Improved Joint Kazakh POS Tagging and Chunking

This paper describes a mixing model of joint POS tagging and chunking for Kazakh where partial optimal solution provide feature information for joint model. A improved beam-search algorithm use dynamic beam instead of unified beam to obtain search space of small-but-excellent during both training and decoding phases of the model. Moreover we can statistical induction the information of chunk to disambiguation of multi-category words and experiment shows the precision is improved from 81.6 % to 87.7 % by information of chunk.

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