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You are given a statement written in Bengali. Choose the most logical word from the given 4 options which can be used to replace the <MASK> token in the statement . Output the word from the correct option .
One example: Statement: ১লা ফেব্রুয়ারী <MASK> ভ্রমণ প্রদর্শক হিসেবে কর্মরত একজন চীনের নাগরিককে দেশে দ্বাদশ করোনার রুগী হিসেবে নিশ্চিত করা হয়। জাপানে করোনায় আক্রান্ত একজন রুগীকে দেখতে গিয়ে তিনি নিজে আক্রান্ত হয়ে পড়েন এবং ১৯শে জানুয়ারী রাজধানী সিওলের গিম্পো আন্তর্জাতিক বিমানবন্দর দিয়ে দেশে প্রবেশ করেন। ২শরা ফেব্রুয়ারী কোরিয়া রোগ নিয়ন্ত্রণ এবং প্রতিরোধ কেন্দ্র (কেসিডিসি) অতিরিক্ত তিনটি মামলা নিশ্চিত করার পরবর্তিতে আক্রান্তদের সংখ্যা মোট পনেরোতে এসে দাঁড়ায়।
Option A: সিঙ্গাপুর
Option B: ভিয়েতনাম
Option C: তাইওয়ান
Option D: জাপানে
Solution is here: জাপানে
Explanation: The most suitable word from the given options to replace the <MASK> token is জাপানে, as the statement mentions that the person came from Japan .
Now, solve this: Statement: জসীম উদ্দিন আহমেদ ১৯৫৬ সালে ঢাকা কলেজে শিক্ষকতা পেশায় যোগদানের মাধ্যমে কর্মজীবন শুরু করেন। এরপর, তিনি উচ্চশিক্ষা অর্জনের জন্য <MASK> গমন করেন। সেখান থেকে ডক্টরেট ডিগ্রি লাভ করার পর তিনি দেশে ফিরে আসেন। তিনি ১৯৬৩ সালে ঢাকার আণবিক শক্তি কেন্দ্রে যোগদান করেন। ১৯৭০ সালে তিনি আন্তর্জাতিক পরমাণু শক্তি সংস্থায় যোগদান করেন পরবর্তীতে, তিনি প্রতিষ্ঠানটির পারমাণবিক বিকিরণ নিরাপত্তা বিভাগের প্রধান হিসেবে নিযুক্ত হন। তিনি ১৯৯৪ সালে ঐ পদ থেকে অবসরগ্রহণ করেন।
Option A: বাংলাদেশের
Option B: আন্দালুসবাসী
Option C: ঢাকা
Option D: যুক্তরাষ্ট্র
Solution:
|
যুক্তরাষ্ট্র
|
task945_wiki_cloze_bn_multiple_choice_question_answering
|
NIv2
|
fs_opt
| 6
|
train
|
Definition: You are given a statement written in Bengali. Choose the most logical word from the given 4 options which can be used to replace the <MASK> token in the statement . Output the word from the correct option .
Input: Statement: ১৯৯৭ সালে হ্যরিসনের গলায় ক্যান্সার ধরা পড়ে। তখন তাকে রেডিওথেরাপি দেয়া হয় যা সফল হিসেবে মনে করা হয়েছিল। ২০০১ সালে তার ফুসফুস থেকে ক্যন্সার টিউমার অপসারণ করা হয়। ২০০১ সালে ২৯ নভেম্বর হ্যরিসন ৫৮ বছর বয়সে মেটাস্টাটিক নন-স্মল সেল লাং ক্যন্সারে মারা যান। হলিউড ফরএভার সিমেট্রিতে তাকে দাহ করা হয়। এরপর তার দেহভস্ম ভারতের <MASK> নিকট গঙ্গা ও যমুনা নদীতে ছড়িয়ে দেয়া হয়। নিকট পারিবারিক লোকেরা ভারতে হিন্দুরীতিতে তার শেষকৃত্য সম্পন্ন করেন।
Option A: (নক্ষত্রমণ্ডল)
Option B: গঙ্গা
Option C: কাশীর
Option D: মুম্বাই
Output:
|
কাশীর
|
task945_wiki_cloze_bn_multiple_choice_question_answering
|
NIv2
|
zs_opt
| 2
|
train
|
Q: You are given a statement written in Bengali. Choose the most logical word from the given 4 options which can be used to replace the <MASK> token in the statement . Output the word from the correct option .
Statement: হিমাচল প্রদেশের অপর নাম দেবভূমি (দেবতাদের দেশ)। ঋগ্বৈদিক যুগের পূর্ব থেকেই এই অঞ্চলে ইন্দো-আর্য প্রভাব লক্ষিত হয়। অ্যাংলো-গোর্খা যুদ্ধের পর এই অঞ্চল <MASK> ঔপনিবেশিক সরকারের অধীনস্থ হয়। পার্বত্য পাঞ্জাবের সিবা রাজ্য (Siba State of Punjab Hills) ব্যতীত এই অঞ্চলের অপরাপর অংশ প্রথম দিকে পাঞ্জাবের অন্তর্গত হয়। উল্লেখ্য সিবা রাজ্য ১৮৫৭ সাল পর্যন্ত মহারাজা রঞ্জিত সিংহের শাসনাধীন ছিল। ১৯৫০ সালে হিমাচল একটি কেন্দ্রশাসিত অঞ্চল ঘোষিত হয়। এরপর ১৯৭১ সালের হিমাচল প্রদেশ রাজ্য আইন অনুযায়ী ভারতীয় প্রজাতন্ত্রের অষ্টাদশ রাজ্য হিসেবে আত্মপ্রকাশ করে হিমাচল প্রদেশ। এ রাজ্যে বহু স্বনামধন্য বোর্ডিং স্কুল অবস্থিত।
Option A: হরিয়ানা
Option B: ব্রিটিশ
Option C: কেরলের
Option D: উত্তরাখণ্ড
A:
|
ব্রিটিশ
|
task945_wiki_cloze_bn_multiple_choice_question_answering
|
NIv2
|
zs_opt
| 7
|
train
|
You are given a statement written in Bengali. Choose the most logical word from the given 4 options which can be used to replace the <MASK> token in the statement . Output the word from the correct option .
Ex Input:
Statement: চিন্ময়ী <MASK> সরকারের কাছ থেকে কর্ণাটক সংগীতের জন্য তরুণ প্রতিভা জন্য সিসিআরটি স্কলারশিপ পেয়েছিলেন। তিনি ২০০০ সালে অল ইন্ডিয়া রেডিও থেকে গজলের জন্য স্বর্ণপদক এবং ২০০২ সালে হিন্দুস্তানি ক্লাসিকাল সংগীতের জন্য রৌপ্য অর্জন করেছিলেন। তিনি চেন্নাইয়ের ম্যাক্স মুয়েলার ভবনে একটি ভাষা হিসাবে জার্মান ভাষা শিখেন এবং ওয়েব ডিজাইনে এনআইআইটি এবং এসএসআইয়ের কাছ থেকে সংসাপ্রত্র কোর্স সম্পন্ন করেন। স্কুলজীবনের সময় তিনি সিফ এবং স্টুডেন্ট কনসেপ্টস আরগ উভয়ের সাথেই চাকরি করতেন। চিন্ময়ী বর্তমানে মাদ্রাজ বিশ্ববিদ্যালয় থেকে মনোবিজ্ঞান স্নাতক ডিগ্রি অর্জন করেছেন। তিনি একটি বহুমুখী নৃত্যশিল্পী এবং বেশিরভাগ নাচের ওডিসি রূপ উপভোগ করেন।
Option A: ভারত
Option B: তামিলনাড়ু
Option C: কর্ণাটক
Option D: OnsOranje
Ex Output:
ভারত
Ex Input:
Statement: ১৯৭৫ সালে <MASK> পূর্ব তিমুর আক্রমণ ও দখল করে এবং ১৯৯৯ সাল পর্যন্ত সেখানে ইন্দোনেশীয় দখলদারিত্ব অব্যাহত থাকে। এসময় হাজার হাজার পূর্ব তিমুরীয় নারী ইন্দোনেশীয় সৈন্য ও পুলিশদের দ্বারা ধর্ষণের শিকার হন। পূর্ব তিমুরীয় বিচ্ছিন্নতাবাদীদের স্ত্রী, নারী বিচ্ছিন্নতাবাদী এবং সন্দেহভাজন বিচ্ছিন্নতাবাদীদের নারী সহযোগীরা ছিলেন ধর্ষিত নারীদের একটি বড় অংশ। অনেক সময় ইন্দোনেশীয় সৈন্য বা পুলিশরা বিচ্ছিন্নতাবাদীদের না পেয়ে তাদের স্ত্রী, বোন বা অন্যান্য নারী আত্মীয়দের ধর্ষণ করত। বন্দি নারীদের অর্ধনগ্ন করে তাদের ওপর নির্যাতন ও ধর্ষণ চালানো হত এবং তাদেরকে মেরে ফেলার হুমকি দেয়া হত। বহু নারীকে সপ্তাহের পর সপ্তাহ ধরে বন্দি করে রেখে বারবার ধর্ষণ করা হত।
Option A: কুয়েত
Option B: শ্রীলঙ্কা
Option C: ইন্দোনেশিয়া
Option D: হাঙ্গেরি
Ex Output:
ইন্দোনেশিয়া
Ex Input:
Statement: প্রতিযোগিতার প্রারম্ভে মনে করা হচ্ছিল ফেলপসের স্বদেশীয় ইয়ান ক্রকার তাঁকে শক্ত প্রতিদ্বন্দ্বিতায় ফেলবেন। কারণ, ক্রকার ফেলপসের ১০০মিটার বাটারফ্লাইয়ের বিশ্বরেকর্ড ২০০৩ সালেই ভাঙেন। পরে, সেই রেকর্ড আরও দুবার গড়েন: একবার ২০০৪ সালে যুক্তরাষ্ট্রের অলিম্পিক ট্রায়ালে ও <MASK> অনুষ্ঠিত গ্যারি হল জুনিয়র দি নিউ ইয়র্ক টাইমসকে দেওয়া এক সাক্ষাৎকারে বলেন যদিও "মাইক (ফেলপস) বলছে যে সে শেষ বারের জন্য অলিম্পিকে ১০০(মিটার) ফ্লাই (বাটারফ্লাই বিভাগ) জিতবে", তাঁর মতে ক্যাভিচ জিতবে।
Option A: গ্রীস
Option B: অস্ট্রেলিয়া
Option C: মন্ট্রিয়লে
Option D: যুক্তরাষ্ট্রে
Ex Output:
|
মন্ট্রিয়লে
|
task945_wiki_cloze_bn_multiple_choice_question_answering
|
NIv2
|
fs_opt
| 1
|
train
|
You will be given a definition of a task first, then some input of the task.
You are given a statement written in Bengali. Choose the most logical word from the given 4 options which can be used to replace the <MASK> token in the statement . Output the word from the correct option .
Statement: বীরভূম জেলা তিনটি মহকুমায় বিভক্ত: সিউড়ি সদর, <MASK> ও রামপুরহাট। সিউড়ি বীরভূমের জেলাসদর। জেলায় মোট ২৩টি থানা, ১৯টি সমষ্টি উন্নয়ন ব্লক, ৬টি পুরসভা ও ১৬৯টি গ্রামপঞ্চায়েত রয়েছে। পুরসভা এলাকা ছাড়াও প্রত্যেকটি মহকুমা সমষ্টি উন্নয়ন ব্লকে বিভক্ত; যেগুলি আবার গ্রামীণ অঞ্চল ও সেন্সাস টাউনে বিভক্ত। সামগ্রিকভাবে এই অঞ্চলে সাতটি নগরাঞ্চল দেখা যায়: ছয়টি পুরসভা ও একটি সেন্সাস টাউন। ২০০০ সালে পৌরসভার মর্যাদা পাওয়া নলহাটি এই জেলার সাম্প্রতিকতম শহর।
Option A: নানুর
Option B: শান্তিনিকেতনে
Option C: লাঢ়ার
Option D: বোলপুর
Output:
|
বোলপুর
|
task945_wiki_cloze_bn_multiple_choice_question_answering
|
NIv2
|
zs_opt
| 1
|
train
|
You are given a statement written in Bengali. Choose the most logical word from the given 4 options which can be used to replace the <MASK> token in the statement . Output the word from the correct option .
Statement: মুখার্জি বেঙ্গল প্রেসিডেন্সির (এখন <MASK>) কলকাতায় নিউ থিয়েটার স্টুডিওতে তাঁর কর্মজীবন শুরু করেছিলেন। পরবর্তীকালে তিনি বোম্বে টকিজের তত্ত্বাবধায়ক প্রযুক্তিবিদ হিসাবে যোগদান করেছিলেন। শীঘ্রই তিনি "ফর্মুলা ছায়াছবি"র একজন পথ নির্দেশক হয়ে ওঠেন। তাঁর প্রথম পরিচালনা ছিল গীতা (১৯৪০), যেটি বিষয়ের উপর ভিত্তি করে তৈরী হয়েছিল। "ক্রাইম-ডাজন্ট-পে", "বয় মীটস গার্ল"-এর বিষয় নিয়ে তৈরী হয়েছিল ঝুলা (১৯৪১)।
Option A: পশ্চিমবঙ্গ
Option B: কলকাতা
Option C: ভারতীয়
Option D: উত্তরপ্রদেশ
|
পশ্চিমবঙ্গ
|
task945_wiki_cloze_bn_multiple_choice_question_answering
|
NIv2
|
zs_opt
| 0
|
train
|
Detailed Instructions: You are given a statement written in Bengali. Choose the most logical word from the given 4 options which can be used to replace the <MASK> token in the statement . Output the word from the correct option .
Q: Statement: লেনের ভাষ্যমতে, চৈনিক মৃৎশিল্পের প্রভাব তিনটি প্রধান ধাপে এগোয়।<MASK> সাথে প্রথম যোগাযোগ হয় ৭৫১ সালে জখন তালাসের যুদ্ধে আরবেরা চীনাদের পরাজিত করে। এটি বিতর্কের বিষয় যে যুদ্ধবন্দী চৈনিক কুমার এবং কাগজ প্রস্তুতকারীরা মুসলমানদের মৃৎশিল্প এবং কাগজ প্রস্তুতের শিল্প শিখিয়ে থাকতে পারে। ৮০০ সালের দিকে চৈনিক পাঁথরের এবং চীনামাটি বাসন আব্বাসীয়দের কাছে পৌঁছায়। দ্বিতীয় ধাপটি সঙ্ঘটিত হয় ১২দশ এবং ১৩দশ শতাব্দীতে, সেলিজুক সাম্রাজ্যের পতনের পরপরই মৃৎশিল্প অবনতির জন্যেএই যুগটি পরিচিত। এই যুগটি মঙ্গোলদের যারা চৈনিক মৃৎশিল্পের ঐতিহ্য নিয়ে আসে তাদের আক্রমণেরও সাক্ষী।
Option A: পারস্য,
Option B: চীনের
Option C: আব্বাসিয়
Option D: আল-আন্দালুজেl
A:
|
চীনের
|
task945_wiki_cloze_bn_multiple_choice_question_answering
|
NIv2
|
zs_opt
| 9
|
train
|
Definition: You are given a statement written in Bengali. Choose the most logical word from the given 4 options which can be used to replace the <MASK> token in the statement . Output the word from the correct option .
Input: Statement: প্রাচীন গ্রিসের আদি জ্যোতির্বিজ্ঞান <MASK> সংস্কৃতি থেকে আহরিত জ্ঞানের দ্বারা প্রভাবিত হয়েছিল। ব্যাবিলনীয়েরা মঙ্গল গ্রহকে তাঁদের যুদ্ধ ও মহামারীর দেবতা নেরগালের সঙ্গে যুক্ত করেছিলেন। গ্রিকরাও এই গ্রহটিকে যুক্ত করেছিলেন তাঁদের যুদ্ধদেবতা আরেসের সঙ্গে। সেই যুগে গ্রহগুলির গতির বিষয়ে গ্রিকদের বিশেষ আগ্রহ ছিল না। হেসিয়ডের ওয়ার্কস অ্যান্ড ডেজ গ্রন্থে (আনুমানিক খ্রিস্টপূর্ব ৬৫০ অব্দ) গ্রহগুলির কোনও উল্লেখ নেই।
Option A: সৌরজগতের
Option B: শনি
Option C: বৃহস্পতি
Option D: মেসোপটেমীয়
Output:
|
মেসোপটেমীয়
|
task945_wiki_cloze_bn_multiple_choice_question_answering
|
NIv2
|
zs_opt
| 2
|
train
|
You are given a statement written in Bengali. Choose the most logical word from the given 4 options which can be used to replace the <MASK> token in the statement . Output the word from the correct option .
[Q]: Statement: ২০০৬, ২০০১ এবং ১৯৯৬ সালের বিধানসভা নির্বাচনে, সিপিআই (এম) এর সুস্মিতা বিশ্বাস বরজোড়া কেন্দ্র থেকে জয়ী হন তৃণমূল কংগ্রেসের শম্পা দাড়িপাকে পরাজিত করেন, তৃণমূল কংগ্রেসের সুধাংশু শেখর তিওয়ারিকে এবং কংগ্রেসের তাপসী ব্যানার্জীকে পরাজিত করেন। অধিকাংশ বছরে প্রতিযোগিতাগুলিতে প্রার্থীদের বিভিন্ন ধরনের কোণঠাসা করে ছিল কিন্তু শুধুমাত্র বিজয়ী ও রানার্সকে উল্লেখ করা হচ্ছে। সিপিআই (এম) এর জয়শ্রী মিত্র ১৯৯১ সালে <MASK> সব্যসাচী রায়কে এবং ১৯৮৭ সালে কংগ্রেসের সুধাংশু শেখর তিওয়ারিকে পরাজিত করেন। সিপিআই (এম) এর বিহারী লাল ভট্টাচার্য ১৯৮২ সালে কংগ্রেসের সুধাংশু শেখর তিওয়ারিকে পরাজিত করেন। সিপিআই (এম) এর অশ্বিনী কুমার রাজ ১৯৭৭ সালে কংগ্রেসের সুধাংশু শেখর তিওয়ারিকে পরাজিত করেন।
Option A: সিপিআইয়ের
Option B: রাজ্য
Option C: কংগ্রেসের
Option D: ভারতীয়
[A]: কংগ্রেসের
[Q]: Statement: অভিজ্ঞতাবিহীন অবস্থায় মিডিয়াম পেস বোলিংয়ে পারদর্শী আনোয়ার ২০০৩ সালের মাঝামাঝি সময়ে অস্ট্রেলিয়া সফরে টেস্ট দলের সদস্যরূপে প্রতিনিধিত্ব করেন। সিরিজের দ্বিতীয় টেস্টে ৩০তম খেলোয়াড়রূপে টেস্ট ক্যাপ পরিধান করেন। ২৫ জুলাই, ২০০৩ তারিখে কেয়ার্নসে স্বাগতিক <MASK> বিপক্ষে তার টেস্ট অভিষেক হয়। কিন্তু কোন উইকেট লাভ করতে পারেননি।
Option A: বিসিবিতে
Option B: অস্ট্রেলিয়ার
Option C: বাংলাদেশের
Option D: IN-PY
[A]: অস্ট্রেলিয়ার
[Q]: Statement: নুরুল কাদের খানের জন্ম তৎকালীন <MASK> জেলার (এখনকার মুন্সিগঞ্জ জেলা) বিক্রমপুর মহকুমার টঙ্গিবাড়িতে। তার বাবার নাম আবদুল লতিফ খান এবং মায়ের নাম কুলসুম বেগম। জন্মের পর তার নাম রাখা হয় মোহাম্মদ নুরুল কাদের খান। ডাক নাম ছিল ঝিলু। ১৯৭১ সালে ঘাতক পাকিস্তানী হানাদার বাহিনীর অত্যাচারের কারণে ঘৃণাবশত নিজের নামের শেষাংশ খান নিজেই ছেঁটে দেন এবং তারপর থেকে মোহাম্মদ নুরুল কাদের এবং সংক্ষেপে নুরুল কাদের নামেই পরিচিতি পান । ছয় ভাইবোনের মধ্যে নুরুল কাদের ছিলেন সবার ছোট।
Option A: বাংলাদেশী
Option B: ভারতীয়
Option C: মুক্তিযোদ্ধা
Option D: ঢাকা
[A]:
|
ঢাকা
|
task945_wiki_cloze_bn_multiple_choice_question_answering
|
NIv2
|
fs_opt
| 5
|
test
|
Q: You are given a statement written in Bengali. Choose the most logical word from the given 4 options which can be used to replace the <MASK> token in the statement . Output the word from the correct option .
Statement: যেমন আমরা তথা আমাদের ছায়াপথ, আকাশগঙ্গা, কোন স্তবকের অন্তর্ভুক্ত নয়। বরং আমাদের ছায়াপথ, <MASK> এবং আরও বেশ কিছু ছায়াপথ ও উপছায়াপথ মিলে একটি ছায়াপথ পুঞ্জ গঠন করেছে যার নাম স্থানীয় পুঞ্জ তথা লোকাল গ্রুপ।
Option A: Baruihuda
Option B: ছায়াপথের
Option C: অ্যান্ড্রোমিডা
Option D: আকাশগঙ্গা
A:
|
অ্যান্ড্রোমিডা
|
task945_wiki_cloze_bn_multiple_choice_question_answering
|
NIv2
|
zs_opt
| 7
|
validation
|
In this task, you are given two lists A,B. Find the longest common subsequence in the lists A and B.
Example input: [5797, 8817, '8297', 'b', 'U', 'b'], [5843, 8809, '8297', 'b', 'W', 'C']
Example output: 8297, b
Example explanation: Here, '8297, b' is the longest common subsequence in both the input lists [5797, 8817, '8297', 'b', 'U', 'b'] and [5843, 8809, '8297', 'b', 'W', 'C'].
Q: [3957, 205, 'U', 'P', 3513, 7985, 'n', 'L', 'G', 'h', '7083', '9427', 'A', 'W', 'Q', '1419', 'V', '3251', 'f', '3763', '1571', '6261', 'v', 'U', 'G', '3687', '3101', 'b', '7555', 'Q', 'q', 579, 2041, 'i', 6279, 7027, 'd', 6323, 'F', 8273, 'f'], [5117, 4221, 'Y', 'l', 'B', 'q', 'g', 'W', 2915, 'a', 'N', 'Z', 'v', 'h', '7083', '9427', 'A', 'W', 'Q', '1419', 'V', '3251', 'f', '3763', '1571', '6261', 'v', 'U', 'G', '3687', '3101', 'b', '7555', 'Q', 'D', 'T', 1057, 'Q', 6761, 'p', 9909, 5243]
A:
|
h, 7083, 9427, A, W, Q, 1419, V, 3251, f, 3763, 1571, 6261, v, U, G, 3687, 3101, b, 7555, Q
|
task605_find_the_longest_common_subsequence_in_two_lists
|
NIv2
|
fs_opt
| 3
|
train
|
You will be given a definition of a task first, then some input of the task.
In this task, you are given two lists A,B. Find the longest common subsequence in the lists A and B.
[8861, 'A', 5269, 'a', 'z', 987, 497, 'd', 'X', 4711, 1305, 'u', '5413', '3195', 'y', 'Y', '2065', 'w', '6747', 'T', '3023', '3645', 'J', '6393', 'z', 'N', 5105, 'D', 'G', 'i'], ['A', 'N', 6055, '5413', '3195', 'y', 'Y', '2065', 'w', '6747', 'T', '3023', '3645', 'J', '6393', 'z', 'T', 8155, 'P']
Output:
|
5413, 3195, y, Y, 2065, w, 6747, T, 3023, 3645, J, 6393, z
|
task605_find_the_longest_common_subsequence_in_two_lists
|
NIv2
|
zs_opt
| 1
|
train
|
In this task, you are given two lists A,B. Find the longest common subsequence in the lists A and B.
Let me give you an example: [5797, 8817, '8297', 'b', 'U', 'b'], [5843, 8809, '8297', 'b', 'W', 'C']
The answer to this example can be: 8297, b
Here is why: Here, '8297, b' is the longest common subsequence in both the input lists [5797, 8817, '8297', 'b', 'U', 'b'] and [5843, 8809, '8297', 'b', 'W', 'C'].
