them as "Paraphrase" , if not label them as "Not paraphrase". The two sentences are seperated by a new line.
The 1990 South Australian National Football League season was the 110th season of the highest Australian rules football competition in South Australia .
The 1990 South Australian National Football League season was the 110th season of the Australian - top rules football - competition in southern Australia .
| Not paraphrase | 5 | NIv2 | task400_paws_paraphrase_classification | zs_opt | [
-0.6582995653152466,
0.5883380770683289,
-0.00030577066354453564,
-1.0736887454986572,
-0.540622889995575,
-0.08094367384910583,
0.8424472808837891,
0.18491420149803162,
-0.045271020382642746,
-0.14322076737880707,
-0.655286431312561,
0.9141392707824707,
-0.8511580228805542,
0.331680655479... |
You will be given a definition of a task first, then some input of the task.
Given a story, answer the question about the story. The question is the last sentence in the input. The story has one of the three following scenarios: (1) when the individual's belief matches reality, (2) when the individual's belief does not match reality, (3) is when an individual has a false belief about another individual's beliefs. The question will ask about the location of an object in the story with respect to either none or one of the three scenarios.
Hannah entered the garage. James entered the garage. The pumpkin is in the blue_container. Hannah moved the pumpkin to the blue_cupboard. Where does Hannah think that James searches for the pumpkin?
Output: | blue_cupboard | 1 | NIv2 | task151_tomqa_find_location_easy_clean | zs_opt | [
0.3238001763820648,
-0.33428576588630676,
-0.07267670333385468,
-0.20058375597000122,
-0.24383632838726044,
-0.7663244009017944,
0.3575759530067444,
0.8863147497177124,
-0.1948588788509369,
0.08364327996969223,
-0.3662440776824951,
0.3126594126224518,
0.23169563710689545,
-0.40014782547950... |
Definition: A text is given in Bengali. Translate it from the Bengali language to the Hindi language. The translation must not omit or add information to the original sentence.
Input: दूसरी वार्षिक बिम्सटेक isaster Management ercise की मेज़बानी के लिए भी भारत तैयार है।
Output: | দ্বিতীয় বার্ষিক বিমস্টেক ডিজাস্টার ম্যানেজমেন্ট এক্সারসাইজ আয়োজনের জন্য ভারত প্রস্তুত। | 2 | NIv2 | task1010_pib_translation_hindi_bengali | zs_opt | [
-0.4596099853515625,
0.2013593167066574,
0.4156080484390259,
0.33376654982566833,
0.2271016389131546,
-0.37283268570899963,
0.12933099269866943,
0.1666346788406372,
-0.08314588665962219,
0.16462519764900208,
-1.1127233505249023,
-0.29663315415382385,
0.03111184760928154,
0.634160578250885,... |
This task is in Spanish. Based on the given context, generate a question which can be answered by the given context. Generate a question that has more than 7 words. You can paraphrase the given context while forming the question.
Suggestion: The question may involve starting question words like WHERE, WHEN, HOW, WHAT (in Spanish).
--------
Question: CONTEXT: Historia
El 7 de diciembre de 1941 los japoneses atacaron Pearl Harbor, Hawái, dejando inutilizados la mayor parte de los acorazados de la flota estadounidense del Pacífico y comenzando un estado de guerra formal entre ambas naciones. Al lanzar este ataque, los líderes japoneses buscaban neutralizar su flota, apoderarse de lugares ricos en recursos naturales y obtener bases militares estratégicas para defender su imperio. Poco después, otras naciones como el Reino Unido, Australia y Nueva Zelanda se unieron a los Estados Unidos como aliados en la guerra contra Japón. En palabras de la «Orden secreta Número uno» de la Flota Combinada de la Armada Imperial Japonesa, fechada el 1 de noviembre de 1941, los objetivos iniciales de las campañas de esta inminente guerra eran «(expulsar) a las fuerzas británicas y estadounidenses de las Indias Neerlandesas y las Filipinas, para establecer una política de autosuficiencia autónoma e independencia económica». Para realizar estos objetivos, durante los primeros meses de 1942 las fuerzas japonesas también atacaron y tomaron el control de Filipinas, Tailandia, Malasia, Singapur, las Indias Orientales Neerlandesas, la Isla Wake, Nueva Bretaña, las Islas Gilbert y Guam.
ANSWER: inutilizados
Answer: ¿Cómo quedaron los navíos estadounidenses tras el ataque japonés de Pearl Harbor?
Question: CONTEXT: La arquitectura románica supone una manera de construir dentro del estilo conocido como arte románico desarrollado en Europa, con sus características propias y su especial evolución a lo largo de más de dos siglos, que comprende desde principios del siglo XI hasta la mitad del siglo XIII. Esa misma arquitectura en España adquiere sus propias peculiaridades dejándose influir tanto por las modas que le llegan desde el exterior a través de Italia y Francia como por la tradición y recursos artísticos antiguos en la península ibérica.
