Towards Open-Domain Semantic Role Labeling
Danilo Croce, Cristina Giannone, Paolo Annesi, Roberto Basili · Cineca Institutional Research Information System (Tor Vergata University) · 2010
Current Semantic Role Labeling technologies are based on inductive algorithms trained over large scale repositories of annotated examples.Frame-based systems currently make use of the FrameNet database but fail to show suitable generalization capabilities in out-of-domain scenarios.In this paper, a state-of-art system for frame-based SRL is extended through the encapsulation of a distributional model of semantic similarity.The resulting argument classification model promotes a simpler feature space that limits the potential overfitting effects.The large scale empirical study here discussed confirms that state-of-art accuracy can be obtained for out-of-domain evaluations.