SynCABEL: Synthetic Contextualized Augmentation for Biomedical Entity Linking

In three linesSynCABEL uses LLMs to generate contextualized synthetic training examples to address scarcity of annotated data in biomedical entity linking. The framework achieves state-of-the-art on MedMentions (English), QUAERO (French), and SPACCC (Spanish), reaching full human supervision performance with 60% less annotated data. An LLM-as-a-judge protocol evaluates clinical validity.

Summary generated by Claude — human-verified