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Given a sentence in the Central Khmer, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
Q: ការផ្ទុះទីពីរកើតឡើងប៉ុន្មាននាទីភ្លាមៗនៅស្ថានីយរថភ្លើងខេនថូនមិនដែលបានបន្សល់រណ្តៅដីក្រហូងដីនៅខាងក្រៅបន្ទប់របស់អ្នកគ្រប់គ្រងស្ថានីយរថភ្លើងនិងទីបីបានកើតឡើងនៅស៊ីវហ្កានហ្កាអេចស្ពេសដែលបានកំពុងចេញដំណើរទៅញ៉ូវឌេលលី។
A:
|
２番目の爆発は数分後にCantonment鉄道駅で起こって駅長室の外に穴を残し、３番目はニューデリーに向けて出発したShivGanga特急で起こった。
|
task1122_alt_khm_ja_translation
|
NIv2
|
zs_opt
| 4
|
train
|
Given a sentence in the Central Khmer, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
Let me give you an example: អ៊ីតាលីបានឈ្នះលើព័រទុយហ្គាល់ 31-5 ក្នុងប៉ូលCនៃពីធីប្រកួតពានរង្វាន់ពិភពលោកនៃកីឡាបាល់ឱបឆ្នាំ2007ដែលប្រព្រឹត្តនៅប៉ាសឌេសប្រីន ក្រុងប៉ារីស បារាំង។
The answer to this example can be: フランスのパリ、パルク・デ・プランスで行われた2007年ラグビーワールドカップのプールCで、イタリアは31対5でポルトガルを下した。
Here is why: The Khamer sentence is correctly converted into Japanese 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.
OK. solve this:
ការប្រកួតអូឌីអាយលើកទីពីរនឹងត្រូវរៀបចំនៅ កីឡាដ្ឋានខោនទ្រីហ្គ្រោន ប្រ៊ីសថុល នៅថ្ងៃទី24 ខែសីហា។
Answer:
|
ＯDＩの第２戦は、８月２４日にブリストルのカントリー・グラウンドで行われる。
|
task1122_alt_khm_ja_translation
|
NIv2
|
fs_opt
| 8
|
train
|
Q: Given a sentence in the Central Khmer, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
មនុស្សយ៉ាងហោចណាស់ 27នាក់បានរងរបួស ហើយភាគច្រើនមានស្នាមមុត និងជាំ។
A:
|
少なくとも27人が怪我をしたが、主に切り傷と打ち身だ。
|
task1122_alt_khm_ja_translation
|
NIv2
|
zs_opt
| 7
|
train
|
Detailed Instructions: Given a sentence in the Central Khmer, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
Q: ថវិកាត្រូវបានគេចាត់ចែងក្នុងប្រតិបត្តិការថ្មីដែលមានការ ចំណាយ9.6ពាន់លានដុល្លានិងដើមទុន2.7ពាន់លានដុល្លាសំរាប់បួនឆ្នាំខាងមុខ។
A:
|
予算はこの先4年間で96億ドルが新しい運営費用に、27億ドルが資本に配分される。
|
task1122_alt_khm_ja_translation
|
NIv2
|
zs_opt
| 9
|
train
|
Teacher: Given a sentence in the Central Khmer, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
Teacher: Now, understand the problem? If you are still confused, see the following example:
អ៊ីតាលីបានឈ្នះលើព័រទុយហ្គាល់ 31-5 ក្នុងប៉ូលCនៃពីធីប្រកួតពានរង្វាន់ពិភពលោកនៃកីឡាបាល់ឱបឆ្នាំ2007ដែលប្រព្រឹត្តនៅប៉ាសឌេសប្រីន ក្រុងប៉ារីស បារាំង។
Solution: フランスのパリ、パルク・デ・プランスで行われた2007年ラグビーワールドカップのプールCで、イタリアは31対5でポルトガルを下した。
Reason: The Khamer sentence is correctly converted into Japanese 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.
Now, solve this instance: វិកគីញូសបានសួរទៅកាន់វិកគីលីកថាហេតុអ្វីពួកគេមិនគ្រាន់តែប្រកាសបញ្ជីនៃគេហទំព័រដែលគេយល់ថាខុសច្បាប់ និងអ្វីផ្សេងទៀតដែលផ្ទុកដោយរូបភាពអាសអាភាសកុមារ ប៉ុន្តែវិកគីលីកបានយល់ថា "វាមិនជាការបង្ហាញដ៏សមរម្យនៃអត្ថបទដែលយើងទទួលបាននោះទេ។"
Student:
|
ウィキニュースはウィキリークスに、なぜ、ただ単に合法的と思うサイトのリストを公表するのではなく、児童ポルノを含むサイトを加えたのかと尋ねたのに対して、ウィキリークスは、「それはわれわれが入手した資料の公平な表現ではない」と感じた。
|
task1122_alt_khm_ja_translation
|
NIv2
|
fs_opt
| 2
|
train
|
Given a sentence in the Central Khmer, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
One example: អ៊ីតាលីបានឈ្នះលើព័រទុយហ្គាល់ 31-5 ក្នុងប៉ូលCនៃពីធីប្រកួតពានរង្វាន់ពិភពលោកនៃកីឡាបាល់ឱបឆ្នាំ2007ដែលប្រព្រឹត្តនៅប៉ាសឌេសប្រីន ក្រុងប៉ារីស បារាំង។
Solution is here: フランスのパリ、パルク・デ・プランスで行われた2007年ラグビーワールドカップのプールCで、イタリアは31対5でポルトガルを下した。
Explanation: The Khamer sentence is correctly converted into Japanese 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.
Now, solve this: ចំនួនមនុស្សចូលរួមក្នុងការបោះឆ្នោតត្រូវបានរាយការមកថាមាន ចំនួនច្រើនជាងហាសិបភាគរយតិចតួច។
Solution:
|
選挙の投票者は50パーセントをわずかに上回ると報告された。
|
task1122_alt_khm_ja_translation
|
NIv2
|
fs_opt
| 6
|
train
|
Definition: Given a sentence in the Central Khmer, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
Input: បង់ក្លាដែសបានសំរេចនូវជ័យជំនះដែលភ្ញាក់ផ្អើលមួយលើអាហ្រ្វិកខាងត្បូង ដោយបញ្ចប់67លើក ក្នុងដំណាក់កាលសូភើ8នៃកីឡាវើលខាប់ នៅពហុកីឡាដ្ឋានព្រូវីឌេន ហ្ស៉ចថនហ្គូយ៉ាណា។
Output:
|
ガイアナ・ジョージタウンのプロビデンス・スタジアムで行われたワールドカップのスーパー8フェーズで、バングラデシュは南アフリカに対し67ランの差をつけ驚きの勝利をつかんだ。
|
task1122_alt_khm_ja_translation
|
NIv2
|
zs_opt
| 2
|
train
|
Given a sentence in the Central Khmer, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
Example input: អ៊ីតាលីបានឈ្នះលើព័រទុយហ្គាល់ 31-5 ក្នុងប៉ូលCនៃពីធីប្រកួតពានរង្វាន់ពិភពលោកនៃកីឡាបាល់ឱបឆ្នាំ2007ដែលប្រព្រឹត្តនៅប៉ាសឌេសប្រីន ក្រុងប៉ារីស បារាំង។
Example output: フランスのパリ、パルク・デ・プランスで行われた2007年ラグビーワールドカップのプールCで、イタリアは31対5でポルトガルを下した。
Example explanation: The Khamer sentence is correctly converted into Japanese 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.
Q: សមាជិកគណៈវិនិឆ្ឆ័យបានផ្ញើរកំណត់ហេតុពីរទៅតុលាការស្រុកសហរដ្ឋអាមេរិក ជេមស៍ ប៊ី. ហ្សាហ្គែល ចាប់តាំងពីការពិភាក្សាចាប់ផ្តើមនៅថ្ងៃពុធ។
A:
|
審議が先週の水曜日に始まってから、陪審は米地方裁判所判事ジェームズ・B・ザゲルに2つの文書を送った。
|
task1122_alt_khm_ja_translation
|
NIv2
|
fs_opt
| 3
|
train
|
Detailed Instructions: Given a sentence in the Central Khmer, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
Problem:គាត់ក៏បានបញ្ជាក់ថា ពួកគេឥលូវនេះមិនមានឧបករណ៍ធន់ធ្ងន់សំរាប់ប្រើបា្រស់បានទេ។
Solution:
|
彼はまた、現在のところ重機を運ぶ手立てがないことを確認した。
|
task1122_alt_khm_ja_translation
|
NIv2
|
zs_opt
| 8
|
test
|
Detailed Instructions: Given a sentence in the Central Khmer, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
Q: : "ទាហានម្នាក់ៗ មិនអាចពាក់អាវពណ៌លឿង និងត្រូវរក្សាឯកសណ្ឋានជាប់ ជំនួសដោយការពាក់ខ្សែបូពណ៌លឿងវិញសំរាប់ការគាំទ្រព្រះមហាក្សត្រ ដែលជាធម្មតាចងជាប់នឹងកាំភ្លើងវែងរបស់គាត់។"
A:
|
「どの兵士も、通常は自分のライフルに結び付けている王への支持の黄色いリボンをつけるのではなく、黄色いシャツを着ることができず制服のままでいました」
|
task1122_alt_khm_ja_translation
|
NIv2
|
zs_opt
| 9
|
validation
|
instruction:
Given an input stream, the objective of this task is to classify whether words in the stream are grammatically correct or not. The input to this task is a stream of words, possibly from captions generated by a speech-to-text engine, and the output is a classification of each word from the labels (reason) = [NO_DIFF (correct), CASE_DIFF (case error), PUNCUATION_DIFF (punctuation error), CASE_AND_PUNCUATION_DIFF (both case and punctuation error), STEM_BASED_DIFF (stem word error), DIGIT_DIFF (digit error), INTRAWORD_PUNC_DIFF (intra-word punctuation error), and UNKNOWN_TYPE_DIFF (an error that does not corrrespond to the previous categories)].
question:
["let's", 'say', "we've", 'got', 'a', 'rectangle', 'draw', 'the', 'rectangle', "there's", 'the', 'rectangle', 'and', 'we', 'have', 'two', 'diagonals', 'across', 'the', 'rectangle', "that's", 'one', 'of', 'them', 'and', 'then', 'we', 'have', 'the', 'other', 'diagonal', 'and', 'this', 'rectangle', 'has', 'a', 'height', 'of', 'H', 'so', 'that', 'distance', 'right', 'there', 'is', 'H', 'and', 'it', 'has', 'a', 'width', 'of', 'W', 'it', 'has', 'a', 'width', 'of', 'W', 'what', "we're", 'going', 'to', 'show', 'in', 'this', 'video', 'is', 'that', 'all', 'of', 'these', 'four', 'triangles', 'have', 'the', 'same', 'area', 'now', 'right', 'when', 'you', 'look', 'at', 'it', 'it', 'might', 'be', 'reasonably', 'obvious', 'that', 'this', 'bottom', 'triangle', 'this', 'bottom', 'triangle', 'right', 'here', 'that']
answer:
['CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_AND_PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF']
question:
["I'd", 'like', 'to', 'start', 'with', 'a', 'simple', 'question', 'why', 'do', 'to', 'poor', 'make', 'so', 'many', 'poor', 'decisions', 'I', 'know', "it's", 'a', 'harsh', 'question', 'but', 'take', 'a', 'look', 'at', 'the', 'data', 'the', 'poor', 'borrow', 'more', 'safe', 'less', 'smoke', 'more', 'exercise', 'less', 'drink', 'more', 'and', 'eat', 'less', 'healthfully', 'why', 'well', 'the', 'standard', 'explanation', 'was', 'once', 'summed', 'up', 'by', 'the', 'briefs', 'Prime', 'Minister', 'Margaret', 'Thatcher', 'and', 'she', 'kept', 'already', 'a', 'personality', 'defect', 'a', 'lack', 'of', 'character', 'basically', 'now', "I'm", 'sure', 'not', 'many', 'of', 'you', 'would', 'be', 'so', 'blunt', 'but', 'the', 'idea', 'that', "there's", 'something', 'wrong', 'with', 'the', 'poor', 'themselves', 'is', 'not', 'restricted', 'to']
answer:
['NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'UNKNOWN_TYPE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'UNKNOWN_TYPE_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_AND_PUNCUATION_DIFF', 'CASE_AND_PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'UNKNOWN_TYPE_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'UNKNOWN_TYPE_DIFF', 'UNKNOWN_TYPE_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'PUNCUATION_DIFF', 'CASE_AND_PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF']
question:
['so', 'today', "we're", 'going', 'to', 'talk', 'about', 'Michaelis', 'Menten', 'kinetics', 'in', 'a', 'steady-state', 'but', 'first', "let's", 'review', 'the', 'idea', 'that', 'enzymes', 'make', 'reactions', 'go', 'faster', 'and', 'that', 'we', 'can', 'divide', 'the', 'enzymes', 'catalysis', 'into', 'two', 'steps', 'first', 'The', 'Binding', 'of', 'enzyme', 'to', 'substrate', 'and', 'second', 'the', 'formation', 'of', 'products', 'and', 'each', 'of', 'these', 'reactions', 'has', 'its', 'own', 'rate', "let's", 'also', 'review', 'the', 'idea', 'that', 'if', 'we', 'keep', 'the', 'concentration', 'of', 'enzyme', 'constant', 'then', 'a', 'really', 'high', 'substrate', 'concentrations', 'will', 'hit', 'the', 'maximum', 'speed', 'for', 'a', 'reaction', 'which', 'we', 'call', 'v-max', 'so', 'first', "we'll", 'talk', 'about', 'the', 'steady', 'state', 'assumption', 'and']
answer:
|
['UNKNOWN_TYPE_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'CASE_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF']
|
task1416_youtube_caption_corrections_incorrect_grammar_classification
|
NIv2
|
fs_opt
| 9
|
train
|
Given an input stream, the objective of this task is to classify whether words in the stream are grammatically correct or not. The input to this task is a stream of words, possibly from captions generated by a speech-to-text engine, and the output is a classification of each word from the labels (reason) = [NO_DIFF (correct), CASE_DIFF (case error), PUNCUATION_DIFF (punctuation error), CASE_AND_PUNCUATION_DIFF (both case and punctuation error), STEM_BASED_DIFF (stem word error), DIGIT_DIFF (digit error), INTRAWORD_PUNC_DIFF (intra-word punctuation error), and UNKNOWN_TYPE_DIFF (an error that does not corrrespond to the previous categories)].
Input: Consider Input: ['relief', 'printmaking', 'the', 'first', 'print', 'process', 'invented', 'had', 'its', 'origins', 'and', 'seals', 'in', 'China', 'around', '255', 'BC', 'if', 'you', 'think', 'of', 'relief', 'printmaking', 'as', 'a', 'stamp', 'which', 'is', 'a', 'very', 'basic', 'transfer', 'of', 'an', 'image', 'from', 'one', 'surface', 'to', 'another', 'that', 'is', 'the', 'initial', 'concept', 'of', 'relief', 'printmaking', 'the', 'image', 'area', 'is', 'raised', 'whereas', 'the', 'non', 'image', 'area', 'is', 'lowered', 'so', 'if', 'you', 'think', 'of', 'a', 'plank', 'of', 'wood', 'and', 'you', 'carve', 'away', 'the', 'white', 'areas', 'what', 'is', 'raised', 'would', 'become', 'the', 'image', 'area', 'one', 'of', 'the', 'modern', 'inventions', 'linoleum', 'for', 'what', 'we', 'call', 'a', 'linocut', 'or', 'linoleum', 'cut', 'provided']
Output: ['CASE_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'UNKNOWN_TYPE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF']
Input: Consider Input: ["we're", 'told', 'given', 'G', 'of', 'X', 'is', 'equal', 'to', '10', 'of', 'X', 'minus', '3', 'PI', 'over', '2', 'plus', '6', 'find', 'a', 'G', 'inverse', 'of', 'X', 'and', 'they', 'want', 'us', 'to', 'type', 'that', 'in', 'here', 'and', 'then', 'they', 'also', 'want', 'us', 'to', 'figure', 'out', 'what', 'is', 'the', 'domain', 'of', 'G', 'inverse', 'the', 'domain', 'of', 'G', 'inverse', 'of', 'X', 'so', "I've", 'got', 'my', 'little', 'scratch', 'pad', 'here', 'to', 'try', 'to', 'work', 'that', 'through', 'so', "let's", "let's", 'figure', 'out', 'what', 'G', 'inverse', 'of', 'X', 'is', 'this', 'is', 'G', 'of', 'X', 'so', 'G', 'inverse', 'of', 'X', "I'm", 'essentially', 'let', 'me', 'just', 'write', 'this', 'is']
Output: ['UNKNOWN_TYPE_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF', 'NO_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'DIGIT_DIFF', 'NO_DIFF', 'CASE_DIFF', 'NO_DIFF', 'DIGIT_DIFF', 'CASE_DIFF', 'NO_DIFF', 'DIGIT_DIFF', 'NO_DIFF', 'DIGIT_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'CASE_DIFF', 'NO_DIFF', 'CASE_AND_PUNCUATION_DIFF', 'NO_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'UNKNOWN_TYPE_DIFF', 'NO_DIFF', 'NO_DIFF']
Input: Consider Input: ['well', 'welcome', 'to', 'the', 'third', 'in', 'the', 'series', 'of', 'algebra', 'of', 'age', 'word', 'problems', 'and', 'I', 'just', 'wanted', 'to', 'start', 'off', 'where', 'I', 'left', 'off', 'in', 'the', 'second', 'one', 'I', 'got', 'myself', 'confused', 'you', 'guys', 'make', 'me', 'very', 'nervous', 'while', 'you', 'just', 'sit', 'there', 'and', 'listening', 'and', 'I', 'have', 'to', 'perform', 'for', 'you', 'but', 'it', 'turns', 'out', 'we', 'did', 'get', 'the', 'right', 'answer', 'if', 'you', 'say', 'armand', 'is', '153', 'andthe', 'rouge', 'is', '765', 'then', '85', 'years', 'ago', 'armand', 'would', 'have', 'been', '68', 'and', 'Tharu', 'should', 'have', 'been', '680', 'and', 'that', 'notice', "that's", '10', 'times', 'so', 'it', 'worked', 'out', 'so', "we're"]
|
Output: ['NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'UNKNOWN_TYPE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_AND_PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'UNKNOWN_TYPE_DIFF', 'NO_DIFF', 'NO_DIFF', 'UNKNOWN_TYPE_DIFF', 'UNKNOWN_TYPE_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'UNKNOWN_TYPE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'UNKNOWN_TYPE_DIFF', 'UNKNOWN_TYPE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF']
|
task1416_youtube_caption_corrections_incorrect_grammar_classification
|
NIv2
|
fs_opt
| 2
|
train
|
Instructions: Given an input stream, the objective of this task is to classify whether words in the stream are grammatically correct or not. The input to this task is a stream of words, possibly from captions generated by a speech-to-text engine, and the output is a classification of each word from the labels (reason) = [NO_DIFF (correct), CASE_DIFF (case error), PUNCUATION_DIFF (punctuation error), CASE_AND_PUNCUATION_DIFF (both case and punctuation error), STEM_BASED_DIFF (stem word error), DIGIT_DIFF (digit error), INTRAWORD_PUNC_DIFF (intra-word punctuation error), and UNKNOWN_TYPE_DIFF (an error that does not corrrespond to the previous categories)].
