Abstract
In this paper we focus on connective identification and sense classification for explicit discourse relations in German, as two individual sub-tasks of the overarching Shallow Discourse Parsing task. We successively augment a purely-empirical approach based on contextualised embeddings with linguistic knowledge encoded in a connective lexicon. In this way, we improve over published results for connective identification, achieving a final F1-score of 87.93; and we introduce, to the best of our knowledge, first results for German sense classification, achieving an F1-score of 87.13. Our approach demonstrates that a connective lexicon can be a valuable resource for those languages that do not have a large PDTB-style-annotated coprus available.- Anthology ID:
- 2020.coling-main.505
- Volume:
- Proceedings of the 28th International Conference on Computational Linguistics
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona, Spain (Online)
- Editors:
- Donia Scott, Nuria Bel, Chengqing Zong
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 5737–5748
- Language:
- URL:
- https://aclanthology.org/2020.coling-main.505
- DOI:
- 10.18653/v1/2020.coling-main.505
- Cite (ACL):
- Peter Bourgonje and Manfred Stede. 2020. Exploiting a lexical resource for discourse connective disambiguation in German. In Proceedings of the 28th International Conference on Computational Linguistics, pages 5737–5748, Barcelona, Spain (Online). International Committee on Computational Linguistics.
- Cite (Informal):
- Exploiting a lexical resource for discourse connective disambiguation in German (Bourgonje & Stede, COLING 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2020.coling-main.505.pdf