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Type of publication: Straipsnis recenzuojamoje užsienio tarptautinės konferencijos medžiagoje / Article in peer-reviewed foreign international conference proceedings (P1d)
Field of Science: Informatika / Informatics (N009)
Author(s): Kapočiūtė-Dzikienė, Jurgita;Nøklestad, Anders;Johannessen, Janne Bondi;Krupavičius, Algis
Title: Exploring features for named entity recognition in Lithuanian text corpus
Is part of: NODALIDA 2013 : proceedings of the 19th Nordic conference of computational linguistics, May 22–24, 2013, Oslo university, Norway / eds. Stephan Oepen, Kristin Hagen, Janne Bondi Johannessen. Linköping : Linköping University Electronic Press, 2013
Extent: p. 73-88
Date: 2013
Series/Report no.: (NEALT Proceedings, Vol. 16 1650-3740)
Note: ISSN (print): 1650-3686
Keywords: Named entity recognition;Named entity classification;Supervised machine learning;Lithuanian language
ISBN: 9789175195896
Abstract: Despite the existence of effective methods that solve named entity recognition tasks for such widely used languages as English, there is no clear answer which methods are the most suitable for languages that are substantially different. In this paper we attempt to solve a named entity recognition task for Lithuanian, using a supervised machine learning approach and exploring different sets of features in terms of orthographic and grammatical information, different windows, etc. Although the performance is significantly higher when language dependent features based on gazetteer lookup and automatic grammatical tools (part-of-speech tagger, lemmatizer or stemmer) are taken into account; we demonstrate that the performance does not degrade when features based on grammatical tools are replaced with affix information only. The best results (micro-averaged F-score=0.895) were obtained using all available features, but the results decreased by only 0.002 when features based on grammatical tools were omitted
Affiliation(s): Kauno technologijos universitetas
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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