Input: ['okay', 'so', 'the', 'term', 'carbohydrate', 'refers', 'to', 'a', 'chemical', 'compound', 'made', 'up', 'of', 'carbon', 'atoms', 'that', 'are', 'fully', 'hydrated', 'so', 'carbo', 'for', 'carbon', 'and', 'hydrate', 'for', 'hydration', 'or', 'or', 'water', 'and', 'because', 'these', 'biological', 'molecules', 'are', 'our', 'hydrates', 'of', 'carbon', 'you', 'can', 'find', 'them', 'fitting', 'into', 'the', 'general', 'formula', 'C', 'so', 'a', 'number', 'of', 'carbon', 'atoms', 'so', 'in', 'for', 'just', 'kind', 'of', 'a', 'generic', 'number', 'of', 'carbon', 'atoms', 'and', 'then', 'a', 'matching', 'number', 'of', 'water', 'molecules', 'so', 'h2o', 's', 'usually', 'in', 'the', 'in', 'the', 'exact', 'same', 'number', 'as', 'as', 'your', 'carbon', 'atoms', 'and', 'because', 'all', 'of', 'these', 'carbons', 'kind', 'of']
Output:
|
['UNKNOWN_TYPE_DIFF', 'UNKNOWN_TYPE_DIFF', 'CASE_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'CASE_DIFF', 'UNKNOWN_TYPE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF']
|
task1416_youtube_caption_corrections_incorrect_grammar_classification
|
NIv2
|
zs_opt
| 3
|
train
|
Given an input stream, the objective of this task is to classify whether words in the stream are grammatically correct or not. The input to this task is a stream of words, possibly from captions generated by a speech-to-text engine, and the output is a classification of each word from the labels (reason) = [NO_DIFF (correct), CASE_DIFF (case error), PUNCUATION_DIFF (punctuation error), CASE_AND_PUNCUATION_DIFF (both case and punctuation error), STEM_BASED_DIFF (stem word error), DIGIT_DIFF (digit error), INTRAWORD_PUNC_DIFF (intra-word punctuation error), and UNKNOWN_TYPE_DIFF (an error that does not corrrespond to the previous categories)].
[Q]: ['use', 'the', 'commutative', 'law', 'of', 'multiplication', 'the', 'commutative', 'law', 'of', 'multiplication', 'to', 'write', '2', 'times', '34', 'in', 'a', 'different', 'way', 'simplify', 'both', 'expressions', 'to', 'show', 'that', 'they', 'have', 'identical', 'results', 'so', 'once', 'again', 'this', 'commutative', 'law', 'just', 'means', 'that', 'order', "doesn't", 'matter', 'it', 'sounds', 'very', 'fancy', 'commutative', 'law', 'of', 'multiplication', 'but', 'all', 'that', 'says', 'is', '', 'it', "doesn't", 'matter', 'whether', 'we', 'do', '2', 'times', '34', 'or', 'whether', 'we', 'do', '34', 'times', '2', 'the', 'order', 'does', 'not', 'matter', 'we', 'can', 'commute', 'the', 'two', 'terms', 'this', 'shall', 'both', 'of', 'these', 'are', 'going', 'to', 'get', 'you', 'the', 'same', 'exact', 'answer', 'so', "let's", 'try']
[A]: ['NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF']
[Q]: ["I'm", 'a', 'textile', 'artist', 'most', 'widely', 'known', 'for', 'starting', 'the', 'yarn-bombing', 'movement', 'yarn', 'mommy', 'is', 'when', 'you', 'take', 'knitted', 'or', 'crocheted', 'material', 'out', 'into', 'the', 'urban', 'environment', 'graffiti', 'style', 'or', 'more', 'specifically', 'without', 'permission', 'and', 'unsanctioned', 'but', 'when', 'I', 'started', 'this', 'over', '10', 'years', 'ago', 'I', "didn't", 'have', 'a', 'word', 'for', 'it', 'I', "didn't", 'have', 'any', 'ambitious', 'notions', 'about', 'it', 'I', 'had', 'no', 'visions', 'of', 'grandeur', 'all', 'I', 'wanted', 'to', 'see', 'was', 'something', 'warm', 'and', 'fuzzy', 'and', 'human-like', 'on', 'the', 'cold', 'steel', 'gray', 'facade', 'that', 'I', 'looked', 'at', 'every', 'day', 'so', 'I', 'wrapped', 'the', 'door', 'handle', 'I', 'call', 'this', 'the']
[A]: ['NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'UNKNOWN_TYPE_DIFF', 'UNKNOWN_TYPE_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF']
[Q]: ['if', 'we', 'wanted', 'to', 'find', 'the', 'mass', 'of', 'one', 'atom', 'of', 'carbon-12', 'right', 'one', 'chemistry', 'class', 'we', 'put', 'things', 'on', 'a', 'balance', 'so', 'just', 'use', 'your', 'imagination', 'here', 'and', 'pretend', 'like', 'you', 'could', 'take', 'one', 'atom', 'of', 'carbon', 'and', 'put', 'it', 'on', 'this', 'tiny', 'little', 'balance', 'here', 'so', 'we', 'have', 'this', 'tiny', 'balance', "it's", 'going', 'to', 'give', 'us', 'the', 'mass', 'of', 'our', 'carbon-12', 'atom', 'and', 'normally', 'in', 'chemistry', 'we', 'measure', 'things', 'in', 'grams', 'right', 'so', 'you', 'could', 'just', 'imagine', 'getting', 'a', 'number', 'in', 'grams', 'and', 'since', 'atoms', 'are', 'extremely', 'small', 'this', 'number', 'would', 'be', 'extremely', 'small', 'and', "it's", 'annoying', 'to']
[A]:
|
['NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'UNKNOWN_TYPE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'UNKNOWN_TYPE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF']
|
task1416_youtube_caption_corrections_incorrect_grammar_classification
|
NIv2
|
fs_opt
| 5
|
train
|
Detailed Instructions: Given an input stream, the objective of this task is to classify whether words in the stream are grammatically correct or not. The input to this task is a stream of words, possibly from captions generated by a speech-to-text engine, and the output is a classification of each word from the labels (reason) = [NO_DIFF (correct), CASE_DIFF (case error), PUNCUATION_DIFF (punctuation error), CASE_AND_PUNCUATION_DIFF (both case and punctuation error), STEM_BASED_DIFF (stem word error), DIGIT_DIFF (digit error), INTRAWORD_PUNC_DIFF (intra-word punctuation error), and UNKNOWN_TYPE_DIFF (an error that does not corrrespond to the previous categories)].
See one example below:
Problem: ['hey', 'everybody', 'ivan', 'from', 'weights', 'and', 'biases', 'here', 'in', 'this', 'video', "i'd"]
Solution: ['CASE_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'CASE_DIFF', 'UNKNOWN_TYPE_DIFF', 'CASE_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF']
Explanation: This sentence is a good example since the input stream is a grammatically incorrect statement and the output labels correctly classify the words that were incorrect.
Problem: ['in', 'this', 'video', "we're", 'going', 'to', 'think', 'about', 'how', 'fractions', 'can', 'be', 'used', 'to', 'represent', 'things', 'in', 'the', 'real', 'world', 'so', 'here', "we're", 'told', 'that', 'on', 'the', 'Sharks', 'dive', 'team', 'there', 'are', 'three', 'divers', 'in', 'third', 'grade', 'there', 'are', 'eight', 'total', 'divers', 'on', 'the', 'team', 'what', 'fraction', 'of', 'sharks', 'dive', 'team', 'is', 'in', 'third', 'grade', 'so', 'pause', 'this', 'video', 'and', 'see', 'if', 'you', 'can', 'figure', 'that', 'out', 'alright', 'so', 'first', 'of', 'all', 'they', 'tell', 'us', 'there', 'are', 'eight', 'total', 'divers', 'on', 'the', 'team', 'so', 'maybe', "I'll", 'represent', 'each', 'diver', 'with', 'a', 'little', 'circle', 'like', 'this', "I'll", 'try', 'to', 'make', 'it']
Solution:
|
['NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF']
|
task1416_youtube_caption_corrections_incorrect_grammar_classification
|
NIv2
|
fs_opt
| 4
|
train
|
Given an input stream, the objective of this task is to classify whether words in the stream are grammatically correct or not. The input to this task is a stream of words, possibly from captions generated by a speech-to-text engine, and the output is a classification of each word from the labels (reason) = [NO_DIFF (correct), CASE_DIFF (case error), PUNCUATION_DIFF (punctuation error), CASE_AND_PUNCUATION_DIFF (both case and punctuation error), STEM_BASED_DIFF (stem word error), DIGIT_DIFF (digit error), INTRAWORD_PUNC_DIFF (intra-word punctuation error), and UNKNOWN_TYPE_DIFF (an error that does not corrrespond to the previous categories)].
Q: ['welcome', 'and', 'thanks', 'for', 'joining', 'me', 'on', 'this', "let's", 'call', 'it', 'a', 'voyage', 'of', 'the', 'mind', 'so', 'before', 'we', 'begin', 'posture', 'and', 'breathing', 'make', 'a', 'big', 'difference', 'in', 'meditation', 'so', 'if', "you're", 'not', 'already', 'on', 'a', 'nice', 'firm', 'chair', 'with', 'your', 'back', 'straight', 'pause', 'this', 'recording', 'and', 'go', 'find', 'a', 'nice', 'firm', 'chair', 'with', 'your', 'back', 'straight', 'ideally', 'in', 'a', 'place', "that's", 'kind', 'of', 'quiet', 'and', 'peaceful', 'so', 'now', 'that', "you're", 'there', 'sit', 'with', 'your', 'back', 'straight', 'try', 'to', 'put', 'your', 'feet', 'firmly', 'on', 'the', 'floor', 'when', 'I', 'do', 'this', 'I', 'like', 'to', 'rest', 'my', 'hands', 'on', 'my', 'lap', 'palms']
A:
|
['NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF']
|
task1416_youtube_caption_corrections_incorrect_grammar_classification
|
NIv2
|
zs_opt
| 4
|
train
|
Given an input stream, the objective of this task is to classify whether words in the stream are grammatically correct or not. The input to this task is a stream of words, possibly from captions generated by a speech-to-text engine, and the output is a classification of each word from the labels (reason) = [NO_DIFF (correct), CASE_DIFF (case error), PUNCUATION_DIFF (punctuation error), CASE_AND_PUNCUATION_DIFF (both case and punctuation error), STEM_BASED_DIFF (stem word error), DIGIT_DIFF (digit error), INTRAWORD_PUNC_DIFF (intra-word punctuation error), and UNKNOWN_TYPE_DIFF (an error that does not corrrespond to the previous categories)].
--------
Question: ['all', 'right', 'so', "here's", 'our', 'motor', 'and', '', 'we', 'talked', 'about', 'all', '', 'the', 'different', 'components', 'in', 'the', 'motor', 'and', 'how', 'they', 'work', 'so', "I'm", 'going', 'to', 'try', 'and', 'and', 'talk', 'about', 'our', 'motor', 'that', 'we', 'made', 'here', 'and', 'show', 'you', 'how', "it's", 'similar', 'to', 'the', 'motor', 'that', 'we', 'have', 'here', 'so', 'these', 'are', 'our', 'permanent', 'magnets', 'so', 'they', 'are', 'just', 'like', "they're", 'behaving', 'just', 'like', 'this', 'guy', 'which', 'is', 'the', 'permanent', 'magnet', 'in', 'our', 'hairdryer', 'motor', 'and', "they're", "they're", 'both', 'opposing', 'poles', 'so', 'this', 'is', 'North', 'Pole', 'and', 'this', 'is', 'a', 'South', 'Pole', 'magnet', 'and', 'so', 'that', 'if', 'you']
Answer: ['NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'UNKNOWN_TYPE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'UNKNOWN_TYPE_DIFF', 'CASE_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF']
Question: ["we're", 'on', 'problem', '99', 'and', 'I', 'like', 'these', 'that', "don't", 'have', 'a', 'lot', 'of', 'words', 'in', 'them', 'M', 'does', 'not', 'equal', 'end', 'we', 'have', 'to', 'prove', 'that', 'is', 'it', 'true', 'that', 'M', 'does', 'not', 'equal', 'n', 'statement', 'number', 'one', 'says', 'that', 'M', 'plus', 'n', 'is', 'less', 'than', 'zero', 'well', "let's", 'see', 'what', 'does', 'this', 'tell', 'us', 'this', 'just', 'tells', 'us', 'that', 'M', 'is', 'less', 'than', 'negative', '', 'and', '', 'it', 'still', "doesn't", 'tell', 'us', 'anything', 'I', 'mean', 'you', 'know', 'maybe', 'negative', 'n', 'maybe', 'negative', 'n', 'is', 'well', "let's", 'say', 'if', 'M', 'is', 'equal', 'to', 'n', 'which', 'is', 'equal', 'to', '10']
Answer: ['CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'UNKNOWN_TYPE_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'DIGIT_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'DIGIT_DIFF', 'CASE_AND_PUNCUATION_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF']
Question: ['welcome', 'to', 'the', 'presentation', 'on', 'solving', 'inequalities', 'or', 'I', 'guess', "you'd", 'call', 'them', 'algebraic', 'inequalities', 'so', "let's", 'get', 'started', 'if', 'I', 'were', 'to', 'toll', 'tell', 'you', 'that', 'well', "let's", 'just', 'say', 'X', 'is', 'greater', 'than', 'five', 'all', 'right', 'so', 'X', 'could', 'be', 'five', 'point', 'zero', 'one', 'it', 'could', 'be', 'five', 'point', 'five', 'it', 'could', 'be', 'a', 'million', 'it', 'just', "can't", 'be', 'four', 'or', 'three', 'or', 'zero', 'or', 'negative', 'eight', 'and', 'actually', 'just', 'just', 'for', 'convenience', "let's", 'actually', 'draw', 'that', 'on', 'the', 'number', 'line', "that's", 'the', 'number', 'line', 'and', 'if', 'this', 'is', '5', 'X', "can't", 'be', 'equal', 'to', '5', 'so', 'we']
Answer:
|
['CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'UNKNOWN_TYPE_DIFF', 'NO_DIFF', 'NO_DIFF', 'STEM_BASED_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'DIGIT_DIFF', 'NO_DIFF', 'DIGIT_DIFF', 'NO_DIFF', 'DIGIT_DIFF', 'NO_DIFF', 'NO_DIFF', 'DIGIT_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF']
|
task1416_youtube_caption_corrections_incorrect_grammar_classification
|
NIv2
|
fs_opt
| 7
|
train
|
Q: Given an input stream, the objective of this task is to classify whether words in the stream are grammatically correct or not. The input to this task is a stream of words, possibly from captions generated by a speech-to-text engine, and the output is a classification of each word from the labels (reason) = [NO_DIFF (correct), CASE_DIFF (case error), PUNCUATION_DIFF (punctuation error), CASE_AND_PUNCUATION_DIFF (both case and punctuation error), STEM_BASED_DIFF (stem word error), DIGIT_DIFF (digit error), INTRAWORD_PUNC_DIFF (intra-word punctuation error), and UNKNOWN_TYPE_DIFF (an error that does not corrrespond to the previous categories)].
