NCSEC2004 Parsing Thai for Machine Translation using Augmented State Transducer and Lexical Functional Grammar

Abstract

This paper presents an efficient, yet finegrained, approach to parsing Thai texts. This approach was intended to resolve omission problems and sentential-NP grouping for Thai-English machine translation. The omission problems are zero anaphora, no explicit tenses and numbers, and no explicit topic markers. To resolve those, the augmented state transducer was exploited to resolve noun grouping and the lexical functional grammar was applied to identify omissions. From the experiment, it was found that the augmented state transducer could properly resolve sentential-noun grouping, while most omissions could be identified by the lexical functional grammar. At average, the parser yields 80.72 % accuracy and the number of produced trees is 30.36 % reduced compared with which of the original LFG