Some experiments with a naive bayes WSD system

Abstract

This document describes the architecture of a WSD system that participated in the SENSEVAL-3 English all words evaluation exercise. The system uses two independent statistical models, one based on local collocations and another based on a bag of words around the target. The model w i t h the higher confidence provides the final answer for each instance. Both models use Naive Bayes and supervised training w i t h different feature sets. The experiments using this system indicate that the specific smoothing parameters used for Naive Bayes make a big impact on the performance, smaller context sizes give better accuracy, and that the bag of words model adds little to the performance.