['the', 'other', 'day', 'one', 'of', 'the', 'pediatric', 'cardiology', 'doctors', 'was', 'joking', 'around', 'with', 'me', "we're", 'talking', 'about', "Epstein's", 'anomaly', 'he', 'said', 'I', 'say', "Epstein's", 'and', 'you', 'say', 'and', 'answer', 'is', 'the', 'lithium', 'so', 'in', 'the', 'minds', 'of', 'a', 'lot', 'of', 'students', 'when', "you're", 'taking', 'tests', "Epstein's", 'and', 'lithium', 'always', 'go', 'together', 'so', 'the', 'theory', 'is', 'that', 'mothers', 'who', 'take', 'lithium', 'which', 'is', 'a', 'drug', 'to', 'treat', 'bipolar', 'disorder', "that's", 'what', 'leads', 'to', 'their', 'children', 'having', "Epstein's", 'the', 'effect', 'when', 'their', 'they', 'develop', 'that', 'in', 'the', 'uterus', 'according', 'to', 'this', 'doctor', 'I', 'was', 'talking', 'to', 'this', 'is', 'just', 'something', "we've", 'taken']
A:
|
['NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_AND_PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_AND_PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF']
|
task1416_youtube_caption_corrections_incorrect_grammar_classification
|
NIv2
|
zs_opt
| 7
|
train
|
Definition: Given an input stream, the objective of this task is to classify whether words in the stream are grammatically correct or not. The input to this task is a stream of words, possibly from captions generated by a speech-to-text engine, and the output is a classification of each word from the labels (reason) = [NO_DIFF (correct), CASE_DIFF (case error), PUNCUATION_DIFF (punctuation error), CASE_AND_PUNCUATION_DIFF (both case and punctuation error), STEM_BASED_DIFF (stem word error), DIGIT_DIFF (digit error), INTRAWORD_PUNC_DIFF (intra-word punctuation error), and UNKNOWN_TYPE_DIFF (an error that does not corrrespond to the previous categories)].
Input: ['all', 'right', 'so', 'in', 'a', 'previous', 'video', 'I', 'talked', 'about', 'how', 'cyclic', 'monosaccharides', 'like', 'this', 'green', 'the', 'screen', 'cyclic', 'glucose', 'can', 'react', 'with', 'alcohols', 'like', 'this', 'pink', 'alcohol', 'to', 'form', 'asset', 'aisles', 'and', 'key', 'towels', 'and', 'I', 'believe', 'that', 'I', 'mentioned', 'that', 'that', 'sometimes', 'the', 'alcohol', 'that', 'comes', 'in', 'and', 'is', 'reduced', 'is', 'actually', 'another', 'carbohydrate', 'so', 'let', 'me', 'kind', 'of', 'draw', 'this', 'in', 'here', 'and', 'it', 'makes', 'sense', 'because', 'what', 'you', 'see', 'with', 'carbohydrates', 'is', 'that', "they're", 'chock', 'full', 'of', 'hydroxyl', 'groups', "they're", 'chock', 'full', 'of', 'these', 'Oh', 'H', 'groups', 'and', 'and', 'so', 'really', 'they', 'can', 'function', 'really', 'similarly']
Output:
|
['NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'UNKNOWN_TYPE_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF']
|
task1416_youtube_caption_corrections_incorrect_grammar_classification
|
NIv2
|
zs_opt
| 2
|
test
|
Detailed Instructions: Given an input stream, the objective of this task is to classify whether words in the stream are grammatically correct or not. The input to this task is a stream of words, possibly from captions generated by a speech-to-text engine, and the output is a classification of each word from the labels (reason) = [NO_DIFF (correct), CASE_DIFF (case error), PUNCUATION_DIFF (punctuation error), CASE_AND_PUNCUATION_DIFF (both case and punctuation error), STEM_BASED_DIFF (stem word error), DIGIT_DIFF (digit error), INTRAWORD_PUNC_DIFF (intra-word punctuation error), and UNKNOWN_TYPE_DIFF (an error that does not corrrespond to the previous categories)].
Q: ['what', 'I', 'want', 'to', 'do', 'is', 'think', 'a', 'little', 'bit', 'about', 'mom', 'and', 'fetus', 'in', 'terms', 'of', 'oxygen', 'flow', 'and', 'really', 'keep', 'track', 'of', 'the', 'total', 'amount', 'of', 'oxygen', "that's", 'going', 'from', 'mom', 'over', 'to', 'the', 'fetus', 'so', 'to', 'do', 'that', "let's", 'actually', 'refresh', 'our', 'memories', 'in', 'terms', 'of', 'where', 'the', 'oxygen', 'is', 'flowing', 'from', 'and', 'where', "it's", 'going', 'to', 'and', 'remember', 'the', 'fetus', 'has', 'these', 'two', 'umbilical', 'arteries', 'these', 'umbilical', 'arteries', 'are', 'coming', 'off', 'of', 'branches', 'from', 'the', 'internal', 'iliac', 'arteries', 'and', 'these', 'umbilical', 'arteries', 'are', 'actually', 'going', 'through', 'the', 'umbilical', 'cord', 'so', 'this', 'is', 'our', 'umbilical', 'cord', 'down']
A:
|
['CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF']
|
task1416_youtube_caption_corrections_incorrect_grammar_classification
|
NIv2
|
zs_opt
| 9
|
validation
|
I have no experience with a lazy 21 yr old. Both my older children have always been independent. My oldest moved out when she started college and never moved back in after she graduated. My other daughter wanted to move out as soon as she hit 21 but her dad and I gave her some rules or rather instructions she had to follow before she can pack her bags and move in with the boyfriend. 1st she had to show us that she had 3months rent saved up in her savings account. Not just her half of the rent but the whole rent. Which was about $3,600 dollars. You never know if something happens to her or she looses her part time job she can still pay her rent. Nobody wants an eviction on their record. 2nd since she was still going to school and we were paying for it we wanted to see proof every semester that she was enrolled. Education is a big deal to me. 3rd she had to get on BIRTH CONTROL. I don't want any ooops sorry Mom I am pregnant. Now I can't finish school because I have to work full time to pay for my baby.. I was a teen Mom and I didn't get to go to college so it is 100% important that my kids go and finish. She complied with all or requests and is doing remarkable. She has been out on her own for almost 2years . So I'm really don't have any advice to give but maybe if you show a little tough love and give your kid a kick in the pants and tell hi it's time to grow the hell up…. Get a job and pay some rent, or go to school and get an education. No more freeloading around here. Sorry that's all I got…. According to the above context, choose the correct option to answer the following question. Question: Why did the author not finish college? Options: A. not enough information B. She was a teen mother C. She did poorly on her SATs D. She was too old
The answer to this question is:
|
B
|
quail_context_description_question_answer_id
|
P3
|
zs_opt
| 7
|
train
|
Q:I had this one guy, who enjoyed being a part time bully and part time neutral to me. To say the least he was annoying. He'd take the liberty to hide my backpack, borrow my books without consent, doodle scandalous stuff on my notebooks with a pen and yada yada. So one day, I was showing this cool trick I learned on an anatomy program on the TV to a couple of classmates who used to sit around me. The thing was that you can't flex your ring finger upwards if you put your middle finger under the palm (try that) We were all kids, and soon everyone in the class started staring at us weirdos looking laughing at out hands. The bully noticed it too, and came near to inquire about this hand stuff. I described the trick and he was impressed. And then, I saw our teacher walking up the corridor, just a couple paces behind the class door. So, I asked him (the bully) if he wanted to see another trick and to that he nodded a big yes. Cool, What I did was, that I grabbed his right arm by the thumb and put it on my throat right above the larynx. Then I quickly shifted my grip to his wrist. He without batting an eye, asked what I was doing, but then I started beating the desk with my other hand and made squeaking noises while pushing his hand against my throat harder with every turning head. And voilà! Every one in the class (including the teacher) thought he was smothering me. After a few ifs and buts between him and the teacher, he was summoned at the principal’s chambers, from where, later he was sent home, where presumably judging from the look on his face for the next few days, he was beat to crap by his folks. And after that, never was I ever bothered by anyone in the school.(^^) According to the above context, choose the correct option to answer the following question. Question: What happened to the bully at the end? Options: A. He got sent home B. not enough information C. He passed his test D. He got a reward
A:
|
A
|
quail_context_description_question_answer_id
|
P3
|
zs_noopt
| 3
|
train
|
It was a dream, then a place, then a memory. My father built it near the Suwannee River. I like to think it was in the heart of Florida, because it was, and is, in my heart. Its name was Dogland. Some people say you can know others if you know the central incidents that shaped their lives. But an incident is an island in time, and to know the effect of the island on those who land there, you must know something about the river they have traveled. And I must warn you before we begin, I don't know that river well. I visit that time and place like a ghost with poor vision and little memory. I look up the river and see fog rolling in. I look down the river, and the brightness of the approaching day blinds me. I see shapes moving behind me and beyond me, but who they are and what they do, I cannot say. I will tell what I know is true, and I will invent what I believe is true, and that, I think, is all you can ask any storyteller to do. I learned the Nix family history from the stories Pa told. Even at the age of four, I suspected that Pa's stories might not be perfectly true. When Pa said we Nixes came to North America as indentured servants working our way out of debtor's prison, Grandma Bette would make a face and say he couldn't know that. When he said we Nixes had Lakota and Ojibwe blood in our veins, Grandma Bette would say she wasn't prejudiced, but it simply wasn't so: she and Pa and his brothers and sisters were dark because her people were Black Dutch, from a part of Holland where everyone had black hair and black eyes. And then Grandma Bette wouldn't say a word for half an hour or more, a very long time for Grandma Bette to be quiet. According to the above context, choose the correct option to answer the following question. Question: How many brothers Pa had? Options: A. three B. not enough information C. one D. two
B
Alona's persistent knocking at the door of room 412 went unanswered for three minutes as she nervously shuffled her feet. Her book bag was super-saturated with textbooks, notebooks, schedules, rough drafts, and various other forms of academic paraphernalia. It was getting heavier. She continued to knock, even though there had as yet been no answer, because the note card tacked to the right of the door indicated that these indeed were Prof. Turgy K. Sigger's office hours. She could see the light under the door and thought she had heard a groan. Just before she decided to give up, slow feet approached from the opposite side, then silence; with a dramatic turn of the knob, the door swung open. "Was this trip really necessary?" asked Prof. Sigger, blinking and brushing his oily, graying hair back into place. "These are your office hours," Alona replied. She nervously smiled, feeling the corners of her mouth twitch. Somewhere in the darkened hall, a janitor coughed. "All right," conceded Prof. Sigger. "Come in." The carpet was smothered by leaning towers of textbooks. Papers lined the left side of the desk, above which was a small note card which read "To Be Graded." On the right side, the oak finish gleamed of the mid-morning light piercing the Venetian blinds. "You've come about your final project," Prof. Sigger stated. "It's only mid-term," Alona reminded him. "Oh yes, yes," continued Prof. Sigger, without conscious embarrassment. "Mid-term grade. I think I have it here. Somewhere." His hands disappeared into the left side of his desk. "You told the class that we would get a C if we maintained that Coca-Cola isn't a crypto-fascist conspiracy." "Oh yes," said Prof. Sigger. "We were discussing social issues, as I remember. I was quoting Marx and some little idiot brought up Rush Limbaugh." "That was me," Alona muttered. According to the above context, choose the correct option to answer the following question. Question: How long did Alona stand outside of Prof. Sigger's office door before entering? Options: A. an hour B. thirty minutes C. not enough information D. a few minutes
D
*Question*
My partner’s parents decided to help with all the planning and set up for his sister’s wedding. I am sure part of the reason was because they had offered to foot part of the expenses. There came a point in the planning, when his mom seemed to sort of run-amok with her ideas. His sister ended up accepting some plans for her wedding that I don’t think she was really that fond of, but she went along with them anyways. One of the things that stands out the most to me, was this idea that they would make a large wooden box with a hole in it, and people would smash their dinner plates into the box. Then the fragments of the broken plates would be put into metal keepsake tins for the guests to take home. (The tins were cute, the trash inside seemed very weird to me.) So imagine it’s the evening of your wedding reception, and people are in a corner of the room smashing their plates into a box. And then part of your wedding party is supposed to go in the back and fix up the tins of broken ceramic ware. It was like an exercise in how to needlessly generate extra stress hormones in a large room full of people. My partner’s sister looked like she cringed every time someone threw a plate in the box. It is weird (and wasteful) to propose to break brand new plates for a tradition that isn’t even part of your ancestry. It’s weird to railroad the people getting married into accepting to do things they don’t really want. Soon after that, my partner’s mother offered that she would be happy to help us plan and throw our wedding too, just like they did for his sister. I think the experience made us both content to elope. According to the above context, choose the correct option to answer the following question. Question: Who does not want mother to help plan a wedding? Options: A. not enough information B. The brother C. The dad D. The partner
**Answer**
|
A
|
quail_context_description_question_answer_id
|
P3
|
fs_opt
| 4
|
train
|
Please answer the following question: There is no hiding from the impact agenda. The impact weighting of the Research Excellence Framework has been increased for 2021, and more recently the UK Government announced a new funding stream for knowledge exchange. But achieving impact isn’t easy, especially for researchers early in their careers. If you ever have a spare week, or ten, it’s worth reading through some of the 6,637 REF impact case studies on the HEFCE website. There are some brilliant and fascinating examples of how researchers have achieved impact, but what strikes me most is how different impact looks across different subjects. At the risk of being flippant, among many of the medical or technological examples there is a familiar pattern and a clear route to impact: make breakthrough; license drug/technology; save lives/£millions. For social and political science (not to mention economics, languages, education, philosophy, etc.) the route to impact is much more fragmented. Among the 97 sociology case studies, for example, impact comes from numerous briefings of government officials and parliamentarians, before the academics join “networks” and “committees” discussing their research and wider issues. Their research is covered by national media, they meet even more people – practitioners or third sector campaigning organisations to pass on their knowledge. And, after all that, and often a good deal more, sometimes there is a policy or practice change that can be pointed to as a direct impact, sometimes not. Central to much of the impact is “access”. Prominent and experienced academics are more likely to get on the committees, know the right journalists and government officials, and have links into third sector organisations, etc. I worked with Professor Sir John Curtice, of election night fame, for a number of years. He didn’t need much support. I advised and facilitated, but after 30 years in the game he knew Whitehall (and Holyrood) inside and out – and they knew him. But many researchers, especially at the start of their careers, don’t... According to the above context, choose the correct option to answer the following question. Question: Who does the author say can make millions if they make a breakthrough? Options: A. the government B. campaigning organizations C. medical researchers D. not enough information
A:
|
C
|
quail_context_description_question_answer_id
|
P3
|
zs_noopt
| 8
|
train
|
Question: Those of you who are regular readers of Beauty Best Friend will know that I suffer from a very sensitive, itchy scalp and I am constantly on the hunt for haircare products that are natural and non-irritating but that also treat my hair well and leave it feeling soft, shiny and clean. So far my experience has generally shown me that natural, SLS-free shampoos and conditioners do not irritate the scalp as much as their chemical filled cousins, but that they do not always clean the hair as well and can leave it looking and feeling greasy, sad and lifeless. One of the first SLS-free shampoo and conditioners that I tried, back in 2013, was Mild Shampoo and Gentle Conditioner from Naked. The relief that I got from my itchy scalp was almost instant, but I did find that it didn’t remove grease and oil from my hair too well, and I had to wash my hair a lot more often. Since then I’ve tried lots of different SLS-free haircare products, all of which have had their benefits and downfalls. For the past month I have been using Rescue Intensive Care Shampoo & Conditioner from Naked, aimed at frizzy, dry and damaged hair. As I had found such relief from my itchy scalp when using Naked products previously I wanted to try out another variant to see if it cleaned my hair any better. Prior to using the Rescue duo I had been having a really hard time with my scalp, but after just the first use of these natural products the itching had subsided about by 75%. Both the shampoo and conditioner have a lovely rich almond scent which stays on the hair after it is dry. The conditioner is a thick, rich cream and it feels like it is giving dry hair a real treat. Unfortunately these Naked products still don’t clean my hair as well as some other products, and I still feel that my hair can look greasy and lank the day after I’ve washed it. I have tried the ‘reverse poo’ method which helps a bit – this means conditioning your hair first, then shampooing it second – but my hair can get very tangled after the shampooing stage. According to the above context, choose the correct option to answer the following question. Question: The writer believes that: Options: A. natural shampoos scent does not stay on the hair B. chemical shampoos leave hair looking greasy C. not enough information D. natural shampoo is better for the skin but doesn't clean as well
Answer: D
Question: SEOUL — The recent U.S. missile strikes against Syria could increase pressure on North Korea to give up its nuclear weapons, or reinforce in Pyongyang the need for nuclear deterrence. The United States, France and Britain fired 105 missiles at three Syrian chemical weapons facilities on Saturday, in response to an alleged Syrian chemical weapons attack in the city of Douma that killed at least 40 people and wounded or sickened hundreds of others. The Syrian government has repeatedly denied any use of banned weapons. The combined military strike on Syria comes as the administration of U.S. President Donald Trump and the government of North Korean leader Kim Jong Un are preparing for an expected summit in late May or early June to discuss dismantling the North’s nuclear program in exchange for security guarantees. Trump’s willingness to use force against Syria can be seen to reinforce his “maximum pressure” campaign message, that in addition to imposing tough sanctions banning most North Korean exports, the U.S. would take military action, if necessary, to force Kim to terminate his nuclear program and end the continued development of a nuclear armed intercontinental ballistic missile that can reach the U.S. mainland. Calling the U.S. attack on Syria “a warning for Pyongyang,” the South Korean newspaper the Korea Joongang Daily, in an editorial on Monday said, “If Kim wants to be free from the fear of a potential raid, then he must be willing to denuclearize.” From this perspective the U.S. show of force in Syria will increase pressure on the leadership in North Korea to offer meaningful nuclear concessions at the Trump-Kim summit. “Unless it abandons at least part of its nuclear and missile capabilities then the Trump administration will not be satisfied,” said Bong Young-shik, a political analyst with the Yonsei University Institute for North Korean Studies in Seoul However the U.S. military strike on Syria could also reinforce concerns in North Korea that giving up its nuclear deterrent would make the... According to the above context, choose the correct option to answer the following question. Question: Who or what will keep the nuclear program if it thinks that its regime is not guaranteed? Options: A. North Korea B. not enough information C. President Trump D. Syria
