A machine learning approach to coreference resolution of noun phrases
Computational Linguistics - Special issue on computational anaphora resolution
A model-theoretic coreference scoring scheme
MUC6 '95 Proceedings of the 6th conference on Message understanding
Resolving pronominal reference to abstract entities
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Improving machine learning approaches to coreference resolution
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Improving pronoun resolution by incorporating coreferential information of candidates
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
A study on convolution kernels for shallow semantic parsing
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Kernel-based pronoun resolution with structured syntactic knowledge
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Unrestricted Coreference: Identifying Entities and Events in OntoNotes
ICSC '07 Proceedings of the International Conference on Semantic Computing
A twin-candidate model for learning-based anaphora resolution
Computational Linguistics
Graph-cut-based anaphoricity determination for coreference resolution
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Resolving event noun phrases to their verbal mentions
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Dependency-driven anaphoricity determination for coreference resolution
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
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Event anaphora resolution plays a critical role in discourse analysis. This paper proposes a tree kernel-based framework for event pronoun resolution. In particular, a new tree expansion scheme is introduced to automatically determine a proper parse tree structure for event pronoun resolution by considering various kinds of competitive information related with the anaphor and the antecedent candidate. Evaluation on the OntoNotes English corpus shows the appropriateness of the tree kernel-based framework and the effectiveness of competitive information for event pronoun resolution.