Modeling Semantic Expectation: Using Script Knowledge for Referent Prediction

ACL 2017

Modeling Semantic Expectation: Using Script Knowledge for Referent Prediction

Jan 21, 2021
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Abstract: Recent research in psycholinguistics has provided increasing evidence that humans predict upcoming content. Prediction also affects perception and might be a key to robustness in human language processing. In this paper, we investigate the factors that affect human prediction by building a computational model that can predict upcoming discourse referents based on linguistic knowledge alone vs. linguistic knowledge jointly with common-sense knowledge in the form of scripts. We find that script knowledge significantly improves model estimates of human predictions. In a second study, we test the highly controversial hypothesis that predictability influences referring expression type but do not find evidence for such an effect. Authors: Ashutosh Modi, Ivan Titov, Vera Demberg, Asad Sayeed, Manfred Pinkal (Universitat des Saarlandes, University of Amsterdam)

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