Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
parquet
Languages:
French
Size:
10K - 100K
ArXiv:
License:
File size: 2,223 Bytes
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---
language:
- fr
license: cc-by-4.0
task_categories:
- token-classification
dataset_info:
features:
- name: ner_tags
sequence: int64
- name: tokens
sequence: string
- name: pos_tags
sequence: string
splits:
- name: train
num_bytes: 17859073
num_examples: 26754
download_size: 3480973
dataset_size: 17859073
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# WikiNER-fr-gold
This dataset is a manually revised version of 20% of the French proportion of [WikiNER](https://doi.org/10.1016/j.artint.2012.03.006).
The original dataset is currently available [here](https://figshare.com/articles/dataset/Learning_multilingual_named_entity_recognition_from_Wikipedia/5462500), based on which WikiNER-fr-gold is created.
The entities are annotated using the BIOES scheme.
The POS tags are not revised i.e. remain the same as the original dataset.
For more information on the revision details, please refer to our paper [WikiNER-fr-gold: A Gold-Standard NER Corpus](https://arxiv.org/abs/2411.00030).
The dataset is available in two formats.
The CoNLL version contains three columns: text, POS and NER.
The Parquet version is downloadable using the `datasets` library.
Originally conceived as a test set, there is no recommended train/dev/test split.
The downloaded dataset is by default labeled `train`.
```python
from datasets import load_dataset
ds = load_dataset('danrun/WikiNER-fr-gold')
ds['train'][0]
# {'ner_tags': [...], 'tokens': [...], 'pos_tags': [...]}
```
The NER tags are indexed using the following table (see `labels.json`):
```
{
'O': 0,
'B-PER': 1,
'I-PER': 2,
'E-PER': 3,
'S-PER': 4,
'B-LOC': 5,
'I-LOC': 6,
'E-LOC': 7,
'S-LOC': 8,
'B-ORG': 9,
'I-ORG': 10,
'E-ORG': 11,
'S-ORG': 12,
'B-MISC': 13,
'I-MISC': 14,
'E-MISC': 15,
'S-MISC': 16
}
```
## Citation
```
@misc{cao2024wikinerfrgoldgoldstandardnercorpus,
title={WikiNER-fr-gold: A Gold-Standard NER Corpus},
author={Danrun Cao and Nicolas Béchet and Pierre-François Marteau},
year={2024},
eprint={2411.00030},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2411.00030},
}
```
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