
# paws-x_fr_prompt_paraphrase_generation
## Summary

**paws-x_fr_prompt_paraphrase_generation** is a subset of the [**Dataset of French Prompts (DFP)**](https://huggingface.co/datasets/CATIE-AQ/DFP).  
It contains **562,728** rows that can be used for a paraphrase generation task.  
The original data (without prompts) comes from the dataset [paws-x](https://huggingface.co/datasets/paws-x) by Yang et al. where only the French part has been kept.  
A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the [xP3](https://huggingface.co/datasets/bigscience/xP3) dataset by Muennighoff et al.


## Prompts used
### List
24 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.

```
'Générer une phrase qui signifie la même chose que celle-ci : "'+sentence1+'"',  
'Génère une phrase qui signifie la même chose que celle-ci : "'+sentence1+'"',  
'Générez une phrase qui signifie la même chose que celle-ci : "'+sentence1+'"',  
'Paraphraser la phrase suivante : "'+sentence1+'"',  
'Paraphrase la phrase suivante : "'+sentence1+'"',  
'Paraphrasez la phrase suivante : "'+sentence1+'"',  
'Créer une phrase qui signifie la même chose que celle-ci : "'+sentence1+'"',  
'Crée une phrase qui signifie la même chose que celle-ci : "'+sentence1+'"',  
'Créez une phrase qui signifie la même chose que celle-ci : "'+sentence1+'"',  
'Créer une paraphrase de la phrase suivante : "'+sentence1+'"',  
'Crée une paraphrase de la phrase suivante : "'+sentence1+'"',  
'Créez une paraphrase de la phrase suivante : "'+sentence1+'"',  
'Ecrire une phrase qui signifie la même chose que celle-ci : "'+sentence1+'"',  
'Ecris une phrase qui signifie la même chose que celle-ci : "'+sentence1+'"',  
'Ecrivez une phrase qui signifie la même chose que celle-ci : "'+sentence1+'"',  
'Ecrire une paraphrase de la phrase suivante : "'+sentence1+'"',  
'Ecris une paraphrase de la phrase suivante : "'+sentence1+'"',  
'Ecrivez une paraphrase de la phrase suivante : "'+sentence1+'"',  
'Rédiger une phrase qui signifie la même chose que celle-ci : "'+sentence1+'"',  
'Rédige une phrase qui signifie la même chose que celle-ci : "'+sentence1+'"',  
'Rédigez une phrase qui signifie la même chose que celle-ci : "'+sentence1+'"',  
'Rédiger une paraphrase de la phrase suivante : "'+sentence1+'"',  
'Rédige une paraphrase de la phrase suivante : "'+sentence1+'"',  
'Rédigez une paraphrase de la phrase suivante : "'+sentence1+'"' 
``` 

### Features used in the prompts
In the prompt list above, `sentence1` and the `target` have been constructed from:
```
paws_x = load_dataset('paws-x','fr')
if paws_x['train'][i]['label'] == 1:
        sentence1 = paws_x['train'][i]['sentence1']
targets = paws_x['train'][i]['sentence2']
```


# Splits
- `train` with 520,416 samples
- `valid` with 20,640 samples
- `test` with 21,672 samples



# How to use?
```
from datasets import load_dataset
dataset = load_dataset("CATIE-AQ/paws-x_fr_prompt_paraphrase_generation")
```

# Citation
## Original data
> @InProceedings{pawsx2019emnlp,
  title = {{PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification}},
  author = {Yang, Yinfei and Zhang, Yuan and Tar, Chris and Baldridge, Jason},
  booktitle = {Proc. of EMNLP},
  year = {2019}
}


## This Dataset
> @misc {centre_aquitain_des_technologies_de_l'information_et_electroniques_2023,  
	author       = { {Centre Aquitain des Technologies de l'Information et Electroniques} },  
	title        = { DFP (Revision 1d24c09) },  
	year         = 2023,  
	url          = { https://huggingface.co/datasets/CATIE-AQ/DFP },  
	doi          = { 10.57967/hf/1200 },  
	publisher    = { Hugging Face }  
}

# License
The dataset may be freely used for any purpose, although acknowledgement of Google LLC ("Google") as the data source would be appreciated. The dataset is provided "AS IS" without any warranty, express or implied. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.
task_categories:text-generation annotations_creators:found language_creators:found multilinguality:monolingual size_categories:100K<n<1M source_datasets:paws-x language:fr license:other paraphrase-generation DFP french prompts region:us
{"annotations_creators": ["found"], "language_creators": ["found"], "language": ["fr"], "license": ["other"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["paws-x"], "task_categories": ["text-generation"], "tags": ["paraphrase-generation", "DFP", "french prompts"]}
TAGS
#task_categories-text-generation #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-paws-x #language-French #license-other #paraphrase-generation #DFP #french prompts #region-us 


# paws-x_fr_prompt_paraphrase_generation
## Summary

paws-x_fr_prompt_paraphrase_generation is a subset of the Dataset of French Prompts (DFP).  
It contains 562,728 rows that can be used for a paraphrase generation task.  
The original data (without prompts) comes from the dataset paws-x by Yang et al. where only the French part has been kept.  
A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the xP3 dataset by Muennighoff et al.


