Paper: A Structured Model for Joint Learning of Argument Roles and Predicate Senses

ACL ID P10-2018
Title A Structured Model for Joint Learning of Argument Roles and Predicate Senses
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2010
Authors

In predicate-argument structure analysis, it is important to capture non-local de- pendencies among arguments and inter- dependencies between the sense of a pred- icate and the semantic roles of its argu- ments. However, no existing approach ex- plicitly handles both non-local dependen- cies and semantic dependencies between predicates and arguments. In this pa- per we propose a structured model that overcomes the limitation of existing ap- proaches; the model captures both types of dependencies simultaneously by introduc- ing four types of factors including a global factor type capturing non-local dependen- cies among arguments and a pairwise fac- tor type capturing local dependencies be- tween a predicate and an argument. In experiments the proposed model achieved competitive results com...