A “bag-of-arguments” mechanism for initial verb predictions
نویسندگان
چکیده
Previous studies have shown that comprehenders use rich contextual information to anticipate upcoming input on the fly, but less is known about how comprehenders integrate different sources of information to generate predictions in real time. The current study examines the time course with which the lexical meaning and structural roles of preverbal arguments impact comprehenders’ lexical semantic predictions about an upcoming verb in two event-related potential (ERP) experiments that use the N400 amplitude as a measure of online predictability. Experiment 1 showed that the N400 was sensitive to predictability when the verb’s cloze probability was reduced by substituting one of the arguments (e.g. “The superintendent overheard which tenant/realtor the landlord had evicted...”), but not when the verb’s cloze probability was reduced by simply swapping the roles of the arguments (e.g. “The restaurant owner forgot which customer/waitress the waitress/customer had served...”). Experiment 2 showed that argument substitution elicited an N400 effect even when the substituted argument appeared elsewhere in the sentence, indicating that verb predictions are specifically driven by the arguments in the same clause as the verb, rather than by a simple “bag-of-words” mechanism. We propose that verb predictions initially rely on a “bag-of-arguments” mechanism, which specifically relies on the lexical meaning, but not the structural roles, of the arguments in a clause. ARTICLE HISTORY Received 24 November 2014 Accepted 21 June 2015
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Prediction as Memory Retrieval: Timing and Mechanisms
In our target article [Chow, W., Smith, C., Lau, E., & Phillips, C. (2015), A “bag-of-arguments” mechanism for initial verb predictions, we investigated the predictions that comprehenders initially make about an upcoming verb as they read and provided evidence that they are sensitive to the arguments’ lexical meaning but not their structural roles. Here we synthesise findings from our work with...
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