應用自動資訊擷取於故事書問答生成之研究

Kai Yen Kao, Chia Hui Chang

研究成果: 書貢獻/報告類型會議論文篇章同行評審

1 引文 斯高帕斯(Scopus)

摘要

For educators, how to generate high quality question-answer pairs from story text is a time-consuming and labor-intensive task. The purpose is not to make students unable to answer, but to ensure that students understand the story text through the generated question-answer pairs. In this paper, we improve the FairyTaleQA question generation method by incorporating question type and its definition to the input for fine-tuning the BART (Lewis et al., 2020) model. Furthermore, we make use of the entity and relation extraction from (Zhong and Chen, 2021) as an element of template-based question generation.

貢獻的翻譯標題Applying Information Extraction to Storybook Question and Answer Generation
原文繁體中文
主出版物標題ROCLING 2022 - Proceedings of the 34th Conference on Computational Linguistics and Speech Processing
編輯Yung-Chun Chang, Yi-Chin Huang, Jheng-Long Wu, Ming-Hsiang Su, Hen-Hsen Huang, Yi-Fen Liu, Lung-Hao Lee, Chin-Hung Chou, Yuan-Fu Liao
發行者The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
頁面289-298
頁數10
ISBN(電子)9789869576956
出版狀態已出版 - 2022
事件34th Conference on Computational Linguistics and Speech Processing, ROCLING 2022 - Taipei, Taiwan
持續時間: 21 11月 202222 11月 2022

出版系列

名字ROCLING 2022 - Proceedings of the 34th Conference on Computational Linguistics and Speech Processing

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???event.eventtypes.event.conference???34th Conference on Computational Linguistics and Speech Processing, ROCLING 2022
國家/地區Taiwan
城市Taipei
期間21/11/2222/11/22

Keywords

  • Information Extraction
  • Question Answering
  • Question-Answer Pairs Generation

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