OK. solve this:
['Z', 1843, 'u', 863, 'y', 'H', '6811', '9025', '1173', 'x', 't'], [5715, 3439, 1025, 10007, 'y', 'H', '6811', '9025', '1173', 'v', 2945, 'V', 'g']
Answer:
|
y, H, 6811, 9025, 1173
|
task605_find_the_longest_common_subsequence_in_two_lists
|
NIv2
|
fs_opt
| 8
|
train
|
In this task, you are given two lists A,B. Find the longest common subsequence in the lists A and B.
Example Input: ['U', 2021, 9935, '873', 'T', '9883', 'y', 8789, 'v'], ['g', 7321, '873', 'T', '9883', 'p', 9721]
Example Output: 873, T, 9883
Example Input: [3323, 'G', 'k', 9183, 't', 9885, 3767, 'D', 'u', 'C', 'O', '9231', 's', 'd', '3497', '6063', 'Z', 'S', '2799', 'u', '2777', '8507', 'G', 'j', 'z', 'B', 'F', 't', '5527', '8931', 'r', '10029', '7305', 'H', 't', 7899, 'F'], ['h', 'E', 4401, 'C', 1267, 1175, 2939, 'g', 'n', 'm', 'u', 'C', 'O', '9231', 's', 'd', '3497', '6063', 'Z', 'S', '2799', 'u', '2777', '8507', 'G', 'j', 'z', 'B', 'F', 't', '5527', '8931', 'r', '10029', '7305', 'H', 'q', 4957, 6929, 6135, 'M', 1875, 4101, 'L', 9477, 'Q', 'Z', 1039, 'A', 4355, 'l', 'w', 's', 4485, 'L', 6895, 753, 'm', 1205, 'V', 821, 8801]
Example Output: u, C, O, 9231, s, d, 3497, 6063, Z, S, 2799, u, 2777, 8507, G, j, z, B, F, t, 5527, 8931, r, 10029, 7305, H
Example Input: ['Q', 'T', 6451, 's', 1077, 's', 4181, 429, '5405', '6625', '8369', 'X', '937', 'R', '5975', '5901', 'D', '4491', 'E', '4257', 'h', '3653', '9221', 'C', '4251', '5739', '2855', '7685', '479', '2013', 'c', '7801', 'H', 'W', '5499', '6453', 'S', 'l', 9589, 719, 9801, 3075, 9803, 'U', 'c', 2487, 'y', 6141, 'd', 1143, 5913, 1233, 's', 6185, 2315, 779, 4681, 51, 7807, 2781, 'C', 7245, 3673], [7547, 8737, 1311, 4627, 'E', 'c', '5405', '6625', '8369', 'X', '937', 'R', '5975', '5901', 'D', '4491', 'E', '4257', 'h', '3653', '9221', 'C', '4251', '5739', '2855', '7685', '479', '2013', 'c', '7801', 'H', 'W', '5499', '6453', 'S', 'C', 8195, 3127, 'h', 'x', 'O', 'z', 'e', 'q', 895, 'B', 'z', 6815, 'M', 673, 'q', 'L', 'e', 'm', 'Z']
Example Output:
|
5405, 6625, 8369, X, 937, R, 5975, 5901, D, 4491, E, 4257, h, 3653, 9221, C, 4251, 5739, 2855, 7685, 479, 2013, c, 7801, H, W, 5499, 6453, S
|
task605_find_the_longest_common_subsequence_in_two_lists
|
NIv2
|
fs_opt
| 3
|
train
|
TASK DEFINITION: In this task, you are given two lists A,B. Find the longest common subsequence in the lists A and B.
PROBLEM: [9875, 'g', 8729, 'h', 'F', 'v', 'v', 8307, 6379, 3165, 7055, 'f', 'p', 3707, 'P', 6305, 'h', '9891', '2783', 'D', '7567', '95', 'T', 'U', '2035', 'W', 'C', 'B', '9943', 'B', '9033', '6511', 'e', '2623', 'O', 'Z', 'k', 7761], [9061, 1241, 'd', 3917, 'm', 9457, 'n', 1493, 725, 'O', 'h', '9891', '2783', 'D', '7567', '95', 'T', 'U', '2035', 'W', 'C', 'B', '9943', 'B', '9033', '6511', 'e', '2623', 'O', 'Z', 'o', 'J', 'c', 6919, 'O', 'O', 8809, 'J', 'v', 'O', 4633, 941, 'z', 6667, 'X', 'C', 'd', 5189]
SOLUTION: h, 9891, 2783, D, 7567, 95, T, U, 2035, W, C, B, 9943, B, 9033, 6511, e, 2623, O, Z
PROBLEM: [93, 'H', 'd', 'z', 'G', 'u', '9033', '709', '6413', 'C', 'j', 8909, 5687], [9451, 2867, 'G', 'u', '9033', '709', '6413', 'Y', 'y']
SOLUTION: G, u, 9033, 709, 6413
PROBLEM: [7023, 'O', 'm', 9813, 6515, 's', '339', '3733', '9085', '2075', '541', '8659', 'Y', 'm', 'w', 'I', 'T', 'M', '1555', '1933', 's', 'x', '1257', '6417', '4493', 'o', 'o', 'q', '9175', '1135', '4305', 'v', '2811', 'H', 6871, 8929, 7909, 2609, 'T', 7237, 1939, 't', 'W', 'r', 'f', 1379, 'q', 3, 6365, 'a'], ['c', 7853, 'Y', 'Q', 'i', 7287, 3327, 'T', 4679, 'b', 's', '339', '3733', '9085', '2075', '541', '8659', 'Y', 'm', 'w', 'I', 'T', 'M', '1555', '1933', 's', 'x', '1257', '6417', '4493', 'o', 'o', 'q', '9175', '1135', '4305', 'v', '2811', 'P', 'd', 221, 7657, 9183]
SOLUTION:
|
s, 339, 3733, 9085, 2075, 541, 8659, Y, m, w, I, T, M, 1555, 1933, s, x, 1257, 6417, 4493, o, o, q, 9175, 1135, 4305, v, 2811
|
task605_find_the_longest_common_subsequence_in_two_lists
|
NIv2
|
fs_opt
| 8
|
train
|
You will be given a definition of a task first, then some input of the task.
In this task, you are given two lists A,B. Find the longest common subsequence in the lists A and B.
['z', 5029, 'C', 3513, 4009, 'C', 'V', 'c', 'y', 'H', 'e', 'u', '2819', '9137', 'V', '5545', '1255', '4149', '1071', '9087', '7251', 'L', 'U', '1697', '2783', 'a', '3571', 'S', 8827, 5201, 8991, 2259, 'B', 'H', 8983, 'v', 'J', 'J', 4531, 'R', 'X', 'I', 1353], ['s', 6237, 'i', 'G', 7329, 4099, 7253, 5751, 1109, 8381, 5525, 'C', 'V', 'c', 'y', 'H', 'e', 'u', '2819', '9137', 'V', '5545', '1255', '4149', '1071', '9087', '7251', 'L', 'U', '1697', '2783', 'a', '3571', 'q', 'R']
Output:
|
C, V, c, y, H, e, u, 2819, 9137, V, 5545, 1255, 4149, 1071, 9087, 7251, L, U, 1697, 2783, a, 3571
|
task605_find_the_longest_common_subsequence_in_two_lists
|
NIv2
|
zs_opt
| 1
|
train
|
Detailed Instructions: In this task, you are given two lists A,B. Find the longest common subsequence in the lists A and B.
Q: ['w', 'q', 1707, 3067, 3239, 3849, 'd', 6265, 'b', 1505, 'F', 8313, '4803', '5211', '647', 't', '9951', '8727', 'N', '5045', '5717', '9915', '5147', '441', 'Y', '2581', 'N', 't', '3763', 'Y', 1849, 8491, 'X', 'G'], [4013, 'f', 7963, 'c', 3789, 'N', 'm', 'E', 7143, 'A', 'c', 4443, 'U', 359, 'h', '4803', '5211', '647', 't', '9951', '8727', 'N', '5045', '5717', '9915', '5147', '441', 'Y', '2581', 'N', 't', '3763', 'U', 'U', 1513, 9409, 8845, 8037, 'c', 'm', 1249, 9671, 8875, 3119]
A:
|
4803, 5211, 647, t, 9951, 8727, N, 5045, 5717, 9915, 5147, 441, Y, 2581, N, t, 3763
|
task605_find_the_longest_common_subsequence_in_two_lists
|
NIv2
|
zs_opt
| 9
|
train
|
Instructions: In this task, you are given two lists A,B. Find the longest common subsequence in the lists A and B.
Input: [2001, 2739, 7183, 5637, 5587, 685, 'G', '107', 'N', 'i', '687', 'm', '161', 'd', '4831', '7457', 'l', 'F', '2137', 'p', '2175', 'x', 'a', 'r', 'D', '6933', '9765', 'x', '5659', 'Y', 'j', 'D', 'b', 'u', 9343, 't', 'z', 6445, 's', 949, 'L', 6259, 2137, 'b', 'W', 6925, 4419, 'P', 1159, 't', 'w', 2379, 4683, 't', 'N', 4329], ['E', 7669, 'R', 1561, '107', 'N', 'i', '687', 'm', '161', 'd', '4831', '7457', 'l', 'F', '2137', 'p', '2175', 'x', 'a', 'r', 'D', '6933', '9765', 'x', '5659', 'Y', 'j', 'D', 'b', 'U', 'v', 3851, 'Y', 'o', 'R', 'C', 713, 'M', 't', 'P', 7615, 'Q']
Output:
|
107, N, i, 687, m, 161, d, 4831, 7457, l, F, 2137, p, 2175, x, a, r, D, 6933, 9765, x, 5659, Y, j, D, b
|
task605_find_the_longest_common_subsequence_in_two_lists
|
NIv2
|
zs_opt
| 3
|
train
|
In this task, you are given two lists A,B. Find the longest common subsequence in the lists A and B.
[6129, 5205, 127, 9057, 6969, 'A', 5777, 2053, 2141, 7555, 'n', 5593, 4695, 2315, 913, 'b', 3471, 2447, 6689, 'B', '1717', 'S', '9761', '4155', '5049', '879', 'n', '7459', '8765', 'p', '5109', '3135', 'F', '4463', '103', '7581', '7305', 'Q', 'V', 'f', '4413', 'E', 'L', '7993', 'Q', 'E', '9719', '6599', 'u', '2895', 'j', 3893, 855, 'M', 831, 'q', 'V', 'h', 'l', 5363, 'H'], [8061, 5223, 'A', 4297, 'e', 4831, 'w', 'a', 8171, 7891, 'F', 8403, 'F', 5379, 4651, 'M', 1727, 'b', 5653, '1717', 'S', '9761', '4155', '5049', '879', 'n', '7459', '8765', 'p', '5109', '3135', 'F', '4463', '103', '7581', '7305', 'Q', 'V', 'f', '4413', 'E', 'L', '7993', 'Q', 'E', '9719', '6599', 'u', '2895', 'Q', 'E', 2833, 9505, 'C', 6339, 'E', 1589, 5851, 'K', 'r', 4829, 'O', 373, 'K', 8289, 3825, 'i', 'p', 7325, 3637, 6649, 'p', 6411, 2201, 'S', 'Q', 9247, 't']
1717, S, 9761, 4155, 5049, 879, n, 7459, 8765, p, 5109, 3135, F, 4463, 103, 7581, 7305, Q, V, f, 4413, E, L, 7993, Q, E, 9719, 6599, u, 2895
[3453, 883, 'a', 'C', 7891, 'T', 8245, 9759, 'J', 'Z', 6515, 'B', 'j', 3353, 859, 2123, 3289, 'I', 'e', 'p', 4473, 'A', 7815, 4401, 'Z', 2071, 'm', 'C', '4283', '8455', '697', '1653', '6739', '7729', 'K', 'a', 'v', 'c', '69', '7427', '4721', '7015', '497', '7697', '7533', 'l', 'l', 'U', '6481', 'm', '5107', 'v', 'M', 'u', '3649', 'O', 5601, 5705, 'B', 2271, 7875, 'E', 4389, 'U', 9283, 'v', 2119, 457, 'W', 'd', 'C', 'i', 3311, 'X'], ['u', 'z', 'I', 'x', 'l', 'm', 'C', '4283', '8455', '697', '1653', '6739', '7729', 'K', 'a', 'v', 'c', '69', '7427', '4721', '7015', '497', '7697', '7533', 'l', 'l', 'U', '6481', 'm', '5107', 'v', 'M', 'u', '3649', 'J', 9139, 9981, 'O', 5677, 9201, 3941, 'r', 'w', 5597, 9451, 2807, 3577]
m, C, 4283, 8455, 697, 1653, 6739, 7729, K, a, v, c, 69, 7427, 4721, 7015, 497, 7697, 7533, l, l, U, 6481, m, 5107, v, M, u, 3649
[9867, 'R', 's', '8405', 'Q', 7753], [6583, 8865, 's', '8405', 'n', 1659]
|
s, 8405
|
task605_find_the_longest_common_subsequence_in_two_lists
|
NIv2
|
fs_opt
| 0
|
test
|
In this task, you are given two lists A,B. Find the longest common subsequence in the lists A and B.
Example: [5797, 8817, '8297', 'b', 'U', 'b'], [5843, 8809, '8297', 'b', 'W', 'C']
Example solution: 8297, b
Example explanation: Here, '8297, b' is the longest common subsequence in both the input lists [5797, 8817, '8297', 'b', 'U', 'b'] and [5843, 8809, '8297', 'b', 'W', 'C'].
Problem: ['B', 5983, 'E', 6691, 'x', 6511, 3905, 'A', '2023', 'j', '2557', '9801', '3717', 'S', 'U', 'I', '5475', '1619', 'G', 5501, 'K', 'h', 2729, 'D', 8299, 4399, 's', 737], [5427, 8515, 2299, 'j', 'm', 't', 'A', '2023', 'j', '2557', '9801', '3717', 'S', 'U', 'I', '5475', '1619', 'w', 'B', 7211, 1485]
|
Solution: A, 2023, j, 2557, 9801, 3717, S, U, I, 5475, 1619
|
task605_find_the_longest_common_subsequence_in_two_lists
|
NIv2
|
fs_opt
| 5
|
validation
|
Detailed Instructions: The provided file includes English sentences, and we ask you to translate those to the Hindi language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) Note the input can be lowercased or upercased. Please do the same in your translations. 3) The numbers present in the input should be preserved in English language in output
See one example below:
Problem: What's going on
Solution: क्या हो रहा है ये?
Explanation: The translation is fluent, formal, and accurate and preserves the question in output language.
Problem: This temple built near golf course and airport is believed to be the residence of God.
Solution:
|
गोल्फ कोर्स और हवाई अड्डे के पास बने इस मंदिर को भगवान का निवास स्थान माना जाता है।
|
task1353_hind_encorp_translation_en_hi
|
NIv2
|
fs_opt
| 4
|
train
|
Detailed Instructions: The provided file includes English sentences, and we ask you to translate those to the Hindi language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) Note the input can be lowercased or upercased. Please do the same in your translations. 3) The numbers present in the input should be preserved in English language in output
See one example below:
Problem: What's going on
Solution: क्या हो रहा है ये?
Explanation: The translation is fluent, formal, and accurate and preserves the question in output language.
Problem: All the ancient medical texts state that prameha of any variety , if neglected , will finally lead to madhumeha and in due course become incurable .
Solution:
|
प्राचीन चिकित्सा शास्त्रों में यह कहा गया है कि यदि किसी भी प्रकार के प्रमेह को उपेक्षित किया जाये तो अंतत : वह मधुमेह बन जाता है जो बाद में लाइलाज हो जाता है .
|
task1353_hind_encorp_translation_en_hi
|
NIv2
|
fs_opt
| 4
|
train
|
TASK DEFINITION: The provided file includes English sentences, and we ask you to translate those to the Hindi language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) Note the input can be lowercased or upercased. Please do the same in your translations. 3) The numbers present in the input should be preserved in English language in output
PROBLEM: How could girls be sent to schools ; it would mean walking through public places , and contact with men .
SOLUTION: लडकियों को स्कूल कैसे भेजा जा सकता था क़्योंकि इसका अर्थ होता सार्वजनिक स्थानों से गुजरना और पुरूषों से संपर्क .
PROBLEM: Because in non technical literature have not clearly definition. so make a difference between the various form of related disease.According to World Heath Organization(WHO) these are define as a asbestosis,Lung cancer,Mesothelioma(It is vary rear cancer),when these are vary general then these are maximum related to asbestos.
SOLUTION: क्योंकि गैर-तकनीकी साहित्य में इसकी स्पष्ट व्याख्या नहीं है इसलिए सम्बन्धित रोगों के अनेक स्वरूपों के बीच अन्तर स्पष्ट करना होगा. विश्व स्वास्थ्य संगठन (डब्ल्यूएचओ) के अनुसार इन्हे एसबेस्टोसिस (asbestosis) फेफड़ों के कैंसर और मेसोथेलिओमा (mesothelioma)(आम तौर पर एक बहुत ही दुर्लभ कैंसर) के रूप में परिभाषित कर सकते हैं जब ये अधिक व्यापक हो जाते हैं तब ये अधिकतर एसबेस्टस से सम्बन्धित ही रहते हैं.
PROBLEM: And finally , there has been much talk but little action about rational energy pricing , reflecting real social cost of alternative sources of energy .
SOLUTION:
|
और अंत में , ऊर्जा के वैकल्पिक स्रोतों की वास्तविक सामाजिक लागत को दर्शाते तर्कसंगत ऊर्जा , मूल्यों के निर्धारण की केवल बातें ही होती रही हैं काम कुछ नहीं हुआ है .
|
task1353_hind_encorp_translation_en_hi
|
NIv2
|
fs_opt
| 8
|
train
|
The provided file includes English sentences, and we ask you to translate those to the Hindi language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) Note the input can be lowercased or upercased. Please do the same in your translations. 3) The numbers present in the input should be preserved in English language in output
Your strength has sorely been taxed imprisonment , banishment and disease , but rather than impairing , these have helped to broaden your sympathiesenlarging your vision so as to embrace the vast perspectives of history beyond any narrow limits of territory . . .. I feel that you have come with an errand to usher a new light of hope in your motherland . . .
|
कारावासों , निर्वासनों ओर रोगों ने तुम्हारी क्षमताओं को बहुत हलकान किया , मगर उन्हें क्षति पहुंचाना तो दूर , उन पीड़ाओं ने तुम्हारी संवेदनाओं को विस्तार दिया , जिससे तुम्हारी दृष्टि व्यापक हुई और तुम क्षेत्रीय संकीर्णताओं से परे रहकर इतिहास के विराट परिप्रेक्ष्य को हृदयंगम कर सके . . . मुझे लगता है , तुम अपनी मातृभूमि के लिए नयी रोशनी और उम्मीद के संदेशवाहक बनकर आये हो .
|
task1353_hind_encorp_translation_en_hi
|
NIv2
|
zs_opt
| 0
|
train
|
The provided file includes English sentences, and we ask you to translate those to the Hindi language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) Note the input can be lowercased or upercased. Please do the same in your translations. 3) The numbers present in the input should be preserved in English language in output
Ex Input:
the relics of creation and inferring what happened at the beginning,
Ex Output:
सृ्ष्टि के अवशेषों के माध्यम से यह अनुमान लगाने का प्रयास करेंगे कि आरंभ में क्या हुआ था,
Ex Input:
Some videos are for people above 18 years only like adult videos, pornography, nudity, defamation, harassment, advertisements and criminal conduct are prohibited.
Ex Output:
कुछ वीडियॊ उन्हीं उपयॊगकर्तॊं के लिए हैं जिनकी उम्र १८ साल या इससे अधिक है ( जैसे आपराधिक सामग्री वाले वीडियॊ) अश्लील साहित्य (pornography) नग्नता (nudity) मानहानि (defamation) उत्पीड़न (harassment) वाणिज्यिक और विज्ञापन सामग्री (advertisements)और आपराधिक व्यवहार कॊ बढ़ावा देने वाली सामग्री वाले वीडियो अपलॊड करना (criminal conduct)निषिद्ध है .
Ex Input:
Most of the highest mountain peaks of the world are situated at Himalaya.
Ex Output:
|
संसार की अधिकाश ऊँची पर्वत चोटियाँ हिमालय में ही स्थित हैं।
|
task1353_hind_encorp_translation_en_hi
|
NIv2
|
fs_opt
| 1
|
train
|
Q: The provided file includes English sentences, and we ask you to translate those to the Hindi language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) Note the input can be lowercased or upercased. Please do the same in your translations. 3) The numbers present in the input should be preserved in English language in output
As a result , production of super varieties was increasing though the acreage was falling .
A:
|
परिणामस्वरूप , अत्यधिक उन्नत किस्मों के उत्पादन में वृद्धि हो रही थी.यद्यपि भूमि क्षेत्र कम हो रहा था .
|
task1353_hind_encorp_translation_en_hi
|
NIv2
|
zs_opt
| 7
|
train
|
Given the task definition, example input & output, solve the new input case.
The provided file includes English sentences, and we ask you to translate those to the Hindi language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) Note the input can be lowercased or upercased. Please do the same in your translations. 3) The numbers present in the input should be preserved in English language in output
Example: What's going on
Output: क्या हो रहा है ये?
The translation is fluent, formal, and accurate and preserves the question in output language.
New input case for you: However , they do not constitute anything like a single all-India cadre .
Output:
|
पिर . . ..भी , उनका कोई एक अखिल भारतीय संवर्ग नहीं है .
|
task1353_hind_encorp_translation_en_hi
|
NIv2
|
fs_opt
| 1
|
train
|
Teacher: The provided file includes English sentences, and we ask you to translate those to the Hindi language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) Note the input can be lowercased or upercased. Please do the same in your translations. 3) The numbers present in the input should be preserved in English language in output
Teacher: Now, understand the problem? If you are still confused, see the following example:
What's going on
Solution: क्या हो रहा है ये?
Reason: The translation is fluent, formal, and accurate and preserves the question in output language.
Now, solve this instance: If I spin this pulley, the small one's going to spin much faster.
Student:
|
अगर मैं इस चक्की को घुमाऊं, तो छोटा वाला तेज़ी से घूमेगा।
|
task1353_hind_encorp_translation_en_hi
|
NIv2
|
fs_opt
| 2
|
train
|
Definition: The provided file includes English sentences, and we ask you to translate those to the Hindi language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) Note the input can be lowercased or upercased. Please do the same in your translations. 3) The numbers present in the input should be preserved in English language in output
Input: They searched everywhere , and found that the oasis was much larger than they could have imagined ;
Output:
|
उन्होंने हर जगह उसकी तलाश की मगर नखलिस्तान उनकी कल्पना से कहीं ज्यादा बड़ा था । <s> उस में सैकड़ों तंबू थे ।
|
task1353_hind_encorp_translation_en_hi
|
NIv2
|
zs_opt
| 2
|
test
|
The provided file includes English sentences, and we ask you to translate those to the Hindi language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) Note the input can be lowercased or upercased. Please do the same in your translations. 3) The numbers present in the input should be preserved in English language in output
One example is below.
Q: What's going on
A: क्या हो रहा है ये?
Rationale: The translation is fluent, formal, and accurate and preserves the question in output language.
Q: Scbaceous prominences: look like spots of mustard emerged from penis's sebaceous glands and common
A:
|
वसामय विशिष्ठताएं (Sebaceous prominences): फ़ोर्डाइस के धब्बे के समान ही शिश्न दण्ड पर वसामय ग्रंथियों में स्थित उभरे हुये छोटे धब्बे हैं और सामान्य हैं।
|
task1353_hind_encorp_translation_en_hi
|
NIv2
|
fs_opt
| 9
|
validation
|
In this task, you are given a list of integers and an integer k. You need to find the kth largest element in the input list.
Q: [102, 296, 258, 44, 199, 174, 216, 299, 188, 147, 255, 28, 241, 21, 32, 243, 276, 128, 57, 142], k=13
A:
|
142
|
task1194_kth_largest_element
|
NIv2
|
zs_opt
| 4
|
train
|
Instructions: In this task, you are given a list of integers and an integer k. You need to find the kth largest element in the input list.
Input: [270, 194, 176, 246, 186, 76, 20, 226, 151, 260, 157, 263, 265, 141, 123, 225, 98, 48, 25, 67], k=20
Output:
|
20
|
task1194_kth_largest_element
|
NIv2
|
zs_opt
| 3
|
train
|
In this task, you are given a list of integers and an integer k. You need to find the kth largest element in the input list.
Example input: [128, 277, 83, 280, 193, 19, 111, 154, 41, 292, 29, 53, 232, 153, 131, 151, 121, 262, 270, 132], k=15
Example output: 111
Example explanation: 111 is the 15th largest element in the list.
