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Type of publication: Straipsnis konferencijos medžiagoje Clarivate Analytics Web of Science ar/ir Scopus / Article in Clarivate Analytics Web of Science or Scopus DB conference proceedings (P1a)
Field of Science: Informatika / Informatics (N009)
Author(s): Boizou, Loic;Kapočiūtė-Dzikienė, Jurgita;Rimkutė, Erika
Title: Deeper error analysis of Lithuanian morphological analyzers
Is part of: Human language technologies - the Baltic perspective: proceedings of the 8th international conference, Baltic HLT, Tartu, Estonia, 27-29 September 2018 / editors K. Muischnek and K. Müürisep. Amsterdam : IOS Press, 2018
Extent: p. 18-25
Date: 2018
Series/Report no.: (Frontiers in artificial intelligence and applications, Vol. 307 0922-6389)
Note: Knygos ISBN 978-1-61499-912-6 (online)
Keywords: Lithuanian language;Morphological analyzers-lemmatizers;
ISBN: 9781614999119
Abstract: In this research we continue the intrinsic evaluation of two the most popular and publicly available Lithuanian morphological analyzers-lemmatizers Lemuoklis and In our previous paper [1] we reported the comparative results of the shallow morphological analysis mostly covering coarse-grained part-of-speech tags. The results were better for on 3 domains (administrative, fiction and periodicals), but not on the scientific texts. The deeper analysis of the fine-grained morphological categories (case, gender, number, degree, tense, mood, person, and voice) gave a more precise account of the strengths and weaknesses of both analyzers. Further investigations showed that the higher performance of Lemuoklis analyzer on the scientific domain is probably related to a more successful analyse of long distance agreements, in a spite of an overall slight superiority of analyzer
Affiliation(s): Lituanistikos katedra
Taikomosios informatikos katedra
Užsienio kalbų, lit. ir vert. s. katedra
Vytauto Didžiojo universitetas
Appears in Collections:3. Konferencijų medžiaga / Conference materials
Universiteto mokslo publikacijos / University Research Publications

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