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Recent research in psycholinguistics has provided increasing evidence thathumans predict upcoming content. Prediction also affects perception and mightbe a key to robustness in human language processing. In this paper, weinvestigate the factors that affect human prediction by building acomputational model that can predict upcoming discourse referents based onlinguistic knowledge alone vs. linguistic knowledge jointly with common-senseknowledge in the form of scripts. We find that script knowledge significantlyimproves model estimates of human predictions. In a second study, we test thehighly controversial hypothesis that predictability influences referringexpression type but do not find evidence for such an effect.

Modeling Semantic Expectation: Using Script Knowledge for Referent Prediction