Accurate knowledge of key genes that promote hair follicle growth and development is of great value in the field of hair research and dermatology. Compared with the traditional time-consuming and laborious experimental methods for obtaining key genes, the literature mining method can extract proven key genes for hair follicle growth from the vast amount of literature more quickly and comprehensively, i.e., perform the tasks of Named Entity Recognition (NER) and Relationship Extraction (RE) of related entities.