Using Verb Subcategorization for Word Sense Disambiguation
13889Authors
nan
Abstract
AbstractWe 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.
Keywords
Full Content
nan
Labeled Text
AbstractWe 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.
Publication Details
- Paper ID:
- 13889
- Year:
- 2012
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan