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EMNLP
2007

Experimental Evaluation of LTAG-Based Features for Semantic Role Labeling

9 years 2 months ago
Experimental Evaluation of LTAG-Based Features for Semantic Role Labeling
In this technical report, we propose the use of Lexicalized Tree-Adjoining Grammar (LTAG) formalism as an important additional source of features for the Semantic Role Labeling (SRL) task. Using a set of one-vs-all Support Vector Machines (SVMs), we evaluate these LTAG-based features. Our experiments show that LTAG-based features can improve SRL accuracy significantly. When compared with the best known set of features that are used in state of the art SRL systems we obtain an improvement in F-score from 82.34% to 85.25%.
Yudong Liu, Anoop Sarkar
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where EMNLP
Authors Yudong Liu, Anoop Sarkar
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