ANSWER: desde principios del siglo XI hasta la mitad del siglo XIII
Answer: ¿Durante qué período evolucionó la arquitectura románica?
Question: CONTEXT: El estilo personal de Wahid y su incapacidad de resolver los problemas económicos, además de la violencia sectaria que sacude las islas Molucas, que ha causado la muerte de miles de personas, y el separatismo en Aceh e Irian Jaya, han provocado las críticas del Parlamento en los últimos meses. Los rumores amenazadores de que los 700 miembros del Parlamento someterían a Wahid a una moción de censura forzaron al presidente que admitiera sus faltas y pidiera perdón el Lunes pasado durante la apertura de la reunión anual del MPR. Mientras tanto, queda por saber si Megawati, ahora con más poderes, será capaz de realizar lo que han exigido a Wahid y que por ahora no ha conseguido. Megawati, hija del fundador de la nación indonesia Sukarno, ha permanecido en la sombra desde que asumió el puesto y, pese a su popularidad, es considerada como una política de poca importancia por muchos intelectuales. Mientras Jusef Wanandi, miembro del Centro de Estudios Estratégicos Internacionales de Yakarta, aseguró a EFE que "parece estar abrumada por el trabajo de vicepresidenta", otros críticos consideran que no será capaz de hacerse con el papel de líder. Barton, por su parte, también dudó de la capacidad de Megawati en su nueva tarea.
ANSWER: Centro de Estudios Estratégicos Internacionales de Yakarta
Answer: | ¿Dónde está asociado Jusef Wanandi?
| 7 | NIv2 | task1335_sqac_question_generation | fs_opt | [
0.49593257904052734,
0.2566490173339844,
-0.3557225465774536,
-0.13550367951393127,
0.3496388792991638,
0.3090088963508606,
1.1466751098632812,
0.6610133647918701,
0.19439640641212463,
0.18306498229503632,
-0.024556169286370277,
0.25328993797302246,
-0.6170914173126221,
0.12157820910215378... |
Given the task definition, example input & output, solve the new input case.
In this task, you're given a statement, and three sentences as choices. Your job is to determine which sentence clearly disagrees with the statement. Indicate your answer as '1', '2', or '3' corresponding to the choice number of the selected sentence.
Example: Statement: Next to the MGM Grand you will find M and M World, four stories of merchandise and memorabilia dedicated to the candy that doesn't melt in your hand. Choices: 1. The candy has many fans who love its attractions. 2. There's four stories of memorabilia dedicated to a candy. 3. That particular candy melts and becomes difficult to eat.
Output: 3
It is said in the statement that the candy doesn't melt in your hand, but the sentence in choice 3 disagrees with it.
New input case for you: Statement: um-hum yeah right what kind of car is it Choices: 1. Yes, what kind of car model is it? 2. In what year was the car made? 3. What kind of a jet plane is it?
Output: | 3 | 1 | NIv2 | task202_mnli_contradiction_classification | fs_opt | [
0.1880204826593399,
0.03750283271074295,
-0.48405858874320984,
0.40418940782546997,
0.30434608459472656,
-0.4739725887775421,
0.16762720048427582,
1.334972620010376,
-0.20871764421463013,
0.12583160400390625,
-0.6033580303192139,
0.15281087160110474,
0.3212036192417145,
-0.6468431353569031... |
In this task, you're given a statement and three sentences as choices. Your job is to determine the neutral choice based on your inference from the statement and your commonsense knowledge. The neutral choice is a sentence that neither agrees nor disagrees with the statement. Indicate your answer as '1', '2', or '3', corresponding to the choice number of the selected sentence. If sentence X agrees with sentence Y, one's correctness follows from the other one. If sentence X disagrees with sentence Y, they can not be correct at the same time.
Example: Statement: Next to the MGM Grand you will find M and M World, four stories of merchandise and memorabilia dedicated to the candy that doesn't melt in your hand. Choices: 1. The candy has many fans who love its attractions. 2. There's four stories of memorabilia dedicated to a candy. 3. That particular candy melts and becomes difficult to eat.
Example solution: 1
Example explanation: The candy may or may not be popular and the first choice is correct. Based on the statement, candy doesn't melt and there's four stories of memorabilia dedicated to a candy. So the second choice agrees with the statement and the third choice disagrees with the statement.
