
# Dataset Card for Dataset Name

## Dataset Description

- **Homepage:** 
- **Repository:** https://github.com/mskandalis/rte3-french
- **Paper:** 
- **Leaderboard:** 
- **Point of Contact:** 

### Dataset Summary

The RTE3-FR dataset is the French translation of the Textual Entailment English dataset used in the [RTE-3 Challenge](https://nlp.stanford.edu/RTE3-pilot/). 

Like its English counterpart, the French RTE-3 dataset is composed of a development set and a test set, each containing 800 T/H pairs. 
All T/H pairs were manually translated into French and proofread.

It is annotated for a 3-way task.

### Supported Tasks and Leaderboards

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.

## Dataset Structure

### Data Fields

- `id`: Index number.
- `language`: The language of the concerned pair of sentences.
- `premise`: The translated premise in the target language.
- `hypothesis`: The translated premise in the target language.
- `label`: The classification label, with possible values 0 (`entailment`), 1 (`neutral`), 2 (`contradiction`).
- `label_text`: The classification label, with possible values `entailment` (0), `neutral` (1), `contradiction` (2).
- `task`: The particular NLP task that the data was drawn from (IE, IR, QA and SUM).
- `length`: The length of the text of the pair.

### Data Splits

|     name    |entailment|neutral|contradiction|
|-------------|---------:|------:|------------:|
|     dev     |   412    |  299  |      89     |
|     test    |   410    |  318  |      72     |

|     name    |short|long|
|-------------|----:|---:|
|     dev     | 665 | 135|
|     test    | 683 | 117|

|     name    | IE| IR| QA|SUM|
|-------------|--:|--:|--:|--:|
|     dev     |200|200|200|200|
|     test    |200|200|200|200|

## Additional Information

### Citation Information

**BibTeX:**

````BibTeX
TBA
````

**ACL:**

TBA

### Acknowledgements

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.
task_categories:text-classification task_ids:natural-language-inference task_ids:multi-input-text-classification size_categories:1K<n<10K language:fr license:cc-by-4.0 region:us
{"language": ["fr"], "license": "cc-by-4.0", "size_categories": ["1K<n<10K"], "task_categories": ["text-classification"], "task_ids": ["natural-language-inference", "multi-input-text-classification"]}
TAGS
#task_categories-text-classification #task_ids-natural-language-inference #task_ids-multi-input-text-classification #size_categories-1K<n<10K #language-French #license-cc-by-4.0 #region-us 

Dataset Card for Dataset Name
=============================


Dataset Description
-------------------


* Homepage:
* Repository: URL
* Paper:
* Leaderboard:
* Point of Contact:


### Dataset Summary


The RTE3-FR dataset is the French translation of the Textual Entailment English dataset used in the RTE-3 Challenge.


Like its English counterpart, the French RTE-3 dataset is composed of a development set and a test set, each containing 800 T/H pairs.
All T/H pairs were manually translated into French and proofread.


It is annotated for a 3-way task.


### Supported Tasks and Leaderboards


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.


Dataset Structure
-----------------


### Data Fields


* 'id': Index number.
* 'language': The language of the concerned pair of sentences.
* 'premise': The translated premise in the target language.
* 'hypothesis': The translated premise in the target language.
* 'label': The classification label, with possible values 0 ('entailment'), 1 ('neutral'), 2 ('contradiction').
* 'label\_text': The classification label, with possible values 'entailment' (0), 'neutral' (1), 'contradiction' (2).
* 'task': The particular NLP task that the data was drawn from (IE, IR, QA and SUM).
* 'length': The length of the text of the pair.


### Data Splits





Additional Information
----------------------


BibTeX:


'


ACL:


TBA


### Acknowledgements


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.



### Dataset Summary


The RTE3-FR dataset is the French translation of the Textual Entailment English dataset used in the RTE-3 Challenge.


Like its English counterpart, the French RTE-3 dataset is composed of a development set and a test set, each containing 800 T/H pairs.
All T/H pairs were manually translated into French and proofread.


It is annotated for a 3-way task. ### Supported Tasks and Leaderboards


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.


Dataset Structure
----------------- ### Data Fields


* 'id': Index number.
* 'language': The language of the concerned pair of sentences.
* 'premise': The translated premise in the target language.
* 'hypothesis': The translated premise in the target language.
* 'label': The classification label, with possible values 0 ('entailment'), 1 ('neutral'), 2 ('contradiction').
* 'label\_text': The classification label, with possible values 'entailment' (0), 'neutral' (1), 'contradiction' (2).
* 'task': The particular NLP task that the data was drawn from (IE, IR, QA and SUM).
* 'length': The length of the text of the pair. ### Data Splits





Additional Information
----------------------


BibTeX:


'


ACL:


TBA ### Acknowledgements


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.
TAGS
#task_categories-text-classification #task_ids-natural-language-inference #task_ids-multi-input-text-classification #size_categories-1K<n<10K #language-French #license-cc-by-4.0 #region-us 
 ### Dataset Summary


The RTE3-FR dataset is the French translation of the Textual Entailment English dataset used in the RTE-3 Challenge.


Like its English counterpart, the French RTE-3 dataset is composed of a development set and a test set, each containing 800 T/H pairs.
All T/H pairs were manually translated into French and proofread.


It is annotated for a 3-way task. ### Supported Tasks and Leaderboards


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.


Dataset Structure
----------------- ### Data Fields


* 'id': Index number.
* 'language': The language of the concerned pair of sentences.
* 'premise': The translated premise in the target language.
* 'hypothesis': The translated premise in the target language.
* 'label': The classification label, with possible values 0 ('entailment'), 1 ('neutral'), 2 ('contradiction').
* 'label\_text': The classification label, with possible values 'entailment' (0), 'neutral' (1), 'contradiction' (2).
* 'task': The particular NLP task that the data was drawn from (IE, IR, QA and SUM).
* 'length': The length of the text of the pair. ### Data Splits





Additional Information
----------------------


BibTeX:


'


ACL:


TBA ### Acknowledgements


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.
passage: TAGS
#task_categories-text-classification #task_ids-natural-language-inference #task_ids-multi-input-text-classification #size_categories-1K<n<10K #language-French #license-cc-by-4.0 #region-us 
### Dataset Summary


The RTE3-FR dataset is the French translation of the Textual Entailment English dataset used in the RTE-3 Challenge.


Like its English counterpart, the French RTE-3 dataset is composed of a development set and a test set, each containing 800 T/H pairs.
All T/H pairs were manually translated into French and proofread.


It is annotated for a 3-way task.### Supported Tasks and Leaderboards


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.


Dataset Structure
-----------------### Data Fields


* 'id': Index number.
* 'language': The language of the concerned pair of sentences.
* 'premise': The translated premise in the target language.
* 'hypothesis': The translated premise in the target language.
* 'label': The classification label, with possible values 0 ('entailment'), 1 ('neutral'), 2 ('contradiction').
* 'label\_text': The classification label, with possible values 'entailment' (0), 'neutral' (1), 'contradiction' (2).
* 'task': The particular NLP task that the data was drawn from (IE, IR, QA and SUM).
* 'length': The length of the text of the pair.### Data Splits





Additional Information
----------------------


BibTeX:


'


ACL:


TBA### Acknowledgements


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.