Answer: A
Question: The young man (boy, really) played with his fingers in the garish light cast from the lone bulb in the concrete bunker. He scratched at an imaginary itch on his right hand (just below his thumb) to take his mind off the man in the lab coat who sat across from him at the beaten, scarred, wood table. It didn't work. And whoever this man in the lab coat was, he was insistent about paperwork. He had three inches clipped onto a weathered clipboard which he flipped through with precision. "Can I offer you a glass of water?" asked the boy's captor in a calm, sensitive tenor. The boy, Kurt, continued to scratch the imaginary itch, which had leapt magically from his right hand to the left. Eventually the falseness of the itch would be deduced, and the lab coated man would disappear out of the cell and return with... God knows what. He had seen torture hundreds-if not thousands-of times on TV, and he was glumly certain that there would be no commercial breaks for him. "Can I offer you a glass of water?" The question was repeated without urgency, like a forgetful waiter. The itch now leaped with the dexterity of a trained flea onto the boy's leg, and the dutiful fingers followed. He watched as the man in the lab coat, without name tag or company insignia, studied his stack of papers attached to the clipboard. Several yellow forms near the top half inch were labeled 27B. The man frowned and wrote a note on the top page. "Note: Find out who isn't duplicating 27B in Pink." "I'm sorry," he said, "I wasn't listening. Was that a yes or no to the water?" Kurt remained in his chair, almost motionless, except for the itching-and-scratching routine. It had leapt again, this time onto his scalp, and the twitching fingers followed. He wondered how long he could keep this up without drawing blood. According to the above context, choose the correct option to answer the following question. Question: Why was the boy scratching himself? Options: A. because he had an imaginary itch B. not enough information C. because the captor wasn't listening D. because he had too much water
Answer:
|
A
|
quail_context_description_question_answer_id
|
P3
|
fs_opt
| 3
|
train
|
Question: "Sometimes," he said, squatting down by the fire and holding his hands to the open flame, "I think that I hear voices from the other side." "Voices, Sartas?" someone laughed. "And what do these voices say to you, lad?" "Were they women's voices?" asked another, his leering face looming up out of the darkness and into the sallow glow of the firelight. "Perhaps some fair-haired temptress willing to relieve you of the weighty burden of your virginity." More laughter, lecherous in tone, and quickly joined by a chorus of rough and lustful glee, which in the closeness of the dark seemed almost feral and far less than mere jest and honest teasing. "I can't speak as to whether they were male or female," said Sartas, trying hard to keep the tremor of embarrassment from his voice. "But it did sound at times like laughter. Of the sort that good men share about a fire and over a meal." He assayed a grin as he cast his gaze over his colleagues. "No doubt a fiction of the sun," offered Tavarius in a commiserating tone. He sat across from the young guard, idly poking at food on the beaten metal plate that was set at his feet. He skewered a square of meat with the tip of his long knife and lifted it to his lips, holding it poised before his mouth a moment before finally clamping square, yellowed teeth about it and pulling it free with a jerk. "It wasn't the sun," Sartas retorted petulantly. Tavarius shrugged, then wiped a trail of juice from his chin with the back of one hand and said, "Be careful, lad." He waggled the blade of his knife back and forth in the young man's direction, frowning with intense sagacity. "You'd be wise to consider spending less time out there in the heat of day, tramping back and forth as though you were guarding the King's own jewels. All that sweating and panting. And for what?" He snorted and shook his head. "Such devotion may well be admirable in some quarters, boy, but you'll curry no favor here with that sort of attitude." According to the above context, choose the correct option to answer the following question. Question: Why were the men laughing? Options: A. The heat of the sun was making them dizzy. B. They were making fun of Sartas. C. They were sitting around the fire. D. not enough information
Answer: B
Question: Greg stopped by the courthouse concession stand for a cup of coffee, even though he had already downed four cups at Jane's Diner across the street. The old man behind the counter reached for Greg's dollar with a noticeably shaky hand that looked as though it had held more cigarettes and booze than money in its lifetime. He took his coffee and walked up the stairs to the second floor. There were about fifty people standing in the hallway outside the courtroom making small talk. He recognized a few of them, but was in no mood to start a conversation. Only four more jurors and two alternates were needed. With a little luck, he would soon be sent on his way. The coffee tasted bitter, but he continued to sip on it anyway, just to occupy himself. After a few minutes, a woman walked out of the courtroom and spoke to the crowd in monotone. "Good morning, ladies and gentlemen. We are ready to get started. We did not get enough jurors yesterday for the criminal trial, so we are going to use part of today's panel for that purpose. Those who are not selected for the criminal trial today must appear tomorrow at 8:00 AM for the civil trial jury selection. "First, I will call the names of the jurors that have already been selected. When I call your name, please go into the courtroom and take your seat in the pews where you sat yesterday. Please sit in the order in which your names are called." "Alexander Littleton… Gail Silestone… " The crowd carefully analyzed each person as he walked through the group and into the courtroom. "Mary McJohnson… William Biscayne … Judy McPhearson… John Nihmbor… Nancy Novelle… and Troy Blockerman." Greg nearly choked on his coffee. Troy Blockerman! That's Cynthia's husband. His blood pressure shot up like a bottle rocket, exploding into a headache. "And now I will call the names of a portion of today's panel. Those whose names are not called will need to stay here in the courthouse since we might still need you today. I will let you know when you can go home. Again, please sit in the order in... According to the above context, choose the correct option to answer the following question. Question: When did John go the courtroom? Options: A. After he got orange juice B. Before he went to Jane's Dinner C. not enough information D. After he had coffee
Answer: D
Question: WASHINGTON — U.S. President Barack Obama has shortened the sentences of 214 inmates of U.S. federal prisons, in what the White House called the largest batch of commutations on a single day in more than a century. The early release is part of Obama's effort to correct what he views as unreasonably long mandatory minimum sentences. The president's push to lessen the burden on nonviolent drug offenders reflects his long-stated view that the nation should remedy the consequences of decades of onerous sentencing rules, which have put tens of thousands of Americans behind bars for far too long. Among those affected by Wednesday's presidential order were 67 individuals serving life sentences - almost all for nonviolent drug crimes, although a few also were charged with firearms violations related to their drug activities. To date, Obama has granted 562 commutations, more than the previous nine presidents combined, and more clemency actions that by any other president in nearly a century. White House counsel Neil Eggleston said in the White House blog that Obama examines each clemency application on its specific merits to identify the appropriate relief, including whether the prisoner would be helped by additional drug treatment, educational programs or counseling. Presidents tend to use their powers to commute sentences or issue pardons more frequently near the end of their terms of office. Administration officials said the rapid pace will continue before Obama's leaves the White House in January 2017. "We are not done yet," Deputy Attorney General Sally Yates said. "We expect that many more men and women will be given a second chance through the clemency initiative." Obama has long called for phasing out strict sentences for drug offenses, arguing they lead to excessive punishment and incarceration rates unseen in other developed countries. With presidential support, the Justice Department in recent years has directed prosecutors to rein in the use of harsh mandatory minimums. Eggleston once again called on... According to the above context, choose the correct option to answer the following question. Question: When did Obama commute the sentences of the inmates? Options: A. before he became president B. not enough information C. before his presidency ended D. after his presidency ended
Answer:
|
C
|
quail_context_description_question_answer_id
|
P3
|
fs_opt
| 3
|
train
|
Former President Barack Obama unveiled plans for his future presidential library and museum on the south side of Chicago where he raised his family and launched his political career. The designs show a complex of modern buildings, with a library, museum and event center, plus a community garden, a children's play area and possibly an athletic field. "What we want this to be is the world-premiere institution for training young people and leadership to make a difference in their communities, in their countries and in the world," he told the crowd that included Chicago Mayor Rahm Emanuel, his one-time chief of staff. Flanked by drawings and renderings, Obama also announced that he and former first lady Michelle Obama will be donating $2 million to fund a Chicago summer jobs program. The museum, the tallest of the three buildings, will hold exhibition space, public spaces, offices and education and meeting rooms, according to the Obama Foundation. The forum and library buildings are intended to be used for study and foundation programming. Obama said his foundation, which is overseeing the project, is also looking into the possibility of locating a Chicago Public Library branch on the site. Obama said he envisioned recording studios where musicians could help young people work on music, and space for movie directors who could take on community storytelling. The center will also have exhibits with campaign memorabilia and personal artifacts. "Let's face it, we want to see Michelle's dresses," the former president joked. Obama also squashed any notion that the library was ever going to be elsewhere. Multiple locations in three states — Illinois, New York and Hawaii — had initially pitched proposals. "The best things that have happened to me in my life happened in this community," he said. "Although we had a formal bidding process to determine where the presidential library was going to be, the fact of the matter was it had to be right here on the south side of Chicago." According to the above context, choose the correct option to answer the following question. Question: What is true about Obama? Options: A. He is tired of being in the spotlight B. He supports the arts and education C. not enough information D. He hates his hometown
B
WHITE HOUSE — The United States is escalating trans-Atlantic and North American trade tensions, imposing a 25 percent tariff on steel imports and a 10 percent tariff on aluminum imports from the European Union, Canada and Mexico beginning on Friday. The U.S. also negotiated quotas or volume limits on other countries, such as South Korea, Argentina, Australia and Brazil, instead of tariffs, Commerce Secretary Wilbur Ross also told reporters Thursday by telephone. China's foreign ministry said on Friday all countries should protect the normal trade order, when asked about U.S. decision. President Donald Trump said Thursday that the days of the U.S. being taken advantage of in trade deals "are over'" in a harshly worded statement responding to Canadian Prime Minister Justin Trudeau's criticism of new steel and aluminum tariffs. He intensified his criticism of Canada Friday for what he says are the country's "highly restrictive" trade practices. Trump has repeatedly said measures such as tariffs are necessary to protect American jobs and industries in key manufacturing sectors. "The president's actions are about protecting American steel, American aluminum," a White House spokesman, Raj Shah, said on Fox News. "They're critical for national security." But the negative reaction from some of America's most important strategic allies has been quick and fierce. European Union Commissioner Cecilia Malmstrom said shortly after the tariffs took effect they were illegal and the 28-nation bloc would initiate a settlement dispute case with the World Trade Organization. "We can do so. We have the right to do so. I think we must do so, as well, to show that we cannot just take these tariffs and stand silent and we do not accept these kind of imposed illegal tariffs," said Malmstrom. Without elaborating, Malmstrom also said the EU would explore "rebalancing measures," which typically are retaliatory actions. Trudeau called the tariffs "totally unacceptable" and vowed retaliation. "This decision is not only unlawful, but it is... According to the above context, choose the correct option to answer the following question. Question: After the end of this story, Macron probably is Options: A. still young and dashing B. not enough information C. still in the Oval office D. still enjoying a lavish welcome from Trump
A
A few times. Mostly whilst doing this job and trying to help drunk people or assholes. Sadly it's becoming a regular occurrence for crews to be assaulted. My last time was a few days ago and the worst thing about it was watching my crew mate and several police officers curl up laughing. I'll set the scene. Imagine. If you will. A large rather expensive hotel. Then add to that image a rather drunk and buxom young lady who is lying on the floor in a drunken slumber after taking off a lot of her clothes. She was just in her underwear. We were called to look after her. On our arrival she was absolutely fine. Stood up, walked to the stretcher and lay down. Whining about how we were the ' oppressors of society', and other such drivel Because I had the cheek to try and give her a tiny bit of dignity by covering her up with a blanket. She didn't want that. We made it to the ambulance without any hassle and started to do the necessary checks we do on every patient. Blood pressure etc etc when out of the blue she decided that she wanted to release her rather large breasts. Try as I might to give her a little bit of dignity she wasn't interested so we just made sure no one could see inside the ambulance. After a few minutes she calmed down so I put the blanket over her. Something I do for almost every patient. Without warning THWACK. she hit my in the face with her boob. Then. As I reeled from this waiting for my brain to catch up and make sense of everything, THWACK she did it again. Right round the face with a large breast!! I turned around to get some support from my colleagues who were crying. Both my crew mate and the officer. Crying. Neither able to speak……….. I didn't know what to say for a while after that…something my crew mate called 'a blessing' Sigh According to the above context, choose the correct option to answer the following question. Question: When were the crew laughing? Options: A. not enough information B. After the woman's dramatic episode C. Before arriving at the hotel D. Before the woman's dramatic episode
|
B
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quail_context_description_question_answer_id
|
P3
|
fs_opt
| 0
|
train
|
Old Zeke handed Justin his day's worth of mail and looked longingly at the cool shade under the porch, half hoping, half anticipating an invitation to enjoy a cool drink and a few minutes out of the sun. His state-of-the-art mail delivery vehicle, an old green Ford with busted air-conditioning, sometimes elicited sympathy from those along his route, but the ones with beer were the best. However, Justin just looked through his mail and then began watching the sky. "You ever think about gravity?" Justin asked suddenly. "No," admitted Old Zeke, wiping the perspiration from his forehead. Justin sighed a little. "You ever fall off your ladder?" "Well," considered Zeke. Damned if this wasn't a round-about way to offer a fella a drink, but maybe after all this Justin would offer him a beer instead of that watery lemonade he made. "Yeah." "How long did it take you to fall?" Well hell, muttered Old Zeke under his breath. Maybe all those stakes he was driving in had given Justin a touch of the sun. The thought made him consider hauling Justin back to town, although the truck might finish the job the sun had started. "A second or two," Zeke replied. But before he could load Justin into the truck, he figured he would have to collect a few things from the house, and maybe from the fridge he'd collect a few drinks... "That thing up there hasn't fallen a foot in ten minutes or so." Maybe Justin had a small bottle of something tucked away under the... "What thing?" Justin pointed. Zeke shielding his eyes with his hands and looked up. "Oh, that weather balloon?" Justin's expectant face seemed to droop. "That what it is?" "Yep. Looks like it's almost out of helium, the way it's floating so low. Launched 'em myself thirty years ago in the Army." According to the above context, choose the correct option to answer the following question. Question: Zeke is worried that Justin: Options: A. Has heat stroke B. not enough information C. Fell off his ladder D. Has been drinking too much
A
For a moment, Paul wasn't even sure who had walked into the room. Chloe had totally transformed herself since he'd last seen her. She wore a wig for starters, and a very good one. It was light brown and shoulder length. It looked so natural that if he didn't know she had much shorter hair, he would have guessed that she had dyed it. But it was the outfit that made the change. She wore a well-tailored, very professional, gray woman's skirt/blazer combo with a yellow silk blouse. Her wrist sported what looked to Paul's uneducated eye like an expensive and fashionable gold lady's watch from which he thought he detected a glint of diamond. In short, she looked just like the high priced lawyer she was supposed to be. She was certainly the best-dressed person in the room. Chloe reached across the table to shake Greg's hand, stretching forward as she did so. Paul watched Greg glance down at her cleavage while he shook her hand. "I'm Rachel Roth, here on behalf of Mr. Paul Reynolds." "Hi," said Greg. "I'm Greg Driscol, and this is..." "I know the rogues gallery here," said Chloe cutting Greg off and looking around at the assembled board members. "I've learned all about you gentlemen." Marie stood up and shook Chloe's hand. "Marie Cooper, from Johnson, Myers, and Wick," she said. "Nice to meet you," she said. "Ok, we've got the intros down, shall we get on with the dirty business?" "Um, sure," Greg said as he sat back down. "I was just about to turn things over to Marie." The plan was now in action, and so far so good. But Paul knew that this was a crucial moment. Chloe didn't really know the law - just a few points that her friend had helped her out with. She couldn't let the real lawyer take over the meeting. Her dramatic, unexpected entrance had them off guard, and Paul hoped she seized the moment and pressed on. According to the above context, choose the correct option to answer the following question. Question: What does Paul think of Chloe's new look? Options: A. He is doubtful that she can fool others into thinking she is professional B. not enough information C. He is impressed by how dramatically different she looks D. He doesn't think her wig looks real
C
(Q).