Problem: Statement: And the doubly-damned fools had let Menes drive millions of slaves to death to build a pyramid to the sky when there were already natural columns that could have been used! Choices: 1. Menes had a pyramid built to the sky but could have used the natural columns they were there. 2. Menes was going to build a pyramid, but decided to use the natural columns. 3. Menes wanted to go to the sky to challenge the Vampire Lord.
| Solution: 3 | 5 | NIv2 | task201_mnli_neutral_classification | fs_opt | [
0.49827805161476135,
0.5657663345336914,
-0.11735236644744873,
0.02724660560488701,
0.08474187552928925,
-0.8670730590820312,
-0.025344466790556908,
0.7468177080154419,
0.11229301989078522,
-0.05730297788977623,
-0.7524121999740601,
-0.1571006029844284,
-0.2615795135498047,
-0.253115266561... |
Write an incorrect answer to the given question based on the associated fact. You are also provided with the correct answer to the given question. Make sure that your incorrect answer is relevant and similar to the associated fact. Also, try to make the incorrect answer similar to the correct answer so that distinguishing the correct answer from the incorrect answer is not very easy. Make sure you don't accidentally provide another correct answer! Also, make sure they sound reasonable (e.g., might be on a school pop quiz). A good incorrect answer can be constructed using words associated with the question, but not the correct answer. For example, for the question "What helps plants survive?", using words like "weeds", "vase", "bee" (associated with "plant"), or "first aid", "parachute", "accident" (associated with "survive") etc. Your incorrect answers make the question hard, so these results in good incorrect answers.
Example Input: Fact: an organism requires energy for rapid expansion.
Question: an organism requires energy for what?
Correct Answer: rapid expansion.
Example Output: falling down.
Example Input: Fact: Seat belts and helmets protect passengers.
Question: What do seat belts and helmets do?
Correct Answer: protect passengers.
Example Output: destroy.
Example Input: Fact: an electric stove transforms electrical energy to kinetic energy.
Question: What transforms electrical energy to kinetic energy?
Correct Answer: an electric stove.
Example Output: | a battery.
| 3 | NIv2 | task042_qasc_incorrect_option_generation | fs_opt | [
0.2712489664554596,
0.8057783246040344,
-0.33182135224342346,
0.5965444445610046,
-0.08382882177829742,
-1.2295560836791992,
0.4151443839073181,
1.039324164390564,
-0.15260249376296997,
0.12869566679000854,
-0.7778918743133545,
0.01975659839808941,
-0.6225848197937012,
0.07892054319381714,... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
Given a sentence, generate a most unlikely next statement. The next statement should not be logically relevant to the given context
The girls continue to speak with one another while the girl knits. They
Solution: put the bars around while speaking and play.
Why? This is incorrect as the girls are not playing, they are knitting.
New input: Remaining expressionless, someone walks towards them. Wind
Solution: | out, someone moves close to someone and closes the door behind her. | 0 | NIv2 | task454_swag_incorrect_answer_generation | fs_opt | [
0.1473071277141571,
0.9313827753067017,
-0.5654322504997253,
0.3247576355934143,
-0.17048385739326477,
-0.6043262481689453,
0.017240852117538452,
0.5078932642936707,
0.16226696968078613,
0.4651370048522949,
-0.3345426321029663,
-0.1137758195400238,
-0.17181453108787537,
-0.0348379015922546... |
Given the task definition and input, reply with output. Given a sentence in Italian, generate a new Italian 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.
Se vuoi salire sul palco allora dovresti diventare un attore.
| Se esitate ad andare sul palco allora dovreste diventare un attore. | 5 | NIv2 | task408_mickey_it_sentence_perturbation_generation | zs_opt | [
-0.06620048731565475,
0.9971814155578613,
0.40263617038726807,
0.17052923142910004,
-0.2484692484140396,
-0.20212125778198242,
0.4813060760498047,
1.314054012298584,
-0.04713551700115204,
-0.3069801330566406,
-0.6395308971405029,
0.18725672364234924,
-0.39864328503608704,
0.195019841194152... |
Given the task definition and input, reply with output. In this task, you are given inputs i,j, and A, where i and j are integers and A is a list. You need to concatenate all elements of A from the ith element to the jth element, and print the resultant string. i and j will be non-negative, and will always have a value less than the length of A. i will always be less than j.
2, 10, ['5395', '3889', 'e', 'P', 'q', '4523', '9951', 'q', 'r', '6903', 'y', 't', 'b', 'N', 'C', 'Z', 'O', 'A', '2653', 'k', '4353', 'H', '4901', 'j', 'r', '7511', 'X']
| 3889ePq45239951qr6903 | 5 | NIv2 | task100_concatenate_all_elements_from_index_i_to_j | zs_opt | [
-0.5309782028198242,
0.6902626752853394,
-0.20736804604530334,
-0.16786283254623413,
-0.1805359572172165,
-0.2760581076145172,
0.2012491524219513,
-0.25943148136138916,
-0.0885419249534607,
0.03313592076301575,
-1.0087449550628662,
0.22299304604530334,
0.09736600518226624,
-0.1441422104835... |
Detailed Instructions: Given a part of privacy policy text, identify the type of personal information which is collected, used, tracked or retained. The type of information should be present inside the given policy text, answer as 'Not Specified' otherwise
Problem:The site collects your cookies or tracking elements for service operations or security. Collection happens in an unspecified way.
