Resumo

SELLAM, Rahma; DEFFAF, Fatima; SADAT, Fatiha  e  BELGUITH, Lamia Hadrich. Improved Statistical Machine Translation by Cross-Lingustic Projection of Named Entities Recognition and Translation. Comp. y Sist. [online]. 2015, vol.19, n.4, pp.701-711. ISSN 2007-9737.  https://doi.org/10.13053/CyS-19-4-2329.

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.

Palavras-chave : Named entity; pivot language; machine translation.

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