The violent ambush that killed five Dallas police officers and wounded seven more could have been a lot worse, the city's police chief says. Dallas Chief of Police David Brown told CNN Sunday that the slain gunman told police negotiators he wanted to "kill white people, especially white officers." Bomb making materials and a journal were found at Johnson's home during a search Friday. "The material were such that it was large enough to have devastating effects throughout our city and our North Texas area," Brown said. Micah Xavier Johnson, 25, was killed by police in the deadly attack Thursday night during a protest against police killings of African American men. Since the shooting deaths of two black men by white police officers over two days last week, protests have been held across the country. Scores of demonstrators have been arrested, with one flash point being the southern city of Baton Rouge, Louisiana, where DeRay McKesson, one of the most prominent activists linked to the police reform protest movement Black Lives Matter, live streamed his own arrest. Police defended his arrest as a matter of public safety, but demonstrators told U.S. news outlets they believe McKesson was targeted. McKesson was freed on bond Sunday afternoon after being charged with obstructing a highway. "I remain disappointed in the Baton Rouge police, who continue to provoke protesters for peacefully protesting. There's a lot of work to be done, with this police department specifically,'' he said. But Louisiana Governor John Bel Edwards disagreed with McKesson's assessment. The governor told a news conference Sunday that he is proud of the state's law enforcement officers, calling their response to the protests "moderate." In the northern city of St. Paul, Minnesota, where a second man, Philando Castile, was shot to death last week by a policeman after a traffic stop for a broken tail light, hundreds of protesters hurled firecrackers, rocks and bottles at police on Saturday. The heavily armed officers used smoke grenades and... According to the above context, choose the correct option to answer the following question. Question: What color shoes was McKesson wearing when he was arrested? Options: A. Red B. Blue C. not enough information D. Green
(A).
|
C
|
quail_context_description_question_answer_id
|
P3
|
fs_opt
| 8
|
train
|
(Question)
Yes. 20 years ago. When I was a lot younger. I was victimised by a gang of bent police men, who arrested me and set me up to get charged with something that I did not do which I believe was connected to other criminals who live in my area, who I believe were connected to a gang of DJ’s who were involved stealing intellectual and copyright works from me (likely their party organisers and drug dealer buddies). I was sent to court and found guilty based on no evidence by a magistrate court judge who was later struck off for corruption after defrauding an old lady of over a million pounds! I was not put in prison for this minor offense but did receive a minor criminal record. This criminal records the same DJ’s and bent ex-police have used to ruin my reputation and career. One of the bent policemen, who incidentally had already been thrown out of the police force for car insurance fraud, even turned up at the uni I went to and spread vicious slander to ruin me there, and in the area that I lived at the time. I was then victimised by the people at the famous college that I went to and all my intellectual and copyright works stolen. Which I note, generated millions for others. Once they made their money and gained credibility on the back of my hard work, innovation and some may say genius, the thieves then did all they could to ruin my reputation in the entertainment industry and in the area that I live. Making my life extremely hard for no more reason than having my work stolen. If I wasn't so tough, and for a few people left who have at least some integrity, I would be dead now, like the rest of their victims. I have lost respect for quite a few people who I used to think were really talented. I now understand where there talent comes from… Shame on them. According to the above context, choose the correct option to answer the following question. Question: How does the author feel about getting her intellectual and copyright works stolen? Options: A. she is very upset B. she is indifferent C. not enough information D. she is forgiving
(Answer)
A
(Question)
Thanks for the A2A Josh: Tough one to reduce to just a single incident but I’ll try. I grew up in North Central Indiana, about 50 miles south of South Bend. It was common to have frequent snow accumulation in the winter and blustery, freezing temps. It seems like this was particularly true during my childhood in the 70’s and 80’s. My family was blue collar through and through. We lived in the heartland in a town of just a few hundred with a sawmill and an on again off again gas station as our only two businesses. My dad worked in a factory for roughly 45 years. He apparently started that job right out of high school. My mom was an incredibly hard worker and Still is to this day. She did factory work, restaurant management and everything in between. It was this Protestant work ethic that led to one of the frequent tasks that my brother and I had to do which was not fun but ultimately was a very good deed. As I said, winters were often snowy and harsh. So my mom would make my brother and me shovel driveways and sidewalks for a couple of elderly residents. We did this of course, after we did our own driveway. Some people had motorized snowblowers but we did not. Standard snow shovels were our tools. I remember us whining about the chore, wishing we could just play in the snow or get out of it altogether. I don’t remember being overly conscious of the relief this provided for our elderly neighbors. I just remember that Mom would be disappointed if we didn’t do a good job. Later in life I would have great appreciation for the things required of me by my parents. Factory work and summer farm jobs helped us learn the value of hard work and would set us on a road to appreciation of future job opportunities that were less taxing. I still remember hating shoveling snow. But I’m forever grateful that I did it. According to the above context, choose the correct option to answer the following question. Question: When did the author appreciate having to shovel snow? Options: A. not enough information B. Later in his life C. As he saw how much it helped his neighbors D. Later at school the next day
(Answer)
B
(Question)
WHITE HOUSE — A day after U.S. President Donald Trump reversed a policy of separating migrant families at the U.S.-Mexico border, the House of Representatives is set to vote Thursday on a pair of immigration bills that address the separations as well as other issues that have divided the country’s major political parties. The outcome of the votes is uncertain. One measure is more hard-line, while the other represents a compromise between the Republican Party’s conservative and moderate wings. The compromise bill includes a provision requiring children and their parents to be detained together if they cross the border illegally. It would also provide $25 billion in funding for Trump’s much-promised border wall, change the existing visa lottery into a merit-based system and provide a path to citizenship for the young undocumented immigrants who came to the United States as children. Republicans hold a majority in both houses of Congress. Party leaders, including President Trump and House Speaker Paul Ryan, have lobbied lawmakers this week in hopes of securing their support for the legislation. “We can enforce our immigration laws without breaking families apart,” Ryan said Wednesday before Trump announced he would sign an executive order to end breaking up families. The president’s policy retreat followed a withering attack by Republican and Democratic officials who characterized the family separations as inhumane. The actions left parents with little or no information about where their children were being taken or when or how they would be reunited. “It’s about keeping families together while at the same time making sure that we have a very powerful, very strong border,” Trump said as he signed the document just before departing the White House for a political rally in the state of Minnesota. Later, at the political rally, the president defended his position saying the executive order he signed hours earlier would not weaken his border strategy: “The border is going to be just as tough as it’s been” despite... According to the above context, choose the correct option to answer the following question. Question: Who claimed that the border would continue to be tough, despite the executive order? Options: A. House Speaker Paul Ryan B. U.S. Attorney General Jeff Sessions C. not enough information D. President Trump
(Answer)
|
D
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quail_context_description_question_answer_id
|
P3
|
fs_opt
| 6
|
test
|
Question: So, I worked with a friend of mine who was a playwright to put together a play to take to the Edinburgh Fringe Festival. It was a three person show, and one of the roles was written specifically for me. Many of the lines were written after we improvised the scenes in my living room as she wrote the piece. Took it to Scotland, where it was quite well received. A year or so later, it was being produced in New York in a much more prestigious setting. I auditioned, was called back a couple times, and got to the play the role again. Fantastic! THEN, it was produced by an even larger theatre. Different producer, different casting director, etc. I went to the open call for it, and the casting director treated me really poorly. It was odd. She looked at my resume and said, “It says you have already played this role.” I said, “Yes, I was fortunate enough to workshop it and originate the role.” She looked at me like I was lying. I mean, shuttled me out the door like I was a crazy woman. Needless to say, I was not called back. And that was okay—(I mean, of course I wanted to do the show with this group of people, but hey, we can’t always get what we want). Fast forward to opening night: my playwright friend invites me to see the show. The actress playing “my” role was fantastic, but they had to change lines in the script that indicated what she looked like, because she was of Hawaiian descent. Again, no big deal…and she was great! What was strange was meeting the director that evening. My friend introduced me as the originator of the role, and the director asked me why I hadn’t auditioned…Overall, it wasn’t a harsh rejection or a terrible story, it was just weird to have been treated like a liar when I was not lying… According to the above context, choose the correct option to answer the following question. Question: How did the casting director react to the actress who originated the role after the play opened? Options: A. She recognized her but pretended she didn't B. She did not recognize her C. She felt hostile towards her D. not enough information
Answer:
|
B
|
quail_context_description_question_answer_id
|
P3
|
zs_opt
| 4
|
validation
|
You will be given a definition of a task first, then some input of the task.
In this task, you are given a country name and you need to return the Top Level Domain (TLD) of the given country. The TLD is the part that follows immediately after the "dot" symbol in a website's address. The output, TLD is represented by a ".", followed by the domain.
Eritrea
Output:
|
.er
|
task1320_country_domain_tld
|
NIv2
|
zs_opt
| 1
|
train
|
Teacher:In this task, you are given a country name and you need to return the Top Level Domain (TLD) of the given country. The TLD is the part that follows immediately after the "dot" symbol in a website's address. The output, TLD is represented by a ".", followed by the domain.
Teacher: Now, understand the problem? Solve this instance: Uganda
Student:
|
.ug
|
task1320_country_domain_tld
|
NIv2
|
zs_opt
| 6
|
train
|
In this task, you are given a country name and you need to return the Top Level Domain (TLD) of the given country. The TLD is the part that follows immediately after the "dot" symbol in a website's address. The output, TLD is represented by a ".", followed by the domain.
Trinidad and Tobago
.tt
Myanmar
.mm
Swaziland
|
.sz
|
task1320_country_domain_tld
|
NIv2
|
fs_opt
| 0
|
train
|
In this task, you are given a country name and you need to return the Top Level Domain (TLD) of the given country. The TLD is the part that follows immediately after the "dot" symbol in a website's address. The output, TLD is represented by a ".", followed by the domain.
Input: Consider Input: Montserrat
Output: .ms
Input: Consider Input: Bermuda
Output: .bm
Input: Consider Input: San Marino
|
Output: .sm
|
task1320_country_domain_tld
|
NIv2
|
fs_opt
| 2
|
train
|
In this task, you are given a country name and you need to return the Top Level Domain (TLD) of the given country. The TLD is the part that follows immediately after the "dot" symbol in a website's address. The output, TLD is represented by a ".", followed by the domain.
East Timor
|
.tp
|
task1320_country_domain_tld
|
NIv2
|
zs_opt
| 0
|
train
|
Teacher: In this task, you are given a country name and you need to return the Top Level Domain (TLD) of the given country. The TLD is the part that follows immediately after the "dot" symbol in a website's address. The output, TLD is represented by a ".", followed by the domain.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Andorra
Solution: .ad
Reason: .ad is the TLD of the country called Andorra.
Now, solve this instance: Sweden
Student:
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.se
|
task1320_country_domain_tld
|
NIv2
|
fs_opt
| 2
|
train
|
In this task, you are given a country name and you need to return the Top Level Domain (TLD) of the given country. The TLD is the part that follows immediately after the "dot" symbol in a website's address. The output, TLD is represented by a ".", followed by the domain.
Example Input: Grenada
Example Output: .gd
Example Input: Macedonia
Example Output: .mk
Example Input: Marshall Islands
Example Output:
|
.mh
|
task1320_country_domain_tld
|
NIv2
|
fs_opt
| 3
|
train
|
In this task, you are given a country name and you need to return the Top Level Domain (TLD) of the given country. The TLD is the part that follows immediately after the "dot" symbol in a website's address. The output, TLD is represented by a ".", followed by the domain.
[Q]: Uruguay
[A]: .uy
[Q]: Vietnam
[A]: .vn
[Q]: American Samoa
[A]:
|
.as
|
task1320_country_domain_tld
|
NIv2
|
fs_opt
| 5
|
train
|
You will be given a definition of a task first, then some input of the task.
In this task, you are given a country name and you need to return the Top Level Domain (TLD) of the given country. The TLD is the part that follows immediately after the "dot" symbol in a website's address. The output, TLD is represented by a ".", followed by the domain.
Qatar
Output:
|
.qa
|
task1320_country_domain_tld
|
NIv2
|
zs_opt
| 1
|
test
|
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 country name and you need to return the Top Level Domain (TLD) of the given country. The TLD is the part that follows immediately after the "dot" symbol in a website's address. The output, TLD is represented by a ".", followed by the domain.
Andorra
Solution: .ad
Why? .ad is the TLD of the country called Andorra.
New input: Western Sahara
Solution:
|
.eh
|
task1320_country_domain_tld
|
NIv2
|
fs_opt
| 0
|
validation
|
TASK DEFINITION: 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.
PROBLEM: Question: What year was the prize that the Assemble collective received first given out? Passage:Nottingham is a research-led institution, and two academics connected with the university were awarded Nobel Prizes in 2003. Clive Granger was jointly awarded the Nobel Prize in Economics. Much of the work on Magnetic Resonance Imaging (MRI) was carried out at Nottingham, work for which Sir Peter Mansfield received the Nobel Prize for Medicine in 2003. Nottingham remains a strong centre for research into MRI. The university has contributed to a number of other significant scientific advances. Frederick Kipping, Professor of Chemistry (1897–1936), made the discovery of silicone polymers at Nottingham. Major developments in the in vitro culture of plants and micropropogation techniques were made by plant scientists at Nottingham, along with the first production of transgenic tomatoes by Don Grierson in the 1980s. Other innovations at the university include cochlear implants for deaf children and the brace-for-impact position used in aircraft. In 2015, the Assemble collective, of which the part-time Architecture Department tutor Joseph Halligan is a member, won the Turner Prize, Europe's most prestigious art award. Other facilities at Nottingham include a 46 teraflop supercomputer.
SOLUTION: b
PROBLEM: Question: Which of Harald's wives was the mother of his son Sweyn? Passage:Gorm's son, Harald Bluetooth succeeded his father as king and married possibly three times with Gunhild, Tove and Gyrid. Harald had a son named Sweyn Forkbeard. Sweyn succeeded his father as king and married Gunhild (Świętosława of Poland). They had a son named Cnut the Great. Sweyn also ruled England in his lifetime and established the Danish Empire. When Sweyn died, his elder son Harald Svendsen became the King of Denmark, while England's former king, Ethelred, reclaimed the throne. Following Harald's death, his brother Cnut the Great became king, re-established the Danish North Sea Empire. He married Emma of Normandy with whom he had a son named Harthacnut. When Cnut died (and after the brothers of Harthacnut also had died), Harthacnut became king of Denmark and England. Upon his death, Edward the Confessor became ruler of England in 1042. Sweyn Forkbeard also had a daughter, Estrid, from whom all ruling kings and queens of Denmark after 1047 descend.
SOLUTION: a
PROBLEM: Question: What were the combined ages of Joseph Urban and Benjamin Wistar Morris the year that they were both hired to come up with blueprints for the house? Passage:The construction of Rockefeller Center occurred between 1932 and 1940 on land that John D. Rockefeller Jr. leased from Columbia University. The Rockefeller Center site was originally supposed to be occupied by a new opera house for the Metropolitan Opera. By 1928, Benjamin Wistar Morris and designer Joseph Urban were hired to come up with blueprints for the house. However, the new building was too expensive for the opera to fund by itself, and it needed an endowment, and the project ultimately gained the support of John D. Rockefeller Jr. The planned opera house was canceled in December 1929 due to various issues, with the new opera house eventually being built at Lincoln Center, opening in 1966.
SOLUTION:
|
a
|
task232_iirc_link_number_classification
|
NIv2
|
fs_opt
| 8
|
train
|
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.
--------
Question: Question: Did Cumberlidge win any championships as part of Northwich Victoria? Passage:Cumberlidge played for Stoke City, before joining Port Vale as an amateur in October 1936. He made his debut in February 1937, and signed professional forms the following month. He made eight Third Division North appearances in the 1936–37 season, and played 23 league games in the 1937–38 season. He featured 35 times in the Third Division South in the 1938–39 campaign. He converted to left-half for the 1939–40 season, having previously been used as a left-back and inside-forward. After the conclusion of World War II, he was out of favour and barely played before he was transferred to Northwich Victoria. He managed the "Vics" in the Cheshire County League in 1968.
Answer: b
Question: Question: When was the building that One Meridian Plaza faced across the street first built? Passage:One Meridian Plaza was a 38-story high-rise office building designed by Vincent Kling & Associates. Construction on the tower began in 1968, was completed in 1972 and approved for occupancy in 1973. Built at the corner of 15th Street and South Penn Square in Center City, Philadelphia, Pennsylvania, the $40 million high-rise was built adjacent to the Girard Trust Building, now the Ritz-Carlton Philadelphia, and the front faced Philadelphia City Hall across the street. It was formerly named Three Girard Plaza (see below). The rectangular building was long and wide and contained . Of the 38 floors, 36 were occupiable and 2 were mechanical floors. The structure also had 3 underground levels. The building's structure was composed of steel and concrete and the facade was a granite curtain wall. There were two helipads on the roof. The building's eastern stairwell connected the building to the adjacent Girard Trust Building, known as Two Girard Plaza. At one point there were plans to build a structure to the south of the building that would share one of the elevator banks in the high-rise, but nothing came of the plans mainly because the two sites had different owners. On the northwest corner of the property is a bronze sculpture called "Triune." Designed by Robert Engman the abstract sculpture was not damaged in the 1991 fire and was still there in 1999. The following year the builders of The Residences at The Ritz-Carlton announced that they were considering demolishing the sculpture. In the end the statue was retained and still stands at the location it was originally installed at as of 2014.
Answer: b
Question: Question: How many games did Millwall lose the season they had 11 consecutive clean sheets in? Passage:In the 1925–26 season Millwall had 11 consecutive clean sheets, a Football League record, which they hold jointly with York City and Reading. Millwall became known as a hard-fighting Cup team and competed in various memorable matches, notably defeating three-time league winners and reigning champions Huddersfield Town 3–1 in the third round of the 1926–27 FA Cup. In the 1927–28 season Millwall won the Third Division South title and scored 87 goals at home in the league, an English record which still stands. Matches against Sunderland and Derby County saw packed crowds of 48,000-plus in the 1930s and 1940s. Their 1937 FA Cup run saw Millwall reach the semi-finals for the third time, and a fifth-round game against Derby still stands as Millwall's record attendance of 48,762. Millwall were the 11th best supported team in England in 1939, despite being in the Second Division. Millwall were one of the most financially wealthy clubs in England. The club proposed plans to improve the Den and signed international players. Winger Reg 'JR' Smith was capped twice, scoring two goals for England in 1938. The Lions were pushing for promotion to the First Division toward the end of the decade, but one week into the 1939–40 season, World War II broke out and Millwall were robbed of their aim.
