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Memorias de investigación
Communications at congresses:
Combining statistical and semantic approaches to the translation of ontologies and taxonomies
Year:2011
Research Areas
  • Computer systems
Information
Abstract
Ontologies and taxonomies are widely used to organize concepts providing the basis for activities such as indexing, and as background knowledge for NLP tasks. As such, translation of these resources would prove useful to adapt these systems to new languages. However, we show that the nature of these resources is significantly different from the ?free-text? paradigm used to train most statistical machine translation systems. In particular, we see significant differences in the linguistic nature of these resources and such resources have rich additional semantics. We demonstrate that as a result of these linguistic differences, standard SMT methods, in particular evaluation metrics, can produce poor performance. We then look to the task of leveraging these semantics for translation, which we approach in three ways: by adapting the translation system to the domain of the resource; by examining if semantics can help to predict the syntactic structure used in translation; and by evaluating if we can use existing translated taxonomies to disambiguate translations. We present some early results from these experiments, which shed light on the degree of success we may have with each approach.
International
Si
Congress
SSST-5 Fifth Workshop on Syntax, Semantics and Structure in Statistical Translation
960
Place
Portland, Oregon, USA
Reviewers
Si
ISBN/ISSN
978-1-932432-99-2
Start Date
23/06/2011
End Date
23/06/2011
From page
116
To page
125
Proceedings of SSST-5, Fifth Workshop on Syntax, Semantics and Structure in Statistical Translation
Participants
  • Autor: J. McCrae
  • Autor: M. Espinoza
  • Autor: Elena Montiel Ponsoda (UPM)
  • Autor: Guadalupe Aguado De Cea (UPM)
  • Autor: P. Cimiano
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Ontology Engineering Group
  • Departamento: Inteligencia Artificial
  • Departamento: Lingüistica Aplicada a la ciencia y a la Tecnología
S2i 2019 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)