Efficient medical NER with limited data: Enhancing LLM performance through annotation guidelines
Including annotation guidelines in prompts enhances the performance of LLMs in NER tasks, making this a practical approach for developing accurate NLP systems in resource-constrained environments. Although annotation guidelines are essential for evaluation and example creation, their integration into LLM prompts can further optimize few-shot learning, especially within specialized domains such as medical NLP.
Authors
- Yoshimasa Kawazoe (ORCID: https://orcid.org/0000-0002-7277-0827)
- Emiko Shinohara
Institutions
- Tokyo Health Care University (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- International Journal of Medical Informatics
- Published
- 2025-12-19
- DOI
- https://doi.org/10.1016/j.ijmedinf.2025.106230
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 0.00