Solution: | Cookies and tracking elements | 8 | NIv2 | task684_online_privacy_policy_text_information_type_generation | zs_opt | [
-0.6846554279327393,
-0.2042085826396942,
-0.6105539202690125,
0.18550816178321838,
-0.9151570200920105,
-0.6668040156364441,
0.32095861434936523,
0.3756716847419739,
0.16729822754859924,
0.7529798746109009,
0.38939374685287476,
-0.2779110074043274,
-0.24734185636043549,
-0.469989836215972... |
Teacher:You are given a sentence in Polish. Your job is to translate the Polish sentence into Farsi.
Teacher: Now, understand the problem? Solve this instance: Inżynierowie pośród was z pewnością powiedzą "" To niemożliwe. Są zbyt małe "".
Student: | حالا مهندسین در جمع شما اونها را می بینند و می گویند ؛ « نه نمیشه. اون سیم ها کوچکند. » | 6 | NIv2 | task1263_ted_translation_pl_fa | zs_opt | [
-0.8008997440338135,
1.2588458061218262,
0.3129238486289978,
-0.9763460755348206,
-0.5512565970420837,
-0.29201120138168335,
0.9786103367805481,
0.2351020872592926,
0.31358301639556885,
0.10022442042827606,
-0.6527513265609741,
0.4325917363166809,
-0.054071277379989624,
-0.3726906478404999... |
Given a sentence in the Japanese and Filipino language. Your task is check if the Filipino sentence is translation of Japanese. if the translation is correct than generate label "Yes", otherwise generate label "No".
Input: Consider Input: Japanese: ハンガリーの釈放と、続いてアゼルバイジャンが恩赦を与えた、アゼリー人で斧を使った殺人で有罪となったラミル・サファロフの送還の後、アルメニアは「戦争の準備」ができていると発表した。
Filipino: Kasunod ng pagpapalaya at pagpapabalik sa sariling bayan ng Hungary sa Azeri na napatunayang may sala sa pagpatay gamit ang palakol na si Ramil Safarov, na ang Azebaijan ay mabigyan ng patawad, ang Armenia ay nag-anunsiyo na "handa na ang giyera."
Output: Yes
Input: Consider Input: Japanese: 全癲癇患者のうちの３〜５％が、攻撃に使われるような、形または色による閃光によって引き起こされる発作にかかりやすい。
Filipino: Sa pagitan ng tatlo at limang porsiyentong may epilepsya ay madaling maatake na pinasisimulan ng mga ilaw na kumikislap, mga hugis o mga kulay, tulad ng ginamit sa pag-atake.
Output: Yes
Input: Consider Input: Japanese: テレビ司会者に加えて、サレー氏は熟練弁護士でもあり、シーテ地区の地域議会にも務めていた。
Filipino: Dagdag pa sa pagiging mamamahayag sa telebisyon, si Saray ay isa ring sanay na abugado, at nagsisilbi sa mga lokal na konseho sa kapitbahayan ng Shiite.
| Output: Yes
| 2 | NIv2 | task1120_alt_ja_fil_answer_generation | fs_opt | [
0.4428962469100952,
-0.3278767466545105,
0.35375338792800903,
0.3666442036628723,
0.32391655445098877,
-0.05365622043609619,
1.0426872968673706,
0.7262051105499268,
-0.5081682205200195,
-0.3837321996688843,
-1.004103422164917,
0.7710462212562561,
-0.8018561005592346,
0.40426838397979736,
... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
This task is about translating a given French language sentence to English.
Vous avez fait quelque chose de tellement bien aujourd'hui ! Pourquoi vous m'évitez ?
Solution: You did such a great thing today, why are you avoiding me?
Why? This is a good example because the French sentence has been translated correctly to English.
New input: Je rembourserai toute ma dette et je partirai.
Solution: | I will pay back all my debt and leave. | 0 | NIv2 | task1690_qed_amara_translation | fs_opt | [
-0.3401378393173218,
0.9151627421379089,
0.5450109243392944,
-0.33833184838294983,
0.21243776381015778,
-0.08062610030174255,
0.5058609247207642,
0.11962588876485825,
0.44632548093795776,
-0.13299685716629028,
-0.2167401760816574,
0.16349482536315918,
-0.4429556131362915,
0.439123421907424... |
Instructions: You are given a statement written in Tamil. Choose the most logical word from the given 4 options which can be used to replace the <MASK> token in the statement. Output the word from the correct option .
