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compnet-renard/bert-base-cased-literary-NER
bert-base-cased-literary-NER is a token classification model from compnet-renard. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
A NER model trained on a literary dataset of the first chapter of 40 novels. The model supports the following NER class: PER, ORG and LOC. If you use the model in a huggingface pipeline, pass aggregationstrategy="first".
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From the Hugging Face model README
A NER model trained on a literary dataset of the first chapter of 40 novels. The model supports the following NER class: PER, ORG and LOC. If you use the model in a huggingface pipeline, pass aggregation_strategy="first".
We corrected the dataset of Dekker et al. (2019) and added LOC and ORG annotations.
If you use this model in your research, please cite:
@InProceedings{amalvy:hal-03972448,
title = {{Data Augmentation for Robust Character Detection in
Fantasy Novels}},
author = {Amalvy, Arthur and Labatut, Vincent and Dufour,
Richard},
url = {https://hal.science/hal-03972448},
booktitle = {{Workshop on Computational Methods in the Humanities
2022}},
YEAR = {2022},
hal_id = {hal-03972448},
hal_version = {v1},
}
The dataset was originally published and annotated by Dekker et al (2019):
@Article{dekker-2019-evaluation_ner_social_networks_novels,
author = {Dekker, N. and Kuhn, T. and van Erp, M.},
journal = {PeerJ Computer Science},
title = {Evaluating named entity recognition tools for extracting social networks from novels},
year = {2019},
pages = {e189},
volume = {5},
doi = {10.7717/peerj-cs.189},
}