A Public Reference Implementation of the RAP Anaphora Resolution Algorithm
Research Area: Natural Language Processing Year: 2004
Type of Publication: In Proceedings  
Authors:
  • Long Qiu
  • Min-Yen Kan
  • Tat-Seng Chua
 
Book title: Proceedings of the Language Resources and Evaluation Conference 2004 (LREC 04)
Address: Lisbon, Portugal
   
Note:
Poster: http://www.comp.nus.edu.sg/%7Ekanmy/papers/LREC04_NUSV6.png
Abstract:
This paper describes a standalone, publicly-available implementation of the Resolution of Anaphora Procedure (RAP) given by Lappin and Leass (1994). The RAP algorithm resolves third person pronouns, lexical anaphors, and identifies pleonastic pronouns. Our implementation, JavaRAP, fills a current need in anaphora resolution research by providing a reference implementation that can be benchmarked against current algorithms. The implementation uses the standard, publicly available Charniak (2000) parser as input, and generates a list of anaphora-antecedent pairs as output. Alternately, an in-place annotation or substitution of the anaphors with their antecedents can be produced. Evaluation on the MUC-6 co-reference task shows JavaRAP has an accuracy of 57.9%, similar to the performance given previously in the literature (e.g., Preiss 2002).
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