Q: [245, 71, 125, 49, 16, 123, 263, 12, 151, 30, 57, 297, 193, 17, 244, 40, 195, 248, 78, 229], k=14
A:
|
57
|
task1194_kth_largest_element
|
NIv2
|
fs_opt
| 3
|
train
|
In this task, you are given a list of integers and an integer k. You need to find the kth largest element in the input list.
Ex Input:
[28, 92, 72, 299, 153, 66, 261, 160, 218, 130, 235, 262, 10, 51, 17, 141, 14, 277, 247, 223], k=18
Ex Output:
17
Ex Input:
[83, 143, 65, 213, 262, 235, 230, 226, 222, 205, 224, 179, 180, 183, 166, 82, 104, 148, 16, 20], k=10
Ex Output:
180
Ex Input:
[190, 182, 128, 18, 241, 135, 93, 298, 40, 144, 262, 147, 140, 204, 254, 11, 168, 276, 117, 13], k=10
Ex Output:
|
147
|
task1194_kth_largest_element
|
NIv2
|
fs_opt
| 1
|
train
|
Detailed Instructions: In this task, you are given a list of integers and an integer k. You need to find the kth largest element in the input list.
Problem:[13, 263, 40, 145, 234, 272, 43, 56, 131, 273, 82, 48, 122, 182, 244, 26, 64, 121, 32, 202], k=4
Solution:
|
244
|
task1194_kth_largest_element
|
NIv2
|
zs_opt
| 8
|
train
|
In this task, you are given a list of integers and an integer k. You need to find the kth largest element in the input list.
Q: [52, 229, 213, 60, 22, 228, 222, 74, 181, 249, 209, 170, 24, 103, 66, 47, 76, 245, 142, 35], k=2
A: 245
****
Q: [287, 125, 243, 144, 189, 12, 284, 91, 294, 51, 52, 19, 281, 166, 192, 269, 199, 18, 61, 180], k=14
A: 91
****
Q: [134, 38, 49, 21, 18, 61, 42, 109, 108, 26, 62, 99, 151, 176, 269, 70, 261, 97, 234, 214], k=11
A:
|
97
****
|
task1194_kth_largest_element
|
NIv2
|
fs_opt
| 4
|
train
|
Given the task definition and input, reply with output. In this task, you are given a list of integers and an integer k. You need to find the kth largest element in the input list.
[125, 193, 215, 227, 176, 50, 92, 145, 258, 271, 203, 262, 273, 30, 237, 139, 121, 272, 107, 115], k=11
|
176
|
task1194_kth_largest_element
|
NIv2
|
zs_opt
| 5
|
train
|
In this task, you are given a list of integers and an integer k. You need to find the kth largest element in the input list.
Example Input: [276, 188, 261, 277, 93, 230, 233, 22, 212, 97, 204, 40, 21, 226, 162, 157, 89, 216, 284, 271], k=2
Example Output: 277
Example Input: [109, 71, 25, 182, 65, 202, 184, 161, 272, 286, 299, 156, 194, 150, 129, 230, 266, 283, 297, 252], k=14
Example Output: 156
Example Input: [140, 52, 172, 175, 201, 159, 291, 255, 93, 10, 111, 125, 221, 149, 92, 218, 199, 205, 108, 55], k=19
Example Output:
|
52
|
task1194_kth_largest_element
|
NIv2
|
fs_opt
| 3
|
train
|
Definition: In this task, you are given a list of integers and an integer k. You need to find the kth largest element in the input list.
Input: [52, 203, 258, 170, 201, 122, 166, 110, 85, 176, 285, 113, 19, 18, 253, 279, 16, 259, 257, 89], k=15
Output:
|
89
|
task1194_kth_largest_element
|
NIv2
|
zs_opt
| 2
|
test
|
In this task, you are given a list of integers and an integer k. You need to find the kth largest element in the input list.
Ex Input:
[59, 234, 102, 24, 260, 125, 79, 116, 159, 285, 173, 105, 21, 29, 40, 279, 130, 15, 222, 219], k=16
Ex Output:
40
Ex Input:
[13, 263, 40, 145, 234, 272, 43, 56, 131, 273, 82, 48, 122, 182, 244, 26, 64, 121, 32, 202], k=4
Ex Output:
244
Ex Input:
[266, 187, 217, 296, 23, 185, 263, 136, 138, 15, 167, 82, 134, 183, 273, 14, 97, 133, 190, 84], k=20
Ex Output:
|
14
|
task1194_kth_largest_element
|
NIv2
|
fs_opt
| 1
|
validation
|
instruction:
In this task, you are given a sentence in the English and Japanese language. Your task is check if the Japanese sentence is translation of English. if the translation is correct than generate label "Yes", otherwise generate label "No".
question:
English: The news lessened fears about the country's major financial institutions collapsing after the collapse of Lehman Brothers in September.
Japanese: そのニュースは、9月のリーマン・ブラザーズの破綻後の、国の大手金融機関の破綻に関する不安を軽減した。
answer:
Yes
question:
English: This spill could devastate the fishing industry of Canada, and harm any potential tourism on the beautiful coastal waters of Eastern Canada.
Japanese: ActionAgainstHungerによると、急性栄養失調の子供たちの数は、シエラレオネのモヤンバ地区で、WHOの緊急状態かどうかの限界のレベルである2％のほぼ2倍に達した。
answer:
No
question:
English: Three million people were affected by the tropical storm which Xinhua, the state news agency, estimated would cost three billion yuan ($375 million) damage.
Japanese: すべては、紛争の結果としてアメリカ合衆国のありうる武装干渉を引き起こすようになっていた。
answer:
|
No
|
task437_alt_en_ja_answer_generation
|
NIv2
|
fs_opt
| 9
|
train
|
instruction:
In this task, you are given a sentence in the English and Japanese language. Your task is check if the Japanese sentence is translation of English. if the translation is correct than generate label "Yes", otherwise generate label "No".
question:
English: Bucharest was chosen from over 500 other candidate cities and has waited for the event for a couple of years.
Japanese: アル・マリキ氏でさえ、ブッシュ氏が到着する5分前まで彼が来ていることを知らなかった。
answer:
No
question:
English: Museveni stressed in this statement on Wednesday, that the Member of Parliament who drafted the legislation in question, although he is a member of the NRM, was not following government policy and did so solely as an individual.
Japanese: ケネディ対ルイジアナ州裁判では、ルイジアナ州ニューオリンズのパトリック・ケネディーは、8才の継娘を強姦した罪で死刑を宣告された。
answer:
No
question:
English: The action is a part of a police operation against drug dealers.
Japanese: P・チダンバラム財務大臣は、供給側の制約によってインフレ率が高まっていることを強く懸念すると言った。
answer:
|
No
|
task437_alt_en_ja_answer_generation
|
NIv2
|
fs_opt
| 9
|
train
|
Definition: In this task, you are given a sentence in the English and Japanese language. Your task is check if the Japanese sentence is translation of English. if the translation is correct than generate label "Yes", otherwise generate label "No".
Input: English: He said that France has a list of 165 organizations considered to be "sects", which not just included Scientology but also covered Baptists such as former U.S. president Bill Clinton.
Japanese: 彼は、1961年にその設立当初から現在はITVボーダーと呼ばれている、カーライルに拠点を置くボーダーテレビジョンで働き続けた。
Output:
|
No
|
task437_alt_en_ja_answer_generation
|
NIv2
|
zs_opt
| 2
|
train
|
Given the task definition, example input & output, solve the new input case.
In this task, you are given a sentence in the English and Japanese language. Your task is check if the Japanese sentence is translation of English. if the translation is correct than generate label "Yes", otherwise generate label "No".
Example: English: Details were given by the UK Transport Secretary, Ruth Kelly, in the House of Commons at 1730 UTC yesterday.
Japanese: 詳細は昨日UTC17時30分、英国議会でイギリスのルス・ケリー運輸大臣によって伝えられた。
Output: Yes
The converted Japanese sentence is correctly translated from English because converted sentence has the same message as the original English sentence that Details were given yesterday in the House of Commons at 1730 UTC by Britain's Transport Secretary Ruth Kelly.
New input case for you: English: Group member Jessica Morrison claims there is a lot of secrecy surrounding the facility.
Japanese: 議会選挙はおそらく2014年の初めに開催され、続いて新しい議会において大統領選挙が行われる。
Output:
|
No
|
task437_alt_en_ja_answer_generation
|
NIv2
|
fs_opt
| 1
|
train
|
In this task, you are given a sentence in the English and Japanese language. Your task is check if the Japanese sentence is translation of English. if the translation is correct than generate label "Yes", otherwise generate label "No".
English: Tartaglia was holding a replica of Milan's famous Domo Cathedral as he struck the premier; the composition of the replica is unknown, but eyewitnesses suggest it may have been made from marble, iron or another heavy material.
Japanese: タルタリアは首相を襲撃した際、ミラノの有名なドーモ大聖堂の複製品を所持していて、複製品の構造は不明だが、目撃者によると大理石、鉄、もしくは他の重い物質から作られたようだ。
Yes
English: Nonetheless the national health system of Sierra Leone demands payment for all treatment with simple consultations costing as much as 25 days of income.
Japanese: それにもかかわらず、シエラレオネの国家保健制度は、簡単な診察が伴ったすべての処置に対し、収入の25日分の支払いを要求する。
Yes
English: Areas worst hit, like the small town of Pangandaran, are beginning to return to normal, and many businesses there have begun to open up again.
Japanese: サブプライムの貸し手は、典型的な信用履歴があるために、大手の貸し手からのローンに不適格な人々に住宅ローンを提供した。
|
No
|
task437_alt_en_ja_answer_generation
|
NIv2
|
fs_opt
| 0
|
train
|
Teacher: In this task, you are given a sentence in the English and Japanese language. Your task is check if the Japanese sentence is translation of English. if the translation is correct than generate label "Yes", otherwise generate label "No".
Teacher: Now, understand the problem? If you are still confused, see the following example:
English: Details were given by the UK Transport Secretary, Ruth Kelly, in the House of Commons at 1730 UTC yesterday.
Japanese: 詳細は昨日UTC17時30分、英国議会でイギリスのルス・ケリー運輸大臣によって伝えられた。
Solution: Yes
Reason: The converted Japanese sentence is correctly translated from English because converted sentence has the same message as the original English sentence that Details were given yesterday in the House of Commons at 1730 UTC by Britain's Transport Secretary Ruth Kelly.
Now, solve this instance: English: The family dispute has led to Ms Moore (59) filing for divorce from her husband of ten years, Gerald Moore (81), in August.
Japanese: 家族の争いは、ムーア（59）が8月に、10年間彼女の夫であるジェラルド・ムーア（81）から離婚を求められる原因となった。
Student:
|
Yes
|
task437_alt_en_ja_answer_generation
|
NIv2
|
fs_opt
| 2
|
train
|
Q: In this task, you are given a sentence in the English and Japanese language. Your task is check if the Japanese sentence is translation of English. if the translation is correct than generate label "Yes", otherwise generate label "No".
English: The blast caused a secondary explosion to some nearby cooking-gas cylinders.
Japanese: ウィルスがメリアルまたはＩＡHの研究室から流出したかどうかはまだ明らかになっていない。
A:
|
No
|
task437_alt_en_ja_answer_generation
|
NIv2
|
zs_opt
| 7
|
train
|
In this task, you are given a sentence in the English and Japanese language. Your task is check if the Japanese sentence is translation of English. if the translation is correct than generate label "Yes", otherwise generate label "No".
[EX Q]: English: After his dentist noticed something unusual with him, Brown was told to visit a doctor immediately.
Japanese: 歯科医が彼がいつもと何か違っていることに気付き、ブラウンはすぐに医者を訪ねるように言われた。
[EX A]: Yes
[EX Q]: English: Amnesty International has also urged the government of Pakistan to ensure the protection of journalists and media workers in the country.
Japanese: デルによると、ニュージーランドの630万台のコンピュータのうち25万台が古い旧式であるのは、調査によると主な理由は多くのコンピュータ保有者が2〜5年ごとに自分のコンピュータをアップグレードするためである。
[EX A]: No
[EX Q]: English: "There is a lot of interest in this product," said editor Keith Alcorn of the National Aids Manual.
Japanese: 「この製品に対して大変関心があります」と、ナショナル・エイズ・マニュアルの編集長キース・アルコーンは言った。
[EX A]:
|
Yes
|
task437_alt_en_ja_answer_generation
|
NIv2
|
fs_opt
| 6
|
train
|
Detailed Instructions: In this task, you are given a sentence in the English and Japanese language. Your task is check if the Japanese sentence is translation of English. if the translation is correct than generate label "Yes", otherwise generate label "No".
Problem:English: Four Greens MPs voted for the farm dog exemption and two against.
Japanese: その後、彼はノースメルボルンの車両基地でディーゼル電車を発車させることに失敗して、鍵を持ったまま逃走したと思われる。
Solution:
|
No
|
task437_alt_en_ja_answer_generation
|
NIv2
|
zs_opt
| 8
|
test
|
In this task, you are given a sentence in the English and Japanese language. Your task is check if the Japanese sentence is translation of English. if the translation is correct than generate label "Yes", otherwise generate label "No".
English: The strength of the decision was unexpected — this is the first major Internet copyright case to reach the Supreme Court in many years, and the Justices' unanimity sends a strong message about their lack of tolerance for companies designed to violate the law.
Japanese: 決定の強さは、予想外で、これは長い年月の中で、最高裁判所に達した最初の重要なインターネット著作権に関する事例であり、そして、裁判官は、満場一致で、法律を犯すように作られている会社を容認できなかったことについて強いメッセージを送る。
|
Yes
|
task437_alt_en_ja_answer_generation
|
NIv2
|
zs_opt
| 0
|
validation
|
Instructions: In this task, you will be presented with a question having multiple possible answers in Portuguese language. And you should choose a most suitable option out of "A", "B", "C", "D", and "E" based on your commonsense knowledge.
Input: Question: O marido nunca trabalhou um dia, mas depois de se divorciar recebeu uma pensão de alimentos, em que é que ele se tornou como resultado?
Options: A mais rico B maus sentimentos C angústia emocional D depressão E culpado
Output:
|
A
|
task1137_xcsr_pt_commonsense_mc_classification
|
NIv2
|
zs_opt
| 3
|
train
|
Teacher:In this task, you will be presented with a question having multiple possible answers in Portuguese language. And you should choose a most suitable option out of "A", "B", "C", "D", and "E" based on your commonsense knowledge.
Teacher: Now, understand the problem? Solve this instance: Question: O que é que os soldados fazem quando os seus oponentes ficam em vantagem?
Options: A seguem ordens B usar armas C reforços de chamada D voltar para casa E morrer em batalha
Student:
|
E
|
task1137_xcsr_pt_commonsense_mc_classification
|
NIv2
|
zs_opt
| 6
|
train
|
Detailed Instructions: In this task, you will be presented with a question having multiple possible answers in Portuguese language. And you should choose a most suitable option out of "A", "B", "C", "D", and "E" based on your commonsense knowledge.
Q: Question: Disseram que começaram o quê à primeira vista, muito antes do seu primeiro beijo?
Options: A apaixonar-se B apaixonando-se C sorriso D abraçar E a fazer perguntas
A:
|
B
|
task1137_xcsr_pt_commonsense_mc_classification
|
NIv2
|
zs_opt
| 9
|
train
|
Definition: In this task, you will be presented with a question having multiple possible answers in Portuguese language. And you should choose a most suitable option out of "A", "B", "C", "D", and "E" based on your commonsense knowledge.
Input: Question: Danny precisava de um rato novo, o seu estava a saltar sempre que o movia. Onde poderia estar o seu rato?
Options: A casas abandonadas B campo de milho C armário D ambiente de trabalho E gabinete
Output:
|
D
|
task1137_xcsr_pt_commonsense_mc_classification
|
NIv2
|
zs_opt
| 2
|
train
|
In this task, you will be presented with a question having multiple possible answers in Portuguese language. And you should choose a most suitable option out of "A", "B", "C", "D", and "E" based on your commonsense knowledge.
Let me give you an example: Question: Foi um presente popular e comum este ano, por isso dirigiu-se para o que seria fácil de encontrar?
Options: (A) árvore de natal (B) meia de natal (C) loja especializada (D) armário (E) grande armazém
The answer to this example can be: E
Here is why: The predicted answer is correct because out of given many options only department stores are easy to find.
OK. solve this:
Question: Se uma pessoa se sente doente, mas tem um projecto para terminar, o que deve fazer?
Options: A graças a deus B sentir vergonha C viver feliz D ficar na cama E trabalhar em casa
Answer:
|
E
|
task1137_xcsr_pt_commonsense_mc_classification
|
NIv2
|
fs_opt
| 8
|
train
|
In this task, you will be presented with a question having multiple possible answers in Portuguese language. And you should choose a most suitable option out of "A", "B", "C", "D", and "E" based on your commonsense knowledge.
Q: Question: Onde se pode ir a milhares de estações de autocarros?
Options: A centro da cidade B mapas C portland D cidade movimentada E rua
A:
|
A
|
task1137_xcsr_pt_commonsense_mc_classification
|
NIv2
|
zs_opt
| 4
|
train
|
You will be given a definition of a task first, then some input of the task.
In this task, you will be presented with a question having multiple possible answers in Portuguese language. And you should choose a most suitable option out of "A", "B", "C", "D", and "E" based on your commonsense knowledge.
Question: Onde poderia encontrar milhares ou milhões de escritórios?
Options: A cidade B trabalho C edifício escolar D edifício público E jardim zoológico
Output:
|
A
|
task1137_xcsr_pt_commonsense_mc_classification
|
NIv2
|
zs_opt
| 1
|
train
|
In this task, you will be presented with a question having multiple possible answers in Portuguese language. And you should choose a most suitable option out of "A", "B", "C", "D", and "E" based on your commonsense knowledge.
Example: Question: Foi um presente popular e comum este ano, por isso dirigiu-se para o que seria fácil de encontrar?
Options: (A) árvore de natal (B) meia de natal (C) loja especializada (D) armário (E) grande armazém
Example solution: E
Example explanation: The predicted answer is correct because out of given many options only department stores are easy to find.
Problem: Question: Onde pode ser encontrada uma abelha falante?
Options: A grande ao ar livre B livro de histórias C florista D campo de flores E jardim de ervas
|
Solution: B
|
task1137_xcsr_pt_commonsense_mc_classification
|
NIv2
|
fs_opt
| 5
|
train
|
In this task, you will be presented with a question having multiple possible answers in Portuguese language. And you should choose a most suitable option out of "A", "B", "C", "D", and "E" based on your commonsense knowledge.
Question: De que precisaria se quisesse fumar?
Options: A é estúpido B cigarro C junta de rolos D suicida-te E líquido de isqueiro.
|
B
|
task1137_xcsr_pt_commonsense_mc_classification
|
NIv2
|
zs_opt
| 0
|
test
|
Teacher:In this task, you will be presented with a question having multiple possible answers in Portuguese language. And you should choose a most suitable option out of "A", "B", "C", "D", and "E" based on your commonsense knowledge.
Teacher: Now, understand the problem? Solve this instance: Question: Durante a caça de inverno, ele podia ouvir cada movimento na floresta, isto era por causa do quê de tudo?
Options: A de estar parado B silêncio C estacionário D quietude E de pé parado
Student:
|
D
|
task1137_xcsr_pt_commonsense_mc_classification
|
NIv2
|
zs_opt
| 6
|
validation
|
The provided file includes inquiries about restaurants, and we ask you to translate those to the Spanish language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) The words between quotation marks *SHOULD NOT* be translated. We expect you to keep those values intact and include the quotation marks around them as well. 3) The fully capitalized words like DATE_0, or DURATION_0 *SHOULD NOT* be translated. Please keep them as they are in the translations. 4) Please do not localize measurement units like miles to kilometers during your translation. miles should be translated to its equivalent in your language. 6) Note the input is all lowercased except for special placeholders. Please do the same in your translations.
Q: what restaurant does " jeff weisnear " review for ?
A:
|
¿para qué restaurante escribe reseñas " jeff weisnear "?
|
task171_spl_translation_en_es
|
NIv2
|
zs_opt
| 4
|
train
|
The provided file includes inquiries about restaurants, and we ask you to translate those to the Spanish language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) The words between quotation marks *SHOULD NOT* be translated. We expect you to keep those values intact and include the quotation marks around them as well. 3) The fully capitalized words like DATE_0, or DURATION_0 *SHOULD NOT* be translated. Please keep them as they are in the translations. 4) Please do not localize measurement units like miles to kilometers during your translation. miles should be translated to its equivalent in your language. 6) Note the input is all lowercased except for special placeholders. Please do the same in your translations.
[EX Q]: search for " mexican " restaurants with at least 3 reviews .
[EX A]: buscar restaurantes " mexican " con, al menos, 3 opiniones.
[EX Q]: show me a list of " italian " restaurants .
[EX A]: muestra una lista de restaurantes " italian " .
[EX Q]: list " japanese " restaurants .
[EX A]:
|
enséñeme los restaurantes "japanese".
|
task171_spl_translation_en_es
|
NIv2
|
fs_opt
| 6
|
train
|
Definition: The provided file includes inquiries about restaurants, and we ask you to translate those to the Spanish language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) The words between quotation marks *SHOULD NOT* be translated. We expect you to keep those values intact and include the quotation marks around them as well. 3) The fully capitalized words like DATE_0, or DURATION_0 *SHOULD NOT* be translated. Please keep them as they are in the translations. 4) Please do not localize measurement units like miles to kilometers during your translation. miles should be translated to its equivalent in your language. 6) Note the input is all lowercased except for special placeholders. Please do the same in your translations.
Input: where can i find the closest " wawa " ?
Output:
|
¿dónde puedo encontrar el "wawa" más cercano?
|
task171_spl_translation_en_es
|
NIv2
|
zs_opt
| 2
|
train
|
Q: The provided file includes inquiries about restaurants, and we ask you to translate those to the Spanish language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) The words between quotation marks *SHOULD NOT* be translated. We expect you to keep those values intact and include the quotation marks around them as well. 3) The fully capitalized words like DATE_0, or DURATION_0 *SHOULD NOT* be translated. Please keep them as they are in the translations. 4) Please do not localize measurement units like miles to kilometers during your translation. miles should be translated to its equivalent in your language. 6) Note the input is all lowercased except for special placeholders. Please do the same in your translations.
what is the address of the " dunkin donuts " closet to me ?
A:
|
¿cuál es la dirección del " dunkin donuts " más cercano a mí?
|
task171_spl_translation_en_es
|
NIv2
|
zs_opt
| 7
|
train
|
The provided file includes inquiries about restaurants, and we ask you to translate those to the Spanish language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) The words between quotation marks *SHOULD NOT* be translated. We expect you to keep those values intact and include the quotation marks around them as well. 3) The fully capitalized words like DATE_0, or DURATION_0 *SHOULD NOT* be translated. Please keep them as they are in the translations. 4) Please do not localize measurement units like miles to kilometers during your translation. miles should be translated to its equivalent in your language. 6) Note the input is all lowercased except for special placeholders. Please do the same in your translations.
Q: show me " mexican " restaurants
A:
|
muéstrame restaurantes " mexican "
|
task171_spl_translation_en_es
|
NIv2
|
zs_opt
| 4
|
train
|
Part 1. Definition
The provided file includes inquiries about restaurants, and we ask you to translate those to the Spanish language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) The words between quotation marks *SHOULD NOT* be translated. We expect you to keep those values intact and include the quotation marks around them as well. 3) The fully capitalized words like DATE_0, or DURATION_0 *SHOULD NOT* be translated. Please keep them as they are in the translations. 4) Please do not localize measurement units like miles to kilometers during your translation. miles should be translated to its equivalent in your language. 6) Note the input is all lowercased except for special placeholders. Please do the same in your translations.
Part 2. Example
are there any " italian " restaurants nearby with 2 star reviews ?
Answer: ¿hay algún restaurante " italian " cerca con opiniones de 2 estrellas?
Explanation: The translation correctly preserves " italian " entity and is accurate
Part 3. Exercise
search for a " vegan " restaurant with at least 8 reviews .