Input: Statement: தென் அமெரிக்காவில் அந்தக் கண்டத்து கிரேட்டான்களின் புவிப்பரப்பு ஆத்திரேலியா, தெற்கு ஆபிரிக்கா போன்றே தொன்மையானதாக இருப்பினும் புவியியல் காலக்கோட்டில் இளமையானதும் உருவாகி வருவதுமான அந்தீசு மலைத்தொடர் இருப்பதால் இப்பகுதியில் மேற்குப் பகுதியில் உருவாகும் வெப்பமண்டல எதிர்ச்சூறாவளிகளால் அத்திலாந்திக்குப் பெருங்கடலிலிருந்து வெப்பமான, ஈரமான காற்றைப் பெறுகிறது. இக்காரணத்தால் மகரக்கோட்டை அடுத்துள்ள <MASK> பகுதிகளில் பெருமளவில் விவசாயம் செய்யப்படுகின்றது; முதன்மைப் பயிராக கரும்பு விளைகின்றது. தவிரவும் இயற்கையான மழைக்காட்டு தாவரங்கள் முற்றிலும் அழிக்கப்பட்டு விவசாயம் நடக்கிறது. கீழே தெற்கிலுள்ள அர்கெந்தீனாவிலுள்ள மிதவெப்பமண்டல புல்வெளிகளான பம்பாசு மண்டலம் உலகிலேயே மிகவும் வளமையான விவசாயக்களமாக விளங்குகின்றது; இங்கு கோதுமை, சோயா அவரை, மக்காச்சோளம் விளைவிப்பதுடன் கால்நடை வேளாண்மையால் மாட்டிறைச்சியும் கிடைக்கின்றது. உலகளவில் வேளாண் பொருட்கள் ஏற்றுமதி நாடுகளில் முதன்மையானதாக அர்கெந்தீனா விளங்குகின்றது.
Option A: மொசாம்பிக்
Option B: பிரேசில்
Option C: தென்னாப்பிரிக்கா
Option D: அர்கெந்தீனா
Output: | பிரேசில் | 3 | NIv2 | task953_wiki_cloze_ta_multiple_choice_question_answering | zs_opt | [
0.5408250093460083,
0.5284610986709595,
-0.218044251203537,
0.36988168954849243,
-0.26094987988471985,
-1.2880558967590332,
-0.9802819490432739,
0.5665649175643921,
-0.11910632997751236,
0.23840001225471497,
-0.024877935647964478,
0.0149156479164958,
-0.6891089677810669,
-0.799462080001831... |
Detailed Instructions: You will be given two pieces of text with the same meaning. One of them is simpler and easier to understand for non-native English speakers. Complex texts may contain more difficult words, have unnecessary phrases or contain long sentences. Your task is to choose the simpler piece of text. You are expected to output 'Text one' if the first sentence is simpler. Otherwise output 'Text two'.
Q: Text one: Normally a pawn moves by advancing a single square, but the first time each pawn is moved from its initial position, it has the option to advance two squares.
Text two: Normally a pawn moves by advancing a single square. The first time each pawn is moved from its initial position, it has the choice to go forward two squares.
A: | Text two | 9 | NIv2 | task112_asset_simple_sentence_identification | zs_opt | [
-1.0182344913482666,
0.3828837275505066,
-0.13115477561950684,
0.033377621322870255,
0.3525300621986389,
-0.5203213691711426,
0.277838796377182,
0.7565324902534485,
0.3013094365596771,
0.1818206012248993,
-0.09508366882801056,
-0.18638569116592407,
-0.6036785840988159,
0.18209746479988098,... |
You are given a sentence in Polish. Your job is to translate the Polish sentence into Arabic.
Ex Input:
Jednak będąc na pokładzie Boeinga 787, nie wiesz, że jest on przykładem indyjskiej niewidzialnej innowacji.
Ex Output:
لكن بالطبع ، عندما تصعد على طائرة البوينغ 787 ، لن تدرك بأن هذا ابتكار غير مرئي ناجم عن الهند.
Ex Input:
Każda grupa może korzystać z jednego komputera, nie z czterech. "" Pamiętacie komputer w ścianie?
Ex Output:
كل مجموعة من أربعة يمكنها استخدام جهاز كمبيوتر واحد وليس أربعة أجهزة كمبيوتر. "" تذكروا ، من مشروع "" فتحة على الحائط "".
