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--- |
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license: cc-by-4.0 |
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language: |
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- fr |
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- en |
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- it |
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- de |
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task_categories: |
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- text-classification |
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task_ids: |
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- natural-language-inference |
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- multi-input-text-classification |
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size_categories: |
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- 1K<n<10K |
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--- |
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# Dataset Card for Dataset Name |
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## Dataset Description |
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- **Homepage:** |
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- **Repository:** https://github.com/mskandalis/rte3-french |
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- **Paper:** |
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- **Leaderboard:** |
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- **Point of Contact:** |
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### Dataset Summary |
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This repository contains all manually translated versions of RTE-3 dataset, plus the original English one. The languages into which RTE-3 dataset has so far been translated are Italian (2012), German (2013), and French (2023). |
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Unlike in other repositories, both our own French version and the older Italian and German ones are here annotated in 3 classes (entailment, neutral, contradiction), and not in 2 (entailment, not entailment). |
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If you want to use the dataset only in a specific language among those provided here, you can filter data by selecting only the language column value you wish. |
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### Supported Tasks and Leaderboards |
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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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- `id`: Index number. |
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- `language`: The language of the concerned pair of sentences. |
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- `premise`: The translated premise in the target language. |
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- `hypothesis`: The translated premise in the target language. |
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- `label`: The classification label, with possible values 0 (`entailment`), 1 (`neutral`), 2 (`contradiction`). |
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- `label_text`: The classification label, with possible values `entailment` (0), `neutral` (1), `contradiction` (2). |
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- `task`: The particular NLP task that the data was drawn from (IE, IR, QA and SUM). |
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- `length`: The length of the text of the pair. |
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### Data Splits |
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| name |development|test| |
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|-------------|----------:|---:| |
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|all_languages| 3200 |3200| |
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| fr | 800 | 800| |
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| de | 800 | 800| |
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| it | 800 | 800| |
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For French RTE-3: |
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| name |entailment|neutral|contradiction| |
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|-------------|---------:|------:|------------:| |
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| dev | 412 | 299 | 89 | |
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| test | 410 | 318 | 72 | |
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| name |short|long| |
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|-------------|----:|---:| |
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| dev | 665 | 135| |
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| test | 683 | 117| |
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| name | IE| IR| QA|SUM| |
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|-------------|--:|--:|--:|--:| |
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| dev |200|200|200|200| |
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| test |200|200|200|200| |
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## Additional Information |
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### Citation Information |
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**BibTeX:** |
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````BibTeX |
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@inproceedings{giampiccolo-etal-2007-third, |
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title = "The Third {PASCAL} Recognizing Textual Entailment Challenge", |
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author = "Giampiccolo, Danilo and |
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Magnini, Bernardo and |
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Dagan, Ido and |
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Dolan, Bill", |
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booktitle = "Proceedings of the {ACL}-{PASCAL} Workshop on Textual Entailment and Paraphrasing", |
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month = jun, |
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year = "2007", |
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address = "Prague", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/W07-1401", |
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pages = "1--9", |
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} |
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```` |
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**ACL:** |
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Danilo Giampiccolo, Bernardo Magnini, Ido Dagan, and Bill Dolan. 2007. [The Third PASCAL Recognizing Textual Entailment Challenge](https://aclanthology.org/W07-1401). In *Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing*, pages 1–9, Prague. Association for Computational Linguistics. |
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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. |
