Improved Statistical Machine Translation by Cross-Lingustic Projection of Named Entities Recognition and Translation

• Autores: Rahma Sellami, Fatima Deffaf, Fatiha Sadat, Lamia Hadrich Belguith
• Localización: Computación y Sistemas (CyS), ISSN 1405-5546, ISSN-e 2007-9737, Vol. 19, Nº. 4, 2015, págs. 701-711
• Idioma: inglés
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  • Abstract: One of the existing difficulties in natural language processing applications is the lack of appropritate tools for the recognition, translation, and/or transliteration of named entities (NEs), specifically for less- resourced languages. In this paper, we propose a new method to automatically label multilingual parallel data for Arabic-French pair of languages with named entity tags and build lexicons of those named entities with their transliteration and/or translation in the target language. For this purpose, we bring in a third well-resourced language, English, that might serve as pivot, in order to build an Arabic-French NE Translation lexicon. Evaluations on the Arabic-French pair of languages using English as pivot in the transitive model showed the effectiveness of the proposed method for mining Arabic- French named entities and their translations. Moreover, the integration of this component in statistical machine translation outperformed the baseline system.