A corpus-based evaluation of centering and pronoun resolution
Computational Linguistics - Special issue on computational anaphora resolution
A machine learning approach to coreference resolution of noun phrases
Computational Linguistics - Special issue on computational anaphora resolution
A flexible architecture for reference resolution
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Anaphora for everyone: pronominal anaphora resoluation without a parser
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Analysis of syntax-based pronoun resolution methods
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Improving machine learning approaches to coreference resolution
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Applying Co-Training to reference resolution
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Coreference resolution using competition learning approach
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
An expectation maximization approach to pronoun resolution
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
JSAI'07 Proceedings of the 2007 conference on New frontiers in artificial intelligence
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Many reference resolution studies omit anaphoric forms found in quotations, assuming that they may need special handling as there is insufficient discourse context to determine the referent. This paper reports on an empirical study performed to evaluate this assumption. Specifically, the study addresses the following questions: Are anaphoric expressions found in quotations sufficiently different to justify ignoring them, and is there enough context available for a system to determine the referents of anaphoric expressions found within quoted text? The current study focuses on the pronoun it within the Givenness Hierarchy framework of Gundel, Hedberg, and Zacharski [13]. We find that this framework can be used in most cases to locate the antecedent for referential it found in quoted text.