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Modeling the Use of Frequency and Contextual Biases in Sentence Processing

Abstract

MacDonald, Pearlmutter, and Seidenberg (1993) propose an alternative to the dominant view in sentence processing that syntactic ambiguities are resolved by heuristics based on structural simplicity. MacDonald et al. argue that such ambiguities can be defined in terms of alternatives associated with information in individual lexical items, and thus that syntactic ambiguities can be resolved by lexical disambiguation mechanisms relying on access to the relative frequencies of alternatives and to biases created by contextual constraints. We present evidence from a computer simulation of the use of frequency-based and contextual constraints in the processing of the main verb/reduced relative syntactic ambiguity, showing that frequency and relatively limited contextual information from a sample of natural language can interact sufficiently to model basic results in the literature.

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