Chinese Named Entity Recognition Combined with Gazetteers and Syntactic Dependency Tree.

Chinese named entity recognition plays an important role in downstream tasks such as machine translation and intelligent question answering. A new Chinese named entity recognition algorithm based on gazetteers and syntactic dependency tree is proposed in this paper. To solve the problem of error transmission caused by the lack of word information in character vector and syntactic dependent structure information between words. This algorithm forms a graph of the gazetteers information and the syntactic dependency tree information in the sentence and then integrates it into the character vector through adaptive gated graph neural networks (AGGNN), so that the semantic relationship between words is obtained well in each character vector and the recognition accuracy is improved. Through the verification in Ecommerce, Resume, QI and other data sets, the new method can greatly improve the accuracy of Chinese entity recognition. [ABSTRACT FROM AUTHOR]