Quantifying the role of discourse topicality in speakers' choices of referring expressions

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Abstract

The salience of an entity in the discourse is correlated with the type of referring expression that speakers use to refer to that entity. Speakers tend to use pronouns to refer to salient entities, whereas they use lexical noun phrases to refer to less salient entities. We propose a novel approach to formalize the interaction between salience and choices of referring expressions using topic modeling, focusing specifically on the notion of topicality. We show that topic models can capture the observation that topical referents are more likely to be pronominalized. This lends support to theories of discourse salience that appeal to latent topic representations and suggests that topic models can capture aspects of speakers' cognitive representations of entities in the discourse.

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Orita, N., Vornov, E., Feldman, N. H., & Boyd-Graber, J. (2014). Quantifying the role of discourse topicality in speakers’ choices of referring expressions. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 63–70). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/w14-2008

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