python-NLP常用数据集0.1.022
MRPC数据集
Microsoft Research Paraphrase Corpus 3600个数据
python
Quality #1 ID #2 ID #1 String #2 String
1 1089874 1089925 PCCW 's chief operating officer , Mike Butcher , and Alex Arena , the chief financial officer , will report directly to Mr So . Current Chief Operating Officer Mike Butcher and Group Chief Financial Officer Alex Arena will report to So .
1 3019446 3019327 The world 's two largest automakers said their U.S. sales declined more than predicted last month as a late summer sales frenzy caused more of an industry backlash than expected . Domestic sales at both GM and No. 2 Ford Motor Co. declined more than predicted as a late summer sales frenzy prompted a larger-than-expected industry backlash .
1 1945605 1945824 According to the federal Centers for Disease Control and Prevention ( news - web sites ) , there were 19 reported cases of measles in the United States in 2002 . The Centers for Disease Control and Prevention said there were 19 reported cases of measles in the United States in 2002 .
0 1430402 1430329 A tropical storm rapidly developed in the Gulf of Mexico Sunday and was expected to hit somewhere along the Texas or Louisiana coasts by Monday night . A tropical storm rapidly developed in the Gulf of Mexico on Sunday and could have hurricane-force winds when it hits land somewhere along the Louisiana coast Monday night .
0 3354381 3354396 The company didn 't detail the costs of the replacement and repairs . But company officials expect the costs of the replacement work to run into the millions of dollars .
1 1390995 1391183 The settling companies would also assign their possible claims against the underwriters to the investor plaintiffs , he added . Under the agreement , the settling companies will also assign their potential claims against the underwriters to the investors , he added .
0XNLI数据集
用户语言翻译和跨语言分类的语料库
- 官网地址：https://github.com/facebookresearch/XNLI
- 下载地址：https://dl.fbaipublicfiles.com/XNLI/XNLI-1.0.zip
- 注意事项：数据集有json格式的，和txt格式的
- 数据格式
txt格式
python
language gold_label sentence1_binary_parse sentence2_binary_parse sentence1_parse sentence2_parse sentence1 sentence2 promptID pairID genre label1 label2 label3 label4 label5 sentence1_tokenized sentence2_tokenized match
ar neutral وقال، ماما، لقد عدت للمنزل. اتصل بأمه حالما أوصلته حافلة المدرسية. 1 1 facetoface neutral contradiction neutral neutral neutral وقال ، ماما ، لقد عدت للمنزل . اتصل بأمه حالما أوصلته حافلة المدرسية . True
ar contradiction وقال، ماما، لقد عدت للمنزل. لم ينطق ببنت شفة. 1 2 facetoface contradiction contradiction contradiction contradiction contradiction وقال ، ماما ، لقد عدت للمنزل . لم ينطق ببنت شفة . True
ar entailment وقال، ماما، لقد عدت للمنزل. أخبر أمه أنه قد عاد للمنزل. 1 3 facetoface entailment entailment neutral entailment entailment وقال ، ماما ، لقد عدت للمنزل . أخبر أمه أنه قد عاد للمنزل . True
ar neutral json格式
python
{"annotator_labels": ["neutral", "contradiction", "neutral", "neutral", "neutral"], "genre": "facetoface", "gold_label": "neutral", "language": "ar", "match": "True", "pairID": "1", "promptID": "1", "sentence1": "\u0648\u0642\u0627\u0644\u060c \u0645\u0627\u0645\u0627\u060c \u0644\u0642\u062f \u0639\u062f\u062a \u0644\u0644\u0645\u0646\u0632\u0644.", "sentence1_tokenized": "\u0648\u0642\u0627\u0644 \u060c \u0645\u0627\u0645\u0627 \u060c \u0644\u0642\u062f \u0639\u062f\u062a \u0644\u0644\u0645\u0646\u0632\u0644 .", "sentence2": "\u0627\u062a\u0635\u0644 \u0628\u0623\u0645\u0647 \u062d\u0627\u0644\u0645\u0627 \u0623\u0648\u0635\u0644\u062a\u0647 \u062d\u0627\u0641\u0644\u0629 \u0627\u0644\u0645\u062f\u0631\u0633\u064a\u0629.", "sentence2_tokenized": "\u0627\u062a\u0635\u0644 \u0628\u0623\u0645\u0647 \u062d\u0627\u0644\u0645\u0627 \u0623\u0648\u0635\u0644\u062a\u0647 \u062d\u0627\u0641\u0644\u0629 \u0627\u0644\u0645\u062f\u0631\u0633\u064a\u0629 ."}