Answer:
|
busque un restaurante "vegan" con al menos 8 comentarios.
|
task171_spl_translation_en_es
|
NIv2
|
fs_opt
| 7
|
train
|
instruction:
The provided file includes inquiries about restaurants, and we ask you to translate those to the Spanish language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) The words between quotation marks *SHOULD NOT* be translated. We expect you to keep those values intact and include the quotation marks around them as well. 3) The fully capitalized words like DATE_0, or DURATION_0 *SHOULD NOT* be translated. Please keep them as they are in the translations. 4) Please do not localize measurement units like miles to kilometers during your translation. miles should be translated to its equivalent in your language. 6) Note the input is all lowercased except for special placeholders. Please do the same in your translations.
question:
show me " cook out " .
answer:
muéstrame " cook out ".
question:
show me all 3 star restaurants
answer:
muéstrame todos los restaurantes de 3 estrellas.
question:
show me " thai " restaurants
answer:
|
muéstreme restaurantes "thai"
|
task171_spl_translation_en_es
|
NIv2
|
fs_opt
| 9
|
train
|
Given the task definition and input, reply with output. The provided file includes inquiries about restaurants, and we ask you to translate those to the Spanish language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) The words between quotation marks *SHOULD NOT* be translated. We expect you to keep those values intact and include the quotation marks around them as well. 3) The fully capitalized words like DATE_0, or DURATION_0 *SHOULD NOT* be translated. Please keep them as they are in the translations. 4) Please do not localize measurement units like miles to kilometers during your translation. miles should be translated to its equivalent in your language. 6) Note the input is all lowercased except for special placeholders. Please do the same in your translations.
what is the address of the " mei wei " restaurant ?
|
¿cuál es la dirección del restaurante " mei wei "?
|
task171_spl_translation_en_es
|
NIv2
|
zs_opt
| 5
|
train
|
Instructions: The provided file includes inquiries about restaurants, and we ask you to translate those to the Spanish language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) The words between quotation marks *SHOULD NOT* be translated. We expect you to keep those values intact and include the quotation marks around them as well. 3) The fully capitalized words like DATE_0, or DURATION_0 *SHOULD NOT* be translated. Please keep them as they are in the translations. 4) Please do not localize measurement units like miles to kilometers during your translation. miles should be translated to its equivalent in your language. 6) Note the input is all lowercased except for special placeholders. Please do the same in your translations.
Input: how many reviews has " mike " written about " pizza hut " ?
Output:
|
¿cuántas opiniones ha escrito " mike " sobre " pizza hut "?
|
task171_spl_translation_en_es
|
NIv2
|
zs_opt
| 3
|
test
|
The provided file includes inquiries about restaurants, and we ask you to translate those to the Spanish language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) The words between quotation marks *SHOULD NOT* be translated. We expect you to keep those values intact and include the quotation marks around them as well. 3) The fully capitalized words like DATE_0, or DURATION_0 *SHOULD NOT* be translated. Please keep them as they are in the translations. 4) Please do not localize measurement units like miles to kilometers during your translation. miles should be translated to its equivalent in your language. 6) Note the input is all lowercased except for special placeholders. Please do the same in your translations.
One example: are there any " italian " restaurants nearby with 2 star reviews ?
Solution is here: ¿hay algún restaurante " italian " cerca con opiniones de 2 estrellas?
Explanation: The translation correctly preserves " italian " entity and is accurate
Now, solve this: find me a restaurant called " lenny 's "
Solution:
|
encuéntrame un restaurante llamado " lenny 's "
|
task171_spl_translation_en_es
|
NIv2
|
fs_opt
| 6
|
validation
|
Given the question: I read this background article the other day: Often, foreign exchange controls can result in the creation of black markets to exchange the weaker currency for stronger currencies. This leads to a situation where the exchange rate for the foreign currency is much higher than the rate set by the government, and therefore creates a shadow currency exchange market. As such, it is unclear whether governments have the ability to enact effective exchange controls.[1] I am facing a new situation today: Pakistan tried to control the foreign exchange market and India didn't. By creating the foreign exchange control department, Pakistan tried to stop the devaluation of their currency. India chose to not interfere and let the exchange market regulate itself. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Which country was less regulated in regards to foreign currency exchange?
The answer is:
|
India
|
ropes_read_background_situation
|
P3
|
zs_opt
| 6
|
train
|
Please answer the following question: I read this background article the other day: Any unused energy in food, whether it comes from carbohydrates, proteins, or lipids, is stored in the body as fat. An extra 3,500 Calories of energy results in the storage of almost half a kilogram (1 pound) of stored body fat. People who consistently consume more food energy then they need may become obese. Obesity occurs when the body mass index is 30.0 kg/m 2 or greater. Body mass index (BMI) is an estimate of the fat content of the body. It is calculated by dividing a person’s weight (in kilograms) by the square of the person’s height (in meters). Obesity increases the risk of health problems such as type 2 diabetes and hypertension. I am facing a new situation today: Two men go into the doctor's office for a checkup. Stepping on the scale, the doctor weighs each of them. Tom has an average and healthy weight. However, Joe has a weight that indicates he is obese. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Who is more likely to have type 2 diabetes?
A:
|
Joe
|
ropes_read_background_situation
|
P3
|
zs_opt
| 8
|
train
|
Please answer the following question: I read this background article the other day: Rain dissolves fertilizer in the soil. Runoff carries it away. The fertilizer ends up in bodies of water, from ponds to oceans. The nitrogen is a fertilizer in the water bodies. Since there is a lot of nitrogen it causes algae to grow out of control. Figure below shows a pond covered with algae. Algae may use up so much oxygen in the water that nothing else can grow. Soon, even the algae die out. Decomposers break down the dead tissue and use up all the oxygen in the water. This creates a dead zone. A dead zone is an area in a body of water where nothing grows because there is too little oxygen. There is a large dead zone in the Gulf of Mexico. You can see it Figure below . I am facing a new situation today: Our family was going to go fishing on Saturday. A few years ago we went fishing down the hill from a mushroom farm called Happy Pond. Since that time, there has been a lot of rain and we noticed Happy Pond had a green coating across the top of it. We also thought about going to a new pond in center of the park called Ridge Pond. We are hoping to catch a lot of fish to serve at our family reunion. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Does Happy Pond have more nitrogen or oxygen?
Answer:
|
nitrogen
|
ropes_read_background_situation
|
P3
|
zs_opt
| 9
|
train
|
[Q]: I read this background article the other day: Alkali, or Alkaline, soils are clay soils with high pH (> 8.5), a poor soil structure and a low infiltration capacity. Often they have a hard calcareous layer at 0.5 to 1 metre depth. Alkali soils owe their unfavorable physico-chemical properties mainly to the dominating presence of sodium carbonate, which causes the soil to swell[1] and difficult to clarify/settle. They derive their name from the alkali metal group of elements, to which sodium belongs, and which can induce basicity. Sometimes these soils are also referred to as alkaline sodic soils. Alkaline soils are basic, but not all basic soils are alkaline. I am facing a new situation today: Two brothers have a piece of land each, situated 2 miles from each other. Jim's land is not very fertile because it has clay soil with a high pH, while Bob's land has very fertile soil and has a good productivity on it. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Which of the two pieces of land has a high filtration capacity?
****
[A]: Bob's
[Q]: I read this background article the other day: To determine the concentration of an acid in an aqueous solution, an acid-base titration is commonly performed. A strong base solution with a known concentration, usually NaOH or KOH, is added to neutralize the acid solution according to the color change of the indicator with the amount of base added.[7] The titration curve of an acid titrated by a base has two axes, with the base volume on the x-axis and the solution's pH value on the y-axis. The pH of the solution always goes up as the base is added to the solution. I am facing a new situation today: Due to increased carbon dioxide in the atmosphere more an more carbon dioxide is mixing with ocean water - thus increasing the acidity of the world's oceans. Rob is a climate scientist. He is measuring the acidity of the Atlantic ocean and the Pacific Ocean. To determine ocean water acidity he performed an acid-base titration. His conclusion is that Atlantic Ocean's acidity reached higher level than Pacific Ocean's acidity. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Whould Rob have to add more base or less base for Pacific Ocean's acidity test?
****
[A]: less base
[Q]: I read this background article the other day: When the temperature of reactants is higher, the rate of the reaction is faster. At higher temperatures, particles of reactants have more energy, so they move faster. As a result, they are more likely to bump into one another and to collide with greater force. For example, food spoils because of chemical reactions, and these reactions occur faster at higher temperatures (see the bread on the left in the Figure below ). This is why we store foods in the refrigerator or freezer (like the bread on the right in the Figure below ). The lower temperature slows the rate of spoilage. I am facing a new situation today: Rob is a chemist with a pharmaceutical company. He is trying to devise a technique that would be able to control chemical reactions. For that, he conducted two tests. In the first test, he used warmer reactants. He called it reactant A. In the second test, he used cooler reactants. He called it reactant B. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Would particles would collide with smaller or greater force in reactant A than in reactant B?
****
[A]: greater
[Q]: I read this background article the other day: Electrons can be removed from some objects using friction, simply by rubbing one substance against another substance. There are many examples of objects becoming charged by friction, including a rubber comb through hair, and a balloon on a sweater. In both these instances, the electrons move from the second object to the first, causing the first object to become negatively charged and the second one positively charged. Friction between the tires on a moving car and the road cause the tires to become charged, and wind causes friction between clouds and air which causes clouds to become charged and can result in tremendous bolts of lightning. I am facing a new situation today: Weather patterns in two cities are rather different. Much to the dismay of many residents of the town, the weather in Smallville is often windy and cloudy. Citizens of Klangton are much happier since they rarely experience heavy winds and generally only have a couple clouds in the sky. Their weather is almost always sunny with almost clear skies. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Does Smallville get more or less thunderstorms than Klangton?
****
[A]:
|
more
|
ropes_read_background_situation
|
P3
|
fs_opt
| 4
|
train
|
Problem: Given the question: I read this background article the other day: Greenhouse Effect: The solar energy reaching the surface of the Earth is concentrated in short wavelengths, which can easily penetrate the greenhouse gases, such as carbon dioxide and methane. The Earth, however, is cooler than the sun and it radiates its heat in the form of energy in the far infrared range. These longer wavelengths are partially absorbed by the greenhouse gases and some of the solar heat is returned to Earth. At a certain temperature these processes are in equilibrium and the surface temperature of the Earth is stable. However, if more greenhouse gases are put in the atmosphere the amount of trapped terrestrial radiation increases, leading to an increase in global temperature. I am facing a new situation today: Two meteorologists were good friends and discussed diverse issues weekly. This week they will talk again. Tim read about the Greenhouse Effect while Norm read about the mini-Ice ages. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Which friend learned less about energy in the far infrared range?
++++++++++++++++++++++++++++++++
The answer is:
Norm
input question: I read this background article the other day: Shown in the Figure below is a cylinder of gas on the left that is at room temperature (300 K). On the right, the cylinder has been heated until the Kelvin temperature has doubled to 600 K. The kinetic energy of the gas molecules increases, so collisions with the walls of the container are now more forceful than they were before. As a result, the pressure of the gas doubles. Decreasing the temperature would have the opposite effect, and the pressure of an enclosed gas would decrease. I am facing a new situation today: In a laboratory, Marcus is working with two identical containers of the same amount of gas inside them. For his next experiment, he needs these containers to be different temperatures. He takes container X and puts it in the refrigerator, and he leaves container Y out on the table. One hour later, he comes back and takes container X out of the refrigerator so he can now begin his experiment. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Which container has more kinetic energy????
output answer: container Y
I read this background article the other day: White blood cells also make chemicals that cause a fever. A fever is a higher-than-normal body temperature. Normal human body temperature is 98.6°F (37°C). Most bacteria and viruses that infect people reproduce fastest at this temperature. When the temperature is higher, the pathogens cannot reproduce as fast, so the body raises the temperature to kill them. A fever also causes the immune system to make more white blood cells. In these ways, a fever helps the body fight infection. I am facing a new situation today: Jim and Pam are a married couple who both have the same illness. They are at home from work today and are in the process of taking their temperatures so they know if they need to go to the doctor or not. After using the thermometer, they learn that Pam has a much higher fever than Jim. They decide they should take Pam to the doctor to get her looked at. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Does Jim have more or less white blood cells than Pam?
----
Answer: less
Q: I read this background article the other day: Apex predators affect prey species' population dynamics and populations of other predators, both in aquatic and in terrestrial ecosystems. Non-native predatory fish, for instance, have sometimes devastated formerly dominant predators. A lake manipulation study found that when the non-native smallmouth bass was removed, lake trout, the suppressed native apex predator, diversified its prey selection and increased its trophic level. As a terrestrial example, the badger, an apex predator, predates on and also competes with the hedgehog, a mesopredator, for food such as insects, small mammals, reptiles, amphibians and ground-nesting bird's eggs. Removal of badgers (in a trial investigating bovine tuberculosis) caused hedgehog densities to more than double. Predators that exert a top-down control on organisms in their community are often considered keystone species. Humans are not considered apex predators because their diets are typically diverse, although human trophic levels increase with consumption of meat. I am facing a new situation today: Rob is a biologist who is interested in native species conservation. To that end, he conducted two studies, case A and case B. In case A, a non native apex predator C was introduced in formerly apex predator D's habitat. In case B, same non native apex predator C was removed from formerly apex predator D's habitat. He now needs to analyze the results of these studies. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Would predator D's trophic level increase or decrease in case A than in case B?
A: decrease
Question: I read this background article the other day: Start right above point on the temperature axis and follow the red line vertically. At very low pressure, the particles of the substance are far apart from one another and the substance is in the gas state. As the pressure is increased, the particles of the substance are forced closer and closer together. Eventually the particles are pushed so close together that attractive forces cause the substance to condense into the liquid state. Continually increasing the pressure on the liquid will eventually cause the substance to solidify. For the majority of substances, the solid state is denser than the liquid state and so putting a liquid under great pressure will cause it to turn into a solid. The line segment represents the process of sublimation, where the substance changes directly from a solid to a gas. At a sufficiently low pressure, the liquid phase does not exist. The point labeled is called the triple point . The triple point is the one condition of temperature and pressure where the solid, liquid, and vapor states of a substance can all coexist at equilibrium. I am facing a new situation today: John is learning about different states of matter. So far, he recognized three states of matter, state A, state B, and state C. State A is in solid state. State B is in liquid state, and state C is in gaseous state. He needs to learn more about their individual characteristics. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: In which state the particles would be closer, state B or state C?
Answer: state B
Please answer this: I read this background article the other day: Noble gases are also used to fill the glass tubes of lighted signs like the one in the Figure below . Although noble gases are chemically nonreactive, their electrons can be energized by sending an electric current through them. When this happens, the electrons jump to a higher energy level. When the electrons return to their original energy level, they give off energy as light. Different noble gases give off light of different colors. Neon gives off reddish-orange light, like the word “Open” in the sign below. Krypton gives off violet light and xenon gives off blue light. I am facing a new situation today: John wanted to make some lighted signs for his business. To that end, he chose noble gases, neon, krypton, and xenon. First, he kept the noble gases in containers. He called it step A. Then he passed electric current through them. He called it step B. In the process, he came up with three signs, sign A, sign B, and sign C. Sign A used neon. Sign B used krypton, and sign C used xenon. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Which sign would have blue color, sign C or sign A?
++++++++
Answer:
|
sign C
|
ropes_read_background_situation
|
P3
|
fs_opt
| 5
|
train
|
I read this background article the other day: Ecologically, the expansion of drainage systems has had tremendous negative effects. Hundreds of thousands of wetland species experienced significant population declines as their habitat was increasingly fragmented and destroyed. Although market hunting within the Central Flyway was a contributing factor in the decline of many waterfowl species' numbers in the early decades of the twentieth century, loss of breeding habitat to agricultural expansion is certainly the most significant. Early maps of midwestern states depict many lakes and marshes that are either nonexistent or significantly reduced in area today. Channelization, a related process of concentrating and facilitating the flow of water from agricultural areas, also contributed to this degradation. I am facing a new situation today: Both Alabama and Florida boast great wetlands. The State of Alabama has experienced extensive drainage system due to expansion of farmlands. Their neighboring state Florida had similar system. But recently Florida had dismantled many of their drainage systems, mostly because of pressure from different environmental groups. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Which state would not see habital loss of species, Alabama or Florida?
A:
|
Florida
|
ropes_read_background_situation
|
P3
|
zs_noopt
| 2
|
train
|
I read this background article the other day: The quantity of small plastic fragments floating in the north-east Pacific Ocean increased a hundredfold between 1972 and 2012.Marine pollution is a generic term for the harmful entry into the ocean of chemicals or particles. The main culprits are those using the rivers for disposing of their waste. The rivers then empty into the ocean, often also bringing chemicals used as fertilizers in agriculture. The excess of oxygen-depleting chemicals in the water leads to hypoxia and the creation of a dead zone.Marine debris, also known as marine litter, is human-created waste that has ended up floating in a lake, sea, ocean, or waterway. Oceanic debris tends to accumulate at the center of gyres and coastlines, frequently washing aground where it is known as beach litter.In addition, the Pacific Ocean has served as the crash site of satellites, including Mars 96, Fobos-Grunt, and Upper Atmosphere Research Satellite. I am facing a new situation today: Tim and Joe were two friends living near two different oceans. Tim lived on the Pacific coast while Joe lived on the Atlantic coast. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Which friend sees more hypoxia in the ocean?
----
Answer: Tim
Q: I read this background article the other day: Reptiles are a class of animals comprising turtles, tuataras, lizards, snakes and crocodiles. They are tetrapods, but the snakes and a few species of lizard either have no limbs or their limbs are much reduced in size. Their bones are better ossified and their skeletons stronger than those of amphibians. The teeth are conical and mostly uniform in size. The surface cells of the epidermis are modified into horny scales which create a waterproof layer. Reptiles are unable to use their skin for respiration as do amphibians and have a more efficient respiratory system drawing air into their lungs by expanding their chest walls. The heart resembles that of the amphibian but there is a septum which more completely separates the oxygenated and deoxygenated bloodstreams. The reproductive system has evolved for internal fertilization, with a copulatory organ present in most species. The eggs are surrounded by amniotic membranes which prevents them from drying out and are laid on land, or develop internally in some species. The bladder is small as nitrogenous waste is excreted as uric acid.Turtles are notable for their protective shells. They have an inflexible trunk encased in a horny carapace above and a plastron below. These are formed from bony plates embedded in the dermis which are overlain by horny ones and are partially fused with the ribs and spine. The neck is long and flexible and the head and the legs can be drawn back inside the shell. Turtles are vegetarians and the typical reptile teeth have been replaced by sharp, horny plates. In aquatic species, the front legs are modified into flippers.Tuataras superficially resemble lizards but the lineages diverged in the Triassic period. There is one living species, Sphenodon punctatus. The skull has two openings (fenestrae) on either side and the jaw is rigidly attached to the skull. There is one row of teeth in the lower jaw and this fits between the two rows in the upper jaw when the animal chews. The teeth are merely projections of bony material from the jaw... I am facing a new situation today: Team A and Team B were two teams of students studying zoology. Team A learned about reptiles, while Team B studied more about amphibians. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Which team learned less about turtles?
A: Team B
Question: I read this background article the other day: Windbreaks reduce wind velocity over and around crops. This increases yields through reduced drying of the crop and/or by preventing the crop from toppling in strong wind gusts. I am facing a new situation today: Two farms had winds destroying their crops. Hill farm started installing windbreaks, while Valley farm didn't have the funds to do that so they postponed the project. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Which farm didn't reduce the wind velocity around crops?
Answer: Valley
[Q]: I read this background article the other day: Vapor pressure is a measure of the pressure exerted by a gas above a liquid in a sealed container. While viscosity and surface tension increase as the strength of intermolecular forces increase, vapor pressure decreases . This is because the stronger the intermolecular forces are, the harder it is for liquid molecules to escape into the gas phase. Vapor pressure a measure of how much of a substance is in the gas phase when that substance is at equilibrium; that is, the number of molecules in the gas and liquid phases are not changing. The more molecules that are able to escape into the gas phase, the higher the vapor pressure. Vapor pressure is also proportional to temperature. As temperature increases, vapor pressure also increases. I am facing a new situation today: Jacob is performing a chemistry experiment using two different liquids. Before starting the experiment, Jacob is told that liquid A molecules have strong intermolecular forces, while liquid B molecules have weak intermolecular forces. Jacob now has to decide how to use this information to guide him as he develops the experimental procedures for these two liquids. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Which liquid will have less molecules escape into the gas phase?
****
[A]: liquid A
input: Please answer the following: I read this background article the other day: When the temperature of reactants is higher, the rate of the reaction is faster. At higher temperatures, particles of reactants have more energy, so they move faster. As a result, they are more likely to bump into one another and to collide with greater force. For example, food spoils because of chemical reactions, and these reactions occur faster at higher temperatures (see the bread on the left in the Figure below ). This is why we store foods in the refrigerator or freezer (like the bread on the right in the Figure below ). The lower temperature slows the rate of spoilage. I am facing a new situation today: John was pondering about what makes a chemical reaction faster or slower. To find the answer he did two tests, test A and test B. In test A he warmed up the reactants, but in test B he cooled down the reactants. To see a practical example of these tests he conducted two more tests, test C and test D. In test C he kept a food item in the refrigerator, but in test D he kept the same food item on the table top. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: In which test particles would move slower, test A or test B?
++++++++++
output: test B
I read this background article the other day: Unfortunately, the layer of good ozone is being destroyed by air pollution. The chief culprits are chlorine and bromine gases. They are released in aerosol sprays, coolants, and other products. Loss of ozone has created an ozone hole over Antarctica. Ozone depletion results in higher levels of UV radiation reaching Earth. In humans, this increases skin cancers and eye cataracts. It also disturbs the nitrogen cycle, kills plankton, and disrupts ocean food webs. The total loss of the ozone layer would be devastating to most life. Its rate of loss has slowed with restrictions on pollutants, but it is still at risk. I am facing a new situation today: Russian research spent most of their time in Antarctica to study the loss of ozone in the atmosphere. The Canadian team went north of the Polar Circle, close to the North Pole to do the same thing. They spent several months there. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Which team was closer to the ozone hole in the atmosphere?
----
Answer:
|
Russian
|
ropes_read_background_situation
|
P3
|
fs_opt
| 0
|
train
|
Answer the following question: I read this background article the other day: Saturated hydrocarbons are given the general name of alkanes . The name of specific alkanes always ends in - ane . The first part of the name indicates how many carbon atoms each molecule of the alkane has. The smallest alkane is methane. It has just one carbon atom. The next largest is ethane, with two carbon atoms. The chemical formulas and properties of methane, ethane, and several other alkanes are listed in Table below . The boiling and melting points of alkanes are determined mainly by the number of carbon atoms they have. Alkanes with more carbon atoms generally have higher boiling and melting points. I am facing a new situation today: Two brothers studied chemistry in school. Ted studied alkanes, while Ned studied cycloalkanes. They both received grade A. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Which brother learned less about methane?
Answer:
|
Ned
|
ropes_read_background_situation
|
P3
|
zs_opt
| 5
|
train
|
I read this background article the other day: Farsightedness, or hyperopia, is the condition in which distant objects are seen clearly, but nearby objects appear blurry. It occurs when the eyeball is shorter than normal (see Figure below ). This causes images to be focused in a spot that would fall behind the retina (if light could pass through the retina). Hyperopia can be corrected with convex lenses. The lenses focus images farther forward in the eye, so they fall on the retina instead of behind it. I am facing a new situation today: Two people went to the eye doctor's office for an annual exam; James had farsightedness, while Bob had perfect 20/20 vision. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Which person saw more nearby objects as blurry?
The answer to this question is:
|
James
|
ropes_read_background_situation
|
P3
|
zs_noopt
| 7
|
test
|
Q:I read this background article the other day: Hypertension , which is also called "high blood pressure," occurs when a person’s blood pressure is always high. Hypertension is said to be present when a person's systolic blood pressure is always 140 or higher, and/or if the person's diastolic blood pressure is always 90 or higher. Having hypertension increases a person’s chance for developing heart disease, having a stroke, or suffering from other serious cardiovascular diseases. Hypertension often does not have any symptoms, so a person may not know that he or she has high blood pressure. For this reason, hypertension is often called the "silent killer." Treatments for hypertension include diet changes, exercise, and medication. Foods thought to lower blood pressure include skim milk, spinach, beans, bananas and dark chocolate. I am facing a new situation today: Jeremy went to the doctor for his yearly physical along with his wife Brenda. The doctor told Jeremy that his blood pressure was consistently high. Brenda, on the other hand, was told that her blood pressure was in the normal range. Aside from this difference, the overall health of Jeremy and Brenda was similar. Using the knowledge I acquired from the background article, how should I answer correctly the following question regarding my new situation: Who does not need to consider making changes to their diet as much?
