Vietnamese transition-based dependency parsing with supertag features
This work addresses dependency parsing for Vietnamese, an incremental improvement using existing methods on new data.
The paper tackled dependency parsing for Vietnamese by incorporating supertag features into a transition-based parser, resulting in an 18.92% improvement in labeled attachment score with gold supertags and a 3.57% improvement with automatic supertags.
In recent years, dependency parsing is a fascinating research topic and has a lot of applications in natural language processing. In this paper, we present an effective approach to improve dependency parsing by utilizing supertag features. We performed experiments with the transition-based dependency parsing approach because it can take advantage of rich features. Empirical evaluation on Vietnamese Dependency Treebank showed that, we achieved an improvement of 18.92% in labeled attachment score with gold supertags and an improvement of 3.57% with automatic supertags.