{"annotator_labels": ["contradiction", "contradiction", "contradiction", "contradiction", "contradiction"], "genre": "facetoface", "gold_label": "contradiction", "language": "ar", "match": "True", "pairID": "2", "promptID": "1", "sentence1": "\u0648\u0642\u0627\u0644\u060c \u0645\u0627\u0645\u0627\u060c \u0644\u0642\u062f \u0639\u062f\u062a \u0644\u0644\u0645\u0646\u0632\u0644.", "sentence1_tokenized": "\u0648\u0642\u0627\u0644 \u060c \u0645\u0627\u0645\u0627 \u060c \u0644\u0642\u062f \u0639\u062f\u062a \u0644\u0644\u0645\u0646\u0632\u0644 .", "sentence2": "\u0644\u0645 \u064a\u0646\u0637\u0642 \u0628\u0628\u0646\u062a \u0634\u0641\u0629.", "sentence2_tokenized": "\u0644\u0645 \u064a\u0646\u0637\u0642 \u0628\u0628\u0646\u062a \u0634\u0641\u0629 ."}SQuAD数据集
- 官网地址：https://rajpurkar.github.io/SQuAD-explorer/
- 下载地址：https://rajpurkar.github.io/SQuAD-explorer/
- 注意事项：测试集没有给出，需要在官网提交模型由平台对模型进行测试集的跑分
- 数据格式：点击https://rajpurkar.github.io/SQuAD-explorer/dataset/dev-v1.1.json
数据由多篇文章组成
一个title就表示一篇文章
文章里由paragraphs组成
paragraphs由多个context组成
每一个context有answers和question
部分数据：
python
{
"data": [{
"title": "Super_Bowl_50",
"paragraphs": [{
"context": "Super Bowl 50 was an American football game to determine the champion of the National Football League (NFL) for the 2015 season. The American Football Conference (AFC) champion Denver Broncos defeated the National Football Conference (NFC) champion Carolina Panthers 24\u201310 to earn their third Super Bowl title. The game was played on February 7, 2016, at Levi's Stadium in the San Francisco Bay Area at Santa Clara, California. As this was the 50th Super Bowl, the league emphasized the \"golden anniversary\" with various gold-themed initiatives, as well as temporarily suspending the tradition of naming each Super Bowl game with Roman numerals (under which the game would have been known as \"Super Bowl L\"), so that the logo could prominently feature the Arabic numerals 50.",
"qas": [{
"answers": [{
"answer_start": 177,
"text": "Denver Broncos"
}, {
"answer_start": 177,
"text": "Denver Broncos"
}, {
"answer_start": 177,
"text": "Denver Broncos"
}],
"question": "Which NFL team represented the AFC at Super Bowl 50?",
"id": "56be4db0acb8001400a502ec"
}, {
"answers": [{
"answer_start": 249,
"text": "Carolina Panthers"
}, {
"answer_start": 249,
"text": "Carolina Panthers"
}, {
"answer_start": 249,
"text": "Carolina Panthers"
}],
"question": "Which NFL team represented the NFC at Super Bowl 50?",
"id": "56be4db0acb8001400a502ed"
}, {
"answers": [{
"answer_start": 403,
"text": "Santa Clara, California"
}, {
"answer_start": 355,
"text": "Levi's Stadium"
}, {
"answer_start": 355,
"text": "Levi's Stadium in the San Francisco Bay Area at Santa Clara, California."
}],
"question": "Where did Super Bowl 50 take place?",
"id": "56be4db0acb8001400a502ee"
}, {
"answers": [{
"answer_start": 177,
"text": "Denver Broncos"
}, {
"answer_start": 177,
"text": "Denver Broncos"
}, {
"answer_start": 177,
"text": "Denver Broncos"
}],
"question": "Which NFL team won Super Bowl 50?",
"id": "56be4db0acb8001400a502ef"
}, {
"answers": [{
"answer_start": 488,
"text": "gold"
}, {
"answer_start": 488,
"text": "gold"
}, {
"answer_start": 521,
"text": "gold"
}],
"question": "What color was used to emphasize the 50th anniversary of the Super Bowl?",
"id": "56be4db0acb8001400a502f0"
}