Investigating fragment usage with a gamified utterance selection task

Nonsentential utterances, or fragments, like A coffee, please! can often be used to communicate a propositional meaning otherwise encoded by a complete sentence I'd like to order a coffee, please!). Previous research focused mostly on the syntax and licensing of fragments, but the questions of why speakers use fragments and how listeners interpret them are still underexplored. I propose a simple game-theoretic account of fragment usage, which predicts that (i) listeners assign fragments the most likely interpretation in context and (ii) that speakers are aware of this and trade-off production cost and the risk of being misunderstood when choosing their utterance. Using a corpus of production data, empirically founded and precise model predictions are generated. These predictions are evaluated with two experiments using a novel gamified utterance selection paradigm. The experiments suggest that, as predicted, speakers take into account both potential gain in efficiency and the risk of being misunderstood when choosing their utterance.

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Publication Details

Journal
Experiments in Linguistic Meaning
Published
2025-01-27
DOI
https://doi.org/10.3765/elm.3.5836
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
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article

Investigating fragment usage with a gamified utterance selection task

Robin Lemke
1 links
Experiments in Linguistic Meaning
Topic Modeling
article

Investigating fragment usage with a gamified utterance selection task

Robin Lemke
article en

Abstract

Nonsentential utterances, or fragments, like A coffee, please! can often be used to communicate a propositional meaning otherwise encoded by a complete sentence I'd like to order a coffee, please!). Previous research focused mostly on the syntax and licensing of fragments, but the questions of why speakers use fragments and how listeners interpret them are still underexplored. I propose a simple game-theoretic account of fragment usage, which predicts that (i) listeners assign fragments the most likely interpretation in context and (ii) that speakers are aware of this and trade-off production cost and the risk of being misunderstood when choosing their utterance. Using a corpus of production data, empirically founded and precise model predictions are generated. These predictions are evaluated with two experiments using a novel gamified utterance selection paradigm. The experiments suggest that, as predicted, speakers take into account both potential gain in efficiency and the risk of being misunderstood when choosing their utterance.

Experiments in Linguistic MeaningVol. 3
Saarland University (DE)
Openalex Percentile: Top 99%
Topic Modeling
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Investigating fragment usage with a gamified utterance selection task — Robin Lemke · Experiments in Linguistic Meaning (2025) | TGRS Research Map | TGRS