MuRIL is fine-tuned on Assamese CLASSER dataset for Fine-grained Named Entity Recognition.

This model is part of the AWED-FiNER project, which provides fine-grained NER solutions across 36 languages.

Paper: AWED-FiNER: Agents, Web applications, and Expert Detectors for Fine-grained Named Entity Recognition across 36 Languages for 6.6 Billion Speakers
GitHub: https://github.com/PrachuryyaKaushik/AWED-FiNER
Interactive Demo: AWED-FiNER Space

The tagset of MultiCoNER2 is a fine-grained tagset. The fine to coarse level mapping of the tags are as follows:

Location (LOC) : Facility, OtherLOC, HumanSettlement, Station
Creative Work (CW) : VisualWork, MusicalWork, WrittenWork, ArtWork, Software
Group (GRP) : MusicalGRP, PublicCORP, PrivateCORP, AerospaceManufacturer, SportsGRP, CarManufacturer, ORG
Person (PER) : Scientist, Artist, Athlete, Politician, Cleric, SportsManager, OtherPER
Product (PROD) : Clothing, Vehicle, Food, Drink, OtherPROD
Medical (MED) : Medication/Vaccine, MedicalProcedure, AnatomicalStructure, Symptom, Disease

Model performance:

Precision: 74.88
Recall: 75.62
F1: 75.25

Training Parameters:

Epochs: 6
Optimizer: AdamW
Learning Rate: 5e-5
Weight Decay: 0.01
Batch Size: 64

Contributors

Prachuryya Kaushik
Prof. Ashish Anand

Sample Usage

The AWED-FiNER agentic tool can be used to interact with expert models trained using this framework. Below is an example:

pip install smolagents gradio_client

from tool import AWEDFiNERTool

tool = AWEDFiNERTool(
    space_id="prachuryyaIITG/AWED-FiNER"
)

result = tool.forward(
    text="Jude Bellingham joined Real Madrid in 2023.",
    language="English"
)

print(result)

Citation

If you use this model, please cite the following papers:

@inproceedings{kaushik-anand-2025-classer,
    title = "{CLASSER}: Cross-lingual Annotation Projection enhancement through Script Similarity for Fine-grained Named Entity Recognition",
    author = "Kaushik, Prachuryya  and
      Anand, Ashish",
    booktitle = "Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics",
    month = dec,
    year = "2025",
    address = "Mumbai, India",
    publisher = "The Asian Federation of Natural Language Processing and The Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.ijcnlp-long.94/",
    pages = "1745--1760",
    ISBN = "979-8-89176-298-5",
}

@misc{kaushik2026awedfineragentswebapplications,
      title={AWED-FiNER: Agents, Web applications, and Expert Detectors for Fine-grained Named Entity Recognition across 36 Languages for 6.6 Billion Speakers}, 
      author={Prachuryya Kaushik and Ashish Anand},
      year={2026},
      eprint={2601.10161},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2601.10161}, 
}

@inproceedings{kaushik2026sampurner,
  title={SampurNER: Fine-grained Named Entity Recognition Dataset for 22 Indian Languages},
  author={Kaushik, Prachuryya and Anand, Ashish},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={40},
  year={2026}
}

@inproceedings{fetahu2023multiconer,
  title={MultiCoNER v2: a Large Multilingual dataset for Fine-grained and Noisy Named Entity Recognition},
  author={Fetahu, Besnik and Chen, Zhiyu and Kar, Sudipta and Oleg and Malmasi, Shervin},
  booktitle={Findings of the Association for Computational Linguistics: EMNLP 2023},
  pages={2027--2051},
  year={2023}
}