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EMNLP
2007

Multilingual Dependency Parsing Using Global Features

9 years 2 months ago
Multilingual Dependency Parsing Using Global Features
In this paper, we describe a two-stage multilingual dependency parser used for the multilingual track of the CoNLL 2007 shared task. The system consists of two components: an unlabeled dependency parser using Gibbs sampling which can incorporate sentence-level (global) features as well as token-level (local) features, and a dependency relation labeling module based on Support Vector Machines. Experimental results show that the global features are useful in all the languages.
Tetsuji Nakagawa
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where EMNLP
Authors Tetsuji Nakagawa
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