Chinese Named Entity Recognition Technology For Enterprise Knowledge Graph Construction

Named entity recognition is an important basic tool in the fields of information extraction,machine translation,knowledge graph,question and answer system,etc.It plays an important role in the process of natural language processing technology becoming practical.Based on the deep neural network model,the Chinese named entity recognition technology involved in construction process of enterprise knowledge graph is researched deeply in this work?Firstly,based on the classical BiLSTM-CRF named entity recognition model,the SA-BiLSTM-CRF model is proposed by incorporating the self-attention mechanism.Experiments show that the model can effectively extract long-distance dependence information,which has better recognition effect than BiLSTM-CRF model.it is found that bidirectional self-attention is better than sigle self-attention when combaining with BiLSTM.Otherwise,position embedding is not necessary for SA-BiLSTM-CRF model because of LSTM.The multi-head mechanism in Attention can improve the model effect,but too many heads will lead to overfitting.Secondly,aimed to apply the SA-BiLSTM-CRF model to the enterprise domain with less corpus and solve the problem that deep network model is difficult to train,four optimizations are proposed which are based on transefer learning,self-training,active learning,self-training and active learning.The experiment verified the effectiveness of the four optimizations.At the same time,in the optimization strategy based on transfer learning,it is found that the best transfer learning method that fits the experimental situation is fine-tuning the whole pre-trained model.Among others,it is found that the algorithm combining self-training and active learning can complement each other,and the optimization effect is better than the single one.Finally,Combining the SA-BiLSTM-CRF model with the transfer learning optimization strategy and the optimization strategy based on self-training and active learning,a named entity recognition system suitable for enterprise domain is proposed,and the enterprise knowledge graph is completed.