Research on equipment entity recognition and attribute extraction for knowledge graph construction

Equipment entity recognition and attribute extraction are the basis of constructing equipment knowledge graph. In this paper, we firstly design a model framework for equipment entity recognition and its attribute extraction. Then, combining the advantages of BiLSTM and CRF, an equipment entity recognition method based on Dic+BiLSTM-CRF is proposed by constructing a domain-specific dictionary for equipment. Furthermore, the equipment entity attribute extraction method is designed based on HMM model and Viterbi algorithm. The experiment results show that compared with the traditional methods, the performance of equipment entity recognition based on Dic+BiLSTM-CRF is close to the general domain entity recognition level. The accuracy rate, recall rate and F1 value of equipment entity attribute extraction are higher than 80%.