Answer:
|
b
|
task232_iirc_link_number_classification
|
NIv2
|
fs_opt
| 7
|
train
|
Teacher: 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.
Teacher: Now, understand the problem? If you are still confused, see the following 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,
.
Solution: b
Reason: The passage describes the 704th's actions during Operation Market Garden so only information about the operation is needed.
Now, solve this instance: Question: How old was Stephen Fry when "Me and My Girl" was revised for production at the Leicester Haymarket Theatre? Passage:The musical was revived in 1941, 1945 and 1949 on the West End. Lupino Lane starred and directed each of these productions, with choreography by Fred Leslie. In 1984, a revised production opened at the Leicester Haymarket Theatre with a revised script by Stephen Fry and contributions by director Mike Ockrent. It transferred to the Adelphi Theatre on 12 February 1985 and closed on 16 January 1993 after an eight-year run and 3,303 performances. It starred Robert Lindsay as Bill Snibson, Emma Thompson and Frank Thornton. The production won two Olivier Awards: Musical of the Year and Outstanding Performance by an Actor in a Musical (Robert Lindsay). Cast changes included Enn Reitel as Bill and Su Pollard as Sally in 1986; Gary Wilmot as Bill and Jessica Martin as Sally in 1989. Thornton was succeeded by Nicholas Smith. The production subsequently toured throughout Britain.
Student:
|
b
|
task232_iirc_link_number_classification
|
NIv2
|
fs_opt
| 2
|
train
|
Definition: 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.
Input: Question: What team finished ahead of Barnsley F.C. during their first season at Midland League? Passage:Barnsley Football Club is an English association football club based in the South Yorkshire town of Barnsley. Founded in 1887 under the name Barnsley St Peter's, the team played in the Sheffield & District League from the 1890–91 season and first entered the FA Cup in 1893–94. Two years later, they were accepted into the Midland League. The club changed its name to Barnsley F.C. in 1897; its team finished as Midland League runners-up in the first season under the new name, and were elected to the newly expanded Second Division of the Football League for the 1898–99 season. A 16th-place finish in their second season meant they had to apply for re-election; the application was successful, and Barnsley continued safely in mid-table until 1911, when they again needed to be re-elected to the League. Their cup form was rather better: either side of that poor League placing, they reached the FA Cup final. In 1909–10, they drew 1–1 with Newcastle United in the final at Crystal Palace, but lost 1–0 in the replay at Everton's Goodison Park ground. Two seasons later, after taking three replays to get through the quarter-final, they played out a goalless draw with West Bromwich Albion at Crystal Palace; this time Barnsley won the replay, at Sheffield United's Bramall Lane ground, by one goal to nil.
Output:
|
b
|
task232_iirc_link_number_classification
|
NIv2
|
zs_opt
| 2
|
train
|
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.
Q: Question: How long had the Second World War been going on before the Normandy landings? Passage:He was back in Toronto in 1939 when the Second World War broke out. He attempted to join the Royal Canadian Navy (RCN), but anti-semitism in the RCN at the time precluded a naval career. Instead Dunkelman enlisted as a private with The Queen's Own Rifles of Canada; as the war progressed he rose from Private to Major. He was in the second wave to land on Juno beach, the Canadian beach in the Normandy landings on D-Day 6 June 1944. During his career with the regiment he earned numerous commendations and a Distinguished Service Order (DSO) for his service in the Hochwald campaign. He also fought in the difficult earlier campaigns in northern France, Belgium, the Netherlands and Germany, including bloody battles at Caen, Falaise, and the Battle of the Scheldt Estuary that led to the critical port of Antwerp.
A:
|
b
|
task232_iirc_link_number_classification
|
NIv2
|
zs_opt
| 4
|
train
|
Given the task definition, example input & output, solve the new input case.
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: 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,
.
Output: b
The passage describes the 704th's actions during Operation Market Garden so only information about the operation is needed.
New input case for you: Question: Who had killed Stephanie Brown in War Crimes? Passage:Besides the aforementioned death of Stephanie Brown, many other side effects came about from this event. The biggest of these included Black Mask becoming the single crime boss in Gotham, something that would remain until his death at the hands of Catwoman. Another would be Commissioner Akins effectively making all vigilantes criminals, a move that would stay in place for over a year until the return of Commissioner Gordon to the Gotham City Police Department. The more controversial effect, not seen until the follow-up story War Crimes, was turning Doctor Leslie Thompkins against Batman, when she allows Stephanie Brown to die from her wounds as Batman's "punishment" for including children in his war on crime. Jason Todd, a former Boy Wonder, confirmed to be alive on as a violent vigilante the Red Hood who waged a one-man war against Black Mask and successfully crippling his criminal operation in the city before seeking revenge towards Batman and the Joker. Finally, the citizens of Gotham City no longer consider Batman to be an urban legend (which has been in place since Zero Hour), as he was caught on camera trying to save the life of a wounded student at the end of Act One. Additionally, Barbara Gordon lost the clock tower that served as her home and headquarters and left Gotham City, eventually moving to Metropolis. She would later re-establish her ties to Batman.
Output:
|
a
|
task232_iirc_link_number_classification
|
NIv2
|
fs_opt
| 1
|
train
|
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.
Question: Who was the leader of the English Catholics? Passage:The early modern period in Britain saw religious conflict resulting from the Reformation and the recusancy that emerged in opposition to it. The Gunpowder Plot of 1605 was a failed attempt by a group of English Catholics to assassinate the Protestant King James I, and to blow up the Palace of Westminster, the English seat of government. Although the modern concept of religious terrorism, or indeed terrorism at all, had not yet come into use in the seventeenth century, David C. Rapoport and Lindsay Clutterbuck point out that the Plot, with its use of explosives, was an early precursor of nineteenth century anarchist terrorism. Sue Mahan and Pamala L. Griset classify the plot as an act of religious terrorism, writing that "Fawkes and his colleagues justified their actions in terms of religion." Peter Steinfels also characterizes this plot as a notable case of religious terrorism.
b
Question: What comes with the title given to Javanshir after he allied with the Byzantine Empire? Passage:Javanshir was known for his bravery and intelligence; he fought against the Arabs during the Muslim conquest of Persia on the side of the Sasanian Empire, and was rewarded by the Sasanian king Yazdegerd III himself two golden spears, two golden shields and a flag, probably the Drafsh e Kavian. In 636, he led an Albanian army, which alongside the Armenian prince Mushegh III Mamikonian and Grigor of Syunik, took part in the Battle of al-Qādisiyyah between the Persian and Arab armies. However, the Sasanians were defeated, which made Javanshir lose hope. He then made a mutiny against his overlords and retreated to Caucasian Albania. Where he wrote a letter to Constans II and became ally with the Byzantine Empire. He was then awarded with the title of patrikios, and recognized as king of the East. He also married to a noble from a princely family of Syunik.
b
Question: Did Phil Brown engineer the album The Colour of Spring? Passage:In 1986, Talk Talk, then a three-piece band consisting of leader and singer Mark Hollis alongside drummer Lee Harris and bassist Paul Webb, released their third album The Colour of Spring, which saw the band shift from their earlier, synthpop-oriented sound and featured a more organic art rock sound, where musicians improvised with their instruments for many hours, then Hollis and producer Tim Friese-Greene edited and arranged the performances to get the sound they wanted. A total of sixteen musicians appeared on the album. It became their most successful album, selling over two million copies and prompting a major world tour. Nonetheless, for their next album Spirit of Eden (1988), the band chose to work towards an even more unconventional and uncommercial direction. The album was compiled from a lengthy recording process at London's Wessex Studios between 1987 and 1988 where the band worked again with Friese-Greene and engineer Phill Brown. Often working in darkness, the band recorded many hours of improvised performances which were heavily edited and re-arranged into the final album.
|
a
|
task232_iirc_link_number_classification
|
NIv2
|
fs_opt
| 0
|
train
|
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.
[Q]: Question: What else of importance happened the year someone broke King's record? Passage:In April 1914 he joined Arsenal for a £1,000 fee, returning to League football. Arsenal had just missed out on promotion on goal average to the First Division, and in 1914–15 King spearheaded their attack, scoring 26 goals in the League and another three in the FA Cup. These included the first hat trick scored at their new Highbury stadium (against Grimsby Town on 14 November 1914), and two four-goal hauls against Wolverhampton Wanderers and Nottingham Forest. King's 29 goals that season were an all-time club record at the time, remaining so until Jimmy Brain broke it in 1925–26. However, Arsenal's defence let them down and they only finished fifth, outside of the promotion places; eventually, they were re-elected back to the First Division when football resumed after the end of the First World War.
[A]: b
[Q]: Question: How many people were in attendance at the University of Colorado at Boulder the year that J.D. Brookhart was hired as passing game coordinator, tight ends coach, and special teams coordinator? Passage:Joseph Daniel Brookhart (born October 17, 1964) is an American football coach and former player. He was most recently an assistant coach at the University of Colorado at Boulder, where he was hired as passing game coordinator, tight ends coach, and special teams coordinator on Jon Embree's staff in December 2010. Brookhart was the head coach at the University of Akron from 2004 to 2009, compiling a record of 30–42. His Akron Zips won the Mid-American Conference (MAC) in 2005, and he was honored as the MAC Coach of the Year the previous season. Brookhart played college football at Brigham Young University as a freshman walk-on before transferring to Colorado State University. He has also served as an assistant coach at the University of Pittsburgh and with the Denver Broncos of the National Football League (NFL).
[A]: b
[Q]: Question: Which The Cars member who worked on This Side of Paradise album is the youngest? Passage:This Side of Paradise is the second solo studio album released by Ric Ocasek, lead singer and songwriter of The Cars. It was released in 1986 by Geffen Records. Though it was a solo album, other members of The Cars played significant roles. Greg Hawkes plays keyboards and bass throughout the album (he appears on most of Ocasek's solo albums), and also co-wrote "Hello Darkness" (most Cars albums feature one Ocasek/Hawkes tune). Benjamin Orr is on backing vocals for three songs. Along with Hawkes and Orr, the track "True To You" also features Elliot Easton on guitar. Had drummer David Robinson been present, the song would have been an unofficial Cars reunion. Both production and drumming were by Chris Hughes (formerly known as "Merrick", drummer for Adam and the Ants). Hughes was the recent producer of Tears for Fears most popular two albums. Steve Stevens from Billy Idol's band plays guitar on over half of the album.
[A]:
|
a
|
task232_iirc_link_number_classification
|
NIv2
|
fs_opt
| 5
|
train
|
Detailed Instructions: 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.
See one example below:
Problem: 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,
.
Solution: b
Explanation: The passage describes the 704th's actions during Operation Market Garden so only information about the operation is needed.
Problem: Question: What are the names of the members of the heel team that defeated the Godwinns? Passage:In 1996, Canterbury was reunited with Knight, who had been renamed Phineas I. Godwinn. The duo were portrayed as being cousins (later brothers) and were collectively known as "The Godwinns". The two were faces and were managed by Hillbilly Jim. They began to feud with the Body Donnas with Phineas having a crush on Sunny and signed her as their manager. They would beat the Body Donnas for the WWF Tag Team Championships. Eventually Sunny turned on them costing them their titles. The Godwinns feuded with the now heel Smoking Gunns, in losing efforts. In 1997, the Godwinns began a heel turn dropping Hillbilly Jim as a manager and picking up Uncle Cletus. The Godwinns quickly won the tag titles a second time from The Headbangers and began a heated feud with the Legion of Doom, which saw the team attempt to break Road Warrior Hawk's neck. They eventually dropped the titles to LOD in a match on WWF Monday Night Raw that had LOD's career on the line. Soon after that match they attacked and fired Cletus.
Solution:
|
b
|
task232_iirc_link_number_classification
|
NIv2
|
fs_opt
| 4
|
test
|
instruction:
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.
question:
Question: Which of the construction materials that St Nicholas was constructed with has a higher value on the Mohs scale? Passage:St Nicholas is constructed in flint, with some conglomerate and brick, and has limestone dressings. The roofs are tiled. Its plan consists of a nave, a chancel with a north vestry (previously a porch), and a west tower. The tower is wholly octagonal. In each face of the upper stage of the tower is a lancet, and there is another lancet on the west side at a lower level. The parapet is battlemented. The tower has a west doorway in Norman style, which has possibly been re-set from elsewhere in the church. It has scalloped capitals, and zig-zag decoration on the arch. Inside the upper part of the tower is a 17th-century dovecote lined with brick nesting boxes. On the south side, between the tower and the nave, is a brick stair turret. The nave windows have two lights with Decorated tracery. Between the windows on the south side is another Norman doorway, again with zig-zag decoration. The north and south walls of the chancel have two-light windows with Y-tracery, and three-light windows with Perpendicular tracery. The east window has five lights. The east gable is decorated with grotesque carvings, and above the east window is head-corbel and a blocked niche. The vestry has two-light north and south windows. In the north wall of the nave is an Early English doorway, with dog-tooth ornament. Around the church are stepped buttresses.
answer:
a
question:
Question: Which NFL team that McKinney met with privately was found first? Passage:Prior to his junior season, McKinney was projected as a first round selection in the 2015 NFL draft. On January 9, 2015, McKinney announced that he had decided to forgo his senior season and enter the 2015 NFL draft. Before the start of the pre-draft events, McKinney was ranked as the second best linebacker in the draft by NFL analyst Mike Mayock. He was one of 34 collegiate linebackers to attend the NFL Scouting Combine in Indianapolis, Indiana. McKinney completed all of the essential combine drills and finished second among all linebackers in the vertical jump, fifth in the broad jump, ninth in the short shuttle, tenth in the 40-yard dash, and tied for 11th amongst his position group in the three-cone drill. On March 4, 2015, he attended Mississippi State's pro day, but opted to stand on his combine numbers and only performed positional drills for the team representatives and scouts from 29 NFL teams, including New York Jets' defensive coordinator Kacy Rodgers and New Orleans Saints' assistant head coach Joe Vitt. As a highly sought after prospect, McKinney attended private visits and workouts with multiple NFL teams, including the Philadelphia Eagles, Dallas Cowboys, San Francisco 49ers, Baltimore Ravens, Miami Dolphins, Carolina Panthers, Cleveland Browns, Denver Broncos, New Orleans Saints, Chicago Bears, and Minnesota Vikings. At the conclusion of the pre-draft process, McKinney was projected to be a second round pick by NFL draft experts and scouts. He was ranked the third best linebacker in the draft by NFL analyst Lance Zierlein, was ranked the fourth best linebacker by Sports Illustrated, was ranked the fifth best inside linebacker by Charles Davis, and was ranked the fifth best linebacker in the draft by NFL analyst Mike Mayock.
answer:
a
question:
Question: How many other games had Rare developed by the year it released Banjo-Kazooie? Passage:Project Dream was the codename of a role-playing video game (RPG) that served as the basis for the 1998 game Banjo-Kazooie. Developed by Rare, it was aimed for release on the Super Nintendo Entertainment System (SNES), and later the Nintendo 64 (N64). The plot revolved around a young boy, Edson, who caused trouble with pirates. The SNES version of Dream used an isometric perspective and had a fairy tale-like theme. After transitioning to the N64, the project became a more complex 3D RPG that had a greater emphasis on the pirate theme. Eventually, Dream was scaled back to a linear platform game in the vein of Donkey Kong Country (1994) that starred Banjo the bear, who became the protagonist of Banjo-Kazooie.
answer:
|
b
|
task232_iirc_link_number_classification
|
NIv2
|
fs_opt
| 9
|
validation
|
Definition: In this task, you are given a sentence and a question, you would be asked to create the answer which is contained in the sentence provided.
Input: Sentence: Urea is made in the liver and excreted in urine. Question: What is made in the liver and excreted in urine?
Output:
|
urea
|
task1555_scitail_answer_generation
|
NIv2
|
zs_opt
| 2
|
train
|
In this task, you are given a sentence and a question, you would be asked to create the answer which is contained in the sentence provided.
Q: Sentence: Radio waves are the broad range of electromagnetic waves with the longest wavelengths and lowest frequencies. Question: What waves are the broad range of electromagnetic waves with the longest wavelengths and lowest frequencies?
A: radio
****
Q: Sentence: Cell -> tissue -> organ -> organ system sequence represents the correct levels of organization for multicellular organisms. Question: Which sequence represents the correct levels of organization for multicellular organisms?
A: cell -> tissue -> organ -> organ system
****
Q: Sentence: When the smooth muscle relaxes, the arterioles dilate, allowing blood to enter the capillaries. Question: When the smooth muscle relaxes, the arterioles dilate, allowing blood to enter the what?
A:
|
capillaries
****
|
task1555_scitail_answer_generation
|
NIv2
|
fs_opt
| 4
|
train
|
In this task, you are given a sentence and a question, you would be asked to create the answer which is contained in the sentence provided.
Example: Sentence: Having white fur trait would a cat most likely inherit from its parents. Question: Which trait would a cat most likely inherit from its parents?
