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Automatic semantic role labelling using a memory-based learning system

Author:

Roser Morante

Abstract

In this paper we present a semantic role labelling system. The main component of the system is a memory-based classifier. The system has been trained with the Cast3LB-CoNLL-SemRol. The features encode information from dependency syntax. The results (F1 0.86) are comparable with state-of-the-art results (F1 around 0.86) from systems that use information from constituent syntax.

Full text (PDF | In Catalan)
How to Cite: Morante, R., (2008). Automatic semantic role labelling using a memory-based learning system. Digithum. (10). DOI: http://doi.org/10.7238/d.v0i10.504
Published on 28 Maig 2008.
Peer Reviewed

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