Semantic role assignment for event nominalisations by leveraging verbal data
Sebastian Padó, Marco Pennacchiotti, Caroline Sporleder · 2008
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.