LowResourceEval-2019: a shared task on morphological analysis for low-resource languages

Dialog 2019, Issue 18, Supplementary volume, Pp. 45-62 The paper describes the results of the first shared task on morphological analysis for the languages of Russia, namely, Evenki, Karelian, Selkup, and Veps. For the languages in question, only small-sized corpora are available. The tasks include...

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Main Authors Klyachko, Elena, Sorokin, Alexey, Krizhanovskaya, Natalia, Krizhanovsky, Andrew, Ryazanskaya, Galina
Format Journal Article
LanguageEnglish
Published 30.01.2020
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Computer Science - Computation and Language
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Abstract Dialog 2019, Issue 18, Supplementary volume, Pp. 45-62 The paper describes the results of the first shared task on morphological analysis for the languages of Russia, namely, Evenki, Karelian, Selkup, and Veps. For the languages in question, only small-sized corpora are available. The tasks include morphological analysis, word form generation and morpheme segmentation. Four teams participated in the shared task. Most of them use machine-learning approaches, outperforming the existing rule-based ones. The article describes the datasets prepared for the shared tasks and contains analysis of the participants' solutions. Language corpora having different formats were transformed into CONLL-U format. The universal format makes the datasets comparable to other language corpura and facilitates using them in other NLP tasks.
AbstractList Dialog 2019, Issue 18, Supplementary volume, Pp. 45-62 The paper describes the results of the first shared task on morphological analysis for the languages of Russia, namely, Evenki, Karelian, Selkup, and Veps. For the languages in question, only small-sized corpora are available. The tasks include morphological analysis, word form generation and morpheme segmentation. Four teams participated in the shared task. Most of them use machine-learning approaches, outperforming the existing rule-based ones. The article describes the datasets prepared for the shared tasks and contains analysis of the participants' solutions. Language corpora having different formats were transformed into CONLL-U format. The universal format makes the datasets comparable to other language corpura and facilitates using them in other NLP tasks.
Author Klyachko, Elena
Krizhanovskaya, Natalia
Sorokin, Alexey
Krizhanovsky, Andrew
Ryazanskaya, Galina
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Snippet Dialog 2019, Issue 18, Supplementary volume, Pp. 45-62 The paper describes the results of the first shared task on morphological analysis for the languages of...
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Title LowResourceEval-2019: a shared task on morphological analysis for low-resource languages
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