How statistical correlations influence discourse-level processing: Clause type as a cue for discourse relations

Marian Marchal*, Merel C. J. Scholman, Vera Demberg

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Linguistic phenomena (e.g., words and syntactic structure) co-occur with a wide variety of meanings. These systematic correlations can help readers to interpret a text and create predictions about upcoming material. However, to what extent these correlations influence discourse processing is still unknown. We address this question by examining whether clause type serves as a cue for discourse relations. We found that the co-occurrence of gerund-free adjuncts and specific discourse relations found in natural language is also reflected in readers' offline expectations for discourse relations. However, we also found that clause structure did not facilitate the online processing of these discourse relations, nor that readers have a preference for these relations in a paraphrase selection task. The present research extends previous research on discourse relation processing, which mostly focused on lexical cues, by examining the role of non-semantic cues. We show that readers are aware of correlations between clause structure and discourse relations in natural language, but that, unlike what has been found for lexical cues, this information does not seem to influence online processing and discourse interpretation.
Original languageEnglish
Pages (from-to)1-12
Number of pages13
JournalJournal of Experimental Psychology: Learning, Memory, and Cognition
DOIs
Publication statusPublished - Oct 2023
Externally publishedYes

Funding

This work was supported by the German Research Foundation (DFG)under Grant SFB 1102 ("Information Density and Linguistic Encoding,"Project-ID 232722074). The preregistered design of Experiment 1 is available athttps://osf.io/bkgf7, Experiment 2 athttps://osf.io/u3gvs, and Experiment 3 athttps://osf.io/cmf3s. All experimental materials, data, and analysis codes of all experiments reported in this study have been made publicly available athttps://osf.io/heqsu/(Marchal et al., 2023)

FundersFunder number
German Research Foundation (DFG)232722074

    Keywords

    • discourse signaling
    • prediction
    • discourse relations
    • clause structure
    • statistical co-occurrence

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