Chinese Named Entity Recognition Method Based on Dictionary Semantic Knowledge Enhancement

Chinese Named Entity Recognition is the fundamental technology in field of Natural Language Process. It extensively adopted into information extraction, intelligent question answering, and knowledge graph. Nevertheless, due to diversity complexity Chinese, most NER methods fail sufficiently capture character granularity semantics, which affects performance NER. In this work, we propose DSKE-Chinese NER: based on Dictionary Semantic Knowledge Enhancement. We novelly integrate semantic vector space characters acquire representation containing by attention mechanism. addition, verify appropriate number layers through comparative experiment. Experiments public datasets such as Weibo, Resume MSRA show that model outperforms character-based LSTM baselines.