Unifying Discourse Resources with Dependency Framework

Cheng Yi, Li Sujian, Li Yueyuan


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
Editors:
Sheng Li (李生), Maosong Sun (孙茂松), Yang Liu (刘洋), Hua Wu (吴华), Kang Liu (刘康), Wanxiang Che (车万翔), Shizhu He (何世柱), Gaoqi Rao (饶高琦)
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:
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/2021.ccl-1.94.pdf
Code
 PKU-TANGENT/UnifiedDep