A central question for psycholinguistics concerns the role of grammatical constraints in online sentence processing. Many current theories maintain that the language processing mechanism constructs a parse or parses that are grammatically consistent with the whole of the perceived input each time it processes a word. Several bottom-up, dynamical models make a contrasting prediction: partial parses which are syntactically compatible with only a proper subpart of the input are sometimes constructed, at least temporarily. Three self-paced reading experiments probed for interference from such locally coherent structures. The first tested for a distracting effect of irrelevant Subject–Predicate interpretations of Noun Phrase–Verb Phrase sequences (e.g., The coach smiled at the player tossed a frisbee) on reading times. The second addressed the question of whether the interference effects can be treated as lexical interference, instead of involving the formation of locally coherent syntactic structures. The third replicated the reading time effects of the first two experiments with grammaticality judgments. We evaluate the dynamical account, comparing it to other approaches that also predict effects of local coherence, and arguing against accounts which rule out the formation of merely locally coherent structures.

A fundamental goal of psycholinguistic research is to understand the architectures and mechanisms that underlie language comprehension. Such an account entails an understanding of the representation and organization of linguistic knowledge in the mind and a theory of how that knowledge is used dynamically to recover the interpretation of the utterances we encounter. While research in theoretical and computational linguistics has demonstrated the tremendous complexities of language understanding, our intuitive experience of language is rather different. For the most part people understand the utterances they encounter effortlessly and accurately. In constructing models of how people comprehend language, we are thus presented with what we dub the performance paradox: How is it that people understand language so effectively given such complexity and ambiguity? In our pursuit and evaluation of new theories, we typically consider how well a particular model is able to account for observed results from the relevant range of controlled psycholinguistic experiments (empirical adequacy), and also the ability of the model to explain why the language comprehension system has the form and function it does (explanatory adequacy). Interestingly, research over the past twenty-five years has led to tremendous variety in proposals for parsing, disambiguation, and reanalysis mechanisms, many of which have been realized as computational models. However, while it is possible to classify models – e.g., according to whether they are modular, interactive, serial, parallel, or probabilistic – consensus at any concrete level has been largely

This article deals with gradience in human sentence processing. We review the experimental evidence for the role of experience in guiding the decisions of the sentence processor. Based on this evidence, we argue that the gradient behavior observed in the processing of certain syntactic constructions can be traced back to the amount of past experience that the processor has had with these constructions. In modeling terms, linguistic experience can be approximated using large, balanced corpora. We give an overview of corpus-based and probabilistic models in the literature that have exploited this fact, and hence are well placed to make gradient predictions about processing behavior. Finally, we discuss a number of questions regarding the relationship between gradience in sentence processing and gradient grammaticality, and come to the conclusion that these two phenomena should be treated separately in conceptual and modeling terms.

A central question for psycholinguistics concerns the role of grammatical constraints in online sentence processing. Many current theories maintain that, at each point in time, the processor constructs an analysis which is consistent with the grammatical information in the input. Several bottom-up, dynamical models make a contrasting prediction: partial parses which are syntactically incompatible with the current input can nevertheless temporarily influence the processor. Three self-paced reading experiments demonstrated the influence of such local structural ambiguities. The first examined