Combination Strategies for Semantic Role Labeling

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Combination Strategies for Semantic Role Labeling
This paper introduces and analyzes a battery of inference models for the problem of semantic role labeling: one based on constraint satisfaction, and several strategies that model the inference as a meta-learning problem using discriminative classifiers. These classifiers are developed with a rich set of novel features that encode proposition and sentence-level information. To our knowledge, this is the first work that: (a) performs a thorough analysis of learning-based inference models for semantic role labeling, and (b) compares several inference strategies in this context. We evaluate the proposed inference strategies in the framework of the CoNLL-2005 shared task using only automatically-generated syntactic information. The extensive experimental evaluation and analysis indicates that all the proposed inference strategies are successful −they all outperform the current best results reported in the CoNLL-2005 evaluation exercise− but each of the proposed approaches has its a...
Mihai Surdeanu, Lluís Màrquez, Xavie
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2007
Where JAIR
Authors Mihai Surdeanu, Lluís Màrquez, Xavier Carreras, Pere Comas
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