Partial Truths: Adults Choose to Mention Agents and Patients in Proportion to Informativity, Even If It Doesn’t Fully Disambiguate the Message
Author(s)
Kline, Melissa; Schulz, Laura E; Gibson, Edward A
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How do we decide what to say to ensure our meanings will be understood? The Rational Speech Act model (RSA; Frank & Goodman, 2012 ) asserts that speakers plan what to say by comparing the informativity of words in a particular context. We present the first example of an RSA model of sentence-level (who-did-what-to-whom) meanings. In these contexts, the set of possible messages must be abstracted from entities in common ground (people and objects) to possible events (Jane eats the apple, Marco peels the banana), with each word contributing unique semantic content. How do speakers accomplish the transformation from context to compositional, informative messages? In a communication game, participants described transitive events (e.g., Jane pets the dog), with only two words, in contexts where two words either were or were not enough to uniquely identify an event. Adults chose utterances matching the predictions of the RSA even when there was no possible fully “successful” utterance. Thus we show that adults’ communicative behavior can be described by a model that accommodates informativity in context, beyond the set of possible entities in common ground. This study provides the first evidence that adults’ language production is affected, at the level of argument structure, by the graded informativity of possible utterances in context, and suggests that full-blown natural speech may result from speakers who model and adapt to the listener’s needs.
Date issued
2017-12Department
Massachusetts Institute of Technology. Department of Brain and Cognitive SciencesJournal
Open Mind
Publisher
MIT Press
Citation
Kline, Melissa et al. "Partial Truths: Adults Choose to Mention Agents and Patients in Proportion to Informativity, Even If It Doesn’t Fully Disambiguate the Message." Open Mind 2, 1 (December 2017): 1-13 © 2017 Massachusetts Institute of Technology
Version: Final published version
ISSN
2470-2986