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dc.contributor.authorGraña Gil, Jorge
dc.contributor.authorBarcala Rodríguez, Francisco Mario
dc.contributor.authorVilares Ferro, Manuel
dc.date.accessioned2005-10-28T15:43:37Z
dc.date.available2005-10-28T15:43:37Z
dc.date.issued2002
dc.identifier.citationProceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing (CICLING-2002), Ciudad de Méjico (Méjico). Published in Lecture Notes in Computer Science, vol. 2276, pp. 240-249. Springer Verlag. Gelbukh, A. (ed.).es_ES
dc.identifier.isbn3-540-43219-1
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/2183/148
dc.description.abstract[Abstract] One of the most important prior tasks for robust part-of-speech tagging is the correct tokenization or segmentation of the texts. This task can involve processes which are much more complex than the simple identification of the diferent sentences in the text and each of their individual components, but it is often obviated in many current applications. Nevertheless, this preprocessing step is an indispensable task in practice, and it is particularly dificult to tackle it with scientific precision with-out falling repeatedly in the analysis of the specific casuistry of every phenomenon detected. In this work, we have developed a scheme of preprocessing oriented towards the disambiguation and robust tagging of Galician. Nevertheless, it is a proposal of a general architecture that can be applied to other languages, such as Spanish, with very slight modifications.es_ES
dc.description.sponsorshipEuropean Commission; 1FD97-0047-C04-02es_ES
dc.description.sponsorshipXunta de Galicia; PGIDT99XI10502B
dc.description.sponsorshipMinisterio de Educación y Ciencia; TIC2000-0370-C02-01
dc.format.mimetypeapplication/postscript
dc.format.mimetypetext/plain
dc.language.isoenges_ES
dc.publisherSpringer-Verlages_ES
dc.titleFormal methods of tokenization for part-of-speech tagginges_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES


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