discopy: A Neural System for Shallow Discourse Parsing

René Knaebel


Abstract
This paper demonstrates discopy, a novel framework that makes it easy to design components for end-to-end shallow discourse parsing. For the purpose of demonstration, we implement recent neural approaches and integrate contextualized word embeddings to predict explicit and non-explicit discourse relations. Our proposed neural feature-free system performs competitively to systems presented at the latest Shared Task on Shallow Discourse Parsing. Finally, a web front end is shown that simplifies the inspection of annotated documents. The source code, documentation, and pretrained models are publicly accessible.
Anthology ID:
2021.codi-main.12
Volume:
Proceedings of the 2nd Workshop on Computational Approaches to Discourse
Month:
November
Year:
2021
Address:
Punta Cana, Dominican Republic and Online
Venues:
CODI | CRAC | EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
128–133
Language:
URL:
https://aclanthology.org/2021.codi-main.12
DOI:
10.18653/v1/2021.codi-main.12
Bibkey:
Cite (ACL):
René Knaebel. 2021. discopy: A Neural System for Shallow Discourse Parsing. In Proceedings of the 2nd Workshop on Computational Approaches to Discourse, pages 128–133, Punta Cana, Dominican Republic and Online. Association for Computational Linguistics.
Cite (Informal):
discopy: A Neural System for Shallow Discourse Parsing (Knaebel, CODI 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.codi-main.12.pdf
Code
 rknaebel/discopy