Automatic Learning Method of Domain Semantic Grammar Based on Fault-tolerant Earley Parsing Algorithm

Abstract

Refined domain text analysis is an important prerequisite for high-quality domain knowledge acquisition.It usually relies on a large number of some form of semantic grammars,but summarizing them is often time-consuming and labor-intensive.In this paper,an automatic learning method of semantic grammar based on fault-tolerant Earley parsing algorithm is proposed,which automatically generates new semantic grammars (including lexicons and grammar production rules) according to seed grammar to reduce labor costs.This method uses the optimized fault-tolerant Earley parser to perform fault-tolerant parsing on the input statements,and then generates candidate semantic grammars based on the parse tree generated by the fault-tolerant parsing.Finally,the candidate semantic grammars are filtered or corrected to obtain the final semantic grammars.In the experiment of five TCM medical records with different diseases,the precision rate of learning new lexicons is 63.88%,and precision rate of learning new grammar production rules is 81.78%.

Keywords

• fault-tolerant earley parser|semantic grammar|grammar learning|filtering algorithm|semantic correction