EESTI KEELE ÜHENDKORPUSTE SARI 2013–2021: MAHUKAIM EESTIKEELSETE DIGITEKSTIDE KOGU

The paper describes the Estonian National Corpus 2021 (Estonian NC 2021), the latest and the largest edition in the Estonian National Corpora series. The entire series of Estonian NC consists of four corpora: Estonian NC 2013, 2017, 2019 and 2021. The series was compiled by the Institute of the Esto...

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Bibliographic Details
Published inEesti Rakenduslingvistika Ühingu aastaraamat Vol. 18; no. 18; pp. 207 - 228
Main Authors Koppel, Kristina, Kallas, Jelena
Format Journal Article
LanguageEstonian
English
Published Eesti Rakenduslingvistika Ühing (ERÜ) 15.06.2022
Estonian Association for Applied Linguistics (EAAL)
Subjects
Computational linguistics
Finno-Ugrian studies
Lexis
Morphology
Philology
Present Times (2010 - today)
corpora
Estonian National Corpus
corpus lexicography
corpus query system
Estonian
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Summary:The paper describes the Estonian National Corpus 2021 (Estonian NC 2021), the latest and the largest edition in the Estonian National Corpora series. The entire series of Estonian NC consists of four corpora: Estonian NC 2013, 2017, 2019 and 2021. The series was compiled by the Institute of the Estonian Language in cooperation with the software company Lexical Computing Ltd. All corpora are accessible through the Sketch Engine interface, a corpus query system developed and maintained by Lexical Computing Ltd. The data are also stored in the repository Entu at Center of Estonian Language Resources. The Estonian National Corpus 2021 contains eleven sub-corpora (i.e. Web 2013, Web 2017, Web 2019, Web 2021, Feeds 2014-2021, Wikipedia 2021, Wikipedia Talk 2017, the Open Access Journals (DOAJ), Literature, the Balanced Corpus, and the Reference Corpus) totalling 2.4 billion words. In addition, the corpus is divided into genres and topics. The most extensive part of the Estonian NC 2021 is the Estonian Web Corpora, i.e. texts crawled from the web. In the paper, we outline the process of crawling the web, the process of cleaning and post-processing the crawled data, and the methodology for classifying web texts into genres and topics. We also introduce new tools for the analysis of corpus data in Sketch Engine, and suggest further perspectives and needs for corpus development.
ISSN:1736-2563
2228-0677
DOI:10.5128/ERYa18.12