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On the Road to High-Quality POS-Tagging

Identifieur interne : 000783 ( Main/Exploration ); précédent : 000782; suivant : 000784

On the Road to High-Quality POS-Tagging

Auteurs : Stefan Klatt [Autriche] ; Karel Oliva [Autriche]

Source :

RBID : ISTEX:5F3C89AF47F7CE4A0237477CB6CE8F582A8DE3D9

Abstract

Abstract: In this paper, we present techniques aimed at avoiding typical errors of state-of-the-art POS-taggers and at constructing high-quality POS-taggers with extremely low error rates. Such taggers are very helpful, if not even necessary, for many NLP applications organized in a pipeline architecture. The appropriateness of the suggested solutions is demonstrated in several experiments. Although these experiments were performed only with German data, the proposed modular architecture is applicable for many other languages, too.

Url:
DOI: 10.1007/11551263_31


Affiliations:


Links toward previous steps (curation, corpus...)


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