Abstract
Lexica distinguishing all morphologically related forms of each lexeme are crucial to many language technologies, yet building them is expensive. We propose a frugal paradigm completion approach that predicts all related forms in a morphological paradigm from as few manually provided forms as possible. It induces typological information during training which it uses to determine the best sources at test time. We evaluate our language-agnostic approach on 7 diverse languages. Compared to popular alternative approaches, ours reduces manual labor by 16-63% and is the most robust to typological variation.- Anthology ID:
- 2020.acl-main.733
- Volume:
- Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2020
- Address:
- Online
- Editors:
- Dan Jurafsky, Joyce Chai, Natalie Schluter, Joel Tetreault
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 8248–8273
- Language:
- URL:
- https://aclanthology.org/2020.acl-main.733
- DOI:
- 10.18653/v1/2020.acl-main.733
- Cite (ACL):
- Alexander Erdmann, Tom Kenter, Markus Becker, and Christian Schallhart. 2020. Frugal Paradigm Completion. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 8248–8273, Online. Association for Computational Linguistics.
- Cite (Informal):
- Frugal Paradigm Completion (Erdmann et al., ACL 2020)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/2020.acl-main.733.pdf