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

In predicate-argument structure analysis, it is important to capture non-local dependencies among arguments and interdependencies between the sense of a predicate and the semantic roles of its arguments. However, no existing approach explicitly handles both non-local dependencies and semantic dependencies between predicates and arguments. In this paper we propose a structured model that overcomes the limitation of existing approaches; the model captures both types of dependencies simultaneously by introducing four types of factors including a global factor type capturing non-local dependencies among arguments and a pairwise factor type capturing local dependencies between a predicate and an argument. In experiments the proposed model achieved competitive results compared to the stateof-the-art systems without applying any feature selection procedure.

• Type: Journal
• Year: 2010
• Where: ACL
• Authors: Yotaro Watanabe, Masayuki Asahara, Yuji Matsumoto
• Keywords: ACL 2010, Computational Linguistics, Factor Type, Non-local Dependencies, Semantic Dependencies