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Korpusomat.eu: A Multilingual Platform for Building and Analysing Linguistic Corpora

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Computational Science – ICCS 2023 (ICCS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14074))

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Abstract

The paper presents Korpusomat, a new, free web-based platform for effortless building and analysing linguistic data sets (corpora). The aim of Korpusomat is to bridge the gap between corpus linguistics, which requires tools for corpus analysis based on various linguistic annotations, and modern multilingual machine learning-based approaches to text processing. A special focus is placed on multilinguality: the platform currently serves 29 languages, but more can be easily added per user request. We discuss the use of Korpusomat in multidisciplinary research, and present a case study located at the intersection between discourse analysis and migration studies, based on a corpus generated and queried in the application. This provides a general framework for using the platform for research based on automatically annotated corpora, and demonstrates the usefulness of Korpusomat for supporting domain researchers in using computational science in their fields.

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Notes

  1. 1.

    The version presented in this paper is available at https://korpusomat.eu.

  2. 2.

    This older version is still maintained and available at https://korpusomat.pl.

  3. 3.

    The Description of the Features, Including the Query Language, Is Available in the Documentation at https://korpusomat-eu.readthedocs.io/en/latest/.

  4. 4.

    A list of possible formats is available in the documentation at http://tika.apache.org/1.17/formats.html.

  5. 5.

    https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Asylum_statistics &oldid=558844.

  6. 6.

    The top countries of origin of asylum applicants (over 30 thousand applications) were: Syria, Afghanistan, Iraq, Iran, Pakistan, Nigeria, Albania, Eritrea, Russia, Bangladesh, Guinea, Sudan, Turkey, Ukraine, Somalia, Georgia, Ivory Coast, Gambia, Venezuela, Algeria, Mali, Morocco, and Senegal.

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Acknowledgements

This work was supported by the European Regional Development Fund as a part of 2014–2020 Smart Growth Operational Programme, CLARIN- Common Language Resources and Technology Infrastructure, project no. POIR.04.02.00-00C002/19 and by the project co-financed by the Minister of Education and Science under the agreement 2022/WK/09.

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Authors and Affiliations

  1. Institute of Computer Science, Polish Academy of Sciences, Jana Kazimierza 5, 01-248, Warszawa, Poland

    Karol Saputa, Aleksandra Tomaszewska, Natalia Zawadzka-Paluektau, Witold Kieraś & Łukasz Kobyliński

Authors
  1. Karol Saputa
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  2. Aleksandra Tomaszewska
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  3. Natalia Zawadzka-Paluektau
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  4. Witold Kieraś
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  5. Łukasz Kobyliński
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Corresponding author

Correspondence to Karol Saputa .

Editor information

Editors and Affiliations

  1. Czech Technical University in Prague, Prague, Czech Republic

    Jiří Mikyška

  2. University of Amsterdam, Amsterdam, The Netherlands

    Clélia de Mulatier

  3. AGH University of Science and Technology, Krakow, Poland

    Maciej Paszynski

  4. University of Amsterdam, Amsterdam, The Netherlands

    Valeria V. Krzhizhanovskaya

  5. University of Tennessee at Knoxville, Knoxville, TN, USA

    Jack J. Dongarra

  6. University of Amsterdam, Amsterdam, The Netherlands

    Peter M.A. Sloot

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Saputa, K., Tomaszewska, A., Zawadzka-Paluektau, N., Kieraś, W., Kobyliński, Ł. (2023). Korpusomat.eu: A Multilingual Platform for Building and Analysing Linguistic Corpora. In: Mikyška, J., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2023. ICCS 2023. Lecture Notes in Computer Science, vol 14074. Springer, Cham. https://doi.org/10.1007/978-3-031-36021-3_22

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  • DOI: https://doi.org/10.1007/978-3-031-36021-3_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-36020-6

  • Online ISBN: 978-3-031-36021-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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