Abstract
Recent research in sentence comprehension suggests that lexically specific information plays a key role in on-line syntactic ambiguity resolution. On the basis of an analysis of the local NP/S-ambiguity, the present study offers a corpus-based approach to sentence processing that supports this view. However, it is proposed that the relevant information used to recover the syntactic structure of an incoming string of words is not retrieved from individual verbs but from a more fine-grained level of form-meaning pairings that distinguishes different verb senses. The investigation proceeds in two steps: First, verb-general and sense-specific preferences for nominal and sentential complementation are induced from corpus data and compared using odds ratios as a measure of association. Second, correlation analyses are performed that relate the computed coeffcients of association to reading time latencies from a recent self-paced moving window experiment (Hare et al. 2003). The results corroborate the view that individual verb senses, rather than individual verbs, guide initial parsing decisions.
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