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Communication Dans Un Congrès Année : 2014

Cross-Lingual Part-of-Speech Tagging through Ambiguous Learning

Résumé

When Part-of-Speech annotated data is scarce, e.g. for under-resourced languages, one can turn to cross-lingual transfer and crawled dictionaries to collect partially supervised data. We cast this problem in the framework of ambiguous learning and show how to learn an accurate history-based model. Experiments on ten languages show significant improvements over prior state of the art performance.
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Dates et versions

hal-01908356 , version 1 (19-12-2018)

Identifiants

  • HAL Id : hal-01908356 , version 1

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Guillaume Wisniewski, Nicolas Pécheux, Souhir Gahbiche-Braham, François Yvon. Cross-Lingual Part-of-Speech Tagging through Ambiguous Learning. Conference on Empirical Methods in Natural Language Processing, Oct 2014, Doha, Qatar. pp.1779 - 1785. ⟨hal-01908356⟩
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