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URN: urn:nbn:de:0030-drops-40441
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Combining Language Independent Part-of-Speech Tagging Tools

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Abstract

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.

BibTeX - Entry

@InProceedings{orosz_et_al:OASIcs:2013:4044,
  author =	{Gy{\"o}rgy  Orosz and L{\'a}szl{\'o} J{\'a}nos  Laki and Attila  Nov{\'a}k and Borb{\'a}la  Sikl{\'o}si},
  title =	{{Combining Language Independent Part-of-Speech Tagging Tools}},
  booktitle =	{2nd Symposium on Languages, Applications and Technologies},
  pages =	{249--257},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-52-1},
  ISSN =	{2190-6807},
  year =	{2013},
  volume =	{29},
  editor =	{Jos{\'e} Paulo Leal and Ricardo Rocha and Alberto Sim{\~o}es},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2013/4044},
  URN =		{urn:nbn:de:0030-drops-40441},
  doi =		{10.4230/OASIcs.SLATE.2013.249},
  annote =	{Keywords: part-of-speech tagging, combination, agglutinative languages, machine learning, machine translation}
}

Keywords: part-of-speech tagging, combination, agglutinative languages, machine learning, machine translation
Seminar: 2nd Symposium on Languages, Applications and Technologies
Issue date: 2013
Date of publication: 2013


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