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The Importance of Syntactic Parsing and Inference in Semantic Role Labeling
We present a general framework for semantic role labeling. The framework combines a machine-learning technique with an integer linear programming-based inference procedure, which incorporatesExpand
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Generalized Inference with Multiple Semantic Role Labeling Systems
We present an approach to semantic role labeling (SRL) that takes the output of multiple argument classifiers and combines them into a coherent predicate-argument output by solving an optimizationExpand
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Semantic Role Labeling Via Integer Linear Programming Inference
We present a system for the semantic role labeling task. The system combines a machine learning technique with an inference procedure based on integer linear programming that supports theExpand
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A Learning Approach to Shallow Parsing
A SNoW based learning approach to shallow parsing tasks is presented and studied experimentally. The approach learns to identify syntactic patterns by combining simple predictors to produce aExpand
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Mapping Dependencies Trees: An Application to Question Answering
We describe an approach for answer selection in a free form question answering task. In order to go beyond the key-word based matching in selecting answers to questions, one would like to incorporateExpand
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The Use of Classifiers in Sequential Inference
We study the problem of combining the outcomes of several different classifiers in a way that provides a coherent inference that satisfies some constraints. In particular, we develop two generalExpand
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Learning and Inference over Constrained Output
We study learning structured output in a discriminative framework where values of the output variables are estimated by local classifiers. In this framework, complex dependencies among the outputExpand
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The Necessity of Syntactic Parsing for Semantic Role Labeling
We provide an experimental study of the role of syntactic parsing in semantic role labeling. Our conclusions demonstrate that syntactic parse information is clearly most relevant in the very firstExpand
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Applying System Combination to Base Noun Phrase Identification
We use seven machine learning algorithms for one task: identifying base noun phrases. The results have been processed by different system combination methods and all of these outperformed the bestExpand
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Semantic Role Labeling Via Generalized Inference Over Classifiers
Abstract : We present a system submitted to the CoNLL-2004 shared task for semantic role labeling. The system is composed of a set of classifiers and an inference procedure used both to clean theExpand
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