This paper presents a new conversion method to automatically transform a constituent-based Vietnamese Treebank into dependency trees. On a dependency Treebank created according to our new approach, we examine two state-of-the-art dependency parsers: the MSTParser and the MaltParser. Experiments show that the MSTParser outperforms the MaltParser. To the best of our knowledge, we report the highest performances published to date in the task of dependency parsing for Vietnamese. Particularly, on gold standard POS tags, we get an unlabeled attachment score of 79.08% and a labeled attachment score of 71.66%. © Springer International Publishing Switzerland 2014.
CITATION STYLE
Nguyen, D. Q., Nguyen, D. Q., Pham, S. B., Nguyen, P. T., & Le Nguyen, M. (2014). From treebank conversion to automatic dependency parsing for Vietnamese. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8455 LNCS, pp. 196–207). Springer Verlag. https://doi.org/10.1007/978-3-319-07983-7_26
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