resource · 2026

TCMKG: Knowledge-Grounded question answering in Traditional Chinese Medicine via dynamic prompt evolution framework

Journal of King Saud University - Computer and Information Sciences

Organizations: Anhui University of Traditional Chinese Medicine / Hefei University

DOI Back to catalog

TCMKG: Knowledge-Grounded question answering in Traditional Chinese Medicine via dynamic prompt evolution framework is a resource in the TCM LLM catalog (Awesome-TCM-LLM), dated 2026. It is maintained alongside the GitHub list of Traditional Chinese Medicine large language models.

TCMKG used expert-guided prompting on the Xin’an medical-case corpus to build a traditional Chinese medicine knowledge graph of 37,192 entities and 130,030 relations, with information-extraction precision 0.89, recall 0.88, and F1 0.88.

Tags kgrag

Links

Related