SemEval2023

Experiment: Notebooks for fine tuning pre-trained language models

train.ipynb: fine tuning pre-trained language models

eval.ipynb: evaluate fine-tuned model

📄 Paper

You can read the full paper here: garNER at SemEval-2023: Simplified Knowledge Augmentation for Multilingual Complex Named Entity Recognition

🤖 Trained Models

All the trained models are available at the following link: Models

Citation

If you find this work useful, please consider citing:

@inproceedings{hossain2023garner,
  title={garNER at SemEval-2023: Simplified knowledge augmentation for multilingual complex named entity recognition},
  author={Hossain, Md Zobaer and So, Averie Ho Zoen and Silwal, Silviya and Gongora, H Andres Gonzalez and Samin, Ahnaf Mozib and Junaed, Jahedul Alam and Mazumder, Aritra and Saha, Sourav and Soha, Sabiha Tahsin},
  booktitle={Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)},
  pages={823--835},
  year={2023}
}