Abstract

This paper makes a very exploratory, tentative, and thinking-aloud kind of suggestion for the corpus-based analysis of alternation data. I start from the observation that studies of alternations/choices in particular in corpus linguistics have become increasingly sophisticated in terms of the statistical methods they employ and the number of predictors they involve. While the predictors employed come from many different levels of linguistic analysis – phonology, morphosyntax, semantics, pragmatics/ discoursal, textual, psycholinguistic, sociolinguistic, and others – they are usually contextual in nature, meaning they characterize the context of the choice the language user needs to make or has just made. However, one aspect of the context seems to be crucially underutilized when it comes to modeling speakers’ choices: the lexical context. In this paper, I build on recent work in computational psycholinguistics to: (a) define a lexical-distribution prototype of each of the (typically, but not necessarily, two) alternants of an alternation; and (b) compute the degree to which each instance of the alternation in question diverges from each of the prototypes. Then, (c) the values that all choices score on the divergences from each of the prototypes are entered as predictors to all others in statistical models to, minimally, serve as a variable that controls for whatever information is contained in the lexical context of an instance of speaker’s choice. I exemplify the approach and its sometimes amazing predictive power on the basis of a choice between near synonyms, two morphosyntactic alternations (preposition stranding vs. pied-piping and of- vs. s genitives), and a distinction between the functions of well.

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