A Knowledge Enhanced Chinese GaoKao Reading Comprehension Method

Xiao Zhang, Heqi Zheng*, Heyan Huang, Zewen Chi, Xian Ling Mao

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Chinese GaoKao Reading Comprehension is a chal-lenging NLP task. It requires strong logical reasoning ability to capture deep semantic relations between the questions and answers. However, most traditional models cannot learn sufficient inference ability, because of the scarcity of Chinese GaoKao reading comprehension data. Intuitively, there are two methods to improve the reading comprehension ability for Chinese GaoKao reading comprehension task. 1). Increase the scale of data. 2). Introduce additional related knowledge. In this paper, we propose a novel method based on adversarial training and knowledge distillation, which can be trained in other knowledge-rich datasets and transferred to the Chinese GaoKao reading comprehension task. Extensive experiments show that our proposed model performs better than the state-of-the-art baselines. The code and the relevant dataset will be publicly avaible.

源语言英语
主期刊名Proceedings - 12th IEEE International Conference on Big Knowledge, ICBK 2021
编辑Zhiguo Gong, Xue Li, Sule Gunduz Oguducu, Lei Chen, Baltasar Fernandez Manjon, Xindong Wu
出版商Institute of Electrical and Electronics Engineers Inc.
347-352
页数6
ISBN(电子版)9781665438582
DOI
出版状态已出版 - 2021
活动12th IEEE International Conference on Big Knowledge, ICBK 2021 - Virtual, Auckland, 新西兰
期限: 7 12月 20218 12月 2021

出版系列

姓名Proceedings - 12th IEEE International Conference on Big Knowledge, ICBK 2021

会议

会议12th IEEE International Conference on Big Knowledge, ICBK 2021
国家/地区新西兰
Virtual, Auckland
时期7/12/218/12/21

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