The self-annotated Chinese electronic medical record(EMR) standard datasetisused, the similarity algorithms and pre-trained models are fused and applied to the candidate entity generation and entity disambiguation stages of entity mapping, and the performance of different similarity algorithms and pre-trained models is compared and analyzed. A method is proposed to improve the mapping effect of drug class entities based on alias similarity, and the Jaccard similarity algorithm and BERT pre-trained model are combined to efficiently realize the task of mapping the entities of massive Chinese EMRs.