You are here

Relation Classification for Semantic Structure Annotation of Text

TitleRelation Classification for Semantic Structure Annotation of Text
Publication TypeConference Paper
Year of Publication2008
AuthorsYan, Y, Matsuo, Y, Ishizuka, M, Yokoi, T
Conference NameIEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology
PublisherIEEE Computer Society
Conference LocationToronto, Canada
ISBN Number978-0-7695-3496-1
Abstract

Confronting the challenges of annotating naturally occurring text into a semantically structured form to facilitate automatic information extraction, current Semantic Role Labeling (SRL) systems have been specifically examining a semantic predicate-argument structure. Based on the Concept Description Language for Natural Language (CDL.nl) which is intended to describe the concept structure of text using a set of pre-defined semantic relations, we develop a parser to add a new layer of semantic annotation of natural language sentences as an extension of SRL. With the assumption that all relation instances are detected, we present a relation classification approach facing the challenges of CDL.nl relation extraction. Preliminary evaluation on a manual dataset, using Support Vector Machine, shows that CDL.nl relations can be classified with good performance.

URLhttp://www.miv.t.u-tokyo.ac.jp/papers/yulan-WI08.pdf
DOI10.1109/WIIAT.2008.128