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--- |
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license: cc-by-sa-4.0 |
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task_categories: |
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- text-classification |
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language: |
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- en |
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- es |
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- fr |
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- de |
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- zh |
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- ja |
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- ru |
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- ar |
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- hi |
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size_categories: |
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- 10K<n<100K |
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--- |
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# Incoherent Text Dataset |
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This dataset is designed for training models to detect incoherence in text. It includes various types of incoherence, such as grammatical errors, word soup, random words, and run-on sentences. |
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## Dataset Details |
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- **Languages:** English, Spanish, French, German, Chinese, Japanese, Russian, Arabic, Hindi |
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- **Size:** ~27,000 samples |
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- **Types of Incoherence:** Grammatical errors, word soup, random words, run-ons, random tokens, random bytes. |
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## Data Fields |
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- **text:** The text sample. |
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- **length:** The number of words in the text sample. |
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- **label:** Whether the text is "OK" (coherent) or "incoherent". |
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- **type:** The type of text (coherent or one of the incoherence types). |
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## Usage |
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This dataset can be used to train machine learning models for text classification tasks, specifically for detecting and categorizing different types of text incoherence. |
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## Limitations |
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The dataset has been generated by an algorithm, so care must be taken in evaluating it in the real world. More data may need to be collected before evaluating a model trained on this data in a real-world setting. |
