Datasets:
source_file stringlengths 35 37 | chunk_index int64 0 1.34k | text stringlengths 20 200 | embedding listlengths 768 768 |
|---|---|---|---|
IMAGES-005-HOUSE_OVERSIGHT_020367.txt | 0 | 215
The final choice he was made to board a non-stop flight to Moscow on June 23, 2013.
To remain in Hong Kong once a criminal complaint was leveled against him would have meant
that, at the very min | [
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IMAGES-005-HOUSE_OVERSIGHT_020367.txt | 1 | s words.
Snowden chose, if he had any choice left at all, the Russian option. Just as he believed Chinese
intelligence could protect him in Hong Kong from the United States, he could assume that the
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IMAGES-005-HOUSE_OVERSIGHT_020367.txt | 2 | two years.
He arranged the encrypted channel with Poitras in February 2013, three months before he would
induce her to come to Hong Kong. He made contact with a foreign diplomatic mission at least a
m | [
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IMAGES-001-HOUSE_OVERSIGHT_011104.txt | 0 | What matters is return. I don’t have to specify “risk-adjusted” return so long as |
describe the collective scale alone. Collective return is implicitly average-risk return.
I prioritize it on the rea | [
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IMAGES-001-HOUSE_OVERSIGHT_011104.txt | 1 | these I question.
I] don’t think much of his view that intended saving (consumption foregone)
becomes actual saving only if invested, and becomes an equal amount of physical
capital growth if it is. | [
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TEXT-001-HOUSE_OVERSIGHT_031683.txt | 0 | From: J [jeevacation@gmail.com]
Sent: 5/30/2019 9:34:38 PM
To: Michael Wolff
Subject: Re:
maybe as a favor to trump. in exchange for yemen and iran support. . smells doesnt it?
On Thu, May 30, 20 | [
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IMAGES-005-HOUSE_OVERSIGHT_018820.txt | 0 | Area Analysis 10
At the national level, the U.S. Virgin Islands elects a delegate to Congress from its at-large
congressional district. However, the elected delegate, while able to vote in committee, | [
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IMAGES-005-HOUSE_OVERSIGHT_018820.txt | 1 | 46,784 2.3%
. Civilian employment 47,301 48,640 49,547 49,589 48,863 47,272 46,124 44,659 41,207 40,687 ~3B.3%
t Unemployment rate (percent) 7.1% 6.2% 5.9% 58% 76% 8.1% 8.9% 11.7% 13.4% 13.0% 14.2%
G | [
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IMAGES-009-HOUSE_OVERSIGHT_027193.txt | 0 | Time: 03/01/17 04:45:15 AM (510065115)
Flags: 1060865
Is Read: Yes
Is Invitation: No
GUID: D79S5CSCB-2EC2-4082-BCS5D-23939C85878B
Message: So they will rally
Sender: e:jeeitunes@gmail.com
Time: | [
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IMAGES-003-HOUSE_OVERSIGHT_014855.txt | 0 | Case 9:0€-ase8D T5é6cK AWK 3B RU BenDs6edmémieieh bh ALB De/dk4i 04/BAGH15 oP&ébe 9 of 10
id. at 10). Petitioners do not contend that Jane Doe 3 and Jane Doe 4’s “participation in this
case” can only | [
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IMAGES-003-HOUSE_OVERSIGHT_014855.txt | 1 | and non-
cumulative.
° The Government contends that Jane Doe 4 is not a true “victim” in this case because
she was not known at the time the Government negotiated the non-prosecution agreement, and
a | [
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IMAGES-004-HOUSE_OVERSIGHT_017182.txt | 0 | 4.2.12
WC: 191694
defended the right of skinny dippers to an isolated section of the Cape Cod National Seashore.
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End of preview. Expand in Data Studio
Epstein Files Document Embeddings
Text embeddings generated from the House Oversight Committee's Epstein document release.
Source Dataset
This dataset is derived from: tensonaut/EPSTEIN_FILES_20K
The source dataset contains OCR'd text from the original House Oversight Committee PDF release.
Dataset Structure
| Field | Type | Description |
|---|---|---|
| source_file | string | Source document filename |
| chunk_index | int | Position of chunk within document |
| text | string | Original document chunk text |
| embedding | list[float] | 768-dimensional embedding vector |
Usage
from datasets import load_dataset
import numpy as np
# Load the dataset
dataset = load_dataset("BoxesBlue/epstein-files-nov11-25-house-post-ocr-embeddings")
# Semantic search example
def search(query_embedding, top_k=5):
similarities = []
for item in dataset['train']:
emb = np.array(item['embedding'])
sim = np.dot(query_embedding, emb)
similarities.append((sim, item['text'], item['source_file']))
return sorted(similarities, reverse=True)[:top_k]
Generation Process
- Source text from tensonaut/EPSTEIN_FILES_20K
- Text chunked into segments for embedding
- Embeddings generated using Ollama nomic-embed-text (768-dim)
- Uploaded to HuggingFace for public access
License
CC-BY-4.0. Original documents are public records from U.S. House Oversight Committee.
Acknowledgments
- Source dataset: tensonaut/EPSTEIN_FILES_20K
- Original release: U.S. House Committee on Oversight and Accountability
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