A Bayesian Approach to German Personal and Demonstrative Pronouns

Clare Patterson, Petra B. Schumacher, Bruno Nicenboim, Johannes Hagen, Andrew Kehler

Research output: Contribution to journalArticleScientificpeer-review

6 Citations (Scopus)

Abstract

When faced with an ambiguous pronoun, an addressee must interpret it by identifying a suitable referent. It has been proposed that the interpretation of pronouns can be captured using Bayes’ Rule: P(referent|pronoun) ∝ P(pronoun|referent)P(referent). This approach has been successful in English and Mandarin Chinese. In this study, we further the cross-linguistic evidence for the Bayesian model by applying it to German personal and demonstrative pronouns, and provide novel quantitative support for the model by assessing model performance in a Bayesian statistical framework that allows implementation of a fully hierarchical structure, providing the most conservative estimates of uncertainty. Data from two story-continuation experiments showed that the Bayesian model overall made more accurate predictions for pronoun interpretation than production and next-mention biases separately. Furthermore, the model accounts for the demonstrative pronoun dieser as well as the personal pronoun, despite the demonstrative having different, and more rigid, resolution preferences.
Original languageEnglish
Article number672927
Pages (from-to)1-23
Number of pages23
JournalFrontiers in Psychology
Volume12
DOIs
Publication statusPublished - 3 Mar 2022

Keywords

  • Bayesian model
  • demonstratives
  • prominence
  • pronouns
  • reference

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