Datasets:

ishumilin
/

epstein-files-ocr-complete

license: cc0-1.0
task_categories:
  - question-answering
  - text-classification
  - text-retrieval
language:
  - en
tags:
  - epstein
  - jeffrey-epstein
  - epstein-files
  - epstein-case
  - court-documents
  - depositions
  - unsealed-documents
  - fbi-files
  - legal
  - flight-logs
  - private-jet
  - passenger-list
  - island-visits
  - us-law
  - news
  - politics
  - corruption
  - elite-networks
  - power-networks
  - social-graph
  - network-analysis
  - named-entities
  - entity-linking
  - relationship-extraction
  - relation-extraction
  - summarization
  - investigative-journalism
  - open-source-intelligence
  - osint
  - ocr
size_categories:
  - 1M<n<10M

Epstein Files — Complete OCR Dataset

This is a comprehensive, structured publication of the Epstein Files OCR dataset, significantly expanding upon the earlier Datasets 1-8 release.

Dataset Summary

This dataset contains page-level OCR output compiled from an extensive release of documents related to Jeffrey Epstein / the Epstein case.

Each row in this dataset represents one scanned PDF document from the original release using a proprietary automated OCR pipeline provided by Wild Ma-Gässli.

The dataset is designed for:

Question answering
Information retrieval
Downstream NLP tasks such as named entity recognition (NER), entity linking, and relationship extraction.

Enhancements from Previous Versions

Scale: This structured release covers 1,380,935 PDF documents, comprising over 2,700,000 total pages.
Format: Restructured from individual .md files into a more efficient Parquet format.
Document Linking: Each page retains its original document_id (e.g., EFTA00000001), resolving the limitation from earlier releases where pages could not be easily traced back to their source PDFs.

Supported Tasks

Text retrieval / search (BM25, hybrid, dense retrieval)
Question answering over retrieved context (RAG)
Entity extraction (names, places, phone numbers, dates) from noisy OCR
Social graph and network analysis

Languages

Primarily English (en).

Related Tools

This dataset is designed to be used with the Epstein Chat analysis tool, which provides a RAG (Retrieval-Augmented Generation) interface for querying these documents.

GitHub Repository: ishumilin/epstein-chat

Dataset Structure

The dataset is provided as a Parquet file, which works natively with Hugging Face's datasets library.

Data Fields

The schema contains the following fields:

document_id (string): The identifier of the original document/page (e.g., EFTA00146767).
content (string): The full OCR-extracted content for that specific document.

Example Row:

{
  "document_id": "EFTA00146767",
  "content": "Hey beautiful. Tried to call you back..."
}

Splits

No predefined train/validation/test splits.

Dataset Creation

Source Data

Primary source: The upstream Epstein Files release hosted at:
- Torrent: https://github.com/yung-megafone/Epstein-Files/blob/main/Torrent%20Files/epstein-files-structured-full-20250204.tar.zst.torrent

Coverage in this dataset: All PDF files from the upstream release.

OCR / Preprocessing

OCR was performed on this dataset using a proprietary model provided by Wild Ma-Gässli.

Considerations for Using the Data

Personal / Sensitive Information

These documents contain personal data (names, phone numbers, addresses, emails) and/or information about alleged criminal activity.

Redaction Policy:

This dataset is published as verbatim OCR output derived from the public source files.
No additional redaction (masking/removal) has been applied beyond what was already redacted by the DOJ or the original releasing entity.

Use Responsibly:

Comply with applicable laws and platform policies.
Avoid doxxing or harassment.
Do not treat OCR text as ground truth; always verify against the original page images/PDFs for high-stakes use.

Known Limitations

OCR noise: While improved, automated extraction can produce recognition errors, incorrect formatting artifacts, or miss obscure characters (especially on poor-quality scans or handwriting). Some pages contain explicit placeholders such as [hidden text] reflecting original redactions made by DOJ.
Content variance: Documents range from dense narrative text to unformatted tables and metadata tags.
Corrupted Source Files: Three files from the original release were severely corrupted and their contents remain unknown and unextracted:
- EFTA00645624.pdf
- EFTA01175426.pdf
- EFTA01220934.pdf

Biases

This dataset reflects:

The selection, redaction, and presentation choices of the original releasing institution.
OCR model performance characteristics (better on clean text, worse on handwriting / low-quality scans).

Licensing

See LICENSE for the full CC0 1.0 legal text.

Citation

If you use this dataset, please cite:

The original public release.
This dataset.