Syntactic features for high precision word sense disambiguation

Authors:
David Martínez;Eneko Agirre;Lluís Màrquez
Affiliations:
University of the Basque Country, Donostia, Spain;University of the Basque Country, Donostia, Spain;Polytechnical University of Catalonia, Barcelona, Spain
Venue:
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Year:
2002

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Abstract

This paper explores the contribution of a broad range of syntactic features to WSD: grammatical relations coded as the presence of adjuncts/arguments in isolation or as subcategorization frames, and instantiated grammatical relations between words. We have tested the performance of syntactic features using two different ML algorithms (Decision Lists and AdaBoost) on the Senseval-2 data. Adding syntactic features to a basic set of traditional features improves performance, especially for AdaBoost. In addition, several methods to build arbitrarily high accuracy WSD systems are also tried, showing that syntactic features allow for a precision of 86% and a coverage of 26% or 95% precision and 8% coverage.