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AgriIR_dataset

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metadata

yaml:
  arxiv: 2604.16353
  annotations:
    - notes: >-
        Agricultural policy queries and knowledge entries for Indian
        agricultural information access
      schema: multichoice
  configs:
    - config_name: default
      dataset_info:
        features:
          - name: text
            dtype: string
          - name: metadata
            dtype: string
          - name: category
            dtype: string
          - name: quality_score
            dtype: float
        split: raw
        subset_num_bytes: 678000000
        total_num_examples: 15247
  language:
    - en
  license: cc-by-4.0
  modalities:
    - text
  papers:
    primary: https://doi.org/10.1007/978-3-032-21324-2_37
    arxiv: https://arxiv.org/abs/2604.16353
  tags:
    - agrir
    - agriculture
    - information-retrieval
    - rag
    - domain-specific
    - indian-agriculture
    - retrieval-augmented-generation
  type: domain-specific-knowledge-dataset

AgriIR Agricultural Knowledge Dataset

This dataset accompanies the AgriIR paper - a scalable framework for domain-specific knowledge retrieval in agricultural contexts. The dataset contains curated agricultural policy queries and retrieved knowledge entries specifically designed for Indian agricultural information access.

Dataset Overview

Total Entries: 15,247 agricultural knowledge entries
Domain: Indian Agricultural Information Access
Format: JSONL (JSON Lines)
Size: ~1.9GB (compressed ~678MB)
Language: English

Citation

If you use this dataset, please cite the original paper. The Springer/ECMIR version is the official peer-reviewed publication.

Springer/Conference Citation (Recommended for academic publications)

@InProceedings{10.1007/978-3-032-21324-2_37,
  author="Banerji Seal, Shuvam and Poddar, Aheli and Mishra, Alok and Roy, Dwaipayan",
  editor="Campos, Ricardo and Jatowt, Adam and Lan, Yanyan and Aliannejadi, Mohammad and Bauer, Christine and MacAvaney, Sean and Anand, Avishek and Ren, Zhaochun and Verberne, Suzan and Bai, Nan and Mansoury, Masoud",
  title="AgriIR: A Scalable Framework for Domain-Specific Knowledge Retrieval",
  booktitle="Advances in Information Retrieval",
  year="2026",
  publisher="Springer Nature Switzerland",
  address="Cham",
  pages="489--504",
  doi={10.1007/978-3-032-21324-2_37},
  isbn="978-3-032-21324-2"
}

arXiv Citation

@misc{BanerjiSeal2026AgriIR,
  title={AgriIR: A Scalable Framework for Domain-Specific Knowledge Retrieval},
  author={Shuvam Banerji Seal and Aheli Poddar and Alok Mishra and Dwaipayan Roy},
  year={2026},
  eprint={2604.16353},
  archivePrefix={arXiv},
  primaryClass={cs.IR},
  url={https://arxiv.org/abs/2604.16353}
}

Authors

Shuvam Banerji Seal GitHub | Email
Indian Institute of Science Education and Research, Kolkata, India
Aheli Poddar GitHub | Email
Institute of Engineering & Management, Kolkata, India
Alok Mishra Email
Indian Institute of Science Education and Research, Kolkata, India
Dwaipayan Roy GitHub | Email
Indian Institute of Science Education and Research, Kolkata, India

License

This dataset is released under the Creative Commons Attribution 4.0 International License.

For questions about the dataset, please contact the authors via email.