Abstract
We present the approach of the Turku NLP group to the PharmaCoNER task on Spanish biomedical named entity recognition. We apply a CRF-based baseline approach and multilingual BERT to the task, achieving an F-score of 88% on the development data and 87% on the test set with BERT. Our approach reflects a straightforward application of a state-of-the-art multilingual model that is not specifically tailored to either the language nor the application domain. The source code is available at: https://github.com/chaanim/pharmaconer- Anthology ID:
- D19-5709
- Volume:
- Proceedings of the 5th Workshop on BioNLP Open Shared Tasks
- Month:
- November
- Year:
- 2019
- Address:
- Hong Kong, China
- Editors:
- Kim Jin-Dong, Nédellec Claire, Bossy Robert, Deléger Louise
- Venue:
- BioNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 56–61
- Language:
- URL:
- https://aclanthology.org/D19-5709
- DOI:
- 10.18653/v1/D19-5709
- Cite (ACL):
- Kai Hakala and Sampo Pyysalo. 2019. Biomedical Named Entity Recognition with Multilingual BERT. In Proceedings of the 5th Workshop on BioNLP Open Shared Tasks, pages 56–61, Hong Kong, China. Association for Computational Linguistics.
- Cite (Informal):
- Biomedical Named Entity Recognition with Multilingual BERT (Hakala & Pyysalo, BioNLP 2019)
- PDF:
- https://preview.aclanthology.org/landing_page/D19-5709.pdf
- Code
- chaanim/pharmaconer