Paper: Solving Relational Similarity Problems Using the Web as a Corpus

ACL ID P08-1052
Title Solving Relational Similarity Problems Using the Web as a Corpus
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2008
Authors
  • Preslav Nakov (University of California at Berkeley, Berkeley CA; Bulgarian Academy of Sciences, Bulgaria)
  • Marti A. Hearst (University of California at Berkeley, Berkeley CA)

We present a simple linguistically-motivated method for characterizing the semantic rela- tions that hold between two nouns. The ap- proach leverages the vast size of the Web in order to build lexically-specific features. The main idea is to look for verbs, preposi- tions, and coordinating conjunctions that can help make explicit the hidden relations be- tween the target nouns. Using these fea- tures in instance-based classifiers, we demon- strate state-of-the-art results on various rela- tional similarity problems, including mapping noun-modifier pairs to abstract relations like TIME, LOCATION and CONTAINER, charac- terizing noun-noun compounds in terms of ab- stract linguistic predicates like CAUSE, USE, and FROM, classifying the relations between nominals in context, and solving SAT ver...