Applying Morphological Structure for Effective Part-of-Speech Tagging in Myanmar Text

Abstract

Part-of-Speech tagging is the process of marking up the words in a text as corresponding to a particular part of speech based on both its definition, as well as its context. Tagsets and word disambiguation rules are fundamental parts of any POS tagger. This system proposed a new approach to POS tagger of Myanmar text. It exploits a hybrid approach which is combination of rule based and statistical methods to tag Myanmar sentence. The tagger of this system demonstrates on the following ideas: (i) Design detail tagsets for Part-of-Speech according from Myanmar Grammar. (ii) Generate rules for disambiguation of word in various part of speech according to different morphological structure. (iii) Explicit use of both preceding and following contexts via a cyclic dependency network representation. So, the expected results of this proposed system shows that tagging accuracy is high by using morphological structure of Myanmar Language.