
# universal_dependencies_fr_partut_fr_prompt_pos
## Summary

**universal_dependencies_fr_partut_fr_prompt_pos** is a subset of the [**Dataset of French Prompts (DFP)**](https://huggingface.co/datasets/CATIE-AQ/DFP).  
It contains **21,420** rows that can be used for a part-of-speech task.  
The original data (without prompts) comes from the dataset [universal_dependencies](https://huggingface.co/datasets/universal_dependencies) where only the French parput split 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 classes des mots du texte suivant : '+text,  
'Extrais les classes des mots du texte suivant : '+text,  
'Extrayez les classes des mots du texte suivant : '+text,  
'Isoler les classes des mots du texte suivant : '+text,  
'Isole les classes des mots du texte suivant : '+text,  
'Isolez les classes des mots du texte suivant : '+text,  
'Dégager les classes des mots dans le texte : '+text,  
'Dégage les classes des mots dans le texte : '+text,  
'Dégagez les classes des mots dans le texte : '+text,  
'Générer les classes des mots issues du texte suivant : '+text,  
'Génère les classes des mots issues du texte suivant : '+text,  
'Générez les classes des mots issues du texte suivant : '+text,  
'Trouver les classes des mots du texte : '+text,  
'Trouve les classes des mots du texte : '+text,  
'Trouvez les classes des mots du texte : '+text,  
'Repérer les classes des mots présentes dans le texte suivant : '+text,  
'Repère les classes des mots présentes dans le texte suivant : '+text,  
'Repérez les classes des mots présentes dans le texte suivant : '+text,  
'Indiquer les classes des mots du texte :'+text,  
'Indique les classes des mots du texte : '+text,  
'Indiquez les classes des mots du texte : '+text
```

### Features used in the prompts
In the prompt list above, `text` and `targets` have been constructed from:
```
fr_partut = load_dataset('universal_dependencies', 'fr_partut')  
# text
fr_partut['train']['tokens'] = list(map(lambda i: ' '.join(fr_partut['train']['tokens'][i]), range(len(fr_partut['train']['tokens']))))
# targets
fr_partut['train']['upos'] = list(map(lambda x: x.replace("[","").replace("]","").replace('17','AUX').replace('16','VERB').replace('15','INTJ').replace('14','ADV').replace('13','_').replace('12','X').replace('11','PRON').replace('10','PROPN').replace('9','CCONJ').replace('8','DET').replace('7','PART').replace('6','ADJ').replace('5','SCONJ').replace('4','SYM').replace('3','NUM').replace('2','ADP').replace('1','PUNCT').replace('0','NOUN'), map(str,fr_partut['train']['upos'])))
```



# Splits
- `train` with 16,863 samples
- `valid` with 2,247 samples
- `test` with 2,310 samples


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

# Citation
## Original data
> Contributors: Cristina Bosco, Manuela Sanguinetti.


## 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
CC BY-SA 4.0
task_categories:token-classification annotations_creators:found language_creators:found multilinguality:monolingual size_categories:10K<n<100K source_datasets:universal_dependencies_fr_partut language:fr license:cc-by-sa-4.0 pos DFP french prompts region:us
{"annotations_creators": ["found"], "language_creators": ["found"], "language": ["fr"], "license": "cc-by-sa-4.0", "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["universal_dependencies_fr_partut"], "task_categories": ["token-classification"], "tags": ["pos", "DFP", "french prompts"]}
TAGS
#task_categories-token-classification #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-universal_dependencies_fr_partut #language-French #license-cc-by-sa-4.0 #pos #DFP #french prompts #region-us 


# universal_dependencies_fr_partut_fr_prompt_pos
## Summary

universal_dependencies_fr_partut_fr_prompt_pos is a subset of the Dataset of French Prompts (DFP).  
It contains 21,420 rows that can be used for a part-of-speech task.  
The original data (without prompts) comes from the dataset universal_dependencies where only the French parput split 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 16,863 samples
- 'valid' with 2,247 samples
- 'test' with 2,310 samples


# How to use?


## Original data
> Contributors: Cristina Bosco, Manuela Sanguinetti.


## 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
CC BY-SA 4.0
# universal_dependencies_fr_partut_fr_prompt_pos ## Summary

universal_dependencies_fr_partut_fr_prompt_pos is a subset of the Dataset of French Prompts (DFP).  
It contains 21,420 rows that can be used for a part-of-speech task.  
The original data (without prompts) comes from the dataset universal_dependencies where only the French parput split 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 16,863 samples
- 'valid' with 2,247 samples
- 'test' with 2,310 samples # How to use? ## Original data
> Contributors: Cristina Bosco, Manuela Sanguinetti. ## 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
CC BY-SA 4.0
TAGS
#task_categories-token-classification #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-universal_dependencies_fr_partut #language-French #license-cc-by-sa-4.0 #pos #DFP #french prompts #region-us 
 # universal_dependencies_fr_partut_fr_prompt_pos ## Summary

universal_dependencies_fr_partut_fr_prompt_pos is a subset of the Dataset of French Prompts (DFP).  
It contains 21,420 rows that can be used for a part-of-speech task.  
The original data (without prompts) comes from the dataset universal_dependencies where only the French parput split 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 16,863 samples
- 'valid' with 2,247 samples
- 'test' with 2,310 samples # How to use? ## Original data
> Contributors: Cristina Bosco, Manuela Sanguinetti. ## 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
CC BY-SA 4.0