Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
csv
Sub-tasks:
multi-input-text-classification
Languages:
French
Size:
1K - 10K
License:
Update README.md
Browse files
README.md
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The task of automatic detection of contradictions between sentences is a sentence-pair binary classification task. It can be viewed as a task related to both natural language inference task and misinformation detection task.
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### Languages
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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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- `id`: Index number.
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| Climate change | 49 | 63 |
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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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#### Who are the source language producers?
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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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## 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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### Licensing Information
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### Citation Information
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**BibTeX:**
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### Acknowledgements
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This work was 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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The task of automatic detection of contradictions between sentences is a sentence-pair binary classification task. It can be viewed as a task related to both natural language inference task and misinformation detection task.
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## Dataset Structure
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### Data Fields
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- `id`: Index number.
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| Covid-19 | 251 | 199 |
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| Climate change | 49 | 63 |
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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 work was 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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