Improving Romanian BioNER Using a Biologically Inspired System

Maria Mitrofan, Vasile Pais


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
Venues:
ACL | 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
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/2022.bionlp-1.30.pdf