A contrastive-learning dataset for training and evaluating domain-adapted text embedding models for Korean Medicine (KM, 한의학). Each example is a query–positive–negatives triplet built from Korean Medicine terminology dictionaries and a curated KM ontology, capturing clinically meaningful semantic relations such as disease–symptom, disease–prescription, prescription–indication, prescription–herb, and herb–indication.
This dataset… See the full description on the dataset page:
https://huggingface.co/datasets/cnupo23/korean-medicine-embedding-dataset.
