An empirical study for Vietnamese dependency parsing

2016/11/03 by Dat Quoc Nguyen, Mark Dras, Nguyen, Dat Quoc +3
Computer Science · #Natural Language Processing Techniques #Speech and dialogue systems #Topic Modeling #cs.CL

paper · pdf · doi:10.48550/arxiv.1611.00995

To appear in Proceedings of the 14th Annual Workshop of the Australasian Language Technology Association

arxiv created 2016/11/03 · arxiv updated 2016/11/04

Abstract

This paper presents an empirical comparison of different dependency parsers for Vietnamese, which has some unusual characteristics such as copula drop and verb serialization. Experimental results show that the neural network-based parsers perform significantly better than the traditional parsers. We report the highest parsing scores published to date for Vietnamese with the labeled attachment score (LAS) at 73.53% and the unlabeled attachment score (UAS) at 80.66%.

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