A POS-Tagger generator for unknown languages

• Autores: Nuno C. Marques, Gabriel Pereira Lopes
• Localización: Procesamiento del lenguaje natural, ISSN 1135-5948, Nº. 27, 2001 (Ejemplar dedicado a: XVII Congreso de la SEPLN: Sociedad Española para el Procesamiento del Lenguaje Natural: Universidad de Jaén, 12-14 septiembre 2001), págs. 199-206
• Idioma: español
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• Resumen

  • It is current belief that POS-taggers need huge amounts of hand tagged text for training (in the order of 10/5 pretagged words). In this paper we show how to generate POS-taggers trained with no more than 10/4 hand tagger words. These taggers achieve precision results that are as good as the best performant state-of-the-art POS-taggers. We overcome the huge training corpus problem by carefully combining a large lexicon with an efficient neural tagger. Experimental results are presented and discussed for the Susanne Corpus and three different Portuguese corpora. 96% precision rates are obtained when unknown words occur in the test set.