Ex Input:
A to dlatego, że szkielety hydrostatyczne, który do tej pory odnajdowaliśmy w przyrodzie, miały te same podstawowe elementy.
Ex Output:
| وذلك بسبب ان كل هيكل هيدروستاتيكي وجدناه في الطبيعة حتى تلك اللحظة له عناصر اساسية.
| 1 | NIv2 | task1259_ted_translation_pl_ar | fs_opt | [
-1.006654977798462,
0.6374471783638,
-0.5399782061576843,
-0.6007806062698364,
-0.2449842095375061,
-0.24612835049629211,
1.17482590675354,
0.44622135162353516,
0.11425019800662994,
0.06547484546899796,
-0.22409489750862122,
0.563312292098999,
-0.03730861842632294,
0.12428346276283264,
0... |
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 the Hindi language and your task is to convert it into the English language. In translation, keep numbers as it is and make it sentence case (capitalize only the first word of each sentence and noun).
2007 में फ़्रांस, पेरिस के पार्क डेस प्रिंसेस में हुए रग्बी विश्व कप के पूल C में इटली ने पुर्तगाल को 31-5 से हराया।
Solution: Italy have defeated Portugal 31-5 in Pool C of the 2007 Rugby World Cup at Parc des Princes, Paris, France.
Why? The Hindi sentence is correctly converted into English because the converted sentence holds the message that Italy defeated Portugal 31–5 in Pool C of the 2007 Rugby World Cup at the Parc des Princes in Paris, France. Also, translated sentence preserves the numbers as it is and converted sentence is sentence case.
New input: स्कॉटलैंड यार्ड ने कहा है कि, "हम देखेंगे कि क्या आरोपों का पीछा करना है, या यह देखना है कि क्या पीड़ित इसका पीछा करना चाहता है।"
Solution: | Scotland Yard have said, "We will see whether to pursue the charges, or see whether the victim wants to pursue it." | 0 | NIv2 | task433_alt_hi_en_translation | fs_opt | [
0.11420652270317078,
0.5698305368423462,
-0.3144102990627289,
0.21003492176532745,
-0.19146034121513367,
-0.4992409944534302,
-0.3331977128982544,
0.42815136909484863,
-0.14992228150367737,
-0.3821212649345398,
-0.4305136203765869,
0.3255324065685272,
-0.08425568789243698,
0.57464182376861... |
In this task, you're given a review from Amazon and category of the product based on the review given by the user and your task is classify whether the given category match the review. Generate "True" if given review and its category match, otherwise generate "False".
Q: Reviews: This product is very old as it will not work properly due to corrosion from batteries erupting. I will be asking for a refund. Oh they do not offer r refunds. DO NOT BUY FROM THIS STORE!
Category: wireless
A: | False | 4 | NIv2 | task1308_amazonreview_category_classification | zs_opt | [
-0.5934267044067383,
0.5577496290206909,
-0.18528614938259125,
-0.7226516604423523,
-0.2064027190208435,
-0.13553866744041443,
0.49652329087257385,
0.6823381185531616,
-0.020261263474822044,
0.5153741240501404,
-0.7170102596282959,
0.27495020627975464,
-0.5355533361434937,
0.04511063545942... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given an input list A. You need to find all the elements of the list that are numbers in the same order as they appear in the list A.
['a', 'R', 's', '2921', 'd', '3211', 'k', '9271', 'P', 'I', 'T', 'p', '1127', 'i', 'Y', '6635', '879', '61', 'K', 'Z', 'a', '4381', 'H', '8675', '8019', 'I', '107', '7133', 'k']
Output: | 2921, 3211, 9271, 1127, 6635, 879, 61, 4381, 8675, 8019, 107, 7133 | 1 | NIv2 | task497_extract_all_numbers_from_list_in_order | zs_opt | [
-0.31416523456573486,
0.5087642669677734,
-0.7112981081008911,
0.0038867269176989794,
-0.5066343545913696,
-0.20064976811408997,
0.32141411304473877,
-0.3609585762023926,
-0.1356353908777237,
0.42334485054016113,
-1.0554652214050293,
-0.28268879652023315,
0.2813643515110016,
0.091864340007... |
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: Ditemi tre cose di voi stessi prima della prossima fermata.
