Integrating linguistic patterns and term-entity associations in Chinese person description extraction

Sujian Li, Wenjie Li, Qin Lu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Person description extraction is an important task in biography generation, question answering and summarization. Most previous extraction approaches select descriptive passages depending on sentence structure and/or word co-occurrence information. In this paper, we focus on Chinese person description extraction verification by measuring the associations between the recognized person entities and the surrounding terms, called Term-Entity associations. The associations are derived from both the semantic knowledge provided in a Chinese well-known thesaurus HowNet and the term distributional information gathered from the news corpus. Relying on Term-Entity associations, the ineligible extracted descriptions could be filtered out so that the higher precision could be achieved in turn. As far as we know, no work on Chinese person description extraction has been reported in the literature.
Original languageEnglish
Title of host publicationIEEE NLP-KE 2007 - Proceedings of International Conference on Natural Language Processing and Knowledge Engineering
Pages301-307
Number of pages7
DOIs
Publication statusPublished - 1 Dec 2007
EventInternational Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE 2007 - Beijing, China
Duration: 30 Aug 20071 Sep 2007

Conference

ConferenceInternational Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE 2007
CountryChina
CityBeijing
Period30/08/071/09/07

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Information Systems and Management

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