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README.md
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test.json contains samples hand-selected to evaluate the quality of models.
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train.json contains synthetic samples generated in various ways
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The purpose of creating the dataset was to test an internal spellchecker for [a generative poetry project](https://github.com/Koziev/verslibre), but it can also be useful in other projects, since it does not have an explicit specialization for poetry.
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You can consider this dataset as an extension of [RuCOLA](https://huggingface.co/datasets/RussianNLP/rucola)
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In addition, for some samples there is a corrected version of the text ("fixed_sentence" field), so it can be used as an extension of datasets in [ai-forever/spellcheck_benchmark](https://huggingface.co/datasets/ai-forever/spellcheck_benchmark).
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### Example
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### Statistics
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Domains:
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prose
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poetry 609
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Violation categories:
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Misspelling
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Syntax
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Semantics
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test.json contains samples hand-selected to evaluate the quality of models.
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train.json contains synthetic samples generated in various ways.
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The purpose of creating the dataset was to test an internal spellchecker for [a generative poetry project](https://github.com/Koziev/verslibre), but it can also be useful in other projects, since it does not have an explicit specialization for poetry.
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You can consider this dataset as an extension of [RuCOLA](https://huggingface.co/datasets/RussianNLP/rucola).
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In addition, for some samples there is a corrected version of the text ("fixed_sentence" field), so it can be used as an extension of datasets in [ai-forever/spellcheck_benchmark](https://huggingface.co/datasets/ai-forever/spellcheck_benchmark).
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### Example
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### Statistics
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Total number of samples in test split: **5829**
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Total number of samples in train split: **435538**
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Statistics for test split.
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Domains:
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prose 5220
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poetry 609
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Violation categories:
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Misspelling 3266
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Syntax 2555
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Semantics 8
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