Using Verb Subcategorization for Word Sense Disambiguation
We develop a model for predicting verb sense from subcategorization information and integrate it into SSI-Dijkstra, a wide-coverage knowledge-based WSD algorithm. Adding syntactic knowledge in this way should correct the current poor performance of WSD systems on verbs. This paper also presents, for the first time, an evaluation of SSI-Dijkstra on a standard data set which enables a comparison of this algorithm with other knowledge-based WSD systems. Our results show that our system is competitive with current graph-based WSD algorithms, and that the subcategorization model can be used to achieve better verb sense disambiguation performance.
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