Proceedings of the Annual Meeting of the Cognitive Science Society

This paper proposes a new model for human sentence processing which makes use of predictability of verbs from nouns for ambiguity resolution. The main claim is that verb distribution given a subject noun and an object noun varies depending on the animacy of the object noun, and that this variance influences the GP effect in Japanese. First, we report experimental results showing the asymmetry for the object-animacy in the GP effect, which cannot be explained in terms of semantic fitness, that is essential in constraint-based models. Then, we show, on the basis of a corpus analysis, that the difference of the object-animacy is related not to semantic fitness between nouns and verbs but to predictability of verbs from nouns. Finally, we propose our model of disambiguation using verb-predictability, and, based on this model, explain the asymmetry for the object-animacy observed in our experiment.