Understanding the value of features for coreference resolution

Eric Bengtson, Dan Roth

Research output: Contribution to conferencePaper

Abstract

In recent years there has been substantial work on the important problem of coreference resolution, most of which has concentrated on the development of new models and algorithmic techniques. These works often show that complex models improve over a weak pairwise baseline. However, less attention has been given to the importance of selecting strong features to support learning a coreference model. This paper describes a rather simple pairwise classification model for coreference resolution, developed with a well-designed set of features. We show that this produces a state-of-the-art system that outperforms systems built with complex models. We suggest that our system can be used as a baseline for the development of more complex models - which may have less impact when a more robust set of features is used. The paper also presents an ablation study and discusses the relative contributions of various features.

Original languageEnglish (US)
Pages294-303
Number of pages10
DOIs
StatePublished - Jan 1 2008
Event2008 Conference on Empirical Methods in Natural Language Processing, EMNLP 2008, Co-located with AMTA 2008 and the International Workshop on Spoken Language Translation - Honolulu, HI, United States
Duration: Oct 25 2008Oct 27 2008

Other

Other2008 Conference on Empirical Methods in Natural Language Processing, EMNLP 2008, Co-located with AMTA 2008 and the International Workshop on Spoken Language Translation
CountryUnited States
CityHonolulu, HI
Period10/25/0810/27/08

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems

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    Bengtson, E., & Roth, D. (2008). Understanding the value of features for coreference resolution. 294-303. Paper presented at 2008 Conference on Empirical Methods in Natural Language Processing, EMNLP 2008, Co-located with AMTA 2008 and the International Workshop on Spoken Language Translation, Honolulu, HI, United States. https://doi.org/10.3115/1613715.1613756