A Joint Model of Implicit Arguments for Nominal Predicates

Matthew Gerber, Joyce Yue Chai, Robert Bart

Abstract: Many prior studies have investigated the recovery of semantic arguments for nominal predicates. The models in many of these studies have assumed that arguments are independent of each other. This assumption simplifies the computational modeling of semantic arguments, but it ignores the joint nature of natural language. This paper presents a preliminary investigation into the joint modeling of implicit arguments for nominal predicates. The joint model uses propositional knowledge extracted from millions of Internet webpages to help guide prediction.