Student: | バス停に着く前にあなたについて３つの事を教えて下さい | 6 | NIv2 | task1248_ted_translation_it_ja | zs_opt | [
-0.17041324079036713,
-0.08062543720006943,
-0.12573257088661194,
-0.4147800803184509,
-0.07336796820163727,
-0.16053858399391174,
0.3169752359390259,
0.3236720561981201,
-0.1782093346118927,
-0.28542107343673706,
-0.30024001002311707,
0.01497263927012682,
-0.10229804366827011,
-0.36591124... |
In this task, based on the given context word, you are asked to create a pair of sentences each containing a blank (_). The sentence pair should look similar and should be about two different persons (PersonX and PersonY). Additionally, the two sentences must be different in terms of trigger words (e.g., "sympathetic" and "stern") which express contrasting attributes about the two persons. The answer to the first and the second sentence must be PersonX and PersonY, respectively. PersonX and PersonY should not be equally likely to fill the blank. For each sentence, there should be an agreed upon answer to fill in the blank. Your generations should NOT contain potentially explicit, offensive, or adult content. Do not use the names of real people (e.g., Donald Trump, Putin, etc.) in your sentences. Avoid repeating the same style or phrase in twin sentences e.g., a contrasting sentence can always be created using simple negation i.e. by adding not, never, etc. Instead, try to increase diversity. Both twin sentences must contain at least 15 and at most 30 words. Twin sentences must have at least 70% overlapping words. You must utilize the given context word while writing the twin sentences. Each of the twin sentences must contain only one blank. Make sure that PersonX and PersonY have the same gender. In each sentence, PersonX and PersonY should be used only ONCE and PersonX should appear earlier than PersonY.
[EX Q]: Context Word: backyard.
[EX A]: Sentence 1: PersonX did not have a large backyard like PersonY did because _ lived in an apartment.
Sentence 2: PersonX did not have a large backyard like PersonY did because _ lived in a house.
[EX Q]: Context Word: MBA.
[EX A]: Sentence 1: PersonX went on to get an MBA after college, while PersonY did not, because _ was granted a loan for school.
Sentence 2: PersonX went on to get an MBA after college, while PersonY did not, because _ was denied a loan for school.
[EX Q]: Context Word: issues.
[EX A]: | Sentence 1: PersonX had a lot of issues that PersonY was tired of dealing with, so _ felt abandoned when they finally moved out.
Sentence 2: PersonX had a lot of issues that PersonY was tired of dealing with, so _ felt relieved when they finally moved out.
| 6 | NIv2 | task030_winogrande_full_person | fs_opt | [
0.09171885251998901,
0.431431382894516,
0.027370009571313858,
-0.34857794642448425,
0.3310912251472473,
-0.4748888611793518,
0.7260158061981201,
0.8737084865570068,
-0.057157065719366074,
-0.500442624092102,
-0.5591588020324707,
-0.12316098064184189,
-0.5954918265342712,
0.054657943546772,... |
In this task, you are given a text of article and corresponding title of an article. Your task is to generate label "yes" if headline (title) is right for article, otherwise generate "no".
[Q]: Article: lawyers for the only `` enemy combatant '' jailed in the united states without trial on friday asked the supreme court to examine whether the government has the right to detain indefinitely terror suspects captured on us soil . Title: us high court asked to examine case of qatari terror suspect
[A]: yes
[Q]: Article: banking stocks in frankfurt soared on friday as the dax moved higher on news that washington is looking to create a new body to rescue troubled financial firms and end the recent turmoil . Title: new zealand shares rise #.## percent
[A]: no
[Q]: Article: thousands of balinese in traditional outfits rallied on the indonesian holiday island wednesday against an anti-pornography bill derided by critics as a threat to local cultures . Title: thousands of balinese rally against indonesian anti-porn bill
[A]: | yes
| 5 | NIv2 | task289_gigaword_summarization | fs_opt | [
-0.19628772139549255,
0.6460088491439819,
-0.49332138895988464,
0.2894733250141144,
-0.22227060794830322,
-0.20710518956184387,
1.0230854749679565,
0.28461527824401855,
-0.21624407172203064,
0.15817075967788696,
-0.7291579842567444,
0.7329082489013672,
-1.1735248565673828,
-0.0856619700789... |
Given the task definition and input, reply with output. In this task, you are presented with a term, a question, and a yes/no answer. For context, the term is associated with a short description. Write the simple facts one needs to know in order to answer the given question. The facts should be easily found on the web (e.g. mentioned in a Wikipedia page)
Term: Subway (restaurant), Description: American fast food chain, Question: Was Subway involved in a pedophilia scandal?, Answer:Yes
| Fact1: In 2000, Jared Fogle became a national spokesman for Subway after he lost a lot of weight eating only Subway sandwiches. Fact2: In 2015, Fogle was found guilty of child molestation and possession of child pornography, and Subway terminated its relationship with him. | 5 | NIv2 | task169_strategyqa_sentence_generation | zs_opt | [
-0.663254976272583,
0.4862658381462097,
0.23761337995529175,
0.42226433753967285,
-0.1800869256258011,
-0.08804706484079361,
-0.06654752790927887,
0.6978234052658081,
0.2663690447807312,
0.31844228506088257,
-0.21821874380111694,
-0.08953077346086502,
0.12852084636688232,
-0.55500411987304... |
Given a sentence in Russian, generate a new Russian 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: Если вы умрёте, чтобы написать программу, вы должны ожидать кода.
