A 'bag-of-arguments' mechanism for initial verb predictions

Wing-Yee Chow, Cybelle Smith, Ellen Lau, Colin Phillips

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.