pysentimiento / robertuito-ner

Named Entity Recognition model for Spanish/English

robertuito-ner

Repository: https://github.com/pysentimiento/pysentimiento/

Model trained with the Spanish/English split of the LinCE NER corpus , a code-switched benchmark . Base model is RoBERTuito , a RoBERTa model trained in Spanish tweets.

Usage

If you want to use this model, we suggest you use it directly from the pysentimiento library as it is not working properly with the pipeline due to tokenization issues

from pysentimiento import create_analyzer

ner_analyzer = create_analyzer("ner", lang="es")

ner_analyzer.predict(
  "rindanse ante el mejor, leonel andres messi cuccitini. serresiete no existis, segui en al-nassr"
)
 

# [{'type': 'PER',
#   'text': 'leonel andres messi cuccitini',
#   'start': 24,
#   'end': 53},
#  {'type': 'PER', 'text': 'serresiete', 'start': 55, 'end': 65},
#  {'type': 'LOC', 'text': 'al-nassr', 'start': 108, 'end': 116}]

Results

Results are taken from the LinCE leaderboard

Citation

If you use this model in your research, please cite pysentimiento, RoBERTuito and LinCE papers:

@misc{perez2021pysentimiento,
      title={pysentimiento: A Python Toolkit for Sentiment Analysis and SocialNLP tasks},
      author={Juan Manuel Pérez and Juan Carlos Giudici and Franco Luque},
      year={2021},
      eprint={2106.09462},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
@inproceedings{perez2022robertuito,
  title={RoBERTuito: a pre-trained language model for social media text in Spanish},
  author={P{\'e}rez, Juan Manuel and Furman, Dami{\'a}n Ariel and Alemany, Laura Alonso and Luque, Franco M},
  booktitle={Proceedings of the Thirteenth Language Resources and Evaluation Conference},
  pages={7235--7243},
  year={2022}
}

@inproceedings{aguilar2020lince,
  title={LinCE: A Centralized Benchmark for Linguistic Code-switching Evaluation},
  author={Aguilar, Gustavo and Kar, Sudipta and Solorio, Thamar},
  booktitle={Proceedings of the 12th Language Resources and Evaluation Conference},
  pages={1803--1813},
  year={2020}
}