Chinese pronominal anaphora resolution using lexical knowledge and entropy-based weight

Pronominal anaphors are commonly observed in written texts. In this article, effective Chinese pronominal anaphora resolution is addressed by using lexical knowledge acquisition and salience measurement. The lexical knowledge acquisition is aimed to extract more semantic features, such as gender, nu...

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Bibliographic Details
Published in:Journal of the American Society for Information Science and Technology 2008-11, Vol.59 (13), p.2138-2145
Main Authors: Wu, Dian-Song, Liang, Tyne
Format: Article
Language:English
Subjects:
Anaphora
Antecedents
Automatic text analysis
Chinese languages
Comparative analysis
Entropy
Exact sciences and technology
Feature extraction
Information and communication sciences
Information management
Information science. Documentation
Knowledge acquisition
Library and information science. General aspects
Natural language processing
Online information retrieval
Pronouns
Rule based
Salience
Sciences and techniques of general use
Semantic features
Semantics
Studies
Use and user studies. Information needs
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Summary:Pronominal anaphors are commonly observed in written texts. In this article, effective Chinese pronominal anaphora resolution is addressed by using lexical knowledge acquisition and salience measurement. The lexical knowledge acquisition is aimed to extract more semantic features, such as gender, number, and collocate compatibility by employing multiple resources. The presented salience measurement is based on entropy‐based weighting on selecting antecedent candidates. The resolution is justified with a real corpus and compared with a rule‐based model. Experimental results by five‐fold cross‐validation show that our approach yields 82.5% success rate on 1343 anaphoric instances. In comparison with a general rule‐based approach, the performance is improved by 7%.
ISSN:1532-2882
2330-1635
1532-2890
2330-1643
DOI:10.1002/asi.20922