Hierarchical semantic role labeling

Abstract

We present a four-step hierarchical SRL strategy which generalizes the classical two-level approach (boundary detection and classification). To achieve this, we have split the classification step by grouping together roles which share linguistic properties (e.g. Core Roles versus Adjuncts). The results show that the nonoptimized hierarchical approach is computationally more efficient than the traditional systems and it preserves their accuracy. © 2005 Association for Computational Linguistics.