A:
|
Brenda
|
ropes_read_background_situation
|
P3
|
zs_opt
| 3
|
validation
|
Answer the following question: Q: What is lava called before it reaches the surface of the earth? A:
Answer:
|
magma
|
sciq_Direct_Question_Closed_Book_
|
P3
|
zs_noopt
| 4
|
train
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Problem:OPTIONS:
- crystals
- ridges
- lava channels
- plates
Q: What are the things moving under the earth's mantle that move the crust? A:
****
A: plates
Q: Fatty acids, triglycerides, phospholipids, and steroids are examples of what? A:
OPTIONS:
- tissues
- enzymes
- proteins
- lipids
lipids
Q: Water, carbon dioxide, and what other element are important agents of chemical weathering? A:
OPTIONS:
- helium
- methane
- sulfur
- oxygen
Answer: oxygen
Question: Q: What is the substance called whenatoms of different elements join together? A:
OPTIONS:
- crusts
- crystals
- plants
- compounds
Answer: compounds
input with options: Q: Comparing anatomy, and characterizing the similarities and differences, provides evidence of what process? A:
OPTIONS:
- regression
- devolution
- emergence
- evolution
output: evolution
Problem: OPTIONS:
- phototropism
- pollenation
- sensitivity
- thigmotropism
Q: Q: What is the touch response in plants called? A:
Answer:
|
thigmotropism
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sciq_Direct_Question_Closed_Book_
|
P3
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fs_opt
| 7
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train
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Q: Huge calderas form when the mountain above an empty chamber of what collapses? A:
OPTIONS:
- gas
- mercury
- coal
- magma
magma
Q: What do all chemical reactions need to get started? A:
OPTIONS:
- expression energy
- kinetic energy
- potential energy
- activation energy
Answer: activation energy
Question: Q: What are plant-like protists called? A:
OPTIONS:
- fungi
- sponge
- spores
- algae
Answer: algae
input with options: Q: The number of possible isomers increases tremendously as carbon skeletons increase in what? A:
OPTIONS:
- variation
- mass
- weight
- size
output: size
Q: Q: What system of the body is generally responsible for breathing? A:
OPTIONS:
- excretory
- integumentary
- cardiac
- respiratory system
A: respiratory system
Q: What is the measure of how closely molecules are packed together? A:
OPTIONS:
- length
- volume
- frequency
- density
|
density
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sciq_Direct_Question_Closed_Book_
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P3
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fs_opt
| 0
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train
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*instance; *median; *frequency; *error;
Q: In statistics a boundary on the precision and accuracy is known as what? A:
Answer:
|
error
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sciq_Direct_Question_Closed_Book_
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P3
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zs_opt
| 5
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train
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Q: What is the term for many different types of animals within the same species? A:
OPTIONS:
- pollution
- habitat
- differentiation
- diversity
Answer: diversity
Problem: OPTIONS:
- staurikosaurus
- sporozoans
- ionconcentrate
- osmoreceptors
Q: Q: What are specialized cells in the brain that monitor the concentration of solutes in the blood called? A:
Answer: osmoreceptors
Problem:OPTIONS:
- basalt oxygen atom
- pyridinium oxygen atom
- carbon carbon atom
- carbonyl oxygen atom
Q: Aldehydes and ketones can work weak hydrogen bonds with water through what atom? A:
****
A: carbonyl oxygen atom
Q: Which layer of the earth is molten? A:
OPTIONS:
- the inner core
- the metallic core
- the mantle
- the outer core
the outer core
Q: What is the unit of liquid measurement in the metric system? A:
OPTIONS:
- pint
- gallon
- cylinder
- liter
Answer: liter
input with options: Q: Parasitism, mutualism, and commensalism are all examples of what type of biological relationship? A:
OPTIONS:
- adaptation
- reproduction
- evolution
- symbiosis
output:
|
symbiosis
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sciq_Direct_Question_Closed_Book_
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P3
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fs_opt
| 3
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train
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Question: Q: Dialysis is a treatment for failure of what organs? A:
OPTIONS:
- lungs
- liver
- spleen
- kidneys
Answer: kidneys
input with options: Q: What term means the time in which half of the original number of radioactive nuclei in a sample decay? A:
OPTIONS:
- reduced life
- quarter-life
- partial-life
- half-life
output: half-life
Q: Q: What is the position of rock layers and the relative ages called? A:
OPTIONS:
- diffraction
- metamorphism
- bifurcation
- superposition
A: superposition
input: OPTIONS:
- sheath
- annulata
- soleus
- sarcolemma Now, answer this question: Q: The plasma membrane of a skeletal muscle fiber is called the what? A:
A:
output: sarcolemma
Q: Ionic bonds are electrostatic attractions between two oppositely charged what? A:
OPTIONS:
- molecules
- gasses
- compounds
- ions
Answer: ions
Q: Q: What is making measurements that are close to the true value known as? A:
OPTIONS:
- estimation
- frequency
- prediction
- accuracy
A:
|
accuracy
|
sciq_Direct_Question_Closed_Book_
|
P3
|
fs_opt
| 4
|
train
|
Q: How many protons and electrons each do carbon atoms have? A:
OPTIONS:
- two
- nine
- five
- six
six
Q: What is used to fluoridate drinking water to promote dental health A:
OPTIONS:
- carbon fluoride
- calcium fluorine
- carbon fluorine
- calcium fluoride
Answer: calcium fluoride
Question: Q: Negative feedback controls insulin secretion by what organ? A:
OPTIONS:
- thyroid
- uterus
- liver
- pancreas
Answer: pancreas
input with options: Q: An individual with down's syndrome has 47 of what instead of the normal 46? A:
OPTIONS:
- ribosomes
- mitochondria
- prokaryotes
- chromosomes
output: chromosomes
Q: Q: An increase in the body's cholesterol levels can lead to your arteries filling with what? A:
OPTIONS:
- triglycerides
- fat
- marble
- plaque
A: plaque
Q: Besides greenland, where are the earth's largest ice sheets found? A:
OPTIONS:
- North America
- Europe
- Asia
- antarctica
|
antarctica
|
sciq_Direct_Question_Closed_Book_
|
P3
|
fs_opt
| 0
|
train
|
input: OPTIONS:
- classic permeation
- induced permeation
- radiation permeation
- selective permeation Now, answer this question: Q: What term means that only molecules or ions of a certain size, shape, polarity or charge are capable of passing through the material? A:
A:
output: selective permeation
Q: What part of the plant anchors it into the soil? A:
OPTIONS:
- stems
- buds
- leaves
- roots
Answer: roots
Problem: OPTIONS:
- Position Replacement
- acceleration
- Direction Replacement
- velocity
Q: Q: What term refers to change in position over time? A:
Answer: velocity
Problem:OPTIONS:
- asexual and biological
- atypical and sexual
- ideal and sexual
- asexual and sexual
Q: The protist life cycle benefits by including what forms of reproduction? A:
****
A: asexual and sexual
Q: What term is used to describe joints in which the bones are connected by cartilage? A:
OPTIONS:
- capillaries joints
- blob joints
- spinal joins
- cartilaginous joints
cartilaginous joints
Q: Bacterial contamination of foods can lead to digestive problems, an illness known as what? A:
OPTIONS:
- acid reflux
- headache
- ulcers
- food poisoning
Answer:
|
food poisoning
|
sciq_Direct_Question_Closed_Book_
|
P3
|
fs_opt
| 1
|
train
|
Q: Q: Oxygen, carbon, hydrogen and what other element make up approximately 96% of living matter? A:
A:
|
nitrogen
|
sciq_Direct_Question_Closed_Book_
|
P3
|
zs_noopt
| 6
|
test
|
Q: Which stage of development is a period during which apoptosis is widespread and plays a crucial role? A:
Choose from:
-puberty;
-transgenic;
-infancy;
-embryonic;
The answer is:
|
embryonic
|
sciq_Direct_Question_Closed_Book_
|
P3
|
zs_opt
| 7
|
validation
|
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 data in tabular format and you need to generate a passage with content in plain text format based on the information present in the table.
Table: ['Pick', 'Player', 'Team', 'Position', 'School']. ['1', 'Ben McDonald', 'Baltimore Orioles', 'RHP', 'Louisiana State University']. ['2', 'Tyler Houston', 'Atlanta Braves', 'C', 'Valley HS (Las Vegas, NV)']. ['3', 'Roger Salkeld', 'Seattle Mariners', 'RHP', 'Saugus (CA) HS']. ['4', 'Jeff Jackson', 'Philadelphia Phillies', 'OF', 'Simeon HS (Chicago, IL)']. ['5', 'Donald Harris', 'Texas Rangers', 'OF', 'Texas Tech University']. ['6', 'Paul Coleman', 'Saint Louis Cardinals', 'OF', 'Frankston (TX) HS']. ['7', 'Frank Thomas', 'Chicago White Sox', '1B', 'Auburn University']. ['8', 'Earl Cunningham', 'Chicago Cubs', 'OF', 'Lancaster (SC) HS']. ['9', 'Kyle Abbott', 'California Angels', 'LHP', 'Long Beach State University']. ['10', 'Charles Johnson', 'Montreal Expos', 'C', 'Westwood HS (Fort Pierce, FL)']. ['11', 'Calvin Murray', 'Cleveland Indians', '3B', 'W.T. White High School (Dallas, TX)']. ['12', 'Jeff Juden', 'Houston Astros', 'RHP', 'Salem (MA) HS']. ['13', 'Brent Mayne', 'Kansas City Royals', 'C', 'Cal State Fullerton']. ['14', 'Steve Hosey', 'San Francisco Giants', 'OF', 'Fresno State University']. ['15', 'Kiki Jones', 'Los Angeles Dodgers', 'RHP', 'Hillsborough HS (Tampa, FL)']. ['16', 'Greg Blosser', 'Boston Red Sox', 'OF', 'Sarasota (FL) HS']. ['17', 'Cal Eldred', 'Milwaukee Brewers', 'RHP', 'University of Iowa']. ['18', 'Willie Greene', 'Pittsburgh Pirates', 'SS', 'Jones County HS (Gray, GA)']. ['19', 'Eddie Zosky', 'Toronto Blue Jays', 'SS', 'Fresno State University']. ['20', 'Scott Bryant', 'Cincinnati Reds', 'OF', 'University of Texas']. ['21', 'Greg Gohr', 'Detroit Tigers', 'RHP', 'Santa Clara University']. ['22', 'Tom Goodwin', 'Los Angeles Dodgers', 'OF', 'Fresno State University']. ['23', 'Mo Vaughn', 'Boston Red Sox', '1B', 'Seton Hall University']. ['24', 'Alan Zinter', 'New York Mets', 'C', 'University of Arizona']. ['25', 'Chuck Knoblauch', 'Minnesota Twins', '2B', 'Texas A&M University']. ['26', 'Scott Burrell', 'Seattle Mariners', 'RHP', 'Hamden (CT) HS']
Solution: Passage: The player named Ben McDonald, plays as Pick-1.Ben McDonald plays for the team Baltimore Orioles, at position RHP. Ben McDonald belongs to the school Louisiana State University. The player named Tyler Houston, plays as Pick-2.Tyler Houston plays for the team Atlanta Braves, at position C. Tyler Houston belongs to the school Valley HS (Las Vegas, NV). The player named Roger Salkeld, plays as Pick-3.Roger Salkeld plays for the team Seattle Mariners, at position RHP. Roger Salkeld belongs to the school Saugus (CA) HS. The player named Jeff Jackson, plays as Pick-4.Jeff Jackson plays for the team Philadelphia Phillies, at position OF. Jeff Jackson belongs to the school Simeon HS (Chicago, IL). The player named Donald Harris, plays as Pick-5.Donald Harris plays for the team Texas Rangers, at position OF. Donald Harris belongs to the school Texas Tech University. The player named Paul Coleman, plays as Pick-6.Paul Coleman plays for the team Saint Louis Cardinals, at position OF. Paul Coleman belongs to the school Frankston (TX) HS. The player named Frank Thomas, plays as Pick-7.Frank Thomas plays for the team Chicago White Sox, at position 1B. Frank Thomas belongs to the school Auburn University. The player named Earl Cunningham, plays as Pick-8.Earl Cunningham plays for the team Chicago Cubs, at position OF. Earl Cunningham belongs to the school Lancaster (SC) HS. The player named Kyle Abbott, plays as Pick-9.Kyle Abbott plays for the team California Angels, at position LHP. Kyle Abbott belongs to the school Long Beach State University. The player named Charles Johnson, plays as Pick-10.Charles Johnson plays for the team Montreal Expos, at position C. Charles Johnson belongs to the school Westwood HS (Fort Pierce, FL). The player named Calvin Murray, plays as Pick-11.Calvin Murray plays for the team Cleveland Indians, at position 3B. Calvin Murray belongs to the school W.T. White High School (Dallas, TX). The player named Jeff Juden, plays as Pick-12.Jeff Juden plays for the team Houston Astros, at position RHP. Jeff Juden belongs to the school Salem (MA) HS. The player named Brent Mayne, plays as Pick-13.Brent Mayne plays for the team Kansas City Royals, at position C. Brent Mayne belongs to the school Cal State Fullerton. The player named Steve Hosey, plays as Pick-14.Steve Hosey plays for the team San Francisco Giants, at position OF. Steve Hosey belongs to the school Fresno State University. The player named Kiki Jones, plays as Pick-15.Kiki Jones plays for the team Los Angeles Dodgers, at position RHP. Kiki Jones belongs to the school Hillsborough HS (Tampa, FL). The player named Greg Blosser, plays as Pick-16.Greg Blosser plays for the team Boston Red Sox, at position OF. Greg Blosser belongs to the school Sarasota (FL) HS. The player named Cal Eldred, plays as Pick-17.Cal Eldred plays for the team Milwaukee Brewers, at position RHP. Cal Eldred belongs to the school University of Iowa. The player named Willie Greene, plays as Pick-18.Willie Greene plays for the team Pittsburgh Pirates, at position SS. Willie Greene belongs to the school Jones County HS (Gray, GA). The player named Eddie Zosky, plays as Pick-19.Eddie Zosky plays for the team Toronto Blue Jays, at position SS. Eddie Zosky belongs to the school Fresno State University. The player named Scott Bryant, plays as Pick-20.Scott Bryant plays for the team Cincinnati Reds, at position OF. Scott Bryant belongs to the school University of Texas. The player named Greg Gohr, plays as Pick-21.Greg Gohr plays for the team Detroit Tigers, at position RHP. Greg Gohr belongs to the school Santa Clara University. The player named Tom Goodwin, plays as Pick-22.Tom Goodwin plays for the team Los Angeles Dodgers, at position OF. Tom Goodwin belongs to the school Fresno State University. The player named Mo Vaughn, plays as Pick-23.Mo Vaughn plays for the team Boston Red Sox, at position 1B. Mo Vaughn belongs to the school Seton Hall University. The player named Alan Zinter, plays as Pick-24.Alan Zinter plays for the team New York Mets, at position C. Alan Zinter belongs to the school University of Arizona. The player named Chuck Knoblauch, plays as Pick-25.Chuck Knoblauch plays for the team Minnesota Twins, at position 2B. Chuck Knoblauch belongs to the school Texas A&M University. The player named Scott Burrell, plays as Pick-26.Scott Burrell plays for the team Seattle Mariners, at position RHP. Scott Burrell belongs to the school Hamden (CT) HS.
Why? The output correctly captures the data in table and generates a long text passage which covers all the given information.
New input: Table: ['Place', 'Position', 'Number', 'Name', 'NASL', 'Playoffs', 'CFU Club Championship', 'CONCACAF Champions League', 'Total']. ['1', 'FW', '11', 'Nicholas Addlery', '9', '0', '0', '1', '10']. ['2', 'FW', '9', 'Jonathan Fana', '4', '0', '4', '0', '8']. ['3', 'FW', '7', 'David Foley', '6', '1', '0', '0', '7']. ['3', 'FW', '24', 'Hector Ramos', '3', '0', '2', '2', '7']. ['5', 'DF', '33', 'Jay Needham', '3', '0', '0', '0', '3']. ['5', 'FW', '22', 'Gregory Richardson', '1', '0', '1', '1', '3']. ['7', 'MF', '20', 'Josh Hansen', '0', '0', '2', '0', '2']. ['7', '', '', 'Own Goal', '0', '0', '2', '0', '2']. ['9', 'DF', '3', 'Richard Martinez', '1', '0', '0', '0', '1']. ['9', 'DF', '16', 'Anthony Vazquez', '1', '0', '0', '0', '1']. ['9', 'DF', '5', 'Noah Delgado', '1', '0', '0', '0', '1']. ['9', 'MF', '14', 'Jarad Van Schaik', '1', '0', '0', '0', '1']. ['9', 'MF', '17', 'Tyler Wilson', '1', '0', '0', '0', '1']. ['9', 'MF', '24', 'Justin Fojo', '1', '0', '0', '0', '1']. ['', '', '', 'TOTALS', '32', '1', '11', '4', '48']
Solution:
|
Passage: The player named Nicholas Addlery with jersey number 11, plays at position FW. There were total 0 playoffs, 0 CFU Club Championships, 1 CONCACAF Champions Leagues. Total 10 matches. The player named Jonathan Fana with jersey number 9, plays at position FW. There were total 0 playoffs, 4 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 8 matches. The player named David Foley with jersey number 7, plays at position FW. There were total 1 playoffs, 0 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 7 matches. The player named Hector Ramos with jersey number 24, plays at position FW. There were total 0 playoffs, 2 CFU Club Championships, 2 CONCACAF Champions Leagues. Total 7 matches. The player named Jay Needham with jersey number 33, plays at position DF. There were total 0 playoffs, 0 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 3 matches. The player named Gregory Richardson with jersey number 22, plays at position FW. There were total 0 playoffs, 1 CFU Club Championships, 1 CONCACAF Champions Leagues. Total 3 matches. The player named Josh Hansen with jersey number 20, plays at position MF. There were total 0 playoffs, 2 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 2 matches. The player named Own Goal with jersey number , plays at position . There were total 0 playoffs, 2 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 2 matches. The player named Richard Martinez with jersey number 3, plays at position DF. There were total 0 playoffs, 0 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 1 matches. The player named Anthony Vazquez with jersey number 16, plays at position DF. There were total 0 playoffs, 0 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 1 matches. The player named Noah Delgado with jersey number 5, plays at position DF. There were total 0 playoffs, 0 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 1 matches. The player named Jarad Van Schaik with jersey number 14, plays at position MF. There were total 0 playoffs, 0 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 1 matches. The player named Tyler Wilson with jersey number 17, plays at position MF. There were total 0 playoffs, 0 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 1 matches. The player named Justin Fojo with jersey number 24, plays at position MF. There were total 0 playoffs, 0 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 1 matches. The player named TOTALS with jersey number , plays at position . There were total 1 playoffs, 11 CFU Club Championships, 4 CONCACAF Champions Leagues. Total 48 matches.
|
task760_msr_sqa_long_text_generation
|
NIv2
|
fs_opt
| 0
|
train
|
Q: You are given data in tabular format and you need to generate a passage with content in plain text format based on the information present in the table.
Table: ['Year', 'Miss Northern Ireland', 'Hometown', 'Placement at Miss World', 'Notes']. ['2012', 'Tiffany Brien', 'Belfast', 'Top 30', 'Top 10 of Beach Fashion and 1st runner-up of Sports & Fitness at Miss World 2012']. ['2011', 'Finola Guinnane', 'Drumbo', 'Non-Finalist', 'Top 20 of Beach Beauty and Top 77 of Beauty with a Purpose at Miss World 2011']. ['2010', 'Lori Moore', 'Belfast', 'Top 25', 'Winner of Sports at Miss World 2010']. ['2009', 'Cherie Gardiner', 'Bangor', 'Non-Finalist', '']. ['2008', 'Judith Wilson', 'Enniskillen', 'Non-Finalist', 'Top 19 of Talent at Miss World 2008']. ['2007', 'Melissa Patton', 'Belfast', 'Non-Finalist', '']. ['2006', 'Catherine Jean Milligan', 'Newtownards', 'Top 17', 'Winner of Miss Talent at Miss World 2006']. ['2005', 'Lucy Evangelista', 'Portglenone', 'Top 15', 'Later Miss United Kingdom 2005 and Miss Universe United Kingdom 2005 2nd runner-up']. ['2004', 'Kirsty Anne Gabriel Stewart', 'Enniskillen', 'Non-Finalist', '']. ['2003', 'Diana Sayers', 'Belfast', 'Non-Finalist', '']. ['2002', 'Gayle Williamson', 'Lurgan', 'Non-Finalist', 'Later Miss United Kingdom 2002']. ['2001', 'Angela McCarthy', 'Belfast', 'Non-Finalist', '']. ['2000', 'Julie Lee-Ann Martin', 'Belfast', 'Non-Finalist', '']
A:
|
Passage: Tiffany Brien from Belfast was Miss Northern Ireland in the year 2012. Tiffany Brien was placed as a Top 30 at Miss World. Tiffany Brien was Top 10 of Beach Fashion and 1st runner-up of Sports & Fitness at Miss World 2012. Finola Guinnane from Drumbo was Miss Northern Ireland in the year 2011. Finola Guinnane was placed as a Non-Finalist at Miss World. Finola Guinnane was Top 20 of Beach Beauty and Top 77 of Beauty with a Purpose at Miss World 2011. Lori Moore from Belfast was Miss Northern Ireland in the year 2010. Lori Moore was placed as a Top 25 at Miss World. Lori Moore was Winner of Sports at Miss World 2010. Cherie Gardiner from Bangor was Miss Northern Ireland in the year 2009. Cherie Gardiner was placed as a Non-Finalist at Miss World. Cherie Gardiner was . Judith Wilson from Enniskillen was Miss Northern Ireland in the year 2008. Judith Wilson was placed as a Non-Finalist at Miss World. Judith Wilson was Top 19 of Talent at Miss World 2008. Melissa Patton from Belfast was Miss Northern Ireland in the year 2007. Melissa Patton was placed as a Non-Finalist at Miss World. Melissa Patton was . Catherine Jean Milligan from Newtownards was Miss Northern Ireland in the year 2006. Catherine Jean Milligan was placed as a Top 17 at Miss World. Catherine Jean Milligan was Winner of Miss Talent at Miss World 2006. Lucy Evangelista from Portglenone was Miss Northern Ireland in the year 2005. Lucy Evangelista was placed as a Top 15 at Miss World. Lucy Evangelista was Later Miss United Kingdom 2005 and Miss Universe United Kingdom 2005 2nd runner-up. Kirsty Anne Gabriel Stewart from Enniskillen was Miss Northern Ireland in the year 2004. Kirsty Anne Gabriel Stewart was placed as a Non-Finalist at Miss World. Kirsty Anne Gabriel Stewart was . Diana Sayers from Belfast was Miss Northern Ireland in the year 2003. Diana Sayers was placed as a Non-Finalist at Miss World. Diana Sayers was . Gayle Williamson from Lurgan was Miss Northern Ireland in the year 2002. Gayle Williamson was placed as a Non-Finalist at Miss World. Gayle Williamson was Later Miss United Kingdom 2002. Angela McCarthy from Belfast was Miss Northern Ireland in the year 2001. Angela McCarthy was placed as a Non-Finalist at Miss World. Angela McCarthy was . Julie Lee-Ann Martin from Belfast was Miss Northern Ireland in the year 2000. Julie Lee-Ann Martin was placed as a Non-Finalist at Miss World. Julie Lee-Ann Martin was .
|
task760_msr_sqa_long_text_generation
|
NIv2
|
zs_opt
| 7
|
train
|
You are given data in tabular format and you need to generate a passage with content in plain text format based on the information present in the table.
