Pronominalization and Expectations for Re-Mention: Modeling Coreference in Contexts With Three Referents

The relationship between pronoun production and pronoun interpretation has been proposed to follow Bayesian principles, combining a comprehender's expectation about which referent will be mentioned next and their estimate of how likely it is that a potential referent will be re-mentioned using a pronoun. The Bayesian model has received support from studies in several languages (English, Mandarin Chinese, Catalan, German), but tested contexts have been limited to two event participants, whereas natural language discourse often involves contexts with more than two event participants. In this study, we conducted three story continuation experiments to assess how the Bayesian model performs in more complex contexts. Our results show that even in contexts with three event participants, comprehenders can behave rationally when interpreting pronouns, but that they appear to require sufficient context to build up a coherent representation of the situation to do so. In addition to testing the basic claim of the Bayesian Model (Weak Bayes), we test the central prediction of the Strong form of the hypothesis: that the two components of the model (next-mention expectations and choice of referring expression) are influenced by dissociated sets of factors. Our experiments do not find any evidence that the predictability of a referent affects pronominalization rates, which corroborates Strong Bayes. Finally, we test whether the existence of additional event participants reduces the overall rate of pronominalization and find that participants produce fewer ambiguous than unambiguous pronouns, but that the effect of ambiguity on pronominalization was very small.