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政大機構典藏 > 資訊學院 > 資訊科學系 > 會議論文 > Item 140.119/135516

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/135516

Title:	A Complete Shift-Reduce Chinese Discourse Parser with Robust Dynamic Oracle
Authors:	黃瀚萱 Huang, Hen-Hsen Hung, Shyh-Shiun Chen, Hsin-Hsi
Contributors:	資科系
Date:	2020-07
Issue Date:	2021-06-04 14:36:53 (UTC+8)
Abstract:	This work proposes a standalone, complete Chinese discourse parser for practical applications. We approach Chinese discourse parsing from a variety of aspects and improve the shift-reduce parser not only by integrating the pre-trained text encoder, but also by employing novel training strategies. We revise the dynamic-oracle procedure for training the shift-reduce parser, and apply unsupervised data augmentation to enhance rhetorical relation recognition. Experimental results show that our Chinese discourse parser achieves the state-of-the-art performance.
Relation:	Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL, pp.133-138
Data Type:	conference
DOI 連結:	http://dx.doi.org/10.18653/v1/2020.acl-main.13
DOI:	10.18653/v1/2020.acl-main.13
Appears in Collections:	[資訊科學系] 會議論文

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