Paper: Corpus-Based Statistical Sense Resolution

ACL ID H93-1051
Title Corpus-Based Statistical Sense Resolution
Venue Human Language Technologies
Session Main Conference
Year 1993

The three corpus-based statistical sense resolution methods studied here attempt to infer the correct sense of a polyse- mous word by using knowledge about patterns of word co- occurrences. The techniques were based on Bayesian decision theory, neural networks, and content vectors as used in in- formation retrieval. To understand these methods better, we posed s very specific problem: given a set of contexts, each containing the noun line in a known sense, construct a classi- fier that selects the correct sense of line for new contexts. To see how the degree of polysemy affects performance, results from three- and slx-sense tasks are compared. The results demonstrate that each of the techniques is able to distinguish six senses of line with an accuracy greater than 70%. Furthermore, the re...