Automatic Extraction of Systematic Polysemy Using Tree-cut

Author: Noriko Tomuro
Journal-ref: In Proceedings of the workshop on Syntactic and Semantic Complexity in Natural Language Processing Systems at Language Technology Joint Conference, Applied Natural Language Processing and the North American Chapter of the Association for Computational Linguistics (ANLP-NAACL2000)

Abstract

This paper describes an automatic method for extracting systematic polysemy from a hierarchically organized semantic lexicon (WordNet). Systematic polysemy is a set of word senses that are related in systematic and predictable ways. Our method uses a modification of a tree generalization technique used in (Li and Abe, 1998), and generates a tree-cut, which is a list of clusters that partition a tree. We compare the systematic relations extracted by our automatic method to manually extracted WordNet cousins.

Paper: Full paper (postscript 600k)