Example solution: having white fur
Example explanation: The given output is correct as the answer provided is from the scientific fact stated
Problem: Sentence: Neurogenesis was first discovered in songbirds that produce new neurons while learning songs. Question: What was first discovered in songbirds that produce new neurons while learning songs?
|
Solution: neurogenesis
|
task1555_scitail_answer_generation
|
NIv2
|
fs_opt
| 5
|
train
|
Given the task definition, example input & output, solve the new input case.
In this task, you are given a sentence and a question, you would be asked to create the answer which is contained in the sentence provided.
Example: Sentence: Having white fur trait would a cat most likely inherit from its parents. Question: Which trait would a cat most likely inherit from its parents?
Output: having white fur
The given output is correct as the answer provided is from the scientific fact stated
New input case for you: Sentence: One of the earliest air pumps was made by robert boyle. Question: One of the earliest air pumps was made by?
Output:
|
robert boyle
|
task1555_scitail_answer_generation
|
NIv2
|
fs_opt
| 1
|
train
|
TASK DEFINITION: In this task, you are given a sentence and a question, you would be asked to create the answer which is contained in the sentence provided.
PROBLEM: Sentence: Biochemical compounds type of compounds make up the cells and tissues of organisms. Question: What type of compounds make up the cells and tissues of organisms?
SOLUTION: biochemical compounds
PROBLEM: Sentence: When your brain senses that your body temperature is increasing, it sends messages to the blood vessels in the skin to increase in diameter. Question: When your brain senses that your body temperature is increasing, it sends messages to the blood vessels in the skin to increase in what?
SOLUTION: diameter
PROBLEM: Sentence: The right atrium receives oxygen-poor blood from the body, then pumps the blood into the right ventricle. Question: What structure of the heart receives oxygen-poor blood from the body, then pumps the blood into the right ventricle?
SOLUTION:
|
right atrium
|
task1555_scitail_answer_generation
|
NIv2
|
fs_opt
| 8
|
train
|
Given the task definition and input, reply with output. In this task, you are given a sentence and a question, you would be asked to create the answer which is contained in the sentence provided.
Sentence: Asci are used by mycelia for sexual kind of reproduction. Question: Asci are used by mycelia for what kind of reproduction?
|
sexual
|
task1555_scitail_answer_generation
|
NIv2
|
zs_opt
| 5
|
train
|
Given the task definition and input, reply with output. In this task, you are given a sentence and a question, you would be asked to create the answer which is contained in the sentence provided.
Sentence: The values of independent variables are controlled by the experimenter over the course of an experiment. Question: The values of which factors are controlled by the experimenter over the course of an experiment?
|
independent variables
|
task1555_scitail_answer_generation
|
NIv2
|
zs_opt
| 5
|
train
|
Teacher: In this task, you are given a sentence and a question, you would be asked to create the answer which is contained in the sentence provided.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Sentence: Having white fur trait would a cat most likely inherit from its parents. Question: Which trait would a cat most likely inherit from its parents?
Solution: having white fur
Reason: The given output is correct as the answer provided is from the scientific fact stated
Now, solve this instance: Sentence: Woolly mammoths began to go extinct thousands of years ago because of hunting by humans. Question: Why did woolly mammoths began to go extinct thousands of years ago?
Student:
|
hunting by humans
|
task1555_scitail_answer_generation
|
NIv2
|
fs_opt
| 2
|
train
|
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
In this task, you are given a sentence and a question, you would be asked to create the answer which is contained in the sentence provided.
Sentence: Having white fur trait would a cat most likely inherit from its parents. Question: Which trait would a cat most likely inherit from its parents?
Solution: having white fur
Why? The given output is correct as the answer provided is from the scientific fact stated
New input: Sentence: Form a protective layer do heavy alkanes affect the skin. Question: How do heavy alkanes affect the skin?
Solution:
|
form a protective layer
|
task1555_scitail_answer_generation
|
NIv2
|
fs_opt
| 0
|
test
|
You will be given a definition of a task first, then some input of the task.
In this task, you are given a sentence and a question, you would be asked to create the answer which is contained in the sentence provided.
Sentence: Convex lenses are thicker in the middle than at the edges so they cause rays of light to converge, or meet, at a point called focus. Question: Convex lenses are thicker in the middle than at the edges so they cause rays of light to converge, or meet, at a point called what?
Output:
|
focus
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task1555_scitail_answer_generation
|
NIv2
|
zs_opt
| 1
|
validation
|
Given a negotiation between two participants, answer 'Yes' if both participants agree to the deal, otherwise answer 'No'.
THEM: can i have two books and one ball? YOU: what if you take both books and i get both balls and we split the hats THEM: okay that works! thank you!
Yes
THEM: hello i want the ball and a hat please. YOU: ok deal THEM: you can take the 2 books and the other hat.
Yes
THEM: i would like the books and the hat. YOU: hat to me, and one ball THEM: how about i get the hat and 2 books YOU: all balls and books to me THEM: no, i'd rather take the books and 1 ball YOU: ok, all books and one ball to you THEM: deal.
|
Yes
|
task1384_deal_or_no_dialog_classification
|
NIv2
|
fs_opt
| 0
|
train
|
Detailed Instructions: Given a negotiation between two participants, answer 'Yes' if both participants agree to the deal, otherwise answer 'No'.
See one example below:
Problem: THEM: i need the hats and the ball YOU: i can give you one hat and the ball. i want 2 books and 1 hat THEM: i have to have both hats and the ball or both hats and a book to make a deal YOU: sorry, i won`t make a deal without a hat THEM: if you take 1 hat i have to have everything else YOU: sorry can`t do THEM: no deal YOU: yesh no deal, sorry THEM: no deal YOU: no deal.
Solution: No
Explanation: Both participants do not agree to the deal, so the answer is No.
Problem: THEM: i'll take the ball, you can have everything else YOU: how about you get teh books and i keep everything else? THEM: i cant use the books YOU: okay, you just want one ball? THEM: yes YOU: deal.
Solution:
|
Yes
|
task1384_deal_or_no_dialog_classification
|
NIv2
|
fs_opt
| 4
|
train
|
Given a negotiation between two participants, answer 'Yes' if both participants agree to the deal, otherwise answer 'No'.
[Q]: THEM: i'll take all the hats and the book. YOU: that's kind of a bad deal for me. how about i get the book and you get all the hats? THEM: ok.
[A]: No
[Q]: THEM: i would like 2 books, you can have the rest YOU: ok deal.
[A]: Yes
[Q]: THEM: if i can have the ball you can have the rest YOU: deal THEM: thank you!
[A]:
|
Yes
|
task1384_deal_or_no_dialog_classification
|
NIv2
|
fs_opt
| 5
|
train
|
Teacher:Given a negotiation between two participants, answer 'Yes' if both participants agree to the deal, otherwise answer 'No'.
Teacher: Now, understand the problem? Solve this instance: THEM: i'd like the ball and two hats. YOU: unfortunately the ball is highest value to me. only way i can give the ball up is if you give me everything else. otherwise, i can take the ball and the book and leave you the hats. THEM: you can have the ball. i'll take the book and we can split the hats. YOU: deal.
Student:
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Yes
|
task1384_deal_or_no_dialog_classification
|
NIv2
|
zs_opt
| 6
|
train
|
Given a negotiation between two participants, answer 'Yes' if both participants agree to the deal, otherwise answer 'No'.
One example is below.
Q: THEM: i need the hats and the ball YOU: i can give you one hat and the ball. i want 2 books and 1 hat THEM: i have to have both hats and the ball or both hats and a book to make a deal YOU: sorry, i won`t make a deal without a hat THEM: if you take 1 hat i have to have everything else YOU: sorry can`t do THEM: no deal YOU: yesh no deal, sorry THEM: no deal YOU: no deal.
A: No
Rationale: Both participants do not agree to the deal, so the answer is No.
Q: THEM: can i have the balls and a hat? YOU: sorry, need the balls and one hat too THEM: take the hats i take the rest YOU: sorry, need 3 balls and one hat or no deal THEM: then no deal YOU: no deal THEM: no deal YOU: no deal THEM: you know the balls are the only one with worth to me YOU: i don`t know that. but i won`t get a good deal THEM: me too, then let me have the balls and books YOU: no deal.
A:
|
No
|
task1384_deal_or_no_dialog_classification
|
NIv2
|
fs_opt
| 9
|
train
|
Given a negotiation between two participants, answer 'Yes' if both participants agree to the deal, otherwise answer 'No'.
Let me give you an example: THEM: i need the hats and the ball YOU: i can give you one hat and the ball. i want 2 books and 1 hat THEM: i have to have both hats and the ball or both hats and a book to make a deal YOU: sorry, i won`t make a deal without a hat THEM: if you take 1 hat i have to have everything else YOU: sorry can`t do THEM: no deal YOU: yesh no deal, sorry THEM: no deal YOU: no deal.
The answer to this example can be: No
Here is why: Both participants do not agree to the deal, so the answer is No.
OK. solve this:
THEM: i'd like a book and one ball please YOU: i need the book. i'd take it and the hat. THEM: if you need the book, i need the rest YOU: ok. i'll take the book. you can have the rest. THEM: deal.
Answer:
|
Yes
|
task1384_deal_or_no_dialog_classification
|
NIv2
|
fs_opt
| 8
|
train
|
Given a negotiation between two participants, answer 'Yes' if both participants agree to the deal, otherwise answer 'No'.
One example: THEM: i need the hats and the ball YOU: i can give you one hat and the ball. i want 2 books and 1 hat THEM: i have to have both hats and the ball or both hats and a book to make a deal YOU: sorry, i won`t make a deal without a hat THEM: if you take 1 hat i have to have everything else YOU: sorry can`t do THEM: no deal YOU: yesh no deal, sorry THEM: no deal YOU: no deal.
Solution is here: No
Explanation: Both participants do not agree to the deal, so the answer is No.
Now, solve this: THEM: i would like the hat and 4 balls YOU: how about i get the hat, and you get everything else? THEM: i need the hat and balls YOU: that's 5 objects to one. THEM: ok i will take all 4 balls and you get the hat and book? YOU: ok THEM: great deal.
Solution:
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Yes
|
task1384_deal_or_no_dialog_classification
|
NIv2
|
fs_opt
| 6
|
train
|
Instructions: Given a negotiation between two participants, answer 'Yes' if both participants agree to the deal, otherwise answer 'No'.
Input: THEM: i would like the book and the hat. YOU: ok.
Output:
|
Yes
|
task1384_deal_or_no_dialog_classification
|
NIv2
|
zs_opt
| 3
|
train
|
Given a negotiation between two participants, answer 'Yes' if both participants agree to the deal, otherwise answer 'No'.
One example: THEM: i need the hats and the ball YOU: i can give you one hat and the ball. i want 2 books and 1 hat THEM: i have to have both hats and the ball or both hats and a book to make a deal YOU: sorry, i won`t make a deal without a hat THEM: if you take 1 hat i have to have everything else YOU: sorry can`t do THEM: no deal YOU: yesh no deal, sorry THEM: no deal YOU: no deal.
Solution is here: No
Explanation: Both participants do not agree to the deal, so the answer is No.
Now, solve this: THEM: hello, can i have the ball and hats and you can have the books? YOU: you can have the hats but, i need the ball and the books.
Solution:
|
No
|
task1384_deal_or_no_dialog_classification
|
NIv2
|
fs_opt
| 6
|
test
|
Given a negotiation between two participants, answer 'Yes' if both participants agree to the deal, otherwise answer 'No'.
--------
Question: THEM: i need the ball and three books YOU: if you take the ball. i need the hats and at least 2 books THEM: i can do that, you get hats and 2 books, i get ball and 2 books YOU: deal.
Answer: Yes
Question: THEM: i would like the book and the hat. YOU: no problem, can i take all 3 balls? THEM: deal. YOU: deal.
Answer: Yes
Question: THEM: hey there! i'd like balls and the hat.. is the book a high value item for you? YOU: i just wan the hat please you take the rest THEM: take the book too, its no value to me. YOU: so i get the hat and book THEM: correct YOU: thanks.
Answer:
|
Yes
|
task1384_deal_or_no_dialog_classification
|
NIv2
|
fs_opt
| 7
|
validation
|
TASK DEFINITION: You are given a math word problem and you are supposed to apply addition or subtraction mathematical operators on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
PROBLEM: Before December , customers buy 1346 ear muffs from the mall . During December , they buy 6444 , and there are none . In all , how many ear muffs do the customers buy ?
SOLUTION: 7790
PROBLEM: Dan grew 42 turnips and 38 cantelopes . Jessica grew 47 turnips . How many turnips did they grow in total ?
SOLUTION: 89
PROBLEM: Ellen made smoothies in the blender . She used 0.2 cup of strawberries , 0.1 cup of yogurt , and 0.2 cup of orange juice . How many cups of ingredients did Ellen use for the smoothies ?
SOLUTION:
|
0.5
|
task865_mawps_addsub_question_answering
|
NIv2
|
fs_opt
| 8
|
train
|
Definition: You are given a math word problem and you are supposed to apply addition or subtraction mathematical operators on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
Input: Vince 's bus ride to school is 0.625 mile and Zachary 's bus ride is 0.5 mile . How much longer is Vince 's bus ride than Zachary 's ?
Output:
|
0.125
|
task865_mawps_addsub_question_answering
|
NIv2
|
zs_opt
| 2
|
train
|
You will be given a definition of a task first, then some input of the task.
You are given a math word problem and you are supposed to apply addition or subtraction mathematical operators on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
Iesha has 58 books . 19 are about school and the rest are about sports . How many books about sports does Iesha have ?
Output:
|
39
|
task865_mawps_addsub_question_answering
|
NIv2
|
zs_opt
| 1
|
train
|
You are given a math word problem and you are supposed to apply addition or subtraction mathematical operators on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
Example input: Last year , 90171 people were born in a country , and 16320 people immigrated to it . How many new people began living in the country last year ?
Example output: 106491
Example explanation: Total people living in the country = born - immigrated = 90171 - 16320 = 106491
Q: Ella owns 2 dogs . Each day , 1 dog eats 0.125 scoop of dog food and the other dog eats 0.125 scoop . Together , how much dog food do the 2 dogs eat each day ?
A:
|
0.25
|
task865_mawps_addsub_question_answering
|
NIv2
|
fs_opt
| 3
|
train
|
Detailed Instructions: You are given a math word problem and you are supposed to apply addition or subtraction mathematical operators on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
See one example below:
Problem: Last year , 90171 people were born in a country , and 16320 people immigrated to it . How many new people began living in the country last year ?
Solution: 106491
Explanation: Total people living in the country = born - immigrated = 90171 - 16320 = 106491
Problem: Amy was playing a video game where she scores 4 points for each treasure she finds . If she found 6 treasures on the first level and 2 on the second , what would her score be ?
Solution:
|
32
|
task865_mawps_addsub_question_answering
|
NIv2
|
fs_opt
| 4
|
train
|
You are given a math word problem and you are supposed to apply addition or subtraction mathematical operators on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
One example is below.
Q: Last year , 90171 people were born in a country , and 16320 people immigrated to it . How many new people began living in the country last year ?
A: 106491
Rationale: Total people living in the country = born - immigrated = 90171 - 16320 = 106491
Q: George had 30 dollars . For his birthday he got 16 more dollars but spent 38 on a new game . How much money does he have now ?
A:
|
8
|
task865_mawps_addsub_question_answering
|
NIv2
|
fs_opt
| 9
|
train
|
You are given a math word problem and you are supposed to apply addition or subtraction mathematical operators on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
Example Input: 2 beavers were working on their home . 1 went for a swim . How many beavers are still working on their home ?
Example Output: 1
Example Input: Adam had 5 dollars . At the store he spent $ 2 on a new game . If he got another 5 dollars for his allowance , how much money does he have now ?
Example Output: 8
Example Input: Lucy has an aquarium with 212 fish . She wants to buy 68 more fish . How many fish would Lucy have then ?
Example Output:
|
280
|
task865_mawps_addsub_question_answering
|
NIv2
|
fs_opt
| 3
|
train
|
You are given a math word problem and you are supposed to apply addition or subtraction mathematical operators on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
Fred has 40 baseball cards . Keith bought 22 of Fred 's baseball cards . How many baseball cards does Fred have now ?
|
18
|
task865_mawps_addsub_question_answering
|
NIv2
|
zs_opt
| 0
|
train
|
You are given a math word problem and you are supposed to apply addition or subtraction mathematical operators on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
[Q]: 30 dogs are barking . 10 more dogs start to bark . How many dogs are barking ?
[A]: 40
[Q]: Scott has 4 tickets . Ernest has with 9 tickets . Ernest finds another 72 . How many tickets does Ernest end with ?
[A]: 81
[Q]: Elise had $ 8 . Then she saved $ 13 from her allowance and spent $ 2 on a comic book and $ 18 on a puzzle . How much money does Elise have left ?
[A]:
|
1
|
task865_mawps_addsub_question_answering
|
NIv2
|
fs_opt
| 5
|
test
|
Given the task definition, example input & output, solve the new input case.
You are given a math word problem and you are supposed to apply addition or subtraction mathematical operators on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
Example: Last year , 90171 people were born in a country , and 16320 people immigrated to it . How many new people began living in the country last year ?
Output: 106491
Total people living in the country = born - immigrated = 90171 - 16320 = 106491
New input case for you: Denise removes 5 bananas from a jar . There were originally 46 bananas in the jar . How many bananas are left in the jar ?
