2007 RobustIEWithPerceptrons

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Subject Headings: Relation Detection from Text Algorithm, ACE Benchmark Task, ACE-2007, Perceptron Algorithm


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We present a system for the extraction of entity and relation mentions. Our work focused on robustness and simplicity: all system components are modeled using variants of the Perceptron algorithm (Rosemblatt, 1958) and only partial syntactic information is used for feature extraction. Our approach has two novel ideas. First, we define a new large-margin Perceptron algorithm tailored for class-unbalanced data which dynamically adjusts its margins, according to the generalization performance of the model. Second, we propose a novel architecture that lets classification ambiguities flow through the system and solves them only at the end. The system achieves competitive accuracy on the ACE English EMD and RMD tasks.


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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2007 RobustIEWithPerceptronsMihai Surdeanu
Massimiliano Ciaramita
Robust Information Extraction with PerceptronsProceedings of NIST 2007 Automatic Content Extraction Workshophttp://research.yahoo.com/publication/robust information extraction with perceptrons2007