Classifying semantic relations in bioscience texts 论文

2004引用 260
Biomedical Text Mining and OntologiesTopic ModelingNatural Language Processing Techniques

详细信息

发表日期
2004-01-01
发表年份
2004

关键词

Biomedical Text Mining and OntologiesTopic ModelingNatural Language Processing Techniques

摘要

A crucial step toward the goal of automatic extraction of propositional information 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 occur between the entities "treatment" and "disease" in bioscience text, and the problem of identifying such entities. We compare five generative graphical models and a neural network, using lexical, syntactic, and semantic features, finding that the latter help achieve high classification accuracy.