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Dependency-based semantic role labeling using sequence labeling with a structural SVM
- Source :
-
Pattern Recognition Letters . Apr2013, Vol. 34 Issue 6, p696-702. 7p. - Publication Year :
- 2013
-
Abstract
- Abstract: Semantic Role Labeling (SRL) systems aim at determining the semantic role labels of the arguments of the predicates in natural language text. SRL systems can usually be built to work upon the result of constitient analysis (constituent-based), or dependency parsing (dependency-based). SRL systems can use either classification or sequence labeling as the main processing mechanism. In this paper, we show that a dependency-based SRL system using sequence labeling can achieve state-of-the-art performance when a new structural SVM adapted from the Pegasos algorithm is exploited for performing sequence labeling. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 01678655
- Volume :
- 34
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- Pattern Recognition Letters
- Publication Type :
- Academic Journal
- Accession number :
- 86155722
- Full Text :
- https://doi.org/10.1016/j.patrec.2013.01.022