Realization and optimization of Chinese syntactic analyzer based on PCFG

Abstract

As a basic research work, syntactic analysis is also a key technology in the field of natural language processing, and is the basis for deep understanding of language. The syntactic analyzer is an important tool for syntactic analysis. The Probabilistic Context Free Grammar (PCFG) model is the basic model of most parsers with excellent performance. Good effect. This article integrates named entity clues into PCFG-based Chinese syntax analysis models, completes joint learning and decoding of named entity recognition, syntactic analysis, and implements a fast and reliable decoding parser.