ogulcanakca/epdk_corpus

Dataset Card for EPDK Electricity Market Corpus (v2)

Dataset Summary

This corpus contains high-quality Turkish text extracted from documents published by the Turkish Energy Market Regulatory Authority (EPDK – Enerji Piyasası Düzenleme Kurumu).
The source materials include regulations, board decisions, and official communiqués related to the electricity market legislation.

Version 2.0.0 introduces a complete re-extraction of the text using the Qwen-2.5-VL vision-language model, which achieves dramatically better OCR accuracy than Tesseract—particularly on scanned and complex multi-column PDFs.
The result is a significantly cleaner and more semantically faithful representation of the original legal texts.

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Version History

Version	Description	Date	Notes
v1.0.0	Initial release using Tesseract OCR (≈ 3.4 K docs)	2025-04	Baseline version. Stored under /v1.0.0/ branch.
v2.0.0	Re-extracted with Qwen-2.5-VL OCR (≈ 3.6 K docs), normalized fields (id, text, kind, method)	2025-10	Recommended for downstream use.

To load a specific version:

from datasets import load_dataset
ds = load_dataset("ogulcanakca/epdk_corpus", revision="v2.0.0")

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Intended Uses

Designed primarily for language-model domain adaptation and continued pre-training on Turkish regulatory language. Potential downstream tasks include:

• Legal Question Answering over EPDK documents
• Summarization of laws and regulations
• Document classification or clustering (e.g., tebliğ / karar / yönetmelik)
• Information retrieval and RAG training for energy-sector LLMs

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Languages

All text is in Turkish (tr).

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Data Fields

Field	Type	Description
id	string	Unique SHA-1-based identifier for the document
text	string	Cleaned text extracted from the source file
kind	string	File type (docx, pdf, xls, etc.)
method	string	Extraction method (python-docx, pandas, qwen-vl-ocr, etc.)

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Example Instance

{
  "id": "b3f7a6d9c49e",
  "text": "Enerji Piyasası Düzenleme Kurumundan:\nKURUL KARARI\nKarar No: 9284 Karar Tarihi: 02/04/2020\n...",
  "kind": "docx",
  "method": "python-docx"
}

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Data Structure & Access

• Format: JSONL (one document per line)
• Total examples: ≈ 3 577
• Dataset path: v2/final_corpus_dataset.jsonl

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@dataset{ogulcanakca_epdk_corpus_v2,
  author    = {Oğulcan Akca},
  title     = {EPDK Corpus (v2)},
  year      = {2025},
  url       = {https://huggingface.co/datasets/ogulcanakca/epdk_corpus}
}

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akca_ogulcan@hotmail.com