A Japanese Predicate Argument Structure Analysis using Decision Lists

This paper describes a new automatic method for Japanese predicate argument structure analysis. The method learns relevant features to assign case roles to the argument of the target predicate using the features of the words located closest to the target predicate under various constraints such as dependency types, words, semantic categories, parts of speech, functional words and predicate voices. We constructed decision lists in which these features were sorted by their learned weights. Using our method, we integrated the tasks of semantic role labeling and zero-pronoun identification, and achieved a 17% improvement compared with a baseline method in a sentence level performance analysis.

• Type: Conference
• Year: 2008
• Where: EMNLP
• Authors: Hirotoshi Taira, Sanae Fujita, Masaaki Nagata
• Keywords: EMNLP 2008, Japanese Predicate Argument, Natural Language Processing, Semantic Role Labeling, Target Predicate