The structure of situation models as revealed by anaphor resolution. (March 2019)

• Record Type: Journal Article
• Authors: Varma, Sashank; Janssen, Amanda
• Is Part Of: Language sciences. Volume 72(2019)
• Page Start: 104
• Page End: 115
• Publication Date: 2019-03
• Subjects: Situation models -- Anaphor resolution -- Exemplar models -- Space -- Time -- Semantics; Linguistics -- Periodicals; Language and languages -- Periodicals; Linguistique -- Périodiques; Langage et langues -- Périodiques; Language and languages; Linguistics; Periodicals; Electronic journals; 405
• DOI: 10.1016/j.langsci.2018.09.002
• Languages: English
• ISSNs: 0388-0001

Abstract

Abstract: This paper investigates the structure of situation models as revealed by the process of anaphor resolution. The situation model for a text combines the meanings of its individual sentences with inferences generated from prior knowledge into an overall understanding of the text. We conceptualize situation models as implemented by collections of traces in episodic long-term memory that are retrieved based on their similarity to cues in working memory. Traces encode both contextual (i.e., spatial and temporal) and semantic information, providing structure to situation models. Four predictions were derived regarding the retrieval of antecedent traces during anaphor resolution. Experiment 1 evaluated the contextual structure of situation models, finding evidence for temporal gradients but not spatial gradients. Experiment 2 evaluated their semantic structure, finding an interaction between (a) the semantic similarity of anaphors and antecedents and (b) the interference caused by non-antecedent referents. These findings have implications for the representation of space and time in situation models, the continuity of working memory and long-term memory, and the conceptualization of situation models. Highlights: Anaphor resolution is used to investigate the structure of situation models. Temporal (not spatial) overlap between anaphors and antecedents speeds resolution. Semantic overlap also speeds resolution. By contrast, semantic interference from non-antecedents slows resolution.