Paper: Acquiring Knowledge from the Web to be used as Selectors for Noun Sense Disambiguation

ACL ID W08-2114
Title Acquiring Knowledge from the Web to be used as Selectors for Noun Sense Disambiguation
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2008
Authors

This paper presents a method of acquiring knowledge from the Web for noun sense disambiguation. Words, called selectors, are acquired which take the place of an instance of a target word in its local con- text. The selectors serve for the system to essentially learn the areas or concepts of WordNet that the sense of a target word should be a part of. The correct sense is chosen based on a combination of the strength given from similarity and related- ness measures over WordNet and the prob- ability of a selector occurring within the lo- cal context. Our method is evaluated using the coarse-grained all-words task from Se- mEval 2007. Experiments reveal that path- based similarity measures perform just as well as information content similarity mea- sures within our system. Overall, the re- s...