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Datasets:
lmqg
/
qg_squad

Tasks:
Text Generation
Modalities:
Text
Sub-tasks:
language-modeling
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
question-generation
Libraries:
Datasets
License:
Dataset card Viewer Files Community
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init

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  1. README.md +2 -4
README.md CHANGED
@@ -65,9 +65,7 @@ An example of 'train' looks as follows.
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  ```
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  {
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  "question": "What is heresy mainly at odds with?",
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- "passage": "Heresy is any provocative belief or theory that is strongly at variance with established beliefs or customs."
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- "A heretic is a proponent of such claims or beliefs. Heresy is distinct from both apostasy, which is the explicit"
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- "renunciation of one's religion, principles or cause, and blasphemy, which is an impious utterance or action concerning God or sacred things.",
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  "answer": "established beliefs or customs",
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  "sentence": "Heresy is any provocative belief or theory that is strongly at variance with established beliefs or customs .",
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  "passage_sentence": "<hl> Heresy is any provocative belief or theory that is strongly at variance with established beliefs or customs . <hl> A heretic is a proponent of such claims or beliefs. Heresy is distinct from both apostasy, which is the explicit renunciation of one's religion, principles or cause, and blasphemy, which is an impious utterance or action concerning God or sacred things.",
@@ -86,7 +84,7 @@ The data fields are the same among all splits.
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  - `passage_sentence`: a `string` feature, which is same as the passage but a sentence containing the answer is highlighted by a special token `<hl>`.
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  - `sentence_answer`: a `string` feature, which is same as the sentence but the answer is highlighted by a special token `<hl>`.
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- Each of `passage_answer`/`passage_sentence`/`sentence_answer` feature is assumed to be used to train a question generation model,
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  but with different information. The `passage_answer` and `sentence_answer` features are for answer-aware question generation and
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  `passage_sentence` feature is for sentence-aware question generation.
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  ```
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  {
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  "question": "What is heresy mainly at odds with?",
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+ "passage": "Heresy is any provocative belief or theory that is strongly at variance with established beliefs or customs. A heretic is a proponent of such claims or beliefs. Heresy is distinct from both apostasy, which is the explicit renunciation of one's religion, principles or cause, and blasphemy, which is an impious utterance or action concerning God or sacred things.",
 
 
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  "answer": "established beliefs or customs",
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  "sentence": "Heresy is any provocative belief or theory that is strongly at variance with established beliefs or customs .",
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  "passage_sentence": "<hl> Heresy is any provocative belief or theory that is strongly at variance with established beliefs or customs . <hl> A heretic is a proponent of such claims or beliefs. Heresy is distinct from both apostasy, which is the explicit renunciation of one's religion, principles or cause, and blasphemy, which is an impious utterance or action concerning God or sacred things.",
 
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  - `passage_sentence`: a `string` feature, which is same as the passage but a sentence containing the answer is highlighted by a special token `<hl>`.
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  - `sentence_answer`: a `string` feature, which is same as the sentence but the answer is highlighted by a special token `<hl>`.
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+ Each of `passage_answer`, `passage_sentence`, and `sentence_answer` feature is assumed to be used to train a question generation model,
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  but with different information. The `passage_answer` and `sentence_answer` features are for answer-aware question generation and
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  `passage_sentence` feature is for sentence-aware question generation.
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