Centering: a framework for modeling the local coherence of discourse
Computational Linguistics
An empirical study on the generation of anaphora in Chinese
Computational Linguistics
Functional centering: grounding referential coherence in information structure
Computational Linguistics
A probabilistic genre-independent model of pronominalization
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
An integrated framework for text planning and pronominalisation
INLG '00 Proceedings of the first international conference on Natural language generation - Volume 14
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Pronominalization is an important component in generating a coherent text. In this paper, we identify features that influence pronominalization, and construct a pronoun generation model by using various machine learning techniques. The old entities, which are the target of pronominalization, are categorized into three types according to their tendency in attentional state: Cb and old-Cp derived from a Centering model, and the remaining old entities. We construct a pronoun generation model for each type. Eighty-seven texts are gathered from three genres for training and testing. Using this, we verify that our proposed features are well defined to explain pronominalization in Korean, and we also show that our model significantly outperforms previous ones with 99% confidence level by t-test. We also identify central features that have a strong influence on pronominalization across genres.