Abstract

Many studies have explored the effects of single-word contexts on visual word recognition, and several models have been proposed to account for the results obtained. However, relatively little is known about the effects of sentence contexts. In the experiment reported, the contexts consisted of sentences with the final word deleted, and subjects made word-nonword (lexical) decisions on target strings of letters. Norms were collected to determine the most common completion for each sentence frame. The experiment yielded three main findings: (1) Lexical decisions were fastest for words that were the most common completions; (2) among words not given as completions in the norming procedure, decisions were faster for words related to the most common completions than for words unrelated to the most common completions; t3t also among words that were not produced as completions, decisions were faster for words that formed acceptable completions than for words that did not. These relatedness and sentence-acceptability effects were independent, so that the relatedness effect held even when the target words formed anomalous sentence completions. In order to account for these results, a model combining two types of processes is required. In the model described, schematic knowledge (Rumelhart & Ortony, 1977) operates upon a semantic network to activate particular nodes, and this activation spreads to related concepts as in the Collins and Loftus (1975) model.

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