--------
Question: Table: ['Species', 'Country of origin', 'Total released', 'First release', 'Last release', 'Areas of release', 'Areas established', 'Pasture type']. ['Bubas bison', 'France, Spain', '1,613', 'April 1983', '1996 (not by CSIRO)', 'WA', 'NSW, SA, WA', 'Winter rainfall']. ['Copris elphenor Klug', 'South Africa', '2,287', 'January 1977', 'May 1983', 'QLD', 'QLD', 'Summer rainfall']. ['Copris hispanus Linnaeus', 'Spain', '294', 'October 1983', 'June 1994', 'WA', 'WA', 'Winter rainfall']. ['Euoniticellus africanus Harold', 'South Africa', '49,009', 'October 1971', 'February 1984', 'NSW, QLD, SA, Tas, Vic, WA', 'NSW, QLD', 'Summer rainfall']. ['Euoniticellus fulvus Goeze', 'France, Turkey', '76,944', 'March 1978', 'February 1983', 'NSW, SA, Tas, Vic, WA', 'NSW, SA, Tas, Vic, WA', 'Winter rainfall']. ['Euoniticellus intermedius Reiche', 'South Africa', '248,637', 'November 1971', 'February 1984', 'ACT, NSW, NT, QLD, SA, Vic, WA', 'NSW, NT, QLD, SA, Vic, WA', 'Summer rainfall']. ['Euoniticellus pallipes Fabricius', 'Iran, Turkey', '46,642', 'March 1977', 'September 1982', 'NSW, SA, WA', 'NSW, SA, Vic, WA', 'Winter rainfall']. ['Geotrupes spiniger Marsham', 'France', '12,082', 'April 1979', 'December 1983', 'ACT, NSW, Tas, Vic', 'ACT, NSW, SA, Tas, Vic', 'Winter rainfall']. ['Liatongus militaris Castelanu', 'South Africa (via Hawaii)', '70,450', 'January 1968', 'November 1979', 'NSW, NT, QLD, WA', 'NSW, NT, QLD', 'Summer rainfall']. ['Onitis alexis Fabricius', 'South Africa', '186,441', 'August 1972', 'February 1984', 'NSW, NT, QLD, WA', 'NSW, NT, QLD, SA, Vic, WA', 'Rainfall, summer rainfall, winter rainfall']. ['Onitis aygalus Fabricius', 'South Africa', '18,682', 'January 1977', 'January 1982', 'NSW, SA, WA', 'NSW, SA, Vic, WA', 'Winter rainfall']. ['Onitis caffer Boheman', 'South Africa', '8,738', 'October 1979', 'April 1984', 'WA', 'QLD, NSW, SA', 'Summer rainfall, winter rainfall']. ['Onitis pecuarius Lansberge', 'South Africa', '11,395', 'November 1976', 'May 1979', 'NSW, QLD', 'NSW, QLD', 'Summer rainfall']. ['Onitis vanderkelleni Lansberge', 'Kenya, Rwanda, Zaire', '10,852', 'October 1974', 'February 1982', 'NSW, QLD', 'QLD', 'Summer rainfall']. ['Onitis viridulus Bohemann', 'South Africa', '8,008', 'September 1976', 'July 1980', 'NSW, NT, QLD', 'NSW, NT, QLD, WA', 'Summer rainfall']. ['Onthophagus binodis Thunberg', 'South Africa', '173,018', 'October 1971', 'February 1982', 'NSW, QLD, SA, Tas, Vic, WA, Norfolk Islands', 'NSW, QLD, SA, Tas, Vic, WA, Norfolk Islands', 'Winter rainfall']. ['Onthophagus gazella Fabricius', 'South Africa', '420,415', 'February 1968', 'February 1984', 'ACT, NSW, NT, QLD, SA, Tas, Vic, WA, Norfolk Islands', 'ACT, NSW, NT, QLD, SA, WA, Norfolk Islands', 'Summer rainfall']. ["Onthophagus nigiventris d'Orbigny", 'East Africa', '29,960', 'May 1975', 'March 1983', 'NSW', 'NSW', 'Summer rainfall']. ['Onthophagus obliquus', 'Nigeria, Senegal, Zaire', '9,300', 'January 1976', 'November 1977', 'QLD, NT', 'QLD', 'Summer rainfall']. ['Onthophagus sagittarius', 'Sri Lanka (via Hawaii)', '9,075', 'January 1968', 'March 1977', 'NSW, NT, QLD, WA', 'NSW, NT', 'Summer rainfall']. ['Onthophagus taurus Schreber', 'Spain, Greece, Italy, Turkey', '164,499', 'February 1975', 'January 1984', 'NSW, SA, Tas, Vic, WA', 'NSW, SA, Tas, Vic, WA', 'Winter rainfall']. ['Sisyphus rubrus Paschalidis', 'South Africa', '85,933', 'March 1973', 'February 1980', 'NSW, QLD, WA', 'NSW, QLD', 'Summer rainfall']. ['Sisyphus spinipes', 'South Africa', '36,125', 'March 1972', 'December 1978', 'NSW, NT, QLD, WA', 'NSW, QLD', 'Summer rainfall']. ['', 'Total:', '1,680,399', '', '', '', '', '']
Answer: Passage: The species Bubas bison originated in the country of France, Spain. The species was first released in April 1983, and last released in 1996 (not by CSIRO) in the WAareas, making the total count of release to 1,613. The species was established in NSW, SA, WA areas. The pasture type for the spices is Winter rainfall. The species Copris elphenor Klug originated in the country of South Africa. The species was first released in January 1977, and last released in May 1983 in the QLDareas, making the total count of release to 2,287. The species was established in QLD areas. The pasture type for the spices is Summer rainfall. The species Copris hispanus Linnaeus originated in the country of Spain. The species was first released in October 1983, and last released in June 1994 in the WAareas, making the total count of release to 294. The species was established in WA areas. The pasture type for the spices is Winter rainfall. The species Euoniticellus africanus Harold originated in the country of South Africa. The species was first released in October 1971, and last released in February 1984 in the NSW, QLD, SA, Tas, Vic, WAareas, making the total count of release to 49,009. The species was established in NSW, QLD areas. The pasture type for the spices is Summer rainfall. The species Euoniticellus fulvus Goeze originated in the country of France, Turkey. The species was first released in March 1978, and last released in February 1983 in the NSW, SA, Tas, Vic, WAareas, making the total count of release to 76,944. The species was established in NSW, SA, Tas, Vic, WA areas. The pasture type for the spices is Winter rainfall. The species Euoniticellus intermedius Reiche originated in the country of South Africa. The species was first released in November 1971, and last released in February 1984 in the ACT, NSW, NT, QLD, SA, Vic, WAareas, making the total count of release to 248,637. The species was established in NSW, NT, QLD, SA, Vic, WA areas. The pasture type for the spices is Summer rainfall. The species Euoniticellus pallipes Fabricius originated in the country of Iran, Turkey. The species was first released in March 1977, and last released in September 1982 in the NSW, SA, WAareas, making the total count of release to 46,642. The species was established in NSW, SA, Vic, WA areas. The pasture type for the spices is Winter rainfall. The species Geotrupes spiniger Marsham originated in the country of France. The species was first released in April 1979, and last released in December 1983 in the ACT, NSW, Tas, Vicareas, making the total count of release to 12,082. The species was established in ACT, NSW, SA, Tas, Vic areas. The pasture type for the spices is Winter rainfall. The species Liatongus militaris Castelanu originated in the country of South Africa (via Hawaii). The species was first released in January 1968, and last released in November 1979 in the NSW, NT, QLD, WAareas, making the total count of release to 70,450. The species was established in NSW, NT, QLD areas. The pasture type for the spices is Summer rainfall. The species Onitis alexis Fabricius originated in the country of South Africa. The species was first released in August 1972, and last released in February 1984 in the NSW, NT, QLD, WAareas, making the total count of release to 186,441. The species was established in NSW, NT, QLD, SA, Vic, WA areas. The pasture type for the spices is Rainfall, summer rainfall, winter rainfall. The species Onitis aygalus Fabricius originated in the country of South Africa. The species was first released in January 1977, and last released in January 1982 in the NSW, SA, WAareas, making the total count of release to 18,682. The species was established in NSW, SA, Vic, WA areas. The pasture type for the spices is Winter rainfall. The species Onitis caffer Boheman originated in the country of South Africa. The species was first released in October 1979, and last released in April 1984 in the WAareas, making the total count of release to 8,738. The species was established in QLD, NSW, SA areas. The pasture type for the spices is Summer rainfall, winter rainfall. The species Onitis pecuarius Lansberge originated in the country of South Africa. The species was first released in November 1976, and last released in May 1979 in the NSW, QLDareas, making the total count of release to 11,395. The species was established in NSW, QLD areas. The pasture type for the spices is Summer rainfall. The species Onitis vanderkelleni Lansberge originated in the country of Kenya, Rwanda, Zaire. The species was first released in October 1974, and last released in February 1982 in the NSW, QLDareas, making the total count of release to 10,852. The species was established in QLD areas. The pasture type for the spices is Summer rainfall. The species Onitis viridulus Bohemann originated in the country of South Africa. The species was first released in September 1976, and last released in July 1980 in the NSW, NT, QLDareas, making the total count of release to 8,008. The species was established in NSW, NT, QLD, WA areas. The pasture type for the spices is Summer rainfall. The species Onthophagus binodis Thunberg originated in the country of South Africa. The species was first released in October 1971, and last released in February 1982 in the NSW, QLD, SA, Tas, Vic, WA, Norfolk Islandsareas, making the total count of release to 173,018. The species was established in NSW, QLD, SA, Tas, Vic, WA, Norfolk Islands areas. The pasture type for the spices is Winter rainfall. The species Onthophagus gazella Fabricius originated in the country of South Africa. The species was first released in February 1968, and last released in February 1984 in the ACT, NSW, NT, QLD, SA, Tas, Vic, WA, Norfolk Islandsareas, making the total count of release to 420,415. The species was established in ACT, NSW, NT, QLD, SA, WA, Norfolk Islands areas. The pasture type for the spices is Summer rainfall. The species Onthophagus nigiventris d'Orbigny originated in the country of East Africa. The species was first released in May 1975, and last released in March 1983 in the NSWareas, making the total count of release to 29,960. The species was established in NSW areas. The pasture type for the spices is Summer rainfall. The species Onthophagus obliquus originated in the country of Nigeria, Senegal, Zaire. The species was first released in January 1976, and last released in November 1977 in the QLD, NTareas, making the total count of release to 9,300. The species was established in QLD areas. The pasture type for the spices is Summer rainfall. The species Onthophagus sagittarius originated in the country of Sri Lanka (via Hawaii). The species was first released in January 1968, and last released in March 1977 in the NSW, NT, QLD, WAareas, making the total count of release to 9,075. The species was established in NSW, NT areas. The pasture type for the spices is Summer rainfall. The species Onthophagus taurus Schreber originated in the country of Spain, Greece, Italy, Turkey. The species was first released in February 1975, and last released in January 1984 in the NSW, SA, Tas, Vic, WAareas, making the total count of release to 164,499. The species was established in NSW, SA, Tas, Vic, WA areas. The pasture type for the spices is Winter rainfall. The species Sisyphus rubrus Paschalidis originated in the country of South Africa. The species was first released in March 1973, and last released in February 1980 in the NSW, QLD, WAareas, making the total count of release to 85,933. The species was established in NSW, QLD areas. The pasture type for the spices is Summer rainfall. The species Sisyphus spinipes originated in the country of South Africa. The species was first released in March 1972, and last released in December 1978 in the NSW, NT, QLD, WAareas, making the total count of release to 36,125. The species was established in NSW, QLD areas. The pasture type for the spices is Summer rainfall. The species originated in the country of Total:. The species was first released in , and last released in in the areas, making the total count of release to 1,680,399. The species was established in areas. The pasture type for the spices is .
Question: Table: ['Name', 'Gender', 'Age', 'From', 'Occupation', 'Prize Money (USD)', 'Status']. ['Trisha', 'Female', '28', 'Santa Monica, CA', 'Artist', '$26,000', 'Winner']. ['London', 'Male', '46', 'Mt. Holly, NJ', 'US Coast Guard (Retired)', '$0', 'Lost']. ['Adria', 'Female', '25', 'Seattle, WA', 'Bartender', '$0', '7th Captured (by Ricky Ortiz)']. ['Lucas', 'Male', '32', 'Carlsbad, CA', 'Student', '$0', '6th Captured (by Kim)']. ['Andrew', 'Male', '21', 'Redondo Beach, CA', 'Student / Lifeguard', '$0', '5th Captured (by Kim)']. ['Tracy', 'Female', '30', 'Mililani, HI', 'Student', '$0', '4th Captured (by Grant)']. ['Lynda', 'Female', '59', 'Los Angeles, CA', 'General Contractor', '$0', '3rd Captured (by Icey)']. ['Darin', 'Male', '46', 'Fontana, CA', 'Sports Official', '$0', '2nd Captured (by Wong)']. ['Evan', 'Male', '29', 'Long Island, NY', 'Teacher', '$2,000', 'Opted Out']. ['Ameenah', 'Female', '34', 'Atlanta, GA', 'Drummer', '$0', '1st Captured (by Grant)']
Answer: Passage: The person named Trisha, finished at position Winner and won $26,000 prize money. Trisha is a 28 years old Female from Santa Monica, CA. Trisha works as a Artist. The person named London, finished at position Lost and won $0 prize money. London is a 46 years old Male from Mt. Holly, NJ. London works as a US Coast Guard (Retired). The person named Adria, finished at position 7th Captured (by Ricky Ortiz) and won $0 prize money. Adria is a 25 years old Female from Seattle, WA. Adria works as a Bartender. The person named Lucas, finished at position 6th Captured (by Kim) and won $0 prize money. Lucas is a 32 years old Male from Carlsbad, CA. Lucas works as a Student. The person named Andrew, finished at position 5th Captured (by Kim) and won $0 prize money. Andrew is a 21 years old Male from Redondo Beach, CA. Andrew works as a Student / Lifeguard. The person named Tracy, finished at position 4th Captured (by Grant) and won $0 prize money. Tracy is a 30 years old Female from Mililani, HI. Tracy works as a Student. The person named Lynda, finished at position 3rd Captured (by Icey) and won $0 prize money. Lynda is a 59 years old Female from Los Angeles, CA. Lynda works as a General Contractor. The person named Darin, finished at position 2nd Captured (by Wong) and won $0 prize money. Darin is a 46 years old Male from Fontana, CA. Darin works as a Sports Official. The person named Evan, finished at position Opted Out and won $2,000 prize money. Evan is a 29 years old Male from Long Island, NY. Evan works as a Teacher. The person named Ameenah, finished at position 1st Captured (by Grant) and won $0 prize money. Ameenah is a 34 years old Female from Atlanta, GA. Ameenah works as a Drummer.
Question: Table: ['Pick #', 'CFL Team', 'Player', 'Position', 'College']. ['25', 'Montreal Alouettes', 'Shawn Gifford', 'OT', 'Charleston Southern']. ['26', 'Toronto Argonauts', 'Kevin Eiben', 'S', 'Bucknell']. ['27', 'Winnipeg Blue Bombers', 'Nick Tsatsaronis', 'RB', 'Memphis']. ['28', 'Hamilton Tiger-Cats', 'Ryan Donnelly', 'OL', 'McMaster']. ['29', 'Montreal Alouettes', 'Peter Moore', 'DL', 'Syracuse']. ['30', 'Calgary Stampeders', 'Andrew Carter', 'OL', "Bishop's"]. ['31', 'Montreal Alouettes', 'Steven Maheu', 'WR/QB', 'Simon Fraser']. ['32', 'BC Lions', 'Kelly Bates', 'OL', 'Saskatchewan']
Answer:
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Passage: The player named Shawn Gifford was picked at 25 position. The player plays at position OT in the team Montreal Alouettes from the college Charleston Southern. The player named Kevin Eiben was picked at 26 position. The player plays at position S in the team Toronto Argonauts from the college Bucknell. The player named Nick Tsatsaronis was picked at 27 position. The player plays at position RB in the team Winnipeg Blue Bombers from the college Memphis. The player named Ryan Donnelly was picked at 28 position. The player plays at position OL in the team Hamilton Tiger-Cats from the college McMaster. The player named Peter Moore was picked at 29 position. The player plays at position DL in the team Montreal Alouettes from the college Syracuse. The player named Andrew Carter was picked at 30 position. The player plays at position OL in the team Calgary Stampeders from the college Bishop's. The player named Steven Maheu was picked at 31 position. The player plays at position WR/QB in the team Montreal Alouettes from the college Simon Fraser. The player named Kelly Bates was picked at 32 position. The player plays at position OL in the team BC Lions from the college Saskatchewan.
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task760_msr_sqa_long_text_generation
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NIv2
|
fs_opt
| 7
|
train
|
Given the task definition and input, reply with output. You are given data in tabular format and you need to generate a passage with content in plain text format based on the information present in the table.
Table: ['Rank', 'Nation', 'Gold', 'Silver', 'Bronze', 'Total']. ['1', 'Algeria', '8', '3', '0', '11']. ['2', 'Tunisia', '4', '3', '5', '12']. ['3', 'Egypt', '3', '3', '3', '9']. ['4', 'Cameroon', '1', '1', '5', '7']. ['5', 'Morocco', '0', '1', '5', '5']. ['6', 'South Africa', '0', '1', '1', '2']. ['7', 'Angola', '0', '1', '0', '1']. ['7', 'Burkina Faso', '0', '1', '0', '1']. ['7', 'Gabon', '0', '1', '0', '1']. ['7', 'Madagascar', '0', '1', '0', '1']. ['11', 'Nigeria', '0', '0', '3', '3']. ['12', 'Senegal', '0', '0', '2', '2']. ['13', 'Congo Republic', '0', '0', '1', '1']. ['13', 'Ivory Coast', '0', '0', '1', '1']. ['13', 'Guinea', '0', '0', '1', '1']. ['13', 'Niger', '0', '0', '1', '1']
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Passage: The nation, Algeria, has ranked 1. Algeria won 8 gold medals, 3 silver medals, and 0 bronze medals. Algeria won 11 medals in total. The nation, Tunisia, has ranked 2. Tunisia won 4 gold medals, 3 silver medals, and 5 bronze medals. Tunisia won 12 medals in total. The nation, Egypt, has ranked 3. Egypt won 3 gold medals, 3 silver medals, and 3 bronze medals. Egypt won 9 medals in total. The nation, Cameroon, has ranked 4. Cameroon won 1 gold medals, 1 silver medals, and 5 bronze medals. Cameroon won 7 medals in total. The nation, Morocco, has ranked 5. Morocco won 0 gold medals, 1 silver medals, and 5 bronze medals. Morocco won 5 medals in total. The nation, South Africa, has ranked 6. South Africa won 0 gold medals, 1 silver medals, and 1 bronze medals. South Africa won 2 medals in total. The nation, Angola, has ranked 7. Angola won 0 gold medals, 1 silver medals, and 0 bronze medals. Angola won 1 medals in total. The nation, Burkina Faso, has ranked 7. Burkina Faso won 0 gold medals, 1 silver medals, and 0 bronze medals. Burkina Faso won 1 medals in total. The nation, Gabon, has ranked 7. Gabon won 0 gold medals, 1 silver medals, and 0 bronze medals. Gabon won 1 medals in total. The nation, Madagascar, has ranked 7. Madagascar won 0 gold medals, 1 silver medals, and 0 bronze medals. Madagascar won 1 medals in total. The nation, Nigeria, has ranked 11. Nigeria won 0 gold medals, 0 silver medals, and 3 bronze medals. Nigeria won 3 medals in total. The nation, Senegal, has ranked 12. Senegal won 0 gold medals, 0 silver medals, and 2 bronze medals. Senegal won 2 medals in total. The nation, Congo Republic, has ranked 13. Congo Republic won 0 gold medals, 0 silver medals, and 1 bronze medals. Congo Republic won 1 medals in total. The nation, Ivory Coast, has ranked 13. Ivory Coast won 0 gold medals, 0 silver medals, and 1 bronze medals. Ivory Coast won 1 medals in total. The nation, Guinea, has ranked 13. Guinea won 0 gold medals, 0 silver medals, and 1 bronze medals. Guinea won 1 medals in total. The nation, Niger, has ranked 13. Niger won 0 gold medals, 0 silver medals, and 1 bronze medals. Niger won 1 medals in total.
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task760_msr_sqa_long_text_generation
|
NIv2
|
zs_opt
| 5
|
train
|
You are given data in tabular format and you need to generate a passage with content in plain text format based on the information present in the table.
Table: ['Place', 'Position', 'Number', 'Name', 'NASL', 'Playoffs', 'CFU Club Championship', 'CONCACAF Champions League', 'Total']. ['1', 'FW', '11', 'Nicholas Addlery', '9', '0', '0', '1', '10']. ['2', 'FW', '9', 'Jonathan Fana', '4', '0', '4', '0', '8']. ['3', 'FW', '7', 'David Foley', '6', '1', '0', '0', '7']. ['3', 'FW', '24', 'Hector Ramos', '3', '0', '2', '2', '7']. ['5', 'DF', '33', 'Jay Needham', '3', '0', '0', '0', '3']. ['5', 'FW', '22', 'Gregory Richardson', '1', '0', '1', '1', '3']. ['7', 'MF', '20', 'Josh Hansen', '0', '0', '2', '0', '2']. ['7', '', '', 'Own Goal', '0', '0', '2', '0', '2']. ['9', 'DF', '3', 'Richard Martinez', '1', '0', '0', '0', '1']. ['9', 'DF', '16', 'Anthony Vazquez', '1', '0', '0', '0', '1']. ['9', 'DF', '5', 'Noah Delgado', '1', '0', '0', '0', '1']. ['9', 'MF', '14', 'Jarad Van Schaik', '1', '0', '0', '0', '1']. ['9', 'MF', '17', 'Tyler Wilson', '1', '0', '0', '0', '1']. ['9', 'MF', '24', 'Justin Fojo', '1', '0', '0', '0', '1']. ['', '', '', 'TOTALS', '32', '1', '11', '4', '48']
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Passage: The player named Nicholas Addlery with jersey number 11, plays at position FW. There were total 0 playoffs, 0 CFU Club Championships, 1 CONCACAF Champions Leagues. Total 10 matches. The player named Jonathan Fana with jersey number 9, plays at position FW. There were total 0 playoffs, 4 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 8 matches. The player named David Foley with jersey number 7, plays at position FW. There were total 1 playoffs, 0 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 7 matches. The player named Hector Ramos with jersey number 24, plays at position FW. There were total 0 playoffs, 2 CFU Club Championships, 2 CONCACAF Champions Leagues. Total 7 matches. The player named Jay Needham with jersey number 33, plays at position DF. There were total 0 playoffs, 0 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 3 matches. The player named Gregory Richardson with jersey number 22, plays at position FW. There were total 0 playoffs, 1 CFU Club Championships, 1 CONCACAF Champions Leagues. Total 3 matches. The player named Josh Hansen with jersey number 20, plays at position MF. There were total 0 playoffs, 2 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 2 matches. The player named Own Goal with jersey number , plays at position . There were total 0 playoffs, 2 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 2 matches. The player named Richard Martinez with jersey number 3, plays at position DF. There were total 0 playoffs, 0 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 1 matches. The player named Anthony Vazquez with jersey number 16, plays at position DF. There were total 0 playoffs, 0 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 1 matches. The player named Noah Delgado with jersey number 5, plays at position DF. There were total 0 playoffs, 0 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 1 matches. The player named Jarad Van Schaik with jersey number 14, plays at position MF. There were total 0 playoffs, 0 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 1 matches. The player named Tyler Wilson with jersey number 17, plays at position MF. There were total 0 playoffs, 0 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 1 matches. The player named Justin Fojo with jersey number 24, plays at position MF. There were total 0 playoffs, 0 CFU Club Championships, 0 CONCACAF Champions Leagues. Total 1 matches. The player named TOTALS with jersey number , plays at position . There were total 1 playoffs, 11 CFU Club Championships, 4 CONCACAF Champions Leagues. Total 48 matches.
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task760_msr_sqa_long_text_generation
|
NIv2
|
zs_opt
| 0
|
train
|
Given the task definition and input, reply with output. You are given data in tabular format and you need to generate a passage with content in plain text format based on the information present in the table.
