transformers pytorch bert token-classification legal pt dataset:bergoliveira/pl-corpus license:mit autotrain_compatible endpoints_compatible region:us
---
datasets:
- bergoliveira/pl-corpus
language:
- pt
license: mit
pipeline_tag: token-classification
tags:
- legal
---
# bertimbau-base-ulyssesner_br-bcod-self_learning

<!-- Provide a quick summary of what the model is/does. -->


This model is a fine-tuned version of the [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-large-portuguese-cased), utilizing self-learning techniques with data sourced from the UlyssesNER-Br corpus and bill summaries from the Brazilian Chamber of Deputies.

Paper accepted at 16th International Conference on Computational Processing of Portuguese (PROPOR 2024).

Paper Link: https://aclanthology.org/2024.propor-1.30/

Bibtex:

@inproceedings{nunes-etal-2024-named,
    title = "A Named Entity Recognition Approach for {P}ortuguese Legislative Texts Using Self-Learning",
    author = "Nunes, Rafael Oleques  and
      Balreira, Dennis Giovani  and
      Spritzer, Andr{\'e} Suslik  and
      Freitas, Carla Maria Dal Sasso",
    editor = "Gamallo, Pablo  and
      Claro, Daniela  and
      Teixeira, Ant{\'o}nio  and
      Real, Livy  and
      Garcia, Marcos  and
      Oliveira, Hugo Gon{\c{c}}alo  and
      Amaro, Raquel",
    booktitle = "Proceedings of the 16th International Conference on Computational Processing of Portuguese",
    month = mar,
    year = "2024",
    address = "Santiago de Compostela, Galicia/Spain",
    publisher = "Association for Computational Lingustics",
    url = "https://aclanthology.org/2024.propor-1.30",
    pages = "290--300",
}
