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AKCES-GEC Grammatical Error Correction Dataset for Czech
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Šebesta, Karel; Bedřichová, Zuzanna; Šormová, Kateřina; Štindlová, Barbora; Hrdlička, Milan; Hrdličková, Tereza; Hana, Jiří; Petkevič, Vladimír; Jelínek, Tomáš; Škodová, Svatava; Janeš, Petr; Lundáková, Kateřina; Skoumalová, Hana; Sládek, Šimon; Pierscieniak, Piotr; Toufarová, Dagmar; Straka, Milan; Rosen, Alexandr; Náplava, Jakub; Poláčková, Marie. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2019
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Abstract:
AKCES-GEC is a grammar error correction corpus for Czech generated from a subset of AKCES. It contains train, dev and test files annotated in M2 format. Note that in comparison to CZESL-GEC dataset, this dataset contains separated edits together with their type annotations in M2 format and also has two times more sentences. If you use this dataset, please use following citation: @article{naplava2019wnut, title={Grammatical Error Correction in Low-Resource Scenarios}, author={N{'a}plava, Jakub and Straka, Milan}, journal={arXiv preprint arXiv:1910.00353}, year={2019} }
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Keyword:
gec; grammatical error correction; natural language correction
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URL: http://hdl.handle.net/11234/1-3057
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Universal Dependencies 2.2
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In: https://hal.archives-ouvertes.fr/hal-01930733 ; 2018 (2018)
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Universal Dependencies 2.1
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In: https://hal.inria.fr/hal-01682188 ; 2017 (2017)
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