Bayesian Pronoun Interpretation in Mandarin Chinese


Kehler and Rohde (2013) proposed a Bayesian theory of pronoun interpretation where the influence of world knowledge emerges as effects on the prior and the influence of information structure as effects on the likelihood: P(referent|pronoun) ∝ P(pronoun|referent)P(referent). Here we present two experiments on Mandarin Chinese that allow us to test the generality of the theory for a language with different syntactic-semantic associations than English. Manipulations involving two different classes of implicit-causality verbs and passive vs. active voice confirmed key predictions of the Bayesian theory: effects of these manipulations on the prior and likelihood in production were consistently reflected in pronoun interpretation preferences. Quantitative analysis shows that the Bayesian model is the best fit for Mandarin compared to two competing analyses. These results lend both qualitative and quantitative support to a cross linguistically general Bayesian theory of pronoun interpretation.

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