Paper: Classifying Semantic Relations In Bioscience Texts

ACL ID P04-1055
Title Classifying Semantic Relations In Bioscience Texts
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2004
Authors

A crucial step toward the goal of au- tomatic extraction of propositional in- formation from natural language text is the identification of semantic relations between constituents in sentences. We examine the problem of distinguishing among seven relation types that can oc- cur between the entities “treatment” and “disease” in bioscience text, and the problem of identifying such entities. We compare five generative graphical mod- els and a neural network, using lexical, syntactic, and semantic features, finding that the latter help achieve high classifi- cation accuracy.