TemplateGEC: Improving Grammatical Error Correction with Detection Template

Yinghao Li, Xuebo Liu, Shuo Wang, Peiyuan Gong, Derek F. Wong, Yang Gao, Heyan Huang, Min Zhang

科研成果: 书/报告/会议事项章节会议稿件同行评审

20 引用 (Scopus)

摘要

Grammatical error correction (GEC) can be divided into sequence-to-edit (Seq2Edit) and sequence-to-sequence (Seq2Seq) frameworks, both of which have their pros and cons. To utilize the strengths and make up for the shortcomings of these frameworks, this paper proposes a novel method, TemplateGEC, which capitalizes on the capabilities of both Seq2Edit and Seq2Seq frameworks in error detection and correction respectively. TemplateGEC utilizes the detection labels from a Seq2Edit model, to construct the template as the input. A Seq2Seq model is employed to enforce consistency between the predictions of different templates by utilizing consistency learning. Experimental results on the Chinese NLPCC18, English BEA19 and CoNLL14 benchmarks show the effectiveness and robustness of TemplateGEC. Further analysis reveals the potential of our method in performing human-in-the-loop GEC. Source code and scripts are available at https://github.com/li-aolong/TemplateGEC.

源语言英语
主期刊名Long Papers
出版商Association for Computational Linguistics (ACL)
6878-6892
页数15
ISBN(电子版)9781959429722
出版状态已出版 - 2023
活动61st Annual Meeting of the Association for Computational Linguistics, ACL 2023 - Toronto, 加拿大
期限: 9 7月 202314 7月 2023

出版系列

姓名Proceedings of the Annual Meeting of the Association for Computational Linguistics
1
ISSN(印刷版)0736-587X

会议

会议61st Annual Meeting of the Association for Computational Linguistics, ACL 2023
国家/地区加拿大
Toronto
时期9/07/2314/07/23

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引用此

Li, Y., Liu, X., Wang, S., Gong, P., Wong, D. F., Gao, Y., Huang, H., & Zhang, M. (2023). TemplateGEC: Improving Grammatical Error Correction with Detection Template. 在 Long Papers (页码 6878-6892). (Proceedings of the Annual Meeting of the Association for Computational Linguistics; 卷 1). Association for Computational Linguistics (ACL).