Update README.md

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.
 
-### Languages
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 ## Dataset Structure
 
-### Data Instances
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 ### Data Fields
 
 - `pair_ID`: Sentence pair ID.
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 The dataset was machine translated from English to French using the latest neural machine translation [opus-mt-tc-big](https://huggingface.co/Helsinki-NLP/opus-mt-tc-big-en-fr) model available for French. 
 The translation of the sentences was carried out on November 26th, 2023.
 
-### Curation Rationale
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-### Source Data
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-#### Initial Data Collection and Normalization
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-#### Who are the source language producers?
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-### Annotations
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-#### Annotation process
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-#### Who are the annotators?
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-### Personal and Sensitive Information
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-## Considerations for Using the Data
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-### Social Impact of Dataset
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-### Discussion of Biases
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-### Other Known Limitations
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 ## Additional Information
 
-### Dataset Curators
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-### Licensing Information
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 ### Citation Information
 
 **BibTeX:**
@@ -192,8 +134,4 @@ Jörg Tiedemann and Santhosh Thottingal. 2020. [OPUS-MT – Building open transl
 
 ### Acknowledgements
 
-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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+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.