---
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:
- 10K<n<100K
---

# Epstein Files OCR — Datasets 1–8 (Early Release)

> **Work in Progress (WIP)**
>
> This is an early publication. We are actively working on improving OCR quality and expanding coverage.

## Dataset Summary

This dataset contains **page-level OCR output** (as Markdown) from a public release of documents related to **Jeffrey Epstein / the Epstein case**.

Each Markdown file represents **one scanned page** converted to text using an automated OCR pipeline. The dataset is designed for:
*   Question answering
*   Information retrieval
*   Downstream NLP tasks such as named entity recognition (NER), entity linking, and relationship extraction over investigative document collections.

### High-level Statistics (This Repository Snapshot)

*   **File format**: `*.md`
*   **Organization**: Flat directory of pages
*   **Page files**: `page_<N>.md` (e.g. `page_10000.md`)
*   **Number of page files**: **42,182** (plus this `README.md`)
*   **Approx size (uncompressed)**: **~172 MB**

## 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](https://github.com/ishumilin/epstein-chat)

## 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

## Languages

Primarily English (`en`).

## Dataset Structure

### Folder Layout

To satisfy Hugging Face repository limits (max 10,000 files per directory), pages are stored in subfolders under `pages/`:

```text
pages/
  00000-00999/
    page_1.md
    ...
  01000-01999/
  ...
  42000-42999/
```

### Data Instances

Each file contains OCR-extracted text in Markdown. Content varies widely:

*   Some pages are short identifiers (e.g. `EFTA00000500`).
*   Some pages contain tables (e.g. call logs) rendered as Markdown tables.
*   Some pages are narrative text.

**Example (truncated):**

```text
DATE 7/6/19
CASE ID 31E-NY-3027571
FBI
...
```

**Example (table excerpt, truncated):**

```text
| BILLED PHONE | CALL DATE | TIME | DIALED NUMBER | DEST NUMBER | ... |
| ... |
```

### Data Fields

This dataset is distributed as raw text files and does not ship a structured Arrow/Parquet schema.

Typical fields you may want to derive during ingestion:

*   `page_number` (integer parsed from filename)
*   `text` (the Markdown content)
*   `source_id` / `document_id` (not included in this flat export; see "Limitations")

### 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/combined-all-epstein-files_archive.torrent
    *   PDF: **`COMBINED_ALL_EPSTEIN_FILES.pdf`**

**Coverage in this dataset:** Currently corresponds to **datasets 1–8** from the upstream release.

### OCR / Preprocessing

OCR was performed on this dataset using a **proprietary model** provided by [Wild Ma-Gässli](https://wildma.ch).

Output was saved as Markdown, one file per page.

## Considerations for Using the Data

### Personal / Sensitive Information

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

**Redaction Policy:**

*   This dataset is published as **verbatim OCR output** derived from the upstream public PDFs.
*   **No additional redaction** (masking/removal) has been applied beyond what is present in the upstream source materials.

**Use Responsibly:**

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

Some pages contain explicit placeholders such as `[hidden text]` reflecting original redactions made by DOJ.

### Known Limitations

*   **OCR noise**: Recognition errors, formatting artifacts, missing characters.
*   **No document grouping**: In this snapshot, pages are stored as `page_<N>.md` without a stable link back to the originating PDF and page-in-PDF.
    *   If you have access to the original PDFs, consider publishing a `metadata.jsonl` with `{page_number, pdf_name, pdf_page_index, sha256, ...}`.

### 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`](./LICENSE) for the full CC0 1.0 legal text.

## Citation

If you use this dataset, please cite:

1.  The original [public release](https://www.justice.gov/epstein/doj-disclosures)
2.  This OCR [dataset](https://huggingface.co/datasets/ishumilin/epstein-files-ocr-datasets-1-8-early-release)