## Prompts used
### List
24 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.

 

### Features used in the prompts
In the prompt list above, 'sentence1' and the 'target' have been constructed from:



# Splits
- 'train' with 520,416 samples
- 'valid' with 20,640 samples
- 'test' with 21,672 samples



# How to use?


## Original data
> @InProceedings{pawsx2019emnlp,
  title = {{PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification}},
  author = {Yang, Yinfei and Zhang, Yuan and Tar, Chris and Baldridge, Jason},
  booktitle = {Proc. of EMNLP},
  year = {2019}
}


## This Dataset
> @misc {centre_aquitain_des_technologies_de_l'information_et_electroniques_2023,  
	author       = { {Centre Aquitain des Technologies de l'Information et Electroniques} },  
	title        = { DFP (Revision 1d24c09) },  
	year         = 2023,  
	url          = { URL },  
	doi          = { 10.57967/hf/1200 },  
	publisher    = { Hugging Face }  
}

# License
The dataset may be freely used for any purpose, although acknowledgement of Google LLC ("Google") as the data source would be appreciated. The dataset is provided "AS IS" without any warranty, express or implied. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.
# paws-x_fr_prompt_paraphrase_generation ## Summary

paws-x_fr_prompt_paraphrase_generation is a subset of the Dataset of French Prompts (DFP).  
It contains 562,728 rows that can be used for a paraphrase generation task.  
The original data (without prompts) comes from the dataset paws-x by Yang et al. where only the French part has been kept.  
A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the xP3 dataset by Muennighoff et al. ## Prompts used ### List
24 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement. ### Features used in the prompts
In the prompt list above, 'sentence1' and the 'target' have been constructed from: # Splits
- 'train' with 520,416 samples
- 'valid' with 20,640 samples
- 'test' with 21,672 samples # How to use? ## Original data
> @InProceedings{pawsx2019emnlp,
  title = {{PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification}},
  author = {Yang, Yinfei and Zhang, Yuan and Tar, Chris and Baldridge, Jason},
  booktitle = {Proc. of EMNLP},
  year = {2019}
} ## This Dataset
> @misc {centre_aquitain_des_technologies_de_l'information_et_electroniques_2023,  
	author       = { {Centre Aquitain des Technologies de l'Information et Electroniques} },  
	title        = { DFP (Revision 1d24c09) },  
	year         = 2023,  
	url          = { URL },  
	doi          = { 10.57967/hf/1200 },  
	publisher    = { Hugging Face }  
} # License
The dataset may be freely used for any purpose, although acknowledgement of Google LLC ("Google") as the data source would be appreciated. The dataset is provided "AS IS" without any warranty, express or implied. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.
TAGS
#task_categories-text-generation #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-paws-x #language-French #license-other #paraphrase-generation #DFP #french prompts #region-us 
 # paws-x_fr_prompt_paraphrase_generation ## Summary

paws-x_fr_prompt_paraphrase_generation is a subset of the Dataset of French Prompts (DFP).  
It contains 562,728 rows that can be used for a paraphrase generation task.  
The original data (without prompts) comes from the dataset paws-x by Yang et al. where only the French part has been kept.  
A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the xP3 dataset by Muennighoff et al. ## Prompts used ### List
24 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement. ### Features used in the prompts
In the prompt list above, 'sentence1' and the 'target' have been constructed from: # Splits
- 'train' with 520,416 samples
- 'valid' with 20,640 samples
- 'test' with 21,672 samples # How to use? ## Original data
> @InProceedings{pawsx2019emnlp,
  title = {{PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification}},
  author = {Yang, Yinfei and Zhang, Yuan and Tar, Chris and Baldridge, Jason},
  booktitle = {Proc. of EMNLP},
  year = {2019}
} ## This Dataset
> @misc {centre_aquitain_des_technologies_de_l'information_et_electroniques_2023,  
	author       = { {Centre Aquitain des Technologies de l'Information et Electroniques} },  
	title        = { DFP (Revision 1d24c09) },  
	year         = 2023,  
	url          = { URL },  
	doi          = { 10.57967/hf/1200 },  
	publisher    = { Hugging Face }  
} # License
The dataset may be freely used for any purpose, although acknowledgement of Google LLC ("Google") as the data source would be appreciated. The dataset is provided "AS IS" without any warranty, express or implied. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.
passage: TAGS
#task_categories-text-generation #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-paws-x #language-French #license-other #paraphrase-generation #DFP #french prompts #region-us 
# paws-x_fr_prompt_paraphrase_generation## Summary

paws-x_fr_prompt_paraphrase_generation is a subset of the Dataset of French Prompts (DFP).  
It contains 562,728 rows that can be used for a paraphrase generation task.  
The original data (without prompts) comes from the dataset paws-x by Yang et al. where only the French part has been kept.  
A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the xP3 dataset by Muennighoff et al.## Prompts used### List
24 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.### Features used in the prompts
In the prompt list above, 'sentence1' and the 'target' have been constructed from:# Splits
- 'train' with 520,416 samples
- 'valid' with 20,640 samples
- 'test' with 21,672 samples# How to use?## Original data
> @InProceedings{pawsx2019emnlp,
  title = {{PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification}},
  author = {Yang, Yinfei and Zhang, Yuan and Tar, Chris and Baldridge, Jason},
  booktitle = {Proc. of EMNLP},
  year = {2019}
}