Abstract
Biomedical entity linking is the task of identifying mentions of biomedical concepts in text documents and mapping them to canonical entities in a target thesaurus. Recent advancements in entity linking using BERT-based models follow a retrieve and rerank paradigm, where the candidate entities are first selected using a retriever model, and then the retrieved candidates are ranked by a reranker model. While this paradigm produces state-of-the-art results, they are slow both at training and test time as they can process only one mention at a time. To mitigate these issues, we propose a BERT-based dual encoder model that resolves multiple mentions in a document in one shot. We show that our proposed model is multiple times faster than existing BERT-based models while being competitive in accuracy for biomedical entity linking. Additionally, we modify our dual encoder model for end-to-end biomedical entity linking that performs both mention span detection and entity disambiguation and out-performs two recently proposed models.- Anthology ID:
- 2021.louhi-1.4
- Volume:
- Proceedings of the 12th International Workshop on Health Text Mining and Information Analysis
- Month:
- April
- Year:
- 2021
- Address:
- online
- Editors:
- Eben Holderness, Antonio Jimeno Yepes, Alberto Lavelli, Anne-Lyse Minard, James Pustejovsky, Fabio Rinaldi
- Venue:
- Louhi
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 28–37
- Language:
- URL:
- https://aclanthology.org/2021.louhi-1.4
- DOI:
- Cite (ACL):
- Rajarshi Bhowmik, Karl Stratos, and Gerard de Melo. 2021. Fast and Effective Biomedical Entity Linking Using a Dual Encoder. In Proceedings of the 12th International Workshop on Health Text Mining and Information Analysis, pages 28–37, online. Association for Computational Linguistics.
- Cite (Informal):
- Fast and Effective Biomedical Entity Linking Using a Dual Encoder (Bhowmik et al., Louhi 2021)
- PDF:
- https://preview.aclanthology.org/revert-3132-ingestion-checklist/2021.louhi-1.4.pdf
- Code
- kingsaint/BioMedical-EL
- Data
- BC5CDR, MedMentions