Combining Language Independent Part-of-Speech Tagging Tools

Authors György Orosz, László János Laki, Attila Novák, Borbála Siklósi

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György Orosz
László János Laki
Attila Novák
Borbála Siklósi

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György Orosz, László János Laki, Attila Novák, and Borbála Siklósi. Combining Language Independent Part-of-Speech Tagging Tools. In 2nd Symposium on Languages, Applications and Technologies. Open Access Series in Informatics (OASIcs), Volume 29, pp. 249-257, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)


Part-of-speech tagging is a fundamental task of natural language processing. For languages with a very rich agglutinating morphology, generic PoS tagging algorithms do not yield very high accuracy due to data sparseness issues. Though integrating a morphological analyzer can efficiently solve this problem, this is a resource-intensive solution. In this paper we show a method of combining language independent statistical solutions -- including a statistical machine translation tool -- of PoS-tagging to effectively boost tagging accuracy. Our experiments show that, using the same training set, our combination of language independent tools yield an accuracy that approaches that of a language dependent system with an integrated morphological analyzer.
  • part-of-speech tagging
  • combination
  • agglutinative languages
  • machine learning
  • machine translation


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