BERT-LCRF Named Entity Recognition Method Oriented Clock Domain.

Named entity recognition is a key step in constructing a knowledge graph in the clock domain. However, the current clock domain has problems such as the small number of labeled samples, which leads to the low accuracy of named entity recognition in the clock domain. To this end, this paper uses the pre-trained language model BERT to extract the features of the text in the clock domain, and then uses the linear chain conditional random field (Linear-CRF) method for sequence labeling, and proposes a BERT-LCRF named entity recognition model. The results of comparative experiments show that the model can fully learn the feature information of the clock domain, improve the accuracy of sequence labeling, and then improve the effect of named entity recognition in the clock domain. [ABSTRACT FROM AUTHOR]