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

應用自動資訊擷取於故事書問答生成之研究

資訊工程學系

研究成果: 書貢獻/報告類型 › 會議論文篇章 › 同行評審

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 2022 → 22 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	21/11/22 → 22/11/22

Keywords

Information Extraction
Question Answering
Question-Answer Pairs Generation

引用此

Kao, K. Y., & Chang, C. H. (2022). 應用自動資訊擷取於故事書問答生成之研究. 於 Y-C. Chang, Y-C. Huang, J-L. Wu, M-H. Su, H-H. Huang, Y-F. Liu, L-H. Lee, C-H. Chou, & Y-F. Liao (編輯), ROCLING 2022 - Proceedings of the 34th Conference on Computational Linguistics and Speech Processing (頁 289-298). (ROCLING 2022 - Proceedings of the 34th Conference on Computational Linguistics and Speech Processing). The Association for Computational Linguistics and Chinese Language Processing (ACLCLP).

Kao, Kai Yen ; Chang, Chia Hui. / 應用自動資訊擷取於故事書問答生成之研究. 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. The Association for Computational Linguistics and Chinese Language Processing (ACLCLP), 2022. 頁 289-298 (ROCLING 2022 - Proceedings of the 34th Conference on Computational Linguistics and Speech Processing).

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title = "應用自動資訊擷取於故事書問答生成之研究",

abstract = "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.",

keywords = "Information Extraction, Question Answering, Question-Answer Pairs Generation",

author = "Kao, {Kai Yen} and Chang, {Chia Hui}",

note = "Publisher Copyright: {\textcopyright} 2022 the Association for Computational Linguistics and Chinese Language Processing (ACLCLP).; 34th Conference on Computational Linguistics and Speech Processing, ROCLING 2022 ; Conference date: 21-11-2022 Through 22-11-2022",

year = "2022",

language = "繁體中文",

series = "ROCLING 2022 - Proceedings of the 34th Conference on Computational Linguistics and Speech Processing",

publisher = "The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)",

pages = "289--298",

editor = "Yung-Chun Chang and Yi-Chin Huang and Jheng-Long Wu and Ming-Hsiang Su and Hen-Hsen Huang and Yi-Fen Liu and Lung-Hao Lee and Chin-Hung Chou and Yuan-Fu Liao",

booktitle = "ROCLING 2022 - Proceedings of the 34th Conference on Computational Linguistics and Speech Processing",

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Kao, KY & Chang, CH 2022, 應用自動資訊擷取於故事書問答生成之研究. 於 Y-C Chang, Y-C Huang, J-L Wu, M-H Su, H-H Huang, Y-F Liu, L-H Lee, C-H Chou & Y-F Liao (編輯), ROCLING 2022 - Proceedings of the 34th Conference on Computational Linguistics and Speech Processing. ROCLING 2022 - Proceedings of the 34th Conference on Computational Linguistics and Speech Processing, The Association for Computational Linguistics and Chinese Language Processing (ACLCLP), 頁 289-298, 34th Conference on Computational Linguistics and Speech Processing, ROCLING 2022, Taipei, Taiwan, 21/11/22.

應用自動資訊擷取於故事書問答生成之研究. / Kao, Kai Yen; Chang, Chia Hui.
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. The Association for Computational Linguistics and Chinese Language Processing (ACLCLP), 2022. p. 289-298 (ROCLING 2022 - Proceedings of the 34th Conference on Computational Linguistics and Speech Processing).

研究成果: 書貢獻/報告類型 › 會議論文篇章 › 同行評審

TY - GEN

T1 - 應用自動資訊擷取於故事書問答生成之研究

AU - Kao, Kai Yen

AU - Chang, Chia Hui

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - Information Extraction

KW - Question Answering

KW - Question-Answer Pairs Generation

UR - http://www.scopus.com/inward/record.url?scp=85154556928&partnerID=8YFLogxK

M3 - 會議論文篇章

AN - SCOPUS:85154556928

T3 - ROCLING 2022 - Proceedings of the 34th Conference on Computational Linguistics and Speech Processing

SP - 289

EP - 298

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

A2 - Chang, Yung-Chun

A2 - Huang, Yi-Chin

A2 - Wu, Jheng-Long

A2 - Su, Ming-Hsiang

A2 - Huang, Hen-Hsen

A2 - Liu, Yi-Fen

A2 - Lee, Lung-Hao

A2 - Chou, Chin-Hung

A2 - Liao, Yuan-Fu

PB - The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)

T2 - 34th Conference on Computational Linguistics and Speech Processing, ROCLING 2022

Y2 - 21 November 2022 through 22 November 2022

ER -

Kao KY, Chang CH. 應用自動資訊擷取於故事書問答生成之研究. 於 Chang Y-C, Huang Y-C, Wu J-L, Su M-H, Huang H-H, Liu Y-F, Lee L-H, Chou C-H, Liao Y-F, 編輯, ROCLING 2022 - Proceedings of the 34th Conference on Computational Linguistics and Speech Processing. The Association for Computational Linguistics and Chinese Language Processing (ACLCLP). 2022. p. 289-298. (ROCLING 2022 - Proceedings of the 34th Conference on Computational Linguistics and Speech Processing).

應用自動資訊擷取於故事書問答生成之研究

摘要

出版系列

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Keywords

指紋

引用此