multiged-2023
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
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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
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Czech description
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Classification
Type
R - Software
CEP classification
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OECD FORD branch
60203 - Linguistics
Result continuities
Project
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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