Paper: Shallow Semantic Parsing Using Support Vector Machines

ACL ID N04-1030
Title Shallow Semantic Parsing Using Support Vector Machines
Venue Human Language Technologies
Session Main Conference
Year 2004
Authors

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.