
# wikiner_fr_prompt_ner
## Summary

**wikiner_fr_prompt_ner** is a subset of the [**Dataset of French Prompts (DFP)**](https://huggingface.co/datasets/CATIE-AQ/DFP).  
It contains **2,534,322** rows that can be used for a name entity recognition task.  
The original data (without prompts) comes from the dataset [wikiner](https://huggingface.co/datasets/Jean-Baptiste/wikiner_fr) by Nothman 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
21 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.

```
'Extraire les entités nommées du texte suivant : '+text,
'Extrais les entitées nommées du texte suivant : '+text,
'Extrayez les entitées nommées du texte suivant : '+text,
'Isoler les entitées nommées du texte suivant : '+text,
'Isole les entitées nommées du texte suivant : '+text,
'Isolez les entitées nommées du texte suivant : '+text,
'Dégager des entitées nommées dans le texte : '+text,
'Dégage des entitées nommées dans le texte : '+text,
'Dégagez des entitées nommées dans le texte : '+text,
'Générer des entitées nommées issues du texte suivant : '+text,
'Génère des entitées nommées issues du texte suivant : '+text,
'Générez des entitées nommées issues du texte suivant : '+text,
'Trouver les entitées nommées du texte : '+text,
'Trouve les entitées nommées du texte : '+text,
'Trouvez les entitées nommées du texte : '+text,
'Repérer les entitées nommées présentes dans le texte suivant : '+text,
'Repère les entitées nommées présentes dans le texte suivant : '+text,
'Repérez les entitées nommées présentes dans le texte suivant : '+text,
'Indiquer les entitées nommées du texte :'+text,
'Indique les entitées nommées du texte : '+text,
'Indiquez les entitées nommées du texte : '+text
```

### Features used in the prompts
In the prompt list above, `text` and `targets` have been constructed from:
```
wikiner_fr = load_dataset('Jean-Baptiste/wikiner_fr')  
wikiner_fr['train']['tokens'] = list(map(lambda i: ' '.join(wikiner_fr['train']['tokens'][i]), range(len(wikiner_fr['train']['tokens']))))
wikiner_fr['train']['ner_tags'] = list(map(lambda x: x.replace("[","").replace("]","").replace('0','O').replace('1','LOC').replace('2','PER').replace('3','O').replace('4','ORG'), map(str, wikiner_fr['train']['ner_tags'])))
```



# Splits
- `train` with 2,534,322 samples
- no `valid` split
- no `test` split



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

# Citation
## Original data
> @article{NOTHMAN2013151,  
title = {Learning multilingual named entity recognition from Wikipedia},  
journal = {Artificial Intelligence},  
volume = {194},  
pages = {151-175},  
year = {2013},  
note = {Artificial Intelligence, Wikipedia and Semi-Structured Resources},  
issn = {0004-3702},  
doi = {https://doi.org/10.1016/j.artint.2012.03.006},  
url = {https://www.sciencedirect.com/science/article/pii/S0004370212000276},  
author = {Joel Nothman and Nicky Ringland and Will Radford and Tara Murphy and James R. Curran},
}



## 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
Unknow
task_categories:token-classification annotations_creators:found language_creators:found multilinguality:monolingual size_categories:1M<n<10M source_datasets:wikiner language:fr license:unknown ner DFP french prompts region:us
{"annotations_creators": ["found"], "language_creators": ["found"], "language": ["fr"], "license": ["unknown"], "multilinguality": ["monolingual"], "size_categories": ["1M<n<10M"], "source_datasets": ["wikiner"], "task_categories": ["token-classification"], "tags": ["ner", "DFP", "french prompts"]}
TAGS
#task_categories-token-classification #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-1M<n<10M #source_datasets-wikiner #language-French #license-unknown #ner #DFP #french prompts #region-us 


# wikiner_fr_prompt_ner
## Summary

wikiner_fr_prompt_ner is a subset of the Dataset of French Prompts (DFP).  
It contains 2,534,322 rows that can be used for a name entity recognition task.  
The original data (without prompts) comes from the dataset wikiner by Nothman 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
21 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, 'text' and 'targets' have been constructed from:




# Splits
- 'train' with 2,534,322 samples
- no 'valid' split
- no 'test' split



# How to use?


## Original data
> @article{NOTHMAN2013151,  
title = {Learning multilingual named entity recognition from Wikipedia},  
journal = {Artificial Intelligence},  
volume = {194},  
pages = {151-175},  
year = {2013},  
note = {Artificial Intelligence, Wikipedia and Semi-Structured Resources},  
issn = {0004-3702},  
doi = {URL  
url = {URL  
author = {Joel Nothman and Nicky Ringland and Will Radford and Tara Murphy and James R. Curran},
}



## 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
Unknow
# wikiner_fr_prompt_ner ## Summary

wikiner_fr_prompt_ner is a subset of the Dataset of French Prompts (DFP).  
It contains 2,534,322 rows that can be used for a name entity recognition task.  
The original data (without prompts) comes from the dataset wikiner by Nothman 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
21 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, 'text' and 'targets' have been constructed from: # Splits
- 'train' with 2,534,322 samples
- no 'valid' split
- no 'test' split # How to use? ## Original data
> @article{NOTHMAN2013151,  
title = {Learning multilingual named entity recognition from Wikipedia},  
journal = {Artificial Intelligence},  
volume = {194},  
pages = {151-175},  
year = {2013},  
note = {Artificial Intelligence, Wikipedia and Semi-Structured Resources},  
issn = {0004-3702},  
doi = {URL  
url = {URL  
author = {Joel Nothman and Nicky Ringland and Will Radford and Tara Murphy and James R. Curran},
} ## 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
Unknow
TAGS
#task_categories-token-classification #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-1M<n<10M #source_datasets-wikiner #language-French #license-unknown #ner #DFP #french prompts #region-us 
 # wikiner_fr_prompt_ner ## Summary

wikiner_fr_prompt_ner is a subset of the Dataset of French Prompts (DFP).  
It contains 2,534,322 rows that can be used for a name entity recognition task.  
The original data (without prompts) comes from the dataset wikiner by Nothman 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
21 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, 'text' and 'targets' have been constructed from: # Splits
- 'train' with 2,534,322 samples
- no 'valid' split
- no 'test' split # How to use? ## Original data
> @article{NOTHMAN2013151,  
title = {Learning multilingual named entity recognition from Wikipedia},  
journal = {Artificial Intelligence},  
volume = {194},  
pages = {151-175},  
year = {2013},  
note = {Artificial Intelligence, Wikipedia and Semi-Structured Resources},  
issn = {0004-3702},  
doi = {URL  
url = {URL  
author = {Joel Nothman and Nicky Ringland and Will Radford and Tara Murphy and James R. Curran},
} ## 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
Unknow