Paper: Discovering Relations between Noun Categories

ACL ID D11-1134
Title Discovering Relations between Noun Categories
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2011

Traditional approaches to Relation Extraction from text require manually defining the rela- tions to be extracted. We propose here an ap- proach to automatically discovering relevant relations, given a large text corpus plus an ini- tial ontology defining hundreds of noun cate- gories (e.g., Athlete, Musician, Instrument). Our approach discovers frequently stated rela- tions between pairs of these categories, using a two step process. For each pair of categories (e.g., Musician and Instrument) it first co- clusters the text contexts that connect known instances of the two categories, generating a candidate relation for each resulting cluster. It then applies a trained classifier to determine which of these candidate relations is semanti- cally valid. Our experiments apply this...