Improved Named Entity Recognition using Machine Translation-based Cross-lingual Information

• Autores: Sandipan Dandapat, Andy Way
• Localización: Computación y Sistemas (CyS), ISSN 1405-5546, ISSN-e 2007-9737, Vol. 20, Nº. 3, 2016, págs. 495-504
• Idioma: inglés
• DOI: 10.13053/cys-20-3-2468
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• Resumen

  • Abstract. In this paper, we describe a technique to improve named entity recognition in a resource-poor language (Hindi) by using cross-lingual information. We use an on-line machine translation system and a separate word alignment phase to find the projection of each Hindi word into the translated English sentence. We estimate the cross-lingual features using an English named entity recognizer and the alignment information. We use these cross-lingual features in a support vector machine-based classifier. The use of cross-lingual features improves F i score by 2.1 points absolute (2.9% relative) over a good-performing baseline model.

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