We describe a simple approach to word sensedisambiguation using information filtering andextraction. The method fully exploits and extends theinformation available in the Hector dictionary. Thealgorithm proceeds by the application of severalfilters to prune the candidate set of word sensesreturning the most frequent if more than one remains.The experimental methodology and its implication arealso discussed.