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Lecture Notes in Computer Science
Named Entity Recognition (NER) is an essential part of many natural language processing (NLP) tasks. The existing Chinese NER methods are mostly based on word segmentation, or use the character sequences as input. However, using a single granularity representation would suffer from the problems of out-of-vocabulary and word segmentation errors, and the semantic content is relatively simple. In this paper, we introduce the self-attention mechanism into the BiLSTM-CRF neural network structure fordoi:10.1007/978-3-030-45439-5_24 fatcat:rrp52ui4u5hvbcpo7hcimtm3gq