Relation classification for semantic structure annotation of text

Yulan Yan, Yutaka Matsuo, Mitsuru Ishizuka, Toshio Yokoi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings - 2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008
Pages377-380
Number of pages4
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008 - Sydney, NSW
Duration: 2008 Dec 92008 Dec 12

Other

Other2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008
CitySydney, NSW
Period08/12/908/12/12

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Electrical and Electronic Engineering

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  • Cite this

    Yan, Y., Matsuo, Y., Ishizuka, M., & Yokoi, T. (2008). Relation classification for semantic structure annotation of text. In Proceedings - 2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008 (pp. 377-380). [4740476] https://doi.org/10.1109/WIIAT.2008.128