Abstract: Syntactic analysis is a research direction with very broad application prospects in the field of natural language processing. In view of the fact that current syntactic analysis is mostly from the perspective of characters and words and there are many shortcomings, a hierarchical analysis algorithm of syntactic rules combining binary and ternary word models is proposed, and word segmentation, part-of-speech tagging and sentence organization information are combined to solve the problem of preferential synthesis between words. At the same time, the effect of grammatical structure relationship between sentence components on part-of-speech and word order is used to achieve a hierarchical analysis experiment of syntactic rules. The results show that the hierarchical rule analysis algorithm combining the binary and ternary word models is more accurate than the independent binary and ternary word models, and it improves the accuracy rate and recall rate to   and  , respectively. Compared with the existing   algorithm and lexical model algorithm based on binary structure syntax analysis, the accuracy and recall are significantly improved. 

Key words: binary and ternary word, syntactic structure, word element combination model, hierarchical analysis algorithm