Composing and Updating Verb Argument Expectations: A Distributional Semantic Model
Alessandro Lenci · CINECA IRIS Institutial research information system (University of Pisa) · 2011
The aim of this paper is to present a computational model of the dynamic composition and update of verb argument expectations using Distributional Memory, a state-of-the-art framework for distributional semantics. The experimental results conducted on psycholinguistic data sets show that the model is able to successfully predict the changes on the patient argument thematic fit produced by different types of verb agents. 1