README.md

---
dataset_info:
  features:
  - name: sentence
    dtype: string
  - name: simplification
    dtype: string
  - name: dataset
    dtype: string
  splits:
  - name: train
    num_bytes: 339019973
    num_examples: 781801
  - name: validation
    num_bytes: 972654
    num_examples: 2385
  - name: test
    num_bytes: 753090
    num_examples: 1439
  download_size: 218816945
  dataset_size: 340745717
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
language:
- fra
task_categories:
- text-generation
pretty_name: frenchSIMPLIFICATION
---



# Dataset information 
**Dataset concatenating Simplification datasets, available in French and open-source.**  
There are a total of **785,625** rows, of which 781,801 are for training, 2,385 for validation and 1,439 for testing.  

#  Usage
```
from datasets import load_dataset
dataset = load_dataset("CATIE-AQ/frenchSIMPLIFICATION")
```


# Dataset
## Details of rows
| Dataset Original | Splits | Note  |
| ----------- | ----------- | ----------- |
| [clear](http://natalia.grabar.free.fr/resources.php#remi)| 4,196 train / 300 validation / 100 test | |           
| [wikilarge](http://natalia.grabar.free.fr/resources.php#remi)| 296,402 train / 992 validation / 359 test | |       
| [GEM/BiSECT](https://huggingface.co/GEM/BiSECT)| 491,035 train / 2,400 validation / 1,036 test | We keep only the data in French (`fr`) |       
| [alector](https://alectorsite.wordpress.com/corpus/)| 1,108 train | We cut the 79 original texts into sentences to obtain 1,108 data instead of 79. |         


## Removing duplicate data and leaks
The sum of the values of the datasets listed here gives the following result:

```
DatasetDict({
    train: Dataset({
        features: ['sentence', 'simplification', 'dataset'],
        num_rows: 792741
    })
    validation: Dataset({
        features: ['sentence', 'simplification', 'dataset'],
        num_rows: 3692
    })
    test: Dataset({
        features: ['sentence', 'simplification', 'dataset'],
        num_rows: 1495
    })
})
```

However, a data item in training split A may not be in A's test split, but may be present in B's test set, creating a leak when we create the A+B dataset.  
The same logic applies to duplicate data. So we need to make sure we remove them.  
After our clean-up, we finally have the following numbers:

```
DatasetDict({
    train: Dataset({
        features: ['sentence', 'simplification', 'dataset'],
        num_rows: 781801
    })
    validation: Dataset({
        features: ['sentence', 'simplification', 'dataset'],
        num_rows: 2385
    })
    test: Dataset({
        features: ['sentence', 'simplification', 'dataset'],
        num_rows: 1439
    })
})
```



## Columns

- the `sentence` column contains the text
- the `simplification` column contains the simplification of the `sentence`
- the `dataset` column identifies the row's original dataset (if you wish to apply filters to it)

## Split
- `train` corresponds to the concatenation of `clear` + `wikilarge` + `bisect` + `alector`
- `validation` corresponds to the concatenation of `clear` + `wikilarge` + `bisect`
- `test` corresponds to `clear` + `wikilarge` + `bisect`



# Citations

### Alector
```
@inproceedings{gala-etal-2020-alector,
    title = "{A}lector: A Parallel Corpus of Simplified {F}rench Texts with Alignments of Misreadings by Poor and Dyslexic Readers",  
    author = {Gala, N{\'u}ria and Tack, Ana{\"\i}s  and Javourey-Drevet, Ludivine and Fran{\c{c}}ois, Thomas and Ziegler, Johannes C.},  
    editor = "Calzolari, Nicoletta and B{\'e}chet, Fr{\'e}d{\'e}ric and Blache, Philippe  and Choukri, Khalid and Cieri, Christopher and Declerck, Thierry and Goggi, Sara  and Isahara, Hitoshi and Maegaard, Bente and Mariani, Joseph and Mazo, H{\'e}l{\`e}ne and Moreno, Asuncion  and Odijk, Jan  and Piperidis, Stelios",  
    booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",  
    month = may,  
    year = "2020",  
    address = "Marseille, France",  
    publisher = "European Language Resources Association",  
    url = "https://aclanthology.org/2020.lrec-1.169",  
    pages = "1353--1361",  
     language = "English",  
    ISBN = "979-10-95546-34-4",}
```

### BiSECT
```
@inproceedings{bisect2021,  
  title={BiSECT: Learning to Split and Rephrase Sentences with Bitexts},  
  author={Kim, Joongwon and Maddela, Mounica and Kriz, Reno and Xu, Wei and Callison-Burch, Chris},  
  booktitle={Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP)},  
  year={2021}}
```

### CLEAR
```
@inproceedings{grabar-cardon-2018-clear,
    title = "{CLEAR} {--} Simple Corpus for Medical {F}rench",
    author = "Grabar, Natalia  and  Cardon, R{\'e}mi",
    editor = {J{\"o}nsson, Arne  and  Rennes, Evelina  and Saggion, Horacio  and  Stajner, Sanja  and  Yaneva, Victoria},
    booktitle = "Proceedings of the 1st Workshop on Automatic Text Adaptation ({ATA})",
    month = nov,
    year = "2018",
    address = "Tilburg, the Netherlands",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W18-7002",
    doi = "10.18653/v1/W18-7002",
    pages = "3--9",
}
```

### Wikilarge
```
@inproceedings{cardon-grabar-2020-french,
    title = "{F}rench Biomedical Text Simplification: When Small and Precise Helps",
    author = "Cardon, R{\'e}mi  and  Grabar, Natalia",
    editor = "Scott, Donia  and   Bel, Nuria  and   Zong, Chengqing",
    booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
    month = dec,
    year = "2020",
    address = "Barcelona, Spain (Online)",
    publisher = "International Committee on Computational Linguistics",
    url = "https://aclanthology.org/2020.coling-main.62",
    doi = "10.18653/v1/2020.coling-main.62",
    pages = "710--716",
}
```

### frenchSIMPLIFICATION
```
@misc{frenchSIMPLIFICATION_2025,
    author       = { {BOURDOIS, Loïck} },  
    organization  = { {Centre Aquitain des Technologies de l'Information et Electroniques} },  
	year         = 2025,
	url          = { https://huggingface.co/datasets/CATIE-AQ/frenchSIMPLIFICATION },
	doi          = { 10.57967/hf/7134 },
	publisher    = { Hugging Face }
}
```

# License
[cc-by-4.0](https://creativecommons.org/licenses/by/4.0/deed.en)