Output:
|
41
|
task865_mawps_addsub_question_answering
|
NIv2
|
fs_opt
| 1
|
validation
|
Definition: A text is given in Hindi. Translate it from the Hindi language to the Urdu language. The translation must not omit or add information to the original sentence.
Input: कार रैली का कार्यक्रम
Output:
|
موٹر کار ریلی کے سفر کی تفصیلات
|
task1053_pib_translation_hindi_urdu
|
NIv2
|
zs_opt
| 2
|
train
|
A text is given in Hindi. Translate it from the Hindi language to the Urdu language. The translation must not omit or add information to the original sentence.
One example is below.
Q: केन्द्रीय सड़क परिवहन और राजमार्ग, नौवहन, रसायन और उर्वरक राज्य मंत्री श्री मनसुख मंडाविया ने कहा कि नागरिकों के लाभ के लिए परिवहन क्षेत्र में बड़ी पहल की गई है।
A: مرکزی روڈ ٹرانسپورٹ اور ہائی وے کے لئے وزیر خارجہ، شپنگ، کیمیکل اور کھاد مسٹر منشوخ منویایا نے کہا کہ شہریوں کے فائدے کے لئے نقل و حمل کے شعبے میں ایک بڑی پہلو ہے.
Rationale: Correct translation for given sentence. Input sentence means 'Minister of State for Central Road Transport and Highway, Shipping, Chemicals and Fertilizer Mr. Manasukh Mandavia said that there has been a large initiative in the transport sector for the benefit of citizens.' which is the same as the output sentence.
Q: केंद्रीय जल संसाधन, नदी विकास एवं गंगा संरक्षण, शिपिंग, सड़क परिवहन एवं राजमार्ग मंत्री श्री नितिन गडकरी ने आज नई दिल्ली में आयोजित एक समारोह में नाबार्ड द्वारा प्रकाशित प्रमुख भारतीय फसलों का जल उत्पादकता मानचित्रण पुस्तक का विमोचन किया।
A:
|
نتن گڈکری نے ہندستان کی اہم فصلوں کی واٹر پروڈکٹی ویٹی میپنگ نام کی نبارڈ کی کتاب کا اجرا کیا
|
task1053_pib_translation_hindi_urdu
|
NIv2
|
fs_opt
| 9
|
train
|
Teacher:A text is given in Hindi. Translate it from the Hindi language to the Urdu language. The translation must not omit or add information to the original sentence.
Teacher: Now, understand the problem? Solve this instance: राजस्थान के किशनगढ़ बास में अल्पसंख्यक मंत्रालय के सहयोग से विश्व स्तरीय शिक्षण संस्थान बनाया जाएगा
Student:
|
راجستھان میں کشن گڑھ باس کے مقام پر اقلیتی امور کی وزارت کی امداد سے عالمی معیار کا ایک تعلیمی ادارہ قائم کیا جائے گا
|
task1053_pib_translation_hindi_urdu
|
NIv2
|
zs_opt
| 6
|
train
|
Detailed Instructions: A text is given in Hindi. Translate it from the Hindi language to the Urdu language. The translation must not omit or add information to the original sentence.
Problem:प्रधानमंत्री ने वैज्ञानिकों को आशान्वित रहने और भारत के अंतरिक्ष कार्यक्रम के लिये कठिन प्रयास जारी रखने के लिए प्रोत्साहित किया
Solution:
|
انہوں نے پُرامید رہنے اور ہندوستان کے خلائی پروگرام پر سخت محنت جاری رکھنے کے لیے ان کی حوصلہ افزائی کی
|
task1053_pib_translation_hindi_urdu
|
NIv2
|
zs_opt
| 8
|
train
|
A text is given in Hindi. Translate it from the Hindi language to the Urdu language. The translation must not omit or add information to the original sentence.
Q: जनवरी-2019 परीक्षा में पंजीकृत अभ्यर्थियों की संख्या।
A:
|
جنوری 2019 امتحان میں رجسٹرڈ امیدواروں کی تعداد
|
task1053_pib_translation_hindi_urdu
|
NIv2
|
zs_opt
| 4
|
train
|
A text is given in Hindi. Translate it from the Hindi language to the Urdu language. The translation must not omit or add information to the original sentence.
--------
Question: नई दिल्ली के हस्तशिल्प संग्रहालय में फैशन डिजाइन काउंसिल ऑफ इंडिया द्वारा वस्त्र मंत्रालय के प्रतिभागियों, मास्टर बुनकर, कपड़ों के डिजाइनरों, फैशन डिजाइनरों और वस्त्र विशेषज्ञों के साथ संगोष्ठी।
Answer: وزارت ٹیکسٹائل کے شرک کے ساتھ فیشن ڈیزائن کونسل آف انڈیا کے ذریعہ نئی دہلی میں کرافٹ میوزیم میں سمپوزیم کا انعقاد کیاجائیگا جس میں معروف بُن کر ، ٹیکسٹائل ڈیزائنر ، فیشن ڈیزائنراورٹیکسٹائل ماہرین شرکت کریں گے ۔
Question: इन एपीए पर हस्ताक्षर किए जाने के साथ ही वित्त वर्ष 2018-19 में सीबीडीटी द्वारा किए गए एपीए की कुल संख्या बढ़कर 52 हो गई है, जिनमें 11 बीएपीए शामिल हैं।
Answer: مارچ 2019میں سی بی ڈی ٹی کے ذریعہ 18 اے پی اے ایس پر دستخط کے ساتھ ہی ہندوستان کے پیشگی قیمتوں کے تعین سے متعلق سمجھوتے کے نظام کی پیش قدمی
Question: इस टर्मिनल से, आदिवासी भाइयों, बहनों और किसानों को आसानी से देश के अन्य बाजारों में अपनी उपज के लिए पहुंच बनाने में मदद मिलेगी।
Answer:
|
وزیر اعظم نریندر مودی نے صاحب گنج میں کثیر ماڈل ٹرانسپورٹ ٹرمنل کا بھی افتتاح کیا۔
|
task1053_pib_translation_hindi_urdu
|
NIv2
|
fs_opt
| 7
|
train
|
A text is given in Hindi. Translate it from the Hindi language to the Urdu language. The translation must not omit or add information to the original sentence.
One example is below.
Q: केन्द्रीय सड़क परिवहन और राजमार्ग, नौवहन, रसायन और उर्वरक राज्य मंत्री श्री मनसुख मंडाविया ने कहा कि नागरिकों के लाभ के लिए परिवहन क्षेत्र में बड़ी पहल की गई है।
A: مرکزی روڈ ٹرانسپورٹ اور ہائی وے کے لئے وزیر خارجہ، شپنگ، کیمیکل اور کھاد مسٹر منشوخ منویایا نے کہا کہ شہریوں کے فائدے کے لئے نقل و حمل کے شعبے میں ایک بڑی پہلو ہے.
Rationale: Correct translation for given sentence. Input sentence means 'Minister of State for Central Road Transport and Highway, Shipping, Chemicals and Fertilizer Mr. Manasukh Mandavia said that there has been a large initiative in the transport sector for the benefit of citizens.' which is the same as the output sentence.
Q: वाणिज्य भवन का निर्माण 226 करोड़ रु. की लागत से किया जा रहा है और दिसंबर 2019 तक इसका निर्माण पूरा कर लिया जाना अनुमानित है।
A:
|
وانجیہ بھون کی تعمیر 226 کروڑ کی لاگت سے ہو رہی ہے اور دسمبر 2019 تک اس کے پورا ہونے کی امید ہے ۔
|
task1053_pib_translation_hindi_urdu
|
NIv2
|
fs_opt
| 9
|
train
|
A text is given in Hindi. Translate it from the Hindi language to the Urdu language. The translation must not omit or add information to the original sentence.
उपराष्ट्रपति ने श्री वेदांत देशिक को उच्च कोटि का विद्वान बताते हुए कहा कि उन्होंने संस्कृत, तमिल, प्राकृत और मणिप्रवलम भाषाओं में कविता, गद्य, नाटक, टिप्पणी, विज्ञान संबंधी लेख और दर्शन के सिद्धांतों की रचना की थी।
نائب صدر جمہوریہ نے سری ویدانتا دیسی کان کی اسکالر شپ کو ایک صحیح معنوں میں غیر معمولی قدم بتایا۔ انہوں نے کہا کہ انہوں نے سنسکرت، تمل، پراکرت اور منی پراولم میں بہترین نظمیں، ڈرامے، سائنس کی نصابی کتابیں، نثر اور رزمیہ اور فلاسفیکل مقالے لکھے۔
हीरा हमारे व्यापार की एक मजबूत कड़ी है।
میں اس کی محض ایک مثال پیش کرتا ہوں۔
म्यांमार के कमांडर-इन-चीफ रक्षा विभाग के वरिष्ठ जनरल मिन आंग ह्लिंग भारत की आधिकारिक यात्रा पर
|
نئی دہلی،29جولائی2019ریبلک آف یونین آف میانمار کی دفاعی خدمات کے کمانڈر اِن چیف (سی ڈی ایس)، سینئر جنرل مِن آنگ ہلینگ(ایم اے ایچ)، 25 جولائی سے 02اگست 2019ء تک ہندوستان کے سرکاری دورے پر ہیں۔
|
task1053_pib_translation_hindi_urdu
|
NIv2
|
fs_opt
| 0
|
train
|
A text is given in Hindi. Translate it from the Hindi language to the Urdu language. The translation must not omit or add information to the original sentence.
Example input: केन्द्रीय सड़क परिवहन और राजमार्ग, नौवहन, रसायन और उर्वरक राज्य मंत्री श्री मनसुख मंडाविया ने कहा कि नागरिकों के लाभ के लिए परिवहन क्षेत्र में बड़ी पहल की गई है।
Example output: مرکزی روڈ ٹرانسپورٹ اور ہائی وے کے لئے وزیر خارجہ، شپنگ، کیمیکل اور کھاد مسٹر منشوخ منویایا نے کہا کہ شہریوں کے فائدے کے لئے نقل و حمل کے شعبے میں ایک بڑی پہلو ہے.
Example explanation: Correct translation for given sentence. Input sentence means 'Minister of State for Central Road Transport and Highway, Shipping, Chemicals and Fertilizer Mr. Manasukh Mandavia said that there has been a large initiative in the transport sector for the benefit of citizens.' which is the same as the output sentence.
Q: मंत्रालयों के माध्यम से समर्थित अन्य कार्यक्रमों से और भी अधिक लोग लाभान्वित होंगे।
A:
|
وزارتوں کے ذریعہ دی جانے والی دیگر پروگراموں کو مدد دیے جانے سے اور زیادہ لوگوں کو فائدہ ہوگا۔
|
task1053_pib_translation_hindi_urdu
|
NIv2
|
fs_opt
| 3
|
test
|
Q: A text is given in Hindi. Translate it from the Hindi language to the Urdu language. The translation must not omit or add information to the original sentence.
यह पुरस्कार ईएसआईसी द्वारा कवरेज विस्तार स्प्री (नियोक्ता और कर्मचारियों की पंजीकरण प्रोत्साहन योजना), नए क्रियान्वित क्षेत्रों में 24 महीनों के लिए अंशदान दर में कमी तथा ईएसआईसी अधिनियम के अंतर्गत कवरेज के लिए वेतन सीमा बढ़ाने जैसे उठाए गए कदमों को मान्यता देता है।
A:
|
مذکورہ ایوارڈ کے تحت ایس پی آر ای ای (آجروں اور ملازمین کے رجسٹریشن کو فروغ دینے کی اسکیم) کے لئے احاطہ کی سرگرمیوں کی توسیع کے لئے ای ایس آئی سی کے ذریعےکئے گئے اقدامات کے اعتراف میں دیا گیا ہے۔ نونفاذ شدہ شعبوں میں 24 مہینوں کے لئے تعاون کی شرحوں میں تخفیف لانے اور ای ایس آئی ایکٹ وغیرہ کے تحت احاطے کے لحاظ سے اُجرت کی حدود میں اضافے جیسے امور بھی اس کے تحت شامل ہیں۔
|
task1053_pib_translation_hindi_urdu
|
NIv2
|
zs_opt
| 7
|
validation
|
Detailed Instructions: You are given a math word problem and you are supposed to apply multiple mathematical operators like addition, subtraction, multiplication or division on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
See one example below:
Problem: a paper bag can hold 16 cookies . if edgar buys 292 cookies how many paper bags does he need ?
Solution: 18.25
Explanation: number of paper bags = 292/16 = 18.25 bags
Problem: there are 820 blocks in bridget 's block collection . if the blocks are organized into 82 groups how big is each group ?
Solution:
|
10
|
task862_asdiv_multidiv_question_answering
|
NIv2
|
fs_opt
| 4
|
train
|
You are given a math word problem and you are supposed to apply multiple mathematical operators like addition, subtraction, multiplication or division on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
Q: mrs. hilt bought carnival tickets . the tickets cost $ 1 for 4 tickets . if mrs. hilt bought 12 tickets how much did she pay ?
A: 3
****
Q: at a candy store you could get 2 giant lollipops for $ 2.40 . how much would it cost to buy 6 lollipops ?
A: 7.2
****
Q: adam had 8 boxes of toys . each box had 6 toys . later adam bought 5 more toys . how many toys did he have total ?
A:
|
53
****
|
task862_asdiv_multidiv_question_answering
|
NIv2
|
fs_opt
| 4
|
train
|
Definition: You are given a math word problem and you are supposed to apply multiple mathematical operators like addition, subtraction, multiplication or division on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
Input: dave had 10 video games but 2 of them were n't working . if he wanted to sell the working games for $ 4 each how much money could he earn ?
Output:
|
32
|
task862_asdiv_multidiv_question_answering
|
NIv2
|
zs_opt
| 2
|
train
|
You are given a math word problem and you are supposed to apply multiple mathematical operators like addition, subtraction, multiplication or division on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
lukas averages 12 points per game in basketball . how many points would he score in 5 games ?
60
a pallet of boxes weighed 267 kilograms . if there were 3 boxes on the pallet and each box weighed the same amount how much did each weigh ?
89
emily is making bead necklaces for her friends . she has 28 beads and each necklace takes 7 beads . how many necklaces can emily make ?
|
4
|
task862_asdiv_multidiv_question_answering
|
NIv2
|
fs_opt
| 0
|
train
|
Part 1. Definition
You are given a math word problem and you are supposed to apply multiple mathematical operators like addition, subtraction, multiplication or division on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
Part 2. Example
a paper bag can hold 16 cookies . if edgar buys 292 cookies how many paper bags does he need ?
Answer: 18.25
Explanation: number of paper bags = 292/16 = 18.25 bags
Part 3. Exercise
a delivery driver had to make 3 more stops on his route . at each stop he had to drop off 9 boxes . how many boxes does he have ?
Answer:
|
27
|
task862_asdiv_multidiv_question_answering
|
NIv2
|
fs_opt
| 7
|
train
|
You are given a math word problem and you are supposed to apply multiple mathematical operators like addition, subtraction, multiplication or division on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
[Q]: chris is inviting 82 friends to a party . he has 1804 cookies and 10 peices of candy . how many cookies will each friend get ?
[A]: 22
[Q]: dean knew that they are going to stay at the beach for a while so he brought 30 sets of clothes for every week of their stay . if dean is staying for 4 weeks there how many sets of clothes did he bring ?
[A]: 120
[Q]: keith has 5530 marbles and 3 pencils . if he shares the marbles among 79 friends how many marbles does each friend get ?
[A]:
|
70
|
task862_asdiv_multidiv_question_answering
|
NIv2
|
fs_opt
| 5
|
train
|
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
You are given a math word problem and you are supposed to apply multiple mathematical operators like addition, subtraction, multiplication or division on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
a paper bag can hold 16 cookies . if edgar buys 292 cookies how many paper bags does he need ?
Solution: 18.25
Why? number of paper bags = 292/16 = 18.25 bags
New input: there are 84 leaves . there are 139 ladybugs on each leaf . how many ladybugs are there in all ?
Solution:
|
11676
|
task862_asdiv_multidiv_question_answering
|
NIv2
|
fs_opt
| 0
|
train
|
You are given a math word problem and you are supposed to apply multiple mathematical operators like addition, subtraction, multiplication or division on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
Let me give you an example: a paper bag can hold 16 cookies . if edgar buys 292 cookies how many paper bags does he need ?
The answer to this example can be: 18.25
Here is why: number of paper bags = 292/16 = 18.25 bags
OK. solve this:
mrs. hilt is baking bread . she needs 5 cups of flour to bake 2 loaves of bread . how much flour will she need to make 1 loaf of bread ?
Answer:
|
2.5
|
task862_asdiv_multidiv_question_answering
|
NIv2
|
fs_opt
| 8
|
train
|
Given the task definition and input, reply with output. You are given a math word problem and you are supposed to apply multiple mathematical operators like addition, subtraction, multiplication or division on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
mrs. hilt read 4 books . each book had 17 chapters in it . how many chapters did mrs. hilt read ?
|
68
|
task862_asdiv_multidiv_question_answering
|
NIv2
|
zs_opt
| 5
|
test
|
Instructions: You are given a math word problem and you are supposed to apply multiple mathematical operators like addition, subtraction, multiplication or division on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
Input: matt and his friends were thinking of making christmas decors for the clubhouse in their neighborhood . they are to repaint 350 balls in 10 different colors . if they painted an equal number of balls for every color how many balls are there for each color ?
Output:
|
35
|
task862_asdiv_multidiv_question_answering
|
NIv2
|
zs_opt
| 3
|
validation
|
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