Semantic Role Assignment for Event Nominalisations by Leveraging Verbal Data

This paper presents a novel approach to the task of semantic role labelling for event nominalisations, which make up a considerable fraction of predicates in running text, but are underrepresented in terms of training data and difficult to model. We propose to address this situation by data expansion. We construct a model for nominal role labelling solely from verbal training data. The best quality results from salvaging grammatical features where applicable, and generalising over lexical heads otherwise.

• Type: Conference
• Year: 2008
• Where: COLING
• Authors: Sebastian Padó, Marco Pennacchiotti, Caroline Sporleder
• Keywords: COLING 2008, Computational Linguistics, Semantic Role Labelling, Training Data, Verbal Training Data