Unsupervised Dependency Parsing for Myanmar Language using Part-of-Speech Information

Abstract

In this paper, we present the preliminary experimentsof unsupervised dependency parsing on rawsegmented and part-of-speech (POS) tagged corpusof Myanmar language. This experiment is aimed tosupport building treebank and get ann-otated corpuswith dependency structures of My-anmar words. Thereferenced word dependency schemes are alsoexplained. We present the expr-imental results ontrees of unsupervised parsed annotated corpus interms of unlabeled and labe-led attachment scores(UAS and LAS) by UDPi-pe 89.79 % and 85.56% fortest and 98.25% and 97.89% for trained datarespectively