Answer: Если вы хотите написать либ, вам следует написать код.
Question: Поместить руку в конус может повредить руку.
Answer: Посадить руку в огонь может повредить руку.
Question: Писатель может печатать письменные переводы на оперативной основе.
Answer: | Писатель может печатать письменные задания на принтере.
| 7 | NIv2 | task410_mickey_ru_sentence_perturbation_generation | fs_opt | [
0.05978388711810112,
0.7258473038673401,
0.21827594935894012,
-0.611757755279541,
-0.4103323221206665,
-0.9576288461685181,
0.9017475843429565,
1.357343316078186,
-0.0762222558259964,
0.23737886548042297,
-1.0445032119750977,
-0.3139859437942505,
-0.17339608073234558,
0.9516304731369019,
... |
Given a sentence and two mentions from the text (arguments), indicate a phrase (a verb or noun phrase) that describes the relationship between the provided arguments.
Example: Sentence: 'Harry glanced again at the raw looking thing that trembled and choked in the shadow beneath the distant chair.', Argument/Subject 1: 'Harry', Argument/Subject 2: 'raw looking thing'
Example solution: glance
Example explanation: The sentence contains the generated relationship - glance, mentioned between two subjects - Harry and raw looking thing
Problem: Sentence: 'Bill proudly served his country from 1953-57 in the U.S. Navy .', Argument/Subject 1: 'bill', Argument/Subject 2: 'us navy'
| Solution: serve in | 5 | NIv2 | task676_ollie_relationship_answer_generation | fs_opt | [
-0.2512991428375244,
0.7460430264472961,
0.34816455841064453,
-0.4409911632537842,
-0.15236389636993408,
-0.9830408096313477,
0.4958966374397278,
0.8922830820083618,
0.2903209626674652,
-0.11003261804580688,
-0.44225013256073,
-0.17359328269958496,
-0.277384877204895,
0.42289257049560547,
... |
Instructions: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Input: greater { hop { filter_eq { all_rows ; artist ; andreas lundstedt } ; points } ; hop { filter_eq { all_rows ; artist ; garmarna } ; points } } = true
Output: | select the rows whose artist record fuzzily matches to andreas lundstedt . take the points record of this row . select the rows whose artist record fuzzily matches to garmarna . take the points record of this row . the first record is greater than the second record . | 3 | NIv2 | task110_logic2text_sentence_generation | zs_opt | [
0.34885019063949585,
-0.019537996500730515,
-0.32908838987350464,
0.23102545738220215,
0.029122961685061455,
-0.5219326019287109,
0.4286278784275055,
0.4792023301124573,
0.08267472684383392,
-0.21046800911426544,
-0.45319050550460815,
-0.07239166647195816,
0.22969001531600952,
0.4940068125... |
Given the task definition and input, reply with output. You are given a sentence in Polish. Your job is to translate the Polish sentence into Italian.
To nie jest szalone, to się już dzieje.
| Non è folle; di fatto sta succedendo proprio ora. | 5 | NIv2 | task1262_ted_translation_pl_it | zs_opt | [
-0.022587019950151443,
1.2651727199554443,
0.11179954558610916,
0.1572803407907486,
-0.5261512398719788,
0.14501909911632538,
0.7024060487747192,
0.26563143730163574,
-0.1851201355457306,
-0.34207189083099365,
0.16874445974826813,
0.3611150085926056,
-0.44895780086517334,
-0.12263495475053... |
In this task, you are given a sentence. You are expected to recognize the name of gene or protein. Although there might be several correct answers, you need to write one of them.
Let me give you an example: Sox - 4 is important for very early B - cell differentiation , while TCF - 1 / LEF - 1 play a crucial role in early thymocyte development
The answer to this example can be: TCF - 1
Here is why: The gene, TCF - 1 has been tagged as protein since it plays a crucial role in early thymocyte development.
OK. solve this:
Multifunctional targets of dietary polyphenols in disease: a case for the chemokine network and energy metabolism.
Answer: | chemokine | 8 | NIv2 | task1482_gene_extraction_chemprot_dataset | fs_opt | [
0.025855114683508873,
0.3420681059360504,
-0.8593757748603821,
-0.6808801889419556,
0.07046577334403992,
-0.69097501039505,
0.38405469059944153,
0.6408487558364868,
0.1374589502811432,
-0.6894307136535645,
-0.21418042480945587,
0.02253926545381546,
-0.9038065671920776,
-0.5406184792518616,... |
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