Memorias de investigación
Ponencias en congresos:
Combining statistical and semantic approaches to the translation of ontologies and taxonomies
Año:2011
Áreas de investigación
  • Informática
Datos
Descripción
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.
Internacional
Si
Nombre congreso
SSST-5 Fifth Workshop on Syntax, Semantics and Structure in Statistical Translation
Tipo de participación
960
Lugar del congreso
Portland, Oregon, USA
Revisores
Si
ISBN o ISSN
978-1-932432-99-2
DOI
Fecha inicio congreso
23/06/2011
Fecha fin congreso
23/06/2011
Desde la página
116
Hasta la página
125
Título de las actas
Proceedings of SSST-5, Fifth Workshop on Syntax, Semantics and Structure in Statistical Translation
Esta actividad pertenece a memorias de investigación
Participantes
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Ontology Engineering Group
  • Departamento: Inteligencia Artificial
  • Departamento: Lingüistica Aplicada a la ciencia y a la Tecnología