No abstract

Noun phrase chunking is an important and useful task in many natural language processing applications. It is studied well for English, however with Vietnamese it is still an open problem. This paper presents a Vietnamese Noun Phrase chunking approach based on Conditional random fields (CRFs) models. We also describe a method to build Vietnamese corpus from a set of hand annotated sentences. For evaluation, we perform several experiments using different feature settings. Outcome results on our corpus show a high performance with the average of recall and precision 82.72% and 82.62% respectively. 1

No abstract

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 treebank showed that the system achieved a good performance and the word cluster feature brought a significant improvement.

Abstract. In this paper, we present a system that automatically extracts lexicalized tree adjoining grammars (LTAG) from treebanks. We first discuss extraction algorithms and compare them to previous works. Then we report the LTAG extraction result for Vietnamese, using a recently released Vietnamese treebank. The implementation of an open source and language independent system for automatic extraction of LTAG grammars is also discussed. . c phân phối du .ó. i da . ng mã nguồn mo . ' .