Centering: a framework for modeling the local coherence of discourse
Computational Linguistics
Japanese discourse and the process of centering
Computational Linguistics
A machine learning approach to coreference resolution of noun phrases
Computational Linguistics - Special issue on computational anaphora resolution
An algorithm for anaphora resolution in Spanish texts
Computational Linguistics - Special issue on computational anaphora resolution
A property-sharing constraint in Centering
ACL '86 Proceedings of the 24th annual meeting on Association for Computational Linguistics
Evaluating automated and manual acquisition of anaphora resolution strategies
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Message Understanding Conference-6: a brief history
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Anaphora resolution of Japanese zero pronouns with deictic reference
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Zero pronoun resolution in Japanese discourse based on centering theory
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
An environment for extracting resolution rules of zero pronouns from corpora
Proceedings of the COLING-2000 Workshop on Semantic Annotation and Intelligent Content
Japanese zero pronoun resolution based on ranking rules and machine learning
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Exploiting syntactic patterns as clues in zero-anaphora resolution
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Zero-anaphora resolution by learning rich syntactic pattern features
ACM Transactions on Asian Language Information Processing (TALIP)
Zero-Anaphora Resolution in Chinese Using Maximum Entropy
IEICE - Transactions on Information and Systems
A fully-lexicalized probabilistic model for Japanese zero anaphora resolution
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Capturing salience with a trainable cache model for zero-anaphora resolution
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
A tree kernel-based unified framework for Chinese zero anaphora resolution
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Chasing the ghost: recovering empty categories in the Chinese treebank
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
A cross-lingual ILP solution to zero anaphora resolution
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
Incremental learning of transfer rules for customized machine translation
INAP'04/WLP'04 Proceedings of the 15th international conference on Applications of Declarative Programming and Knowledge Management, and 18th international conference on Workshop on Logic Programming
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This paper proposes a method to analyze Japanese anaphora, in which zero pronouns (omitted obligatory cases) are used to refer to preceding entities (antecedents). Unlike the case of general coreference resolution, zero pronouns have to be detected prior to resolution because they are not expressed in discourse. Our method integrates two probability parameters to perform zero pronoun detection and resolution in a single framework. The first parameter quantifies the degree to which a given case is a zero pronoun. The second parameter quantifies the degree to which a given entity is the antecedent for a detected zero pronoun. To compute these parameters efficiently, we use corpora with/without annotations of anaphoric relations. We show the effectiveness of our method by way of experiments.