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A key assumption in language comprehension is that biases in behavioral data, such as the tendency to interpret John said that Mary left yesterday to mean that yesterday modifies the syntactically local verb left, not the distant verb said, reflect inherent biases in the language comprehension system. In the present article, an alternative production-distribution-comprehension (PDC) account is pursued; this account states that comprehension biases emerge from different interpretation frequencies in the language, which themselves emerge from pressures on the language production system to produce some structures more than others. In two corpus analyses and two self-paced reading experiments, we investigated these claims for verb modification ambiguities, for which phrase length is hypothesized to shape production. The results support claims that tendencies to produce short phrases before long ones create distributional regularities for modification ambiguities in the language and that learning over these regularities shapes comprehenders' interpretations of modification ambiguities. Implications for the PDC and other accounts are discussed.

Two experiments investigated the relation between individual differences in working memory capacity and differences in the efficiency of syntactic processing. In one experiment, readers comprehended sentences containing main-verb/reduced-relative ambiguities that all resolved to the reduced-relative interpretation. High-span (but not low-span) readers processed sentences more slowly when the sentences were biased to the preferred, main-verb interpretation than when they were biased to the reduced-relative interpretation. Moreover, high-span (but not low-span) readers used information about the plausibility of the different interpretations even though low-span readers appeared to possess the requisite knowledge. In Experiment 2, readers received intensive exposure to sentences with main-verb/reduced-relative ambiguities. Exposure enhanced low-span readers' use of plausibility information. Moreover, the effect of exposure generalized to sentences that were not included in the training materials.

Contains fulltext : 55261.pdf (Publisher’s version ) (Closed access) We present a computational model that provides a unified account of inference, coherence, and disambiguation. It simulates how the build-up of coherence in text leads to the knowledge-based resolution of referential ambiguity. Possible interpretations of an ambiguity are represented by centers of gravity in a high-dimensional space. The unresolved ambiguity forms a vector in the same space. This vector is attracted by the centers of gravity, while also being affected by context information and world knowledge. When the vector reaches one of the centers of gravity, the ambiguity is resolved to the corresponding interpretation. The model accounts for reading time and error rate data from experiments on ambiguous pronoun resolution and explains the effects of context informativeness, anaphor type, and processing depth. It shows how implicit causality can have an early effect during reading. A novel prediction is that ambiguities can remain unresolved if there is insufficient disambiguating information. 16 p.