RTV: tree kernels for thematic role classification

Authors:
Daniele Pighin;Alessandro Moschitti;Roberto Basili
Affiliations:
University of Trento;University of Trento;University of Rome Tor Vergata
Venue:
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Year:
2007

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Abstract

We present a simple, two-steps supervised strategy for the identification and classification of thematic roles in natural language texts. We employ no external source of information but automatic parse trees of the input sentences. We use a few attribute-value features and tree kernel functions applied to specialized structured features. The resulting system has an F1 of 75.44 on the SemEval2007 closed task on semantic role labeling.