Research on Named Entity Recognition of MRC Model in Water Conservancy Field Based on Data Enhancement
The recognition of named entities in the field of water conservancy is of great significance for the building of water conservancy knowledge graphs and intelligent question answering systems.However,in the current field of water conservancy,there are shortcomings in named entity recognition,such as a lack of annotated corpus,low recognition accuracy of traditional methods and inability to solve polyse-mous entities.Aiming at the characteristics of water conservancy texts,a Named Entity Recognition Model for Machine Reading Comprehen-sion(MRC)based on data(vocabulary and entity type labels)enhancement,namely the MRC-WLE model was put forward.Mainly,the vo-cabulary feature information and entity type label feature information in water conservancy texts were injected into the model as"knowledge".It introduced models such as BERT-CRF,BERT-CRF-Word,BERT-BiLSTM-CRF and BERT-BiLSTM-CRF-Word as controls to evaluate the performance of the MRC-WLE model.The results show that compared with the BERT-CRF and other models mentioned above,the micro av-erage F1 value of the MRC-WLE model has been improved.Compared with the MRC model,the micro average F1 value of the MRC-WLE model has been increased by 0.85%,reflecting the effectiveness of data augmentation.
water conservancy fieldnamed entity recognitiondata enhancedMRC
国家科技期刊平台
NSTL
万方数据
