Semantic similarity, predictability, and models of sentence processing.

The effects of word predictability and shared semantic similarity between a target word and other words that could have taken its place in a sentence on language comprehension are investigated using data from a reading time study, a sentence completion study, and linear mixed-effects regression modeling. We find that processing is facilitated if the different possible words that could occur in a given context are semantically similar to each other, meaning that processing is affected not only by the nature of the words that do occur, but also the relationships between the words that do occur and those that could have occurred. We discuss possible causes of the semantic similarity effect and point to possible limitations of using probability as a model of cognitive effort.

Frequency of Basic English Grammatical Structures: A Corpus Analysis.

Many recent models of language comprehension have stressed the role of distributional frequencies in determining the relative accessibility or ease of processing associated with a particular lexical item or sentence structure. However, there exist relatively few comprehensive analyses of structural frequencies, and little consideration has been given to the appropriateness of using any particular set of corpus frequencies in modeling human language. We provide a comprehensive set of structural frequencies for a variety of written and spoken corpora, focusing on structures that have played a critical role in debates on normal psycholinguistics, aphasia, and child language acquisition, and compare our results with those from several recent papers to illustrate the implications and limitations of using corpus data in psycholinguistic research.

Why is that? Structural prediction and ambiguity resolution in a very large corpus of English sentences.

Previous psycholinguistic research has shown that a variety of contextual factors can influence the interpretation of syntactically ambiguous structures, but psycholinguistic experimentation inherently does not allow for the investigation of the role that these factors play in natural (uncontrolled) language use. We use regression modeling in conjunction with data from the British National Corpus to measure the amount and specificity of the information available for disambiguation in natural language use. We examine the Direct Object/Sentential Complement ambiguity and the closely related issue of complementizer use in sentential complements, and find that both ambiguity resolution and complementizer use can be predicted from contextual information.

Verb subcategorization frequencies: American English corpus data, methodological studies, and cross-corpus comparisons.

Verb subcategorization frequencies (verb biases) have been widely studied in psycholinguistics and play an important role in human sentence processing. Yet available resources on subcategorization frequencies suffer from limited coverage, limited ecological validity, and divergent coding criteria. Prior estimates of verb transitivity, for example, vary widely with corpus size, coverage, and coding criteria This article provides norming data for 281 verbs of interest to psycholinguistic research, sampled from a corpus of American English, along with a detailed coding manual.