Natural language parsing using Fuzzy Simple LR (FSLR) parser
Suvarna G. Kanakaraddi, V. Ramaswamy · 2014
In daily life the language used for communication can be termed as Natural Language (NL) and it evolves from generation to generation. NL is the most powerful tool that humans possess for conveying information. At the core of Natural Language Processing (NLP) task there is an important issue of Natural Language Understanding (NLU). NLP is computer manipulation of NL. In this paper we propose a fuzzy parser which is a form of syntax analyzer that performs analysis of a complete source input. The Bottom up LR (left to right) syntax analysis [1] method is a useful and versatile technique for parsing deterministic Fuzzy context-free languages. Here we have proposed a Fuzzy Simple LR parser (FSLR) for parsing English sentences which uses Fuzzy Context Free Grammar (FCFG). LR parsers are a family of efficient, bottom-up shift-reduce parsers that can be used to parse a large class of context-free languages. The system is intended to rank the large number of syntactic analyses produced by NL grammars according to the frequency of occurrence of the individual rules deployed in each analysis. This paper discusses a procedure for constructing an LR parse table from Fuzzy context free grammar and using this table the input sentence is tested for syntactic correctness.