Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Resolving pronominal reference to abstract entities
Resolving pronominal reference to abstract entities
A machine learning approach to coreference resolution of noun phrases
Computational Linguistics - Special issue on computational anaphora resolution
Getting at discourse referents
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
A machine learning approach to pronoun resolution in spoken dialogue
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Specialized models and ranking for coreference resolution
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Language Resources and Evaluation
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We annotate and resolve a particular case of abstract anaphora, namely, this-issue anaphora. We propose a candidate ranking model for this-issue anaphora resolution that explores different issue-specific and general abstract-anaphora features. The model is not restricted to nominal or verbal antecedents; rather, it is able to identify antecedents that are arbitrary spans of text. Our results show that (a) the model outperforms the strong adjacent-sentence baseline; (b) general abstract-anaphora features, as distinguished from issue-specific features, play a crucial role in this-issue anaphora resolution, suggesting that our approach can be generalized for other NPs such as this problem and this debate; and (c) it is possible to reduce the search space in order to improve performance.