Table: ['Species', 'Country of origin', 'Total released', 'First release', 'Last release', 'Areas of release', 'Areas established', 'Pasture type']. ['Bubas bison', 'France, Spain', '1,613', 'April 1983', '1996 (not by CSIRO)', 'WA', 'NSW, SA, WA', 'Winter rainfall']. ['Copris elphenor Klug', 'South Africa', '2,287', 'January 1977', 'May 1983', 'QLD', 'QLD', 'Summer rainfall']. ['Copris hispanus Linnaeus', 'Spain', '294', 'October 1983', 'June 1994', 'WA', 'WA', 'Winter rainfall']. ['Euoniticellus africanus Harold', 'South Africa', '49,009', 'October 1971', 'February 1984', 'NSW, QLD, SA, Tas, Vic, WA', 'NSW, QLD', 'Summer rainfall']. ['Euoniticellus fulvus Goeze', 'France, Turkey', '76,944', 'March 1978', 'February 1983', 'NSW, SA, Tas, Vic, WA', 'NSW, SA, Tas, Vic, WA', 'Winter rainfall']. ['Euoniticellus intermedius Reiche', 'South Africa', '248,637', 'November 1971', 'February 1984', 'ACT, NSW, NT, QLD, SA, Vic, WA', 'NSW, NT, QLD, SA, Vic, WA', 'Summer rainfall']. ['Euoniticellus pallipes Fabricius', 'Iran, Turkey', '46,642', 'March 1977', 'September 1982', 'NSW, SA, WA', 'NSW, SA, Vic, WA', 'Winter rainfall']. ['Geotrupes spiniger Marsham', 'France', '12,082', 'April 1979', 'December 1983', 'ACT, NSW, Tas, Vic', 'ACT, NSW, SA, Tas, Vic', 'Winter rainfall']. ['Liatongus militaris Castelanu', 'South Africa (via Hawaii)', '70,450', 'January 1968', 'November 1979', 'NSW, NT, QLD, WA', 'NSW, NT, QLD', 'Summer rainfall']. ['Onitis alexis Fabricius', 'South Africa', '186,441', 'August 1972', 'February 1984', 'NSW, NT, QLD, WA', 'NSW, NT, QLD, SA, Vic, WA', 'Rainfall, summer rainfall, winter rainfall']. ['Onitis aygalus Fabricius', 'South Africa', '18,682', 'January 1977', 'January 1982', 'NSW, SA, WA', 'NSW, SA, Vic, WA', 'Winter rainfall']. ['Onitis caffer Boheman', 'South Africa', '8,738', 'October 1979', 'April 1984', 'WA', 'QLD, NSW, SA', 'Summer rainfall, winter rainfall']. ['Onitis pecuarius Lansberge', 'South Africa', '11,395', 'November 1976', 'May 1979', 'NSW, QLD', 'NSW, QLD', 'Summer rainfall']. ['Onitis vanderkelleni Lansberge', 'Kenya, Rwanda, Zaire', '10,852', 'October 1974', 'February 1982', 'NSW, QLD', 'QLD', 'Summer rainfall']. ['Onitis viridulus Bohemann', 'South Africa', '8,008', 'September 1976', 'July 1980', 'NSW, NT, QLD', 'NSW, NT, QLD, WA', 'Summer rainfall']. ['Onthophagus binodis Thunberg', 'South Africa', '173,018', 'October 1971', 'February 1982', 'NSW, QLD, SA, Tas, Vic, WA, Norfolk Islands', 'NSW, QLD, SA, Tas, Vic, WA, Norfolk Islands', 'Winter rainfall']. ['Onthophagus gazella Fabricius', 'South Africa', '420,415', 'February 1968', 'February 1984', 'ACT, NSW, NT, QLD, SA, Tas, Vic, WA, Norfolk Islands', 'ACT, NSW, NT, QLD, SA, WA, Norfolk Islands', 'Summer rainfall']. ["Onthophagus nigiventris d'Orbigny", 'East Africa', '29,960', 'May 1975', 'March 1983', 'NSW', 'NSW', 'Summer rainfall']. ['Onthophagus obliquus', 'Nigeria, Senegal, Zaire', '9,300', 'January 1976', 'November 1977', 'QLD, NT', 'QLD', 'Summer rainfall']. ['Onthophagus sagittarius', 'Sri Lanka (via Hawaii)', '9,075', 'January 1968', 'March 1977', 'NSW, NT, QLD, WA', 'NSW, NT', 'Summer rainfall']. ['Onthophagus taurus Schreber', 'Spain, Greece, Italy, Turkey', '164,499', 'February 1975', 'January 1984', 'NSW, SA, Tas, Vic, WA', 'NSW, SA, Tas, Vic, WA', 'Winter rainfall']. ['Sisyphus rubrus Paschalidis', 'South Africa', '85,933', 'March 1973', 'February 1980', 'NSW, QLD, WA', 'NSW, QLD', 'Summer rainfall']. ['Sisyphus spinipes', 'South Africa', '36,125', 'March 1972', 'December 1978', 'NSW, NT, QLD, WA', 'NSW, QLD', 'Summer rainfall']. ['', 'Total:', '1,680,399', '', '', '', '', '']
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Passage: The species Bubas bison originated in the country of France, Spain. The species was first released in April 1983, and last released in 1996 (not by CSIRO) in the WAareas, making the total count of release to 1,613. The species was established in NSW, SA, WA areas. The pasture type for the spices is Winter rainfall. The species Copris elphenor Klug originated in the country of South Africa. The species was first released in January 1977, and last released in May 1983 in the QLDareas, making the total count of release to 2,287. The species was established in QLD areas. The pasture type for the spices is Summer rainfall. The species Copris hispanus Linnaeus originated in the country of Spain. The species was first released in October 1983, and last released in June 1994 in the WAareas, making the total count of release to 294. The species was established in WA areas. The pasture type for the spices is Winter rainfall. The species Euoniticellus africanus Harold originated in the country of South Africa. The species was first released in October 1971, and last released in February 1984 in the NSW, QLD, SA, Tas, Vic, WAareas, making the total count of release to 49,009. The species was established in NSW, QLD areas. The pasture type for the spices is Summer rainfall. The species Euoniticellus fulvus Goeze originated in the country of France, Turkey. The species was first released in March 1978, and last released in February 1983 in the NSW, SA, Tas, Vic, WAareas, making the total count of release to 76,944. The species was established in NSW, SA, Tas, Vic, WA areas. The pasture type for the spices is Winter rainfall. The species Euoniticellus intermedius Reiche originated in the country of South Africa. The species was first released in November 1971, and last released in February 1984 in the ACT, NSW, NT, QLD, SA, Vic, WAareas, making the total count of release to 248,637. The species was established in NSW, NT, QLD, SA, Vic, WA areas. The pasture type for the spices is Summer rainfall. The species Euoniticellus pallipes Fabricius originated in the country of Iran, Turkey. The species was first released in March 1977, and last released in September 1982 in the NSW, SA, WAareas, making the total count of release to 46,642. The species was established in NSW, SA, Vic, WA areas. The pasture type for the spices is Winter rainfall. The species Geotrupes spiniger Marsham originated in the country of France. The species was first released in April 1979, and last released in December 1983 in the ACT, NSW, Tas, Vicareas, making the total count of release to 12,082. The species was established in ACT, NSW, SA, Tas, Vic areas. The pasture type for the spices is Winter rainfall. The species Liatongus militaris Castelanu originated in the country of South Africa (via Hawaii). The species was first released in January 1968, and last released in November 1979 in the NSW, NT, QLD, WAareas, making the total count of release to 70,450. The species was established in NSW, NT, QLD areas. The pasture type for the spices is Summer rainfall. The species Onitis alexis Fabricius originated in the country of South Africa. The species was first released in August 1972, and last released in February 1984 in the NSW, NT, QLD, WAareas, making the total count of release to 186,441. The species was established in NSW, NT, QLD, SA, Vic, WA areas. The pasture type for the spices is Rainfall, summer rainfall, winter rainfall. The species Onitis aygalus Fabricius originated in the country of South Africa. The species was first released in January 1977, and last released in January 1982 in the NSW, SA, WAareas, making the total count of release to 18,682. The species was established in NSW, SA, Vic, WA areas. The pasture type for the spices is Winter rainfall. The species Onitis caffer Boheman originated in the country of South Africa. The species was first released in October 1979, and last released in April 1984 in the WAareas, making the total count of release to 8,738. The species was established in QLD, NSW, SA areas. The pasture type for the spices is Summer rainfall, winter rainfall. The species Onitis pecuarius Lansberge originated in the country of South Africa. The species was first released in November 1976, and last released in May 1979 in the NSW, QLDareas, making the total count of release to 11,395. The species was established in NSW, QLD areas. The pasture type for the spices is Summer rainfall. The species Onitis vanderkelleni Lansberge originated in the country of Kenya, Rwanda, Zaire. The species was first released in October 1974, and last released in February 1982 in the NSW, QLDareas, making the total count of release to 10,852. The species was established in QLD areas. The pasture type for the spices is Summer rainfall. The species Onitis viridulus Bohemann originated in the country of South Africa. The species was first released in September 1976, and last released in July 1980 in the NSW, NT, QLDareas, making the total count of release to 8,008. The species was established in NSW, NT, QLD, WA areas. The pasture type for the spices is Summer rainfall. The species Onthophagus binodis Thunberg originated in the country of South Africa. The species was first released in October 1971, and last released in February 1982 in the NSW, QLD, SA, Tas, Vic, WA, Norfolk Islandsareas, making the total count of release to 173,018. The species was established in NSW, QLD, SA, Tas, Vic, WA, Norfolk Islands areas. The pasture type for the spices is Winter rainfall. The species Onthophagus gazella Fabricius originated in the country of South Africa. The species was first released in February 1968, and last released in February 1984 in the ACT, NSW, NT, QLD, SA, Tas, Vic, WA, Norfolk Islandsareas, making the total count of release to 420,415. The species was established in ACT, NSW, NT, QLD, SA, WA, Norfolk Islands areas. The pasture type for the spices is Summer rainfall. The species Onthophagus nigiventris d'Orbigny originated in the country of East Africa. The species was first released in May 1975, and last released in March 1983 in the NSWareas, making the total count of release to 29,960. The species was established in NSW areas. The pasture type for the spices is Summer rainfall. The species Onthophagus obliquus originated in the country of Nigeria, Senegal, Zaire. The species was first released in January 1976, and last released in November 1977 in the QLD, NTareas, making the total count of release to 9,300. The species was established in QLD areas. The pasture type for the spices is Summer rainfall. The species Onthophagus sagittarius originated in the country of Sri Lanka (via Hawaii). The species was first released in January 1968, and last released in March 1977 in the NSW, NT, QLD, WAareas, making the total count of release to 9,075. The species was established in NSW, NT areas. The pasture type for the spices is Summer rainfall. The species Onthophagus taurus Schreber originated in the country of Spain, Greece, Italy, Turkey. The species was first released in February 1975, and last released in January 1984 in the NSW, SA, Tas, Vic, WAareas, making the total count of release to 164,499. The species was established in NSW, SA, Tas, Vic, WA areas. The pasture type for the spices is Winter rainfall. The species Sisyphus rubrus Paschalidis originated in the country of South Africa. The species was first released in March 1973, and last released in February 1980 in the NSW, QLD, WAareas, making the total count of release to 85,933. The species was established in NSW, QLD areas. The pasture type for the spices is Summer rainfall. The species Sisyphus spinipes originated in the country of South Africa. The species was first released in March 1972, and last released in December 1978 in the NSW, NT, QLD, WAareas, making the total count of release to 36,125. The species was established in NSW, QLD areas. The pasture type for the spices is Summer rainfall. The species originated in the country of Total:. The species was first released in , and last released in in the areas, making the total count of release to 1,680,399. The species was established in areas. The pasture type for the spices is .
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task760_msr_sqa_long_text_generation
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NIv2
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zs_opt
| 5
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train
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You are given data in tabular format and you need to generate a passage with content in plain text format based on the information present in the table.
[Q]: Table: ['Wager', 'Winner', 'Loser', 'Location', 'Date', 'Notes']. ['Hair', 'Psycho Clown', 'Super Crazy', 'Mexico City, Distrito Federal', 'May 29, 2011', 'Six man tag team steel cage Masks vs. Hairs match, where Los Perros del Mal (Crazy, El Hijo del Perro Aguayo and Damian 666) faced Los Psycho Circus (Psycho Clown, Monster Clown and Murder Clown).']. ['Hair', 'Halloween', 'Coco Rojo', 'Tlalnepantla de Baz, State of Mexico', 'July 10, 2011', 'Steel cage match, where Los Perros del Mal (Halloween, Damian 666 and Ek Balam) faced Los Payasos Tricolor (Coco Rojo, Coco Azul and Coco Amarillo) and Los Psycho Circus (Monster Clown, Murder Clown and Psycho Clown).']. ['Hair', 'Psycho Clown', 'X-Fly', 'Guadalajara, Jalisco', 'July 31, 2011', 'Six man tag team steel cage Masks vs. Hairs match, where Los Perros del Mal (X-Fly, Damian 666 and Halloween) faced Los Psycho Circus.']. ['Title', 'Damian 666', 'Monster Clown', 'Naucalpan, Mexico', 'August 28, 2011', 'Four tag team steel cage match, where Los Psycho Circus put their IWRG Intercontinental Trios Championship on the line against the hairs/masks of Los Perros del Mal (Damian 666, Bestia 666 and X-Fly), Los Temerarios (Black Terry, Durok and Machin) and Los Villanos (Kortiz, Ray Mendoza, Jr. and Villano IV).']. ['Hair', 'Monster Clown, Murder Clown and Psycho Clown', 'Halloween, Damian 666 and Nicho el Millonario', 'Monterrey, Nuevo Leon', 'October 9, 2011', 'Steel cage Masks vs. Hairs match.']. ['Hair', 'Psicosis', 'Joe Lider', 'Mexico City', 'August 5, 2012', '']. ['Hair', 'Dark Cuervo', 'Halloween', 'San Luis Potosi, San Luis Potosi', 'October 7, 2012', 'Domo de la Muerte, where Los Perros del Mal (Halloween, El Hijo del Perro Aguayo, Psicosis and Teddy Hart) faced Dark Cuervo, Cibernetico, Dark Ozz and Jack Evans.']
[A]: Passage: On May 29, 2011, there was Hair based wager on the professional wrestlers, row[1] and Super Crazy at the location Mexico City, Distrito Federal. row[1] won the match , and row[2] lost the match. Additional details: Six man tag team steel cage Masks vs. Hairs match, where Los Perros del Mal (Crazy, El Hijo del Perro Aguayo and Damian 666) faced Los Psycho Circus (Psycho Clown, Monster Clown and Murder Clown).. On July 10, 2011, there was Hair based wager on the professional wrestlers, row[1] and Coco Rojo at the location Tlalnepantla de Baz, State of Mexico. row[1] won the match , and row[2] lost the match. Additional details: Steel cage match, where Los Perros del Mal (Halloween, Damian 666 and Ek Balam) faced Los Payasos Tricolor (Coco Rojo, Coco Azul and Coco Amarillo) and Los Psycho Circus (Monster Clown, Murder Clown and Psycho Clown).. On July 31, 2011, there was Hair based wager on the professional wrestlers, row[1] and X-Fly at the location Guadalajara, Jalisco. row[1] won the match , and row[2] lost the match. Additional details: Six man tag team steel cage Masks vs. Hairs match, where Los Perros del Mal (X-Fly, Damian 666 and Halloween) faced Los Psycho Circus.. On August 28, 2011, there was Title based wager on the professional wrestlers, row[1] and Monster Clown at the location Naucalpan, Mexico. row[1] won the match , and row[2] lost the match. Additional details: Four tag team steel cage match, where Los Psycho Circus put their IWRG Intercontinental Trios Championship on the line against the hairs/masks of Los Perros del Mal (Damian 666, Bestia 666 and X-Fly), Los Temerarios (Black Terry, Durok and Machin) and Los Villanos (Kortiz, Ray Mendoza, Jr. and Villano IV).. On October 9, 2011, there was Hair based wager on the professional wrestlers, row[1] and Halloween, Damian 666 and Nicho el Millonario at the location Monterrey, Nuevo Leon. row[1] won the match , and row[2] lost the match. Additional details: Steel cage Masks vs. Hairs match.. On August 5, 2012, there was Hair based wager on the professional wrestlers, row[1] and Joe Lider at the location Mexico City. row[1] won the match , and row[2] lost the match. Additional details: . On October 7, 2012, there was Hair based wager on the professional wrestlers, row[1] and Halloween at the location San Luis Potosi, San Luis Potosi. row[1] won the match , and row[2] lost the match. Additional details: Domo de la Muerte, where Los Perros del Mal (Halloween, El Hijo del Perro Aguayo, Psicosis and Teddy Hart) faced Dark Cuervo, Cibernetico, Dark Ozz and Jack Evans..
[Q]: Table: ['Date', 'City', 'Venue', 'Member', 'Performance', 'Notes']. ['15 January', 'Dublin', 'RTE Studios', 'Brian & Roger', '(1) We Will Rock You', '']. ['(2) We Are the Champions', 'The Late Late Show', '', '', '', '']. ['31 January', 'Dublin', 'The O2', 'Brian', '(1) Bohemian Rhapsody', 'Matinee and Evening performances. Roger attended but did not perform.']. ['10 May', 'London', 'Dominion Theatre', 'Brian & Roger', '(1) Bohemian Rhapsody', '8th anniversary.']. ['3 September', 'Utrecht', 'Beatrix Theatre', 'Brian', '(1) Bohemian Rhapsody', '']. ['4 September', 'London', 'Dominion Theatre', 'Brian', '(1) Bohemian Rhapsody', 'Matinee and Evening performances']. ['12 September', 'Stockholm', 'Cirkus Arena Restaurang', 'Brian', '(1) Bohemian Rhapsody', '']. ['21 October', 'Berlin', 'Theater des Westens', 'Brian', '(1) Bohemian Rhapsody', '']
[A]: Passage: The artist Brian & Roger gave a live performance at RTE Studios in the city of Dublin on 15 January. The artist Brian & Roger performed (1) We Will Rock You. Additional details: . The artist gave a live performance at in the city of The Late Late Show on (2) We Are the Champions. The artist performed . Additional details: . The artist Brian gave a live performance at The O2 in the city of Dublin on 31 January. The artist Brian performed (1) Bohemian Rhapsody. Additional details: Matinee and Evening performances. Roger attended but did not perform.. The artist Brian & Roger gave a live performance at Dominion Theatre in the city of London on 10 May. The artist Brian & Roger performed (1) Bohemian Rhapsody. Additional details: 8th anniversary.. The artist Brian gave a live performance at Beatrix Theatre in the city of Utrecht on 3 September. The artist Brian performed (1) Bohemian Rhapsody. Additional details: . The artist Brian gave a live performance at Dominion Theatre in the city of London on 4 September. The artist Brian performed (1) Bohemian Rhapsody. Additional details: Matinee and Evening performances. The artist Brian gave a live performance at Cirkus Arena Restaurang in the city of Stockholm on 12 September. The artist Brian performed (1) Bohemian Rhapsody. Additional details: . The artist Brian gave a live performance at Theater des Westens in the city of Berlin on 21 October. The artist Brian performed (1) Bohemian Rhapsody. Additional details: .
[Q]: Table: ['Rank', 'Nation', 'Gold', 'Silver', 'Bronze', 'Total']. ['1', 'Algeria', '8', '3', '0', '11']. ['2', 'Tunisia', '4', '3', '5', '12']. ['3', 'Egypt', '3', '3', '3', '9']. ['4', 'Cameroon', '1', '1', '5', '7']. ['5', 'Morocco', '0', '1', '5', '5']. ['6', 'South Africa', '0', '1', '1', '2']. ['7', 'Angola', '0', '1', '0', '1']. ['7', 'Burkina Faso', '0', '1', '0', '1']. ['7', 'Gabon', '0', '1', '0', '1']. ['7', 'Madagascar', '0', '1', '0', '1']. ['11', 'Nigeria', '0', '0', '3', '3']. ['12', 'Senegal', '0', '0', '2', '2']. ['13', 'Congo Republic', '0', '0', '1', '1']. ['13', 'Ivory Coast', '0', '0', '1', '1']. ['13', 'Guinea', '0', '0', '1', '1']. ['13', 'Niger', '0', '0', '1', '1']
[A]:
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Passage: The nation, Algeria, has ranked 1. Algeria won 8 gold medals, 3 silver medals, and 0 bronze medals. Algeria won 11 medals in total. The nation, Tunisia, has ranked 2. Tunisia won 4 gold medals, 3 silver medals, and 5 bronze medals. Tunisia won 12 medals in total. The nation, Egypt, has ranked 3. Egypt won 3 gold medals, 3 silver medals, and 3 bronze medals. Egypt won 9 medals in total. The nation, Cameroon, has ranked 4. Cameroon won 1 gold medals, 1 silver medals, and 5 bronze medals. Cameroon won 7 medals in total. The nation, Morocco, has ranked 5. Morocco won 0 gold medals, 1 silver medals, and 5 bronze medals. Morocco won 5 medals in total. The nation, South Africa, has ranked 6. South Africa won 0 gold medals, 1 silver medals, and 1 bronze medals. South Africa won 2 medals in total. The nation, Angola, has ranked 7. Angola won 0 gold medals, 1 silver medals, and 0 bronze medals. Angola won 1 medals in total. The nation, Burkina Faso, has ranked 7. Burkina Faso won 0 gold medals, 1 silver medals, and 0 bronze medals. Burkina Faso won 1 medals in total. The nation, Gabon, has ranked 7. Gabon won 0 gold medals, 1 silver medals, and 0 bronze medals. Gabon won 1 medals in total. The nation, Madagascar, has ranked 7. Madagascar won 0 gold medals, 1 silver medals, and 0 bronze medals. Madagascar won 1 medals in total. The nation, Nigeria, has ranked 11. Nigeria won 0 gold medals, 0 silver medals, and 3 bronze medals. Nigeria won 3 medals in total. The nation, Senegal, has ranked 12. Senegal won 0 gold medals, 0 silver medals, and 2 bronze medals. Senegal won 2 medals in total. The nation, Congo Republic, has ranked 13. Congo Republic won 0 gold medals, 0 silver medals, and 1 bronze medals. Congo Republic won 1 medals in total. The nation, Ivory Coast, has ranked 13. Ivory Coast won 0 gold medals, 0 silver medals, and 1 bronze medals. Ivory Coast won 1 medals in total. The nation, Guinea, has ranked 13. Guinea won 0 gold medals, 0 silver medals, and 1 bronze medals. Guinea won 1 medals in total. The nation, Niger, has ranked 13. Niger won 0 gold medals, 0 silver medals, and 1 bronze medals. Niger won 1 medals in total.
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task760_msr_sqa_long_text_generation
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NIv2
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fs_opt
| 5
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train
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You are given data in tabular format and you need to generate a passage with content in plain text format based on the information present in the table.
