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.
Highlights
The interpretation of anaphoric pronouns has provided a puzzle for many decades of linguistic research
11The pointwise log predictive density is proportional to the MSE if the model is normal with constant variance, but it is appropriate for models that are not normally distributed (Gelman et al, 2013, ch. 7). 12The tabulated data can be found in Supplementary Material
The Expectancy model resolves the pronoun to the referent that is most expected; one of the functions of demonstrative pronouns is to highlight a less expected referent
Summary
The interpretation of anaphoric pronouns has provided a puzzle for many decades of linguistic research. Despite this ease of interpretation, it has proven difficult to accurately describe how pronouns are resolved It has, been possible to identify a range of individual factors which seem to influence resolution; for instance, there is evidence that referents mentioned from subject position are preferred to those mentioned from other positions (Crawley and Stevenson, 1990; Crawley et al, 1990; Gordon et al, 1993; Järvikivi et al, 2005); that referents mentioned first are preferred to those mentioned later (Clark and Sengul, 1979; Gernsbacher and Hargreaves, 1988; Järvikivi et al, 2005); that referents with an agentive thematic role are preferred to those with a patient thematic role (Stevenson et al, 1994; Schumacher et al, 2016); that referents which are topics are preferred to Bayesian Model for German Pronouns non-topics (e.g., Grosz et al, 1995). The way in which individual factors work together, allowing the addressee to identify the correct referent, is still debated
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