Towards better language representation in Natural Language Processing A multilingual dataset for text-level Grammatical Error Correction
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11210%2F25%3A10513028" target="_blank" >RIV/00216208:11210/25:10513028 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11320/26:SHY6B8WN
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=uVkuQkp2Ul" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=uVkuQkp2Ul</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1075/ijlcr.24033.mas" target="_blank" >10.1075/ijlcr.24033.mas</a>
Alternative languages
Result language
angličtina
Original language name
Towards better language representation in Natural Language Processing A multilingual dataset for text-level Grammatical Error Correction
Original language description
This paper introduces MultiGEC, a dataset for multilingual Grammatical Error Correction (GEC) in twelve European languages: Czech, English, Estonian, German, Greek, Icelandic, Italian, Latvian, Russian, Slovene, Swedish and Ukrainian. MultiGEC distinguishes itself from previous G E C datasets in that it covers several underrepresented languages, which we argue should be included in resources used to train models for Natural Language Processing tasks which, as G E C itself, have implications for Learner Corpus Research and Second Language Acquisition. Aside from multilingualism, the novelty of the MultiGEC dataset is that it consists of full texts - typically learner essays - rather than individual sentences, making it possible to train systems that take a broader context into account. The dataset was built for MultiGEC-2025, the first shared task in multilingual text-level GEC, but it remains accessible after its competitive phase, serving as a resource to train new error correction systems and perform cross-lingual G E C studies.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
60203 - Linguistics
Result continuities
Project
<a href="/en/project/LM2023044" target="_blank" >LM2023044: Czech National Corpus</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Learner Corpus Research
ISSN
2215-1478
e-ISSN
2215-1486
Volume of the periodical
11
Issue of the periodical within the volume
2
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
27
Pages from-to
309-335
UT code for WoS article
001457603500001
EID of the result in the Scopus database
2-s2.0-105003035015