%0 Conference Proceedings %T discopy: A Neural System for Shallow Discourse Parsing %A Knaebel, René %Y Braud, Chloé %Y Hardmeier, Christian %Y Li, Junyi Jessy %Y Louis, Annie %Y Strube, Michael %Y Zeldes, Amir %S Proceedings of the 2nd Workshop on Computational Approaches to Discourse %D 2021 %8 November %I Association for Computational Linguistics %C Punta Cana, Dominican Republic and Online %F knaebel-2021-discopy %X 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. %R 10.18653/v1/2021.codi-main.12 %U https://aclanthology.org/2021.codi-main.12 %U https://doi.org/10.18653/v1/2021.codi-main.12 %P 128-133