While the general knowledge of the world plays a role in language use, language processing in humans is also guided by formal intuitions about linguistic representation. Understanding the interaction between world knowledge and formal representation in processing at the sentence level is the central theme of my most recent work. In this talk, I discuss research results in finding the boundaries between world knowledge and formalism-driven intuitions and situate them in the context of a larger research program in computational psycholinguistics.

My research focuses on the semantics of predicates and their argument and how they are interpreted by the human parser. English-speaking human raters judge doctors as more appropriate givers of advice than recipients and lunches as much more appropriate objects of "eat" than subjects.I discuss my recent successes in building large-scale computational models of predicate-argument "thematic fit" ratings, using vector-space and neural network techniques. 

English-speakers also tend to judge that the sentence "every child climbed a tree" refers to more than one tree, while "every jeweler appraised a diamond" is comparatively more likely to refer to a single diamond, based on their knowledge of trees and diamonds.