An algorithm for pronominal anaphora resolution
Computational Linguistics
Centering: a framework for modeling the local coherence of discourse
Computational Linguistics
The nature of statistical learning theory
The nature of statistical learning theory
Cogniac: a discourse processing engine
Cogniac: a discourse processing engine
A machine learning approach to coreference resolution of noun phrases
Computational Linguistics - Special issue on computational anaphora resolution
A centering approach to pronouns
ACL '87 Proceedings of the 25th annual meeting on Association for Computational Linguistics
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
Corpus-based identification of non-anaphoric noun phrases
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Identifying anaphoric and non-anaphoric noun phrases to improve coreference resolution
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Improving machine learning approaches to coreference resolution
ACL '02 Proceedings of the 40th 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
Coreference resolution using competition learning approach
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
High-precision identification of discourse new and unique noun phrases
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 2
Combining sample selection and error-driven pruning for machine learning of coreference rules
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Japanese dependency analysis using cascaded chunking
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
ANARESOLUTION '97 Proceedings of a Workshop on Operational Factors in Practical, Robust Anaphora Resolution for Unrestricted Texts
Using decision trees for conference resolution
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
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)
ACM Transactions on Speech and Language Processing (TSLP)
Annotating a Japanese text corpus with predicate-argument and coreference relations
LAW '07 Proceedings of the Linguistic Annotation Workshop
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
Incorporating extra-linguistic information into reference resolution in collaborative task dialogue
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Identification of non-referential zero pronouns for Korean-English machine translation
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
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We propose a machine learning-based approach to noun-phrase anaphora resolution that combines the advantages of previous learning-based models while overcoming their drawbacks. Our anaphora resolution process reverses the order of the steps in the classification-then-search model proposed by Ng and Cardie [2002b], inheriting all the advantages of that model. We conducted experiments on resolving noun-phrase anaphora in Japanese. The results show that with the selection-then-classification-based modifications, our proposed model outperforms earlier learning-based approaches.