Datasets:
lmqg
/

Languages:
Japanese
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Source Datasets:
SkelterLabsInc/JaQuAD
ArXiv:
Tags:
question-generation
License:
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  ## Dataset Description
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  - **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
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- - **Paper:** [TBA](TBA)
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  - **Point of Contact:** [Asahi Ushio](http://asahiushio.com/)
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  ### Dataset Summary
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  This is a subset of [QG-Bench](https://github.com/asahi417/lm-question-generation/blob/master/QG_BENCH.md#datasets), a unified question generation benchmark proposed in
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- ["Generative Language Models for Paragraph-Level Question Generation: A Unified Benchmark and Evaluation, EMNLP 2022 main conference"](paper_link).
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  This is [JaQuAD](https://github.com/SkelterLabsInc/JaQuAD) dataset compiled for question generation (QG) task. The test set of the original
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  data is not publicly released, so we randomly sampled test questions from the training set. There are no overlap in terms of the paragraph across train, test, and validation split.
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  ## Dataset Description
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  - **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
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+ - **Paper:** [https://arxiv.org/abs/2210.03992](https://arxiv.org/abs/2210.03992)
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  - **Point of Contact:** [Asahi Ushio](http://asahiushio.com/)
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  ### Dataset Summary
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  This is a subset of [QG-Bench](https://github.com/asahi417/lm-question-generation/blob/master/QG_BENCH.md#datasets), a unified question generation benchmark proposed in
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+ ["Generative Language Models for Paragraph-Level Question Generation: A Unified Benchmark and Evaluation, EMNLP 2022 main conference"](https://arxiv.org/abs/2210.03992).
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  This is [JaQuAD](https://github.com/SkelterLabsInc/JaQuAD) dataset compiled for question generation (QG) task. The test set of the original
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  data is not publicly released, so we randomly sampled test questions from the training set. There are no overlap in terms of the paragraph across train, test, and validation split.
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