Datasets:
Update README.md
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README.md
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This dataset can be used for the task of Natural Language Inference (NLI), also known as Recognizing Textual Entailment (RTE), which is a sentence-pair classification task.
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### Languages
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[More Information Needed]
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## Dataset Structure
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### Data Instances
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[More Information Needed]
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### Data Fields
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- `premise`: The machine translated premise in the target language.
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|mnli_fr | 705 | 641 | 654 |
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## Dataset Creation
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### Curation Rationale
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[More Information Needed]
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### Source Data
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#### Initial Data Collection and Normalization
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[More Information Needed]
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#### Who are the source language producers?
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[More Information Needed]
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### Annotations
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#### Annotation process
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[More Information Needed]
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#### Who are the annotators?
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[More Information Needed]
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### Personal and Sensitive Information
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[More Information Needed]
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed]
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### Discussion of Biases
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[More Information Needed]
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### Other Known Limitations
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[More Information Needed]
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## Additional Information
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### Dataset Curators
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[More Information Needed]
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### Licensing Information
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[More Information Needed]
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### Citation Information
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**BibTeX:**
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### Acknowledgements
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This translation of the original dataset was done as part of a research project supported by the Defence Innovation Agency (AID) of the Directorate General of Armament (DGA) of the French Ministry of Armed Forces, and by the ICO, _Institut Cybersécurité Occitanie_, funded by Région Occitanie, France.
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### Contributions
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[More Information Needed]
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This dataset can be used for the task of Natural Language Inference (NLI), also known as Recognizing Textual Entailment (RTE), which is a sentence-pair classification task.
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## Dataset Structure
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### Data Fields
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- `premise`: The machine translated premise in the target language.
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|--------|---------:|------:|------------:|
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|mnli_fr | 705 | 641 | 654 |
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## Additional Information
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### Citation Information
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**BibTeX:**
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### Acknowledgements
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This translation of the original dataset was done as part of a research project supported by the Defence Innovation Agency (AID) of the Directorate General of Armament (DGA) of the French Ministry of Armed Forces, and by the ICO, _Institut Cybersécurité Occitanie_, funded by Région Occitanie, France.
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