Three Algorithms for Competence-Oriented Anaphor Resolution

  • In the last decade, much effort went into the design of robust third-person pronominal anaphor resolution algorithms. Typical approaches are reported to achieve an accuracy of 60-85%. Recent research addresses the question of how to deal with the remaining difficult-toresolve anaphors. Lappin (2004) proposes a sequenced model of anaphor resolution according to which a cascade of processing modules employing knowledge and inferencing techniques of increasing complexity should be applied. The individual modules should only deal with and, hence, recognize the subset of anaphors for which they are competent. It will be shown that the problem of focusing on the competence cases is equivalent to the problem of giving precision precedence over recall. Three systems for high precision robust knowledge-poor anaphor resolution will be designed and compared: a ruleset-based approach, a salience threshold approach, and a machine-learning-based approach. According to corpus-based evaluation, there is no unique best approach. Which approach scores highest depends upon type of pronominal anaphor as well as upon text genre.

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Author:Roland Stuckardt
Parent Title (German):Proc. 5th Discourse Anaphora and Anaphor Resolution Colloquium (DAARC04), São Miguel/Azores, Sept. 2004
Document Type:Conference Proceeding
Date of Publication (online):2005/07/27
Year of first Publication:2004
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2005/07/27
GND Keyword:Textanalyse ; Linguistische Datenverarbeitung; Computerlinguistik
Page Number:7
Source:Publ in: Proc. 5th Discourse Anaphora and Anaphor Resolution Colloquium (DAARC04), São Miguel/Azores, Sept. 2004, 157-163 ,
Institutes:Informatik und Mathematik / Informatik
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):License LogoDeutsches Urheberrecht