Abstract
This paper discusses the computational parsing of GP sentences. By an approach of combining computational linguistic methods, e.g. CFG, ATN and BNF, we analyze the various syntactic structures of pre-grammatical, common, ambiguous and GP sentences. The evidence shows both ambiguous and GP sentences have lexical or syntactic crossings. Any choice of the crossing in ambiguous sentences can bring a full-parsed structure. In GP sentences, the probability-based choice is the cognitive prototype of parsing. Once the part-parsed priority structure is replaced by the full-parsed structure of low probability, the distinctive feature of backtracking appears. The computational analysis supports Pritchett’s idea on processing breakdown of GP sentences.
Highlights
The advent of the World Wide Web has greatly increased demand for natural language processing (NLP)
NLP relates to human-computer interaction, discusses linguistic coverage issues, and explores the development of natural language widgets and their integration into multi user interfaces[1].The development of language technology has been facilitated by two technical breakthroughs: the first emphasizes empirical approaches and the second highlights networked machines [2].Natural language and databases are core components of information systems, and NLP techniques may substantially enhance most phases of query processing, natural language understanding and the information system [3,4,5]
The pre-grammatical sentences, common sentences and ambiguous sentences will be analyzed from the perspective of computational linguistics as the comparison and contrast to Garden Path (GP) sentences
Summary
The advent of the World Wide Web has greatly increased demand for natural language processing (NLP). Plant& Murrell’s Dialogue NLP System discusses the importance of Backus–Naur Form (BNF) This system analyzes the possibility for any user who understands formal grammars to replace or upgrade the system or to produce all possible parses of the input query without requiring any programming. The matching agent searches through a knowledge base of scripts and selects the most closely matching one In this model, BNF is very helpful and useful for system to analyze natural language. With the help of special word or phrase, they find that the syntactic structure which is being built up is different from the structure which has been created, namely it is a wrong path down which they have been led They have to return and reinterpret, which is called backtracking. The pre-grammatical sentences, common sentences and ambiguous sentences will be analyzed from the perspective of computational linguistics as the comparison and contrast to GP sentences
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