
# paws-x_fr_prompt_paraphrase_detection
## Summary

**paws-x_fr_prompt_paraphrase_detection** is a subset of the [**Dataset of French Prompts (DFP)**](https://huggingface.co/datasets/CATIE-AQ/DFP).  
It contains **1,174,822** rows that can be used for a paraphrase detection 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
22 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.

```
'Puis-je remplacer la phrase "'+sentence1+'" par la phrase "'+sentence2+'" et que cela garde la même signification ?',  
'Peut-on remplacer la phrase "'+sentence1+'" par la phrase "'+sentence2+'" et que cela garde la même signification ?',  
'Les deux phrases suivantes signifient-elles la même chose ? \n "'+sentence1+'"\n "'+sentence2+'"',  
'Je veux savoir si les deux phrases suivantes signifient la même chose. \n "'+sentence1+'"\n "'+sentence2+'"\n Le sont-elles ?',  
'On veut savoir si les deux phrases suivantes signifient la même chose. \n "'+sentence1+'"\n "'+sentence2+'"\n Le sont-elles ?',  
'Nous voulons savoir si les deux phrases suivantes signifient la même chose. \n "'+sentence1+'"\n "'+sentence2+'"\n Le sont-elles ?',  
'La phrase "'+sentence1+'" paraphrase-t-elle (= signifie-t-elle la même chose que) cette phrase ? "'+sentence2+'"',  
'Les deux phrases suivantes sont-elles équivalentes ou non équivalentes ? "'+ sentence1+'"\n"'+sentence2+'"',  
'Déterminer si les deux phrases suivantes se paraphrasent ou non. Phrase 1 : "'+sentence1+'\n Phrase 2 : "'+sentence2+'"',  
'Déterminez si les deux phrases suivantes se paraphrasent ou non. Phrase 1 : "'+sentence1+'\n Phrase 2 : "'+sentence2+'"',  
'Détermine si les deux phrases suivantes se paraphrasent ou non. Phrase 1 : "'+sentence1+'\n Phrase 2 : "'+sentence2+'"',  
'"'+sentence1+'" Est-ce une paraphrase de la phrase suivante ? "'+sentence2+'"',  
'"'+sentence1+'" Est-ce une paraphrase de la phrase suivante ? "'+sentence2+'" Oui ou Non ?',  
'"'+sentence1+'" Question : "'+sentence2+'" est une paraphrase ou non ?',  
'Phrase 1 : "'+sentence1+'"\n Phrase 2 : "'+sentence2+'"\n Question : La phrase 1 et la phrase 2 expriment-elles le même sens ?',  
'Phrase 1 : "'+sentence1+'"\n Phrase 2 : "'+sentence2+'"\n Question : La phrase 1 et la phrase 2 expriment-elles le même sens ? Oui ou Non ?',  
'Phrase 1 : "'+sentence1+'"\n Phrase 2 : "'+sentence2+'"\n Question : Peut-on réécrire la phrase 1 en phrase 2 ?' ,  
'Phrase 1 : "'+sentence1+'"\n Phrase 2 : "'+sentence2+'"\n Question : Puis-je réécrire la phrase 1 en phrase 2 ?' ,  
'Phrase 1 : "'+sentence1+'"\n Phrase 2 : "'+sentence2+'"\n Question : Peut-on réécrire la phrase 1 en phrase 2 ? Oui ou Non ?',  
'Phrase 1 : "'+sentence1+'"\n Phrase 2 : "'+sentence2+'"\n Question : Puis-je réécrire la phrase 1 en phrase 2 ? Oui ou Non ?',  
'Phrase 1 : "'+sentence1+'"\n Phrase 2 : "'+sentence2+'"\n Question : La phrase 1 paraphrase-t-elle la phrase 2 ?',  
'Phrase 1 : "'+sentence1+'"\n Phrase 2 : "'+sentence2+'"\n Question : La phrase 1 paraphrase-t-elle la phrase 2 ? Oui ou Non ?'  
```

### Features used in the prompts
In the prompt list above, `sentence1`, `sentence2` and the `target` have been constructed from:
```
paws_x = load_dataset('paws-x','fr')  
sentence1 = paws_x['train'][i]['sentence1']  
sentence2 = paws_x['train'][i]['sentence2']  
targets = str(paws_x['train'][i]['label']).replace('0','Non').replace('1','Oui'))
```


# Splits
- `train` with 1,086,822 samples
- `valid` with 44,000 samples
- `test` with 44,000 samples


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

# 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-classification annotations_creators:found language_creators:found multilinguality:monolingual size_categories:1M<n<10M source_datasets:paws-x language:fr license:other paraphrase-detection DFP french prompts region:us
{"annotations_creators": ["found"], "language_creators": ["found"], "language": ["fr"], "license": ["other"], "multilinguality": ["monolingual"], "size_categories": ["1M<n<10M"], "source_datasets": ["paws-x"], "task_categories": ["text-classification"], "tags": ["paraphrase-detection", "DFP", "french prompts"]}
TAGS
#task_categories-text-classification #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-1M<n<10M #source_datasets-paws-x #language-French #license-other #paraphrase-detection #DFP #french prompts #region-us 


# paws-x_fr_prompt_paraphrase_detection
## Summary

paws-x_fr_prompt_paraphrase_detection is a subset of the Dataset of French Prompts (DFP).  
It contains 1,174,822 rows that can be used for a paraphrase detection 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
22 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', 'sentence2' and the 'target' have been constructed from:



# Splits
- 'train' with 1,086,822 samples
- 'valid' with 44,000 samples
- 'test' with 44,000 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_detection ## Summary

paws-x_fr_prompt_paraphrase_detection is a subset of the Dataset of French Prompts (DFP).  
It contains 1,174,822 rows that can be used for a paraphrase detection 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
22 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', 'sentence2' and the 'target' have been constructed from: # Splits
- 'train' with 1,086,822 samples
- 'valid' with 44,000 samples
- 'test' with 44,000 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-classification #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-1M<n<10M #source_datasets-paws-x #language-French #license-other #paraphrase-detection #DFP #french prompts #region-us 
 # paws-x_fr_prompt_paraphrase_detection ## Summary

paws-x_fr_prompt_paraphrase_detection is a subset of the Dataset of French Prompts (DFP).  
It contains 1,174,822 rows that can be used for a paraphrase detection 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
22 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', 'sentence2' and the 'target' have been constructed from: # Splits
- 'train' with 1,086,822 samples
- 'valid' with 44,000 samples
- 'test' with 44,000 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.