Abstract
For text-level discourse analysis there are various discourse schemes but relatively few labeleddata because discourse research is still immature and it is labor-intensive to annotate the innerlogic of a text. In this paper we attempt to unify multiple Chinese discourse corpora under different annotation schemes with discourse dependency framework by designing semi-automatic methods to convert them into dependency structures. We also implement several benchmark dependency parsers and research on how they can leverage the unified data to improve performance.1- Anthology ID:
- 2021.ccl-1.94
- 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:
- 1058–1065
- Language:
- English
- URL:
- https://aclanthology.org/2021.ccl-1.94
- DOI:
- Cite (ACL):
- Cheng Yi, Li Sujian, and Li Yueyuan. 2021. Unifying Discourse Resources with Dependency Framework. In Proceedings of the 20th Chinese National Conference on Computational Linguistics, pages 1058–1065, Huhhot, China. Chinese Information Processing Society of China.
- Cite (Informal):
- Unifying Discourse Resources with Dependency Framework (Yi et al., CCL 2021)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2021.ccl-1.94.pdf
- Code
- PKU-TANGENT/UnifiedDep