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From Word Segmentation to POS Tagging for Vietnamese by Nguyen, Dat Quoc; Vu, Thanh; Nguyen, Dai Quoc; Dras, Mark; Johnson, Mark is a scholarly article available to read on EtoBox.

What is From Word Segmentation to POS Tagging for Vietnamese about?

This paper presents an empirical comparison of two strategies for Vietnamese Part-of-Speech (POS) tagging from unsegmented text: (i) a pipeline strategy where we consider the output of a word segmenter as the input of a POS tagger, and (ii) a joint strategy where we predict a combined segmentation and POS tag for each syllable. We also make a comparison between state-of-the-art (SOTA) feature-based and neural network-based models. On the benchmark Vietnamese treebank (Nguyen et al., 2009), experimental results show that the pipeline strategy produces better scores of POS tagging from unsegmented text than the joint strategy, and the highest accuracy is obtained by using a feature-based model.

Author

Nguyen, Dat Quoc; Vu, Thanh; Nguyen, Dai Quoc; Dras, Mark; Johnson, Mark

Published

2017

Language

EN