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.
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CITATION STYLE
Knaebel, R. (2021). discopy: A Neural System for Shallow Discourse Parsing. In 2nd Workshop on Computational Approaches to Discourse, CODI 2021 - Proceedings of the Workshop (pp. 128–133). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2021.codi-main.12