{"pk":26465,"title":"Bayesian Pronoun Interpretation in Mandarin Chinese","subtitle":null,"abstract":"Kehler and Rohde (2013) proposed a Bayesian theory of pro-noun interpretation where the influence of world knowledgeemerges as effects on the prior and the influence of informationstructure as effects on the likelihood: P(referent|pronoun) μP(pronoun|referent)P(referent). Here we present two experi-ments on Mandarin Chinese that allow us to test the generalityof the theory for a language with different syntactic-semanticassociations than English. Manipulations involving two dif-ferent classes of implicit-causality verbs and passive vs. activevoice confirmed key predictions of the Bayesian theory: effectsof these manipulations on the prior and likelihood in produc-tion were consistently reflected in pronoun interpretation pref-erences. Quantitative analysis shows that the Bayesian modelis the best fit for Mandarin compared to two competing anal-yses. These results lend both qualitative and quantitative sup-port to a cross linguistically general Bayesian theory of pro-noun interpretation.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"Bayesian modeling; pronoun interpretation; Man-darin Chinese"}],"section":"Papers","is_remote":true,"remote_url":"https://escholarship.org/uc/item/09q935qk","frozenauthors":[{"first_name":"Meilin","middle_name":"","last_name":"Zhan","name_suffix":"","institution":"University of California, San Diego","department":""},{"first_name":"Roger","middle_name":"P.","last_name":"Levy","name_suffix":"","institution":"University of California, San Diego ; Massachusetts Institute of Technology","department":""},{"first_name":"Andrew","middle_name":"","last_name":"Kehler","name_suffix":"","institution":"University of California, San Diego","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2016-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/26465/galley/16101/download/"}]}