Abstract
Recognition of named entities present in text is an important step towards information extraction and natural language understanding. This work presents a named entity recognition system for the Romanian biomedical domain. The system makes use of a new and extended version of SiMoNERo corpus, that is open sourced. Also, the best system is available for direct usage in the RELATE platform.- Anthology ID:
- 2022.bionlp-1.30
- Volume:
- Proceedings of the 21st Workshop on Biomedical Language Processing
- Month:
- May
- Year:
- 2022
- Address:
- Dublin, Ireland
- Editors:
- Dina Demner-Fushman, Kevin Bretonnel Cohen, Sophia Ananiadou, Junichi Tsujii
- Venue:
- BioNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 316–322
- Language:
- URL:
- https://aclanthology.org/2022.bionlp-1.30
- DOI:
- 10.18653/v1/2022.bionlp-1.30
- Cite (ACL):
- Maria Mitrofan and Vasile Pais. 2022. Improving Romanian BioNER Using a Biologically Inspired System. In Proceedings of the 21st Workshop on Biomedical Language Processing, pages 316–322, Dublin, Ireland. Association for Computational Linguistics.
- Cite (Informal):
- Improving Romanian BioNER Using a Biologically Inspired System (Mitrofan & Pais, BioNLP 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2022.bionlp-1.30.pdf