Example: Table: ['Pick', 'Player', 'Team', 'Position', 'School']. ['1', 'Ben McDonald', 'Baltimore Orioles', 'RHP', 'Louisiana State University']. ['2', 'Tyler Houston', 'Atlanta Braves', 'C', 'Valley HS (Las Vegas, NV)']. ['3', 'Roger Salkeld', 'Seattle Mariners', 'RHP', 'Saugus (CA) HS']. ['4', 'Jeff Jackson', 'Philadelphia Phillies', 'OF', 'Simeon HS (Chicago, IL)']. ['5', 'Donald Harris', 'Texas Rangers', 'OF', 'Texas Tech University']. ['6', 'Paul Coleman', 'Saint Louis Cardinals', 'OF', 'Frankston (TX) HS']. ['7', 'Frank Thomas', 'Chicago White Sox', '1B', 'Auburn University']. ['8', 'Earl Cunningham', 'Chicago Cubs', 'OF', 'Lancaster (SC) HS']. ['9', 'Kyle Abbott', 'California Angels', 'LHP', 'Long Beach State University']. ['10', 'Charles Johnson', 'Montreal Expos', 'C', 'Westwood HS (Fort Pierce, FL)']. ['11', 'Calvin Murray', 'Cleveland Indians', '3B', 'W.T. White High School (Dallas, TX)']. ['12', 'Jeff Juden', 'Houston Astros', 'RHP', 'Salem (MA) HS']. ['13', 'Brent Mayne', 'Kansas City Royals', 'C', 'Cal State Fullerton']. ['14', 'Steve Hosey', 'San Francisco Giants', 'OF', 'Fresno State University']. ['15', 'Kiki Jones', 'Los Angeles Dodgers', 'RHP', 'Hillsborough HS (Tampa, FL)']. ['16', 'Greg Blosser', 'Boston Red Sox', 'OF', 'Sarasota (FL) HS']. ['17', 'Cal Eldred', 'Milwaukee Brewers', 'RHP', 'University of Iowa']. ['18', 'Willie Greene', 'Pittsburgh Pirates', 'SS', 'Jones County HS (Gray, GA)']. ['19', 'Eddie Zosky', 'Toronto Blue Jays', 'SS', 'Fresno State University']. ['20', 'Scott Bryant', 'Cincinnati Reds', 'OF', 'University of Texas']. ['21', 'Greg Gohr', 'Detroit Tigers', 'RHP', 'Santa Clara University']. ['22', 'Tom Goodwin', 'Los Angeles Dodgers', 'OF', 'Fresno State University']. ['23', 'Mo Vaughn', 'Boston Red Sox', '1B', 'Seton Hall University']. ['24', 'Alan Zinter', 'New York Mets', 'C', 'University of Arizona']. ['25', 'Chuck Knoblauch', 'Minnesota Twins', '2B', 'Texas A&M University']. ['26', 'Scott Burrell', 'Seattle Mariners', 'RHP', 'Hamden (CT) HS']
Example solution: Passage: The player named Ben McDonald, plays as Pick-1.Ben McDonald plays for the team Baltimore Orioles, at position RHP. Ben McDonald belongs to the school Louisiana State University. The player named Tyler Houston, plays as Pick-2.Tyler Houston plays for the team Atlanta Braves, at position C. Tyler Houston belongs to the school Valley HS (Las Vegas, NV). The player named Roger Salkeld, plays as Pick-3.Roger Salkeld plays for the team Seattle Mariners, at position RHP. Roger Salkeld belongs to the school Saugus (CA) HS. The player named Jeff Jackson, plays as Pick-4.Jeff Jackson plays for the team Philadelphia Phillies, at position OF. Jeff Jackson belongs to the school Simeon HS (Chicago, IL). The player named Donald Harris, plays as Pick-5.Donald Harris plays for the team Texas Rangers, at position OF. Donald Harris belongs to the school Texas Tech University. The player named Paul Coleman, plays as Pick-6.Paul Coleman plays for the team Saint Louis Cardinals, at position OF. Paul Coleman belongs to the school Frankston (TX) HS. The player named Frank Thomas, plays as Pick-7.Frank Thomas plays for the team Chicago White Sox, at position 1B. Frank Thomas belongs to the school Auburn University. The player named Earl Cunningham, plays as Pick-8.Earl Cunningham plays for the team Chicago Cubs, at position OF. Earl Cunningham belongs to the school Lancaster (SC) HS. The player named Kyle Abbott, plays as Pick-9.Kyle Abbott plays for the team California Angels, at position LHP. Kyle Abbott belongs to the school Long Beach State University. The player named Charles Johnson, plays as Pick-10.Charles Johnson plays for the team Montreal Expos, at position C. Charles Johnson belongs to the school Westwood HS (Fort Pierce, FL). The player named Calvin Murray, plays as Pick-11.Calvin Murray plays for the team Cleveland Indians, at position 3B. Calvin Murray belongs to the school W.T. White High School (Dallas, TX). The player named Jeff Juden, plays as Pick-12.Jeff Juden plays for the team Houston Astros, at position RHP. Jeff Juden belongs to the school Salem (MA) HS. The player named Brent Mayne, plays as Pick-13.Brent Mayne plays for the team Kansas City Royals, at position C. Brent Mayne belongs to the school Cal State Fullerton. The player named Steve Hosey, plays as Pick-14.Steve Hosey plays for the team San Francisco Giants, at position OF. Steve Hosey belongs to the school Fresno State University. The player named Kiki Jones, plays as Pick-15.Kiki Jones plays for the team Los Angeles Dodgers, at position RHP. Kiki Jones belongs to the school Hillsborough HS (Tampa, FL). The player named Greg Blosser, plays as Pick-16.Greg Blosser plays for the team Boston Red Sox, at position OF. Greg Blosser belongs to the school Sarasota (FL) HS. The player named Cal Eldred, plays as Pick-17.Cal Eldred plays for the team Milwaukee Brewers, at position RHP. Cal Eldred belongs to the school University of Iowa. The player named Willie Greene, plays as Pick-18.Willie Greene plays for the team Pittsburgh Pirates, at position SS. Willie Greene belongs to the school Jones County HS (Gray, GA). The player named Eddie Zosky, plays as Pick-19.Eddie Zosky plays for the team Toronto Blue Jays, at position SS. Eddie Zosky belongs to the school Fresno State University. The player named Scott Bryant, plays as Pick-20.Scott Bryant plays for the team Cincinnati Reds, at position OF. Scott Bryant belongs to the school University of Texas. The player named Greg Gohr, plays as Pick-21.Greg Gohr plays for the team Detroit Tigers, at position RHP. Greg Gohr belongs to the school Santa Clara University. The player named Tom Goodwin, plays as Pick-22.Tom Goodwin plays for the team Los Angeles Dodgers, at position OF. Tom Goodwin belongs to the school Fresno State University. The player named Mo Vaughn, plays as Pick-23.Mo Vaughn plays for the team Boston Red Sox, at position 1B. Mo Vaughn belongs to the school Seton Hall University. The player named Alan Zinter, plays as Pick-24.Alan Zinter plays for the team New York Mets, at position C. Alan Zinter belongs to the school University of Arizona. The player named Chuck Knoblauch, plays as Pick-25.Chuck Knoblauch plays for the team Minnesota Twins, at position 2B. Chuck Knoblauch belongs to the school Texas A&M University. The player named Scott Burrell, plays as Pick-26.Scott Burrell plays for the team Seattle Mariners, at position RHP. Scott Burrell belongs to the school Hamden (CT) HS.
Example explanation: The output correctly captures the data in table and generates a long text passage which covers all the given information.
Problem: Table: ['Year', 'Title', 'Peak chart positions US Air', 'Peak chart positions US Main', 'Peak chart positions US Mod', 'Album']. ['1990', 'Dig a Hole', '--', '--', '--', 'Non-album single']. ['1993', 'Mister Love', '--', '--', '--', 'Velvet']. ['1994', 'Mister Love', '--', '--', '--', 'Rubberneck']. ['1995', 'Possum Kingdom', '40', '9', '4', 'Rubberneck']. ['1995', 'Away', '--', '23', '28', 'Rubberneck']. ['1996', 'Tyler', '--', '--', '--', 'Rubberneck']. ['1996', 'Backslider', '--', '--', '--', 'Rubberneck']. ['2001', 'Push the Hand', '--', '34', '--', 'Hell Below/Stars Above']. ['2008', 'No Deliverance', '--', '38', '--', 'No Deliverance']. ['2009', 'Song I Hate', '--', '--', '--', 'No Deliverance']. ['2012', 'Summer of the Strange', '--', '--', '--', 'Play.Rock.Music']
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Solution: Passage: The title track 'Dig a Hole' from the album 'Non-album single', was released in the year 1990. Dig a Hole's chart positions in US Air, US Main, and US mod were --, --, and -- respectively. The title track 'Mister Love' from the album 'Velvet', was released in the year 1993. Mister Love's chart positions in US Air, US Main, and US mod were --, --, and -- respectively. The title track 'Mister Love' from the album 'Rubberneck', was released in the year 1994. Mister Love's chart positions in US Air, US Main, and US mod were --, --, and -- respectively. The title track 'Possum Kingdom' from the album 'Rubberneck', was released in the year 1995. Possum Kingdom's chart positions in US Air, US Main, and US mod were 40, 9, and 4 respectively. The title track 'Away' from the album 'Rubberneck', was released in the year 1995. Away's chart positions in US Air, US Main, and US mod were --, 23, and 28 respectively. The title track 'Tyler' from the album 'Rubberneck', was released in the year 1996. Tyler's chart positions in US Air, US Main, and US mod were --, --, and -- respectively. The title track 'Backslider' from the album 'Rubberneck', was released in the year 1996. Backslider's chart positions in US Air, US Main, and US mod were --, --, and -- respectively. The title track 'Push the Hand' from the album 'Hell Below/Stars Above', was released in the year 2001. Push the Hand's chart positions in US Air, US Main, and US mod were --, 34, and -- respectively. The title track 'No Deliverance' from the album 'No Deliverance', was released in the year 2008. No Deliverance's chart positions in US Air, US Main, and US mod were --, 38, and -- respectively. The title track 'Song I Hate' from the album 'No Deliverance', was released in the year 2009. Song I Hate's chart positions in US Air, US Main, and US mod were --, --, and -- respectively. The title track 'Summer of the Strange' from the album 'Play.Rock.Music', was released in the year 2012. Summer of the Strange's chart positions in US Air, US Main, and US mod were --, --, and -- respectively.
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task760_msr_sqa_long_text_generation
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NIv2
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fs_opt
| 5
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train
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You are given data in tabular format and you need to generate a passage with content in plain text format based on the information present in the table.
Q: Table: ['Club', 'Played', 'Won', 'Drawn', 'Lost', 'Points for', 'Points against', 'Bonus points', 'Points']. ['Biarritz Olympique', '26', '19', '', '7', '694', '350', '14', '90']. ['Stade Francais', '26', '19', '', '7', '633', '437', '13', '89']. ['Stade Toulousain', '26', '19', '', '7', '713', '427', '12', '88']. ['USA Perpignan', '26', '18', '', '8', '671', '398', '12', '84']. ['SU Agen', '26', '15', '', '11', '655', '540', '10', '70']. ['CS Bourgoin-Jallieu', '26', '14', '', '12', '591', '516', '11', '67']. ['Castres Olympique', '26', '13', '', '13', '685', '559', '14', '66']. ['ASM Clermont', '26', '14', '', '12', '577', '569', '7', '63']. ['CA Brive', '26', '10', '1', '15', '431', '553', '9', '51']. ['RC Narbonne', '26', '11', '', '15', '533', '775', '3', '47']. ['Montpellier RC', '26', '9', '0', '17', '574', '659', '10', '46']. ['Aviron Bayonnais', '26', '8', '1', '17', '514', '669', '9', '43']. ['Section Paloise', '26', '9', '0', '17', '476', '790', '4', '40']. ['RC Toulonnais', '26', '3', '0', '23', '332', '837', '7', '19']
A:
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Passage: The club named Biarritz Olympique, played 26 matches. Out of it, 19 matches resulted in win, resulted in draw, and 7 matches were lost. The total points the 26 club scored is 694. Total points scored against the 26 team is 350. The team scored 14 bonus points. Total points scored by the 26 club this season this 90. The club named Stade Francais, played 26 matches. Out of it, 19 matches resulted in win, resulted in draw, and 7 matches were lost. The total points the 26 club scored is 633. Total points scored against the 26 team is 437. The team scored 13 bonus points. Total points scored by the 26 club this season this 89. The club named Stade Toulousain, played 26 matches. Out of it, 19 matches resulted in win, resulted in draw, and 7 matches were lost. The total points the 26 club scored is 713. Total points scored against the 26 team is 427. The team scored 12 bonus points. Total points scored by the 26 club this season this 88. The club named USA Perpignan, played 26 matches. Out of it, 18 matches resulted in win, resulted in draw, and 8 matches were lost. The total points the 26 club scored is 671. Total points scored against the 26 team is 398. The team scored 12 bonus points. Total points scored by the 26 club this season this 84. The club named SU Agen, played 26 matches. Out of it, 15 matches resulted in win, resulted in draw, and 11 matches were lost. The total points the 26 club scored is 655. Total points scored against the 26 team is 540. The team scored 10 bonus points. Total points scored by the 26 club this season this 70. The club named CS Bourgoin-Jallieu, played 26 matches. Out of it, 14 matches resulted in win, resulted in draw, and 12 matches were lost. The total points the 26 club scored is 591. Total points scored against the 26 team is 516. The team scored 11 bonus points. Total points scored by the 26 club this season this 67. The club named Castres Olympique, played 26 matches. Out of it, 13 matches resulted in win, resulted in draw, and 13 matches were lost. The total points the 26 club scored is 685. Total points scored against the 26 team is 559. The team scored 14 bonus points. Total points scored by the 26 club this season this 66. The club named ASM Clermont, played 26 matches. Out of it, 14 matches resulted in win, resulted in draw, and 12 matches were lost. The total points the 26 club scored is 577. Total points scored against the 26 team is 569. The team scored 7 bonus points. Total points scored by the 26 club this season this 63. The club named CA Brive, played 26 matches. Out of it, 10 matches resulted in win, 1 resulted in draw, and 15 matches were lost. The total points the 26 club scored is 431. Total points scored against the 26 team is 553. The team scored 9 bonus points. Total points scored by the 26 club this season this 51. The club named RC Narbonne, played 26 matches. Out of it, 11 matches resulted in win, resulted in draw, and 15 matches were lost. The total points the 26 club scored is 533. Total points scored against the 26 team is 775. The team scored 3 bonus points. Total points scored by the 26 club this season this 47. The club named Montpellier RC, played 26 matches. Out of it, 9 matches resulted in win, 0 resulted in draw, and 17 matches were lost. The total points the 26 club scored is 574. Total points scored against the 26 team is 659. The team scored 10 bonus points. Total points scored by the 26 club this season this 46. The club named Aviron Bayonnais, played 26 matches. Out of it, 8 matches resulted in win, 1 resulted in draw, and 17 matches were lost. The total points the 26 club scored is 514. Total points scored against the 26 team is 669. The team scored 9 bonus points. Total points scored by the 26 club this season this 43. The club named Section Paloise, played 26 matches. Out of it, 9 matches resulted in win, 0 resulted in draw, and 17 matches were lost. The total points the 26 club scored is 476. Total points scored against the 26 team is 790. The team scored 4 bonus points. Total points scored by the 26 club this season this 40. The club named RC Toulonnais, played 26 matches. Out of it, 3 matches resulted in win, 0 resulted in draw, and 23 matches were lost. The total points the 26 club scored is 332. Total points scored against the 26 team is 837. The team scored 7 bonus points. Total points scored by the 26 club this season this 19.
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task760_msr_sqa_long_text_generation
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NIv2
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zs_opt
| 4
|
test
|
You are given data in tabular format and you need to generate a passage with content in plain text format based on the information present in the table.
Input: Consider Input: Table: ['Date', 'City', 'Venue', 'Member', 'Performance', 'Notes']. ['15 January', 'Dublin', 'RTE Studios', 'Brian & Roger', '(1) We Will Rock You', '']. ['(2) We Are the Champions', 'The Late Late Show', '', '', '', '']. ['31 January', 'Dublin', 'The O2', 'Brian', '(1) Bohemian Rhapsody', 'Matinee and Evening performances. Roger attended but did not perform.']. ['10 May', 'London', 'Dominion Theatre', 'Brian & Roger', '(1) Bohemian Rhapsody', '8th anniversary.']. ['3 September', 'Utrecht', 'Beatrix Theatre', 'Brian', '(1) Bohemian Rhapsody', '']. ['4 September', 'London', 'Dominion Theatre', 'Brian', '(1) Bohemian Rhapsody', 'Matinee and Evening performances']. ['12 September', 'Stockholm', 'Cirkus Arena Restaurang', 'Brian', '(1) Bohemian Rhapsody', '']. ['21 October', 'Berlin', 'Theater des Westens', 'Brian', '(1) Bohemian Rhapsody', '']
Output: Passage: The artist Brian & Roger gave a live performance at RTE Studios in the city of Dublin on 15 January. The artist Brian & Roger performed (1) We Will Rock You. Additional details: . The artist gave a live performance at in the city of The Late Late Show on (2) We Are the Champions. The artist performed . Additional details: . The artist Brian gave a live performance at The O2 in the city of Dublin on 31 January. The artist Brian performed (1) Bohemian Rhapsody. Additional details: Matinee and Evening performances. Roger attended but did not perform.. The artist Brian & Roger gave a live performance at Dominion Theatre in the city of London on 10 May. The artist Brian & Roger performed (1) Bohemian Rhapsody. Additional details: 8th anniversary.. The artist Brian gave a live performance at Beatrix Theatre in the city of Utrecht on 3 September. The artist Brian performed (1) Bohemian Rhapsody. Additional details: . The artist Brian gave a live performance at Dominion Theatre in the city of London on 4 September. The artist Brian performed (1) Bohemian Rhapsody. Additional details: Matinee and Evening performances. The artist Brian gave a live performance at Cirkus Arena Restaurang in the city of Stockholm on 12 September. The artist Brian performed (1) Bohemian Rhapsody. Additional details: . The artist Brian gave a live performance at Theater des Westens in the city of Berlin on 21 October. The artist Brian performed (1) Bohemian Rhapsody. Additional details: .
Input: Consider Input: Table: ['Pos', 'No', 'Driver', 'Constructor', 'Laps', 'Time/Retired', 'Grid', 'Points']. ['1', '5', 'Fernando Alonso', 'Renault', '56', '1:31:33.736', '1', '10']. ['2', '16', 'Jarno Trulli', 'Toyota', '56', '+24.327', '2', '8']. ['3', '8', 'Nick Heidfeld', 'Williams-BMW', '56', '+32.188', '10', '6']. ['4', '10', 'Juan Pablo Montoya', 'McLaren-Mercedes', '56', '+41.631', '11', '5']. ['5', '17', 'Ralf Schumacher', 'Toyota', '56', '+51.854', '5', '4']. ['6', '14', 'David Coulthard', 'Red Bull-Cosworth', '56', '+1:12.543', '8', '3']. ['7', '1', 'Michael Schumacher', 'Ferrari', '56', '+1:19.988', '13', '2']. ['8', '15', 'Christian Klien', 'Red Bull-Cosworth', '56', '+1:20.835', '7', '1']. ['9', '9', 'Kimi Raikkonen', 'McLaren-Mercedes', '56', '+1:21.580', '6', '']. ['10', '12', 'Felipe Massa', 'Sauber-Petronas', '55', '+1 Lap', '14', '']. ['11', '19', 'Narain Karthikeyan', 'Jordan-Toyota', '54', '+2 Laps', '17', '']. ['12', '18', 'Tiago Monteiro', 'Jordan-Toyota', '53', '+3 Laps', '18', '']. ['13', '21', 'Christijan Albers', 'Minardi-Cosworth', '52', '+4 Laps', '19', '']. ['Ret', '2', 'Rubens Barrichello', 'Ferrari', '49', 'Handling', '12', '']. ['Ret', '6', 'Giancarlo Fisichella', 'Renault', '36', 'Collision', '3', '']. ['Ret', '7', 'Mark Webber', 'Williams-BMW', '36', 'Collision', '4', '']. ['Ret', '11', 'Jacques Villeneuve', 'Sauber-Petronas', '26', 'Spun Off', '16', '']. ['Ret', '3', 'Jenson Button', 'BAR-Honda', '2', 'Engine', '9', '']. ['Ret', '4', 'Anthony Davidson', 'BAR-Honda', '2', 'Engine', '15', '']. ['Ret', '20', 'Patrick Friesacher', 'Minardi-Cosworth', '2', 'Spun Off', '20', '']
Output: Passage: The driver with number 5, Fernando Alonso, from Renault constructor, finished at position 1. Fernando Alonso completed 56 laps in 1:31:33.736 time and earned 10 points. The driver with number 16, Jarno Trulli, from Toyota constructor, finished at position 2. Jarno Trulli completed 56 laps in +24.327 time and earned 8 points. The driver with number 8, Nick Heidfeld, from Williams-BMW constructor, finished at position 3. Nick Heidfeld completed 56 laps in +32.188 time and earned 6 points. The driver with number 10, Juan Pablo Montoya, from McLaren-Mercedes constructor, finished at position 4. Juan Pablo Montoya completed 56 laps in +41.631 time and earned 5 points. The driver with number 17, Ralf Schumacher, from Toyota constructor, finished at position 5. Ralf Schumacher completed 56 laps in +51.854 time and earned 4 points. The driver with number 14, David Coulthard, from Red Bull-Cosworth constructor, finished at position 6. David Coulthard completed 56 laps in +1:12.543 time and earned 3 points. The driver with number 1, Michael Schumacher, from Ferrari constructor, finished at position 7. Michael Schumacher completed 56 laps in +1:19.988 time and earned 2 points. The driver with number 15, Christian Klien, from Red Bull-Cosworth constructor, finished at position 8. Christian Klien completed 56 laps in +1:20.835 time and earned 1 points. The driver with number 9, Kimi Raikkonen, from McLaren-Mercedes constructor, finished at position 9. Kimi Raikkonen completed 56 laps in +1:21.580 time and earned points. The driver with number 12, Felipe Massa, from Sauber-Petronas constructor, finished at position 10. Felipe Massa completed 55 laps in +1 Lap time and earned points. The driver with number 19, Narain Karthikeyan, from Jordan-Toyota constructor, finished at position 11. Narain Karthikeyan completed 54 laps in +2 Laps time and earned points. The driver with number 18, Tiago Monteiro, from Jordan-Toyota constructor, finished at position 12. Tiago Monteiro completed 53 laps in +3 Laps time and earned points. The driver with number 21, Christijan Albers, from Minardi-Cosworth constructor, finished at position 13. Christijan Albers completed 52 laps in +4 Laps time and earned points. The driver with number 2, Rubens Barrichello, from Ferrari constructor, finished at position Ret. Rubens Barrichello completed 49 laps in Handling time and earned points. The driver with number 6, Giancarlo Fisichella, from Renault constructor, finished at position Ret. Giancarlo Fisichella completed 36 laps in Collision time and earned points. The driver with number 7, Mark Webber, from Williams-BMW constructor, finished at position Ret. Mark Webber completed 36 laps in Collision time and earned points. The driver with number 11, Jacques Villeneuve, from Sauber-Petronas constructor, finished at position Ret. Jacques Villeneuve completed 26 laps in Spun Off time and earned points. The driver with number 3, Jenson Button, from BAR-Honda constructor, finished at position Ret. Jenson Button completed 2 laps in Engine time and earned points. The driver with number 4, Anthony Davidson, from BAR-Honda constructor, finished at position Ret. Anthony Davidson completed 2 laps in Engine time and earned points. The driver with number 20, Patrick Friesacher, from Minardi-Cosworth constructor, finished at position Ret. Patrick Friesacher completed 2 laps in Spun Off time and earned points.
Input: Consider Input: Table: ['Rank', 'Name', 'Nationality', 'Time (hand)', 'Notes']. ['', 'Tommy Green', 'Great Britain', '4:50:10', 'OR']. ['', 'Janis Dalins', 'Latvia', '4:57:20', '']. ['', 'Ugo Frigerio', 'Italy', '4:59:06', '']. ['4', 'Karl Hahnel', 'Germany', '5:06:06', '']. ['5', 'Ettore Rivolta', 'Italy', '5:07:39', '']. ['6', 'Paul Sievert', 'Germany', '5:16:41', '']. ['7', 'Henri Quintric', 'France', '5:27:25', '']. ['8', 'Ernie Crosbie', 'United States', '5:28:02', '']. ['9', 'Bill Chisholm', 'United States', '5:51:00', '']. ['10', 'Alfred Maasik', 'Estonia', '6:19:00', '']. ['', 'Henry Cieman', 'Canada', '', 'DNF']. ['', 'John Moralis', 'Greece', '', 'DNF']. ['', 'Francesco Pretti', 'Italy', '', 'DNF']. ['', 'Arthur Tell Schwab', 'Switzerland', '', 'DNF']. ['', 'Harry Hinkel', 'United States', '', 'DNF']
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Output: Passage: The Great Britain athlete named Tommy Green is ranked globally. Tommy Green completed the marathon in 4:50:10 seconds. The Latvia athlete named Janis Dalins is ranked globally. Janis Dalins completed the marathon in 4:57:20 seconds. The Italy athlete named Ugo Frigerio is ranked globally. Ugo Frigerio completed the marathon in 4:59:06 seconds. The Germany athlete named Karl Hahnel is ranked 4 globally. Karl Hahnel completed the marathon in 5:06:06 seconds. The Italy athlete named Ettore Rivolta is ranked 5 globally. Ettore Rivolta completed the marathon in 5:07:39 seconds. The Germany athlete named Paul Sievert is ranked 6 globally. Paul Sievert completed the marathon in 5:16:41 seconds. The France athlete named Henri Quintric is ranked 7 globally. Henri Quintric completed the marathon in 5:27:25 seconds. The United States athlete named Ernie Crosbie is ranked 8 globally. Ernie Crosbie completed the marathon in 5:28:02 seconds. The United States athlete named Bill Chisholm is ranked 9 globally. Bill Chisholm completed the marathon in 5:51:00 seconds. The Estonia athlete named Alfred Maasik is ranked 10 globally. Alfred Maasik completed the marathon in 6:19:00 seconds. The Canada athlete named Henry Cieman is ranked globally. Henry Cieman completed the marathon in seconds. The Greece athlete named John Moralis is ranked globally. John Moralis completed the marathon in seconds. The Italy athlete named Francesco Pretti is ranked globally. Francesco Pretti completed the marathon in seconds. The Switzerland athlete named Arthur Tell Schwab is ranked globally. Arthur Tell Schwab completed the marathon in seconds. The United States athlete named Harry Hinkel is ranked globally. Harry Hinkel completed the marathon in seconds.
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task760_msr_sqa_long_text_generation
|
NIv2
|
fs_opt
| 2
|
validation
|
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