The interplay of content and context is observable in a moment to moment manner as propositional content unfolds. The current contribution illustrates this through data from real-time language comprehension indicating that propositional content is not computed in isolation but relies in important ways on context during every step of the computation of meaning. The relevant notion of context that we have to adopt includes all aspects of possible worlds and draws on a variety of knowledge representations, which in a first (...) processing phase serve to generate expectations for upcoming words. In a second phase, the discourse representation is assessed and if necessary updated by means of inferential reasoning and enrichment to reflect the speaker’s intended meaning. (shrink)

Bringing together different theoretical frameworks, the volume provides thought-provoking discussions of how the notion of context can be understood, modeled, and implemented in linguistics.

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 ∝ PP. 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. (shrink)