Building an Efficient Functional-Tag Labeling System for Vietnamese

Functional tags represent the role of syntactic constituents such as noun phrases and verb phrases in a tree. Functional-tag labeling has been studied for languages such as English and Chinese. In this paper, we present a new system for tagging Vietnamese sentences functionally. We used maximum entropy model for this task with six tree-based features. Besides, a new feature based on word cluster has also been made use of. Our experiments on Vietnamese tree bank showed that the system achieved a good performance and the word cluster feature brought a significant improvement.