Good-Enough Representations in Language Comprehension

Abstract

People comprehend utterances rapidly and without conscious effort. Traditional theories assume that sentence processing is algorithmic and that meaning is derived compositionally. The language processor is believed to generate representations of the linguistic input that are complete, detailed, and accurate. However, recent findings challenge these assumptions. Investigations of the misinterpretation of both garden-path and passive sentences have yielded support for the idea that the meaning people obtain for a sentence is often not a reflection of its true content. Moreover, incorrect interpretations may persist even after syntactic reanalysis has taken place. Our good-enough approach to language comprehension holds that language processing is sometimes only partial and that semantic representations are often incomplete. Future work will elucidate the conditions under which sentence processing is simply good enough.