Unsupervised discovery of generic relationships using pattern clusters and its evaluation by automatically generated SAT analogy questions

Dmitry Davidov*, Ari Rappoport

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

48 Scopus citations

Abstract

We present a novel framework for the discovery and representation of general semantic relationships that hold between lexical items. We propose that each such relationship can be identified with a cluster of patterns that captures this relationship. We give a fully unsupervised algorithm for pattern cluster discovery, which searches, clusters and merges highfrequency words-based patterns around randomly selected hook words. Pattern clusters can be used to extract instances of the corresponding relationships. To assess the quality of discovered relationships, we use the pattern clusters to automatically generate SAT analogy questions. We also compare to a set of known relationships, achieving very good results in both methods. The evaluation (done in both English and Russian) substantiates the premise that our pattern clusters indeed reflect relationships perceived by humans.

Original languageAmerican English
Title of host publicationACL-08
Subtitle of host publicationHLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference
Pages692-700
Number of pages9
StatePublished - 2008
Event46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-08: HLT - Columbus, OH, United States
Duration: 15 Jun 200820 Jun 2008

Publication series

NameACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference

Conference

Conference46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-08: HLT
Country/TerritoryUnited States
CityColumbus, OH
Period15/06/0820/06/08

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