Cross-lingual induction of selectional preferences with bilingual vector spaces

  • Authors:
  • Yves Peirsman;Sebastian Padó

  • Affiliations:
  • University of Leuven;University of Stuttgart

  • Venue:
  • HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
  • Year:
  • 2010

Quantified Score

Hi-index 0.02

Visualization

Abstract

We describe a cross-lingual method for the induction of selectional preferences for resource-poor languages, where no accurate monolingual models are available. The method uses bilingual vector spaces to "translate" foreign language predicate-argument structures into a resource-rich language like English. The only prerequisite for constructing the bilingual vector space is a large unparsed corpus in the resource-poor language, although the model can profit from (even noisy) syntactic knowledge. Our experiments show that the cross-lingual predictions correlate well with human ratings, clearly outperforming monolingual baseline models.