Efficient dependency analysis for Korean sentences based on lexical association and multi-layered chunking
Jinsung Yoon · Literary and Linguistic Computing · 2001
Syntactic analysis often plays an important role in natural language processing application systems such as document processing and question–answering. To use parsed results in the application systems, the parser should be efficient without losing accuracy. In this paper, we present a method for Korean dependency analysis using three types of chunking and lexical co–occurrences extracted from a large corpus. The chunking, which is crucial for reducing disambiguation decisions in the parsing process, is conducted using a finite state transducer and lexical collocation. In addition, lexical information has a great impact on parsing for a free-ordered language such as Korean, as the lexical association is more important than the word order in analysing such languages. The parser that we propose is a hybrid system directed by statistical data and syntactic rules, and based on right–to–left analysis to effectively treat sentences in Korean, which is a head final language. Experiments show that the method is very effective in that it gives accuracy as well as efficiency by reducing irrelevant parsing decisions.