Skell corpora as a part of the language portal Sõnaveeb: Problems and perspectives

Kristina Koppel, Jelena Kallas, Maria Khokhlova, Vít Suchomel, Vít Baisa, Jan Michelfeit

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations

Abstract

The paper provides an analysis of the quality and presentation of authentic corpus sentences from Sketch Engine for Language Learning (SkELL) corpora (Baisa & Suchomel 2014), based on the example of Sõnaveeb (Wordweb), a new language portal being developed in the Institute of the Estonian Language. Currently Sõnaveeb contains a total of 150,000 Estonian headwords; about 70,000 of them have Russian equivalents. Authentic corpus sentences are displayed for both languages. In some cases (e.g. terms, derived forms, compounds and multi-word expressions), corpus sentences are the only source of usage examples that are available on the portal. We describe the parameters of Good Dictionary Examples (GDEX) (Kilgarriff et al., 2008) configurations for Estonian and for Russian used for the compilation of etSkELL 2018 and ruSkELL 1.6 corpora, give an overview of an evaluation of the GDEX configuration for Estonian, and outline the requirements for the user-friendly presentation of SkELL corpora as a part of the language portal.

Original languageEnglish
Pages (from-to)763-782
JournalProceedings of Electronic Lexicography in the 21st Century Conference
Volume2019-October
StatePublished - 1 Oct 2019
Event6th Biennial Conference on Electronic Lexicography in the 21st Century: Smart Lexicography, eLex 2019 - Sintra, Portugal
Duration: 1 Oct 20193 Oct 2019

Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language

Keywords

  • Estonian
  • GDEX
  • Learner corpus
  • Russian
  • SkELL

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