Semantic role labeling using complete syntactic analysis (2005)
| Venue: | In Proceedings of CoNLL-2005 shared task |
| Citations: | 10 - 1 self |
BibTeX
@INPROCEEDINGS{Surdeanu05semanticrole,
author = {Mihai Surdeanu and Jordi Turmo},
title = {Semantic role labeling using complete syntactic analysis},
booktitle = {In Proceedings of CoNLL-2005 shared task},
year = {2005},
pages = {221--224}
}
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Abstract
In this paper we introduce a semantic role labeling system constructed on top of the full syntactic analysis of text. The labeling problem is modeled using a rich set of lexical, syntactic, and semantic attributes and learned using one-versus-all AdaBoost classifiers. Our results indicate that even a simple approach that assumes that each semantic argument maps into exactly one syntactic phrase obtains encouraging performance, surpassing the best system that uses partial syntax by almost 6%. 1
Citations
| 780 | Head-Driven Statistical Models for Natural Language Parsing - Collins - 1999 |
| 561 | Y: Improved boosting algorithms using confidence-rated predictions - RE, Singer - 1999 |
| 466 | Automatic Labeling of Semantic Roles - Gildea, Jurafsky - 2002 |
| 90 | Using predicate-argument structures for information extraction - Surdeanu, Harabagiu, et al. - 2003 |
| 89 | Introduction to the CoNLL-2004 Shared Task: Semantic Role Labeling - Carreras, rques, et al. |
| 67 | Support vector learning for semantic argument classification - Pradhan, Hacioglu, et al. - 2005 |
| 37 | Semantic role labeling by tagging syntactic chunks - Hacioglu, Pradhan, et al. - 2004 |
| 9 | Hierarchical recognition of propositional arguments with perceptrons - Carreras, MÃ rquez, et al. - 2004 |
