Shallow semantic parsing using support vector machines. Pradhan, S., Ward, W., Hacioglu, K., Martin, J., H., & Jurafsky, D. Baseline, Association for Computational Linguistics, 2004.
Shallow semantic parsing using support vector machines [pdf]Paper  Shallow semantic parsing using support vector machines [pdf]Website  abstract   bibtex   
In this paper, we propose a machine learning al- gorithm for shallow semantic parsing, extend- ing the work of Gildea and Jurafsky (2002), Surdeanu et al. (2003) and others. Our al- gorithm is based on Support Vector Machines which we show give an improvement in perfor- mance over earlier classifiers. We show perfor- mance improvements through a number of new features and measure their ability to general- ize to a new test set drawn from the AQUAINT corpus.

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