airefinery/esg_cid

ESG-CID: A Content Index Dataset for ESG Reports

Usage

from datasets import load_dataset

# Load the content index annotations
cid_dataset = load_dataset("airefinery/esg_cid", "cid")

# Load the fixed version with normalized standard_ids
cid_fixed = load_dataset("airefinery/esg_cid", "cid_fixed")

# Load PDF source data
cid_pdfs = load_dataset("airefinery/esg_cid", "pdfs")

Working with PDFs

The PDF bytes are stored in ["pdf"]["bytes"]. Here's how to use them with PyMuPDF:

import pymupdf

# Get a PDF from the dataset
pdf_item = cid_pdfs["dev"][0]
pdf_bytes = pdf_item["pdf"]["bytes"]
report_name = pdf_item["report_name"]

# Open and work with the PDF
with pymupdf.open(stream=pdf_bytes, filetype="pdf") as doc:
    print(f"{report_name}: {len(doc)} pages")

    # Extract text from first page
    first_page_text = doc[0].get_text()

    # Get page labels
    page_labels = doc.get_page_labels()

Citation

If you find this dataset useful in your research, please consider citing the following paper:

@misc{ahmed2025enhancingretrievalesgllmesgcid,
      title={Enhancing Retrieval for ESGLLM via ESG-CID -- A Disclosure Content Index Finetuning Dataset for Mapping GRI and ESRS}, 
      author={Shafiuddin Rehan Ahmed and Ankit Parag Shah and Quan Hung Tran and Vivek Khetan and Sukryool Kang and Ankit Mehta and Yujia Bao and Wei Wei},
      year={2025},
      eprint={2503.10674},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2503.10674}, 
}

License

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