Parsing of Myanmar sentences with function tagging
This addresses parsing challenges for Myanmar language, which has free-phrase-order and complex morphology, but is incremental as it applies existing methods to a new domain.
The paper tackled parsing Myanmar sentences by using Naive Bayes for function tagging and context-free grammar, achieving good results on simple and three types of complex sentences.
This paper describes the use of Naive Bayes to address the task of assigning function tags and context free grammar (CFG) to parse Myanmar sentences. Part of the challenge of statistical function tagging for Myanmar sentences comes from the fact that Myanmar has free-phrase-order and a complex morphological system. Function tagging is a pre-processing step for parsing. In the task of function tagging, we use the functional annotated corpus and tag Myanmar sentences with correct segmentation, POS (part-of-speech) tagging and chunking information. We propose Myanmar grammar rules and apply context free grammar (CFG) to find out the parse tree of function tagged Myanmar sentences. Experiments show that our analysis achieves a good result with parsing of simple sentences and three types of complex sentences.