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The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11210%2F23%3A10476292" target="_blank" >RIV/00216208:11210/23:10476292 - isvavai.cz</a>

  • Result on the web

    <a href="https://github.com/spraakbanken/multiged-2023" target="_blank" >https://github.com/spraakbanken/multiged-2023</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    multiged-2023

  • Original language description

    This corpus consists of texts written by non-native learners, used in the first shared task on Multilingual Grammatical Error Detection, MultiGED. We provide training, development and test data for each of the five languages: Czech, English, German, Italian and Swedish. Some of these datasets are already used in Grammatical Error Detection/Correction (GED/GEC) research, but we also release two new datasets: REALEC (English) and SweLL-gold (Swedish). Where possible, we use the same train/dev/test split as previous work (GECCC, FCE, Falko-MERLIN), and only create new splits when necessary (REALEC, MERLIN, SweLL). All datasets are derived from annotated second language learner essays.

  • Czech name

  • Czech description

Classification

  • Type

    R - Software

  • CEP classification

  • OECD FORD branch

    60203 - Linguistics

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Internal product ID

    multiged-2023

  • Technical parameters

    Asi 1,7 mil. tokenů v 6 jazycích

  • Economical parameters

    data pro shared task

  • Owner IČO

    00216208

  • Owner name

    Univerzita Karlova