Datasets:

compnet-renard
/

7-romans-ner

dataset_info:
  features:
    - name: tokens
      sequence: string
    - name: labels
      sequence:
        class_label:
          names:
            '0': B-LOC
            '1': B-MISC
            '2': B-ORG
            '3': B-PER
            '4': I-LOC
            '5': I-MISC
            '6': I-ORG
            '7': I-PER
            '8': O
    - name: novel
      dtype: string
  splits:
    - name: train
      num_bytes: 21690413
      num_examples: 26785
  download_size: 3685914
  dataset_size: 21690413
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

7-romans

This dataset contains 7 French novels, entirely annoted for the NER task. See the related alias resolution dataset.

Novel	Autor	Publication Year	Nombre de tokens	Number of characters
Les Trois Mousquetaires	Alexandre Dumas	1849	294 989	213
Le Rouge et le Noir	Stendhal	1854	216 445	318
Eugénie Grandet	Honoré de Balzac	1855	80 659	107
Germinal	Émile Zola	1885	220 273	102
Bel-Ami	Guy de Maupassant	1901	138 156	150
Notre-Dame de Paris	Victor Hugo	1904	221 351	536
Madame Bovary	Gustave Flaubert	1910	148 861	175

This gold standard corpus was created in the context of a project at the ObTIC laboratory, Sorbonne University. The project was directed by Motasem Alrahabi, and annnotations were performed by Perrine Maurel, Una Faller and Romaric Parnasse.

The corpus was then used to train a CamemBERT NER model in collaboration with Arthur Amalvy and Vincent Labatut, from Avignon University.

Usage

>>> from datasets import load_dataset
>>> dataset = load_dataset("compnet-renard/7-romans-ner")
>>> dataset["train"][0]
{'tokens': ['Quand', 'la', 'caissière', 'lui', 'eut', 'rendu', 'la', 'monnaie', 'de', 'sa', 'pièce', 'de', 'cent', 'sous', ',', 'Georges', 'Duroy', 'sortit', 'du', 'restaurant', '.'], 'labels': [8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 3, 7, 8, 8, 8, 8], 'novel': 'BelAmi'}

Citation

If you use this dataset in your research, please cite:

@InProceedings{Maurel2025,
  authors = {Maurel, P. and Amalvy, A. and Labatut, V. and Alrahabi, M.},
  title = {Du repérage à l’analyse : un modèle pour la reconnaissance d’entités nommées dans les textes littéraires en français},
  booktitle = {Digital Humanities 2025},
  year = {2025},
}