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Abstract

The presence of high quality Named Entity gazetteer within a CLIR system is crucial in order to provide multilingual access to digital resources, particularly in the domain of Digital Libraries. In our paper we investigate an approach for automatically extracting this kind of resources from Wikipedia using an unsupervised approach that leverages the DBpedia classification of the English articles in order to induce the same classification onto encyclopedia pages expressed in other languages. By exploiting the structured information present in Wikipedia we furthermore aim at enriching our standard gazetteer with translations to other languages as well as with the alternative spellings of the entities.

Keywords

Digital Library Machine Translation Search Query Statistical Machine Translation Entity Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Alessio Bosca
    • 1
  • Luca Dini
    • 1
  1. 1.CELI s.r.l.TorinoItaly

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