AutoTagTCG : A Framework for Automatic Thai CG Tagging

Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC 2010)

Abstract

This paper aims to develop a framework for automatic CG tagging. We investigated two main algorithms, CRF and Statistical alignment model based on information theory (SAM). We found that SAM gives the best results both in word level and sentence level. We got the accuracy 89.25% in word level and 82.49% in sentence level. Combining both methods can be suited for both known and unknown word.