An Empirical Study of Vietnamese Noun Phrase Chunking with Discriminative Sequence Models

This paper presents an empirical work for Vietnamese NP chunking task. We show how to build an annotation corpus of NP chunking and how discriminative sequence models are trained using the corpus. Experiment results using 5 fold cross validation test show that discriminative sequence learning are well suitable for Vietnamese chunking. In addition, by empirical experiments we show that the part of speech information contribute significantly to the performance of there learning models.