IAI @ SocialDisNER : Catch me if you can! Capturing complex disease mentions in tweets
Aman Sinha, Cristina Garcia Holgado, Marianne Clausel, Matthieu Constant
Abstract
Biomedical NER is an active research area today. Despite the availability of state-of-the-art models for standard NER tasks, their performance degrades on biomedical data due to OOV entities and the challenges encountered in specialized domains. We use Flair-NER framework to investigate the effectiveness of various contextual and static embeddings for NER on Spanish tweets, in particular, to capture complex disease mentions.- Anthology ID:
- 2022.smm4h-1.25
- Volume:
- Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Graciela Gonzalez-Hernandez, Davy Weissenbacher
- Venue:
- SMM4H
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 85–89
- Language:
- URL:
- https://aclanthology.org/2022.smm4h-1.25
- DOI:
- Cite (ACL):
- Aman Sinha, Cristina Garcia Holgado, Marianne Clausel, and Matthieu Constant. 2022. IAI @ SocialDisNER : Catch me if you can! Capturing complex disease mentions in tweets. In Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task, pages 85–89, Gyeongju, Republic of Korea. Association for Computational Linguistics.
- Cite (Informal):
- IAI @ SocialDisNER : Catch me if you can! Capturing complex disease mentions in tweets (Sinha et al., SMM4H 2022)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2022.smm4h-1.25.pdf
- Code
- amansinha09/sm4hht10