Abstract
篇章分析作为自然语言处理领域的基础问题一直广受关注。由于语料规模有限,绝大多数已有研究仍依赖于外部特征的加入。针对该问题,本文提出了提出一种通用的表征增强方法,借助图卷积神经网络将词汇链信息融入到基本篇章单元的表征中。在RST-DT和CDTB上的实验证明,本文提出的表征增强方法能够提升多种篇章解析器的性能。- Anthology ID:
- 2021.ccl-1.43
- Volume:
- Proceedings of the 20th Chinese National Conference on Computational Linguistics
- Month:
- August
- Year:
- 2021
- Address:
- Huhhot, China
- Venue:
- CCL
- SIG:
- Publisher:
- Chinese Information Processing Society of China
- Note:
- Pages:
- 467–476
- Language:
- Chinese
- URL:
- https://aclanthology.org/2021.ccl-1.43
- DOI:
- Cite (ACL):
- Jinfeng Wang and Fang Kong. 2021. 基于词汇链强化表征的篇章修辞结构分析研究(Lexical Chain Based Strengthened Representation for Discourse Rhetorical Structure Parsing). In Proceedings of the 20th Chinese National Conference on Computational Linguistics, pages 467–476, Huhhot, China. Chinese Information Processing Society of China.
- Cite (Informal):
- 基于词汇链强化表征的篇章修辞结构分析研究(Lexical Chain Based Strengthened Representation for Discourse Rhetorical Structure Parsing) (Wang & Kong, CCL 2021)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2021.ccl-1.43.pdf