Centering: a framework for modeling the local coherence of discourse
Computational Linguistics
Japanese discourse and the process of centering
Computational Linguistics
Functional centering: grounding referential coherence in information structure
Computational Linguistics
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
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
Centering: A Parametric Theory and Its Instantiations
Computational Linguistics
Anaphora resolution by antecedent identification followed by anaphoricity determination
ACM Transactions on Asian Language Information Processing (TALIP)
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Game theory and discourse anaphora
Journal of Logic, Language and Information
System for supporting web-based public debate using transcripts of face-to-face meeting
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
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Referential coherence represents the smoothness of discourse resulting from topic continuity and pronominalization. Rational individuals prefer a referentially coherent structure of discourse when they select a language expression and its interpretation. This is a preference for cooperation in communication. By what principle do they share coherent expressions and interpretations? Centering theory is the standard theory of referential coherence [Grosz et al. 1995]. Although it is well designed on the bases of first-order inference rules [Joshi and Kuhn 1979], it does not embody a behavioral principle for the cooperation evident in communication. Hasida [1996] proposed a game-theoretic hypothesis in relation to this issue. We aim to empirically verify Hasida's hypothesis by using corpora of multiple languages. We statistically design language-dependent parameters by using a corpus of the target language. This statistical design enables us to objectively absorb language-specific differences and to verify the universality of Hasida's hypothesis by using corpora. We empirically verified our model by using large Japanese and English corpora. The result proves the language universality of the hypothesis.