Full dataset: documents, pages (3.1M w/ embeddings), entities (31M), topics, features, keywords, events, relationships

README.md

@@ -1,106 +1,71 @@
 ---
-license: mit
-task_categories:
-- text-classification
-- token-classification
-- text-mining
 language:
-- en
-tags:
-- government-documents
-- nlp
-- named-entity-recognition
-- declassified
-- jfk
-- cia
-- ocr
-- document-analysis
+  - en
+license: cc0-1.0
+task_categories:
+  - text-classification
+  - token-classification
+  - feature-extraction
 size_categories:
-- 100K<n<1M
+  - 100K<n<1M
+tags:
+  - declassified
+  - government
+  - historical
+  - ocr
+  - entities
+  - embeddings
 ---
 
 # Research Document Archive
 
-234,630 declassified U.S. government documents processed through a 13-step ML pipeline. 3.2 million pages OCR'd, 31 million named entities extracted and linked, 288 topic clusters identified.
-
-**Live platform:** [tanglewoodapp.com](https://tanglewoodapp.com)
-
-## Collections
-
-| Collection | Documents | Pages | Size |
-|---|---|---|---|
-| House Resolutions | 181,092 | 2,719,832 | 34.2 GB |
-| JFK Assassination Records | 35,979 | 241,860 | 22.5 GB |
-| CIA Stargate Program | 13,937 | 100,056 | 5.4 GB |
-| CIA MKUltra | 1,936 | 64,244 | 3.4 GB |
-| CIA Declassified | 1,605 | 29,744 | 2.4 GB |
-| Lincoln Archives | 21 | 9,330 | 962.9 MB |
+Computational analysis of **234,630 declassified U.S. government documents** across 7 archival collections. Output of a 13-step ML pipeline extracting OCR text, entities, topics, keywords, redactions, and semantic embeddings from 3.1 million pages.
 
-## ML Pipeline (13 Steps)
+## Files
 
-1. Document ingestion and format normalization
-2. OCR with Tesseract + post-correction
-3. Classification stamp detection (SECRET, CONFIDENTIAL, UNCLASSIFIED, etc.)
-4. Redaction detection and boundary mapping
-5. Named entity recognition (people, organizations, locations, dates)
-6. Entity disambiguation and cross-document linking
-7. Relationship extraction
-8. Topic modeling (LDA + BERTopic)
-9. Timeline event extraction
-10. Network graph construction
-11. Sentiment and tone analysis
-12. Document similarity clustering
-13. Index building for search and retrieval
+| File | Rows | Description |
+|------|------|-------------|
+| `documents.parquet` | 234,630 | Document metadata: id, source_section, file_path, file_hash, total_pages |
+| `pages/<section>.parquet` | 3.1M | Per-page OCR text + 1536-dim sentence-transformer embeddings. Sharded by collection. |
+| `entities/<section>.parquet` | 31M | Named entities (spaCy `en_core_web_lg`): PERSON, ORG, DATE, GPE, FAC, LOC, NORP, EVENT. Sharded by collection. |
+| `document_topics.parquet` | 234,629 | BART-large-MNLI zero-shot topic assignments (per doc, top-1 topic + probability) |
+| `document_features.parquet` | 1.17M | EAV feature table: `redaction_summary`, `forensic_metadata`, `bertopic`, `sentiment`, `topic_distribution`, `exact_duplicate` |
+| `document_keywords.parquet` | 3.5M | TF-IDF keywords (top 15 per document, unigrams + bigrams) |
+| `document_dates.parquet` | 234,630 | Inferred document dates (regex + header parsing) |
+| `document_events.parquet` | 296K | Document-to-historical-event correlations (20 crisis events) |
+| `historical_events.parquet` | 20 | Crisis event dictionary (event_name, date range, category, keywords) |
+| `entity_relationships.parquet` | 2.88M | Entity co-occurrence pairs with counts, distances, and sample documents |
 
-## Classification Stamps Detected
-
-| Stamp | Count |
-|---|---|
-| UNCLASSIFIED | 16,501 |
-| SECRET | 13,736 |
-| CLASSIFIED | 10,730 |
-| EXEMPT | 6,739 |
-| CONFIDENTIAL | 5,554 |
-| RESTRICTED | 4,722 |
-
-## Key Statistics
+## Collections
 
-- **31M** named entities extracted
-- **2.9M** entity cross-document links
-- **59,830** redactions detected and mapped
-- **288** topic clusters identified
-- **6** document collections spanning 1860s–2000s
+| source_section | Documents | Source |
+|---|---|---|
+| `cia_declassified` | 1,605 | CIA Reading Room |
+| `cia_mkultra` | 1,936 | MKULTRA release |
+| `cia_stargate` | 13,937 | Stargate remote viewing program |
+| `doj_disclosures` | — | DOJ public disclosures |
+| `house_resolutions` | 181,092 | House.gov bill text (GovInfo API) |
+| `jfk_assassination` | 35,979 | National Archives JFK release |
+| `lincoln_archives` | 21 | Library of Congress |
 
-## Usage
+## Loading
 
 ```python
 from datasets import load_dataset
+docs = load_dataset("datamatters24/research-document-archive", data_files="documents.parquet")
 
-ds = load_dataset("datamatters24/research-document-archive")
-
-# Filter by collection
-jfk = ds.filter(lambda x: x["collection"] == "jfk_assassination")
-
-# Search by entity
-cia_docs = ds.filter(lambda x: "CIA" in x["entities"])
+# Or load a specific sharded table:
+import pyarrow.parquet as pq
+pages = pq.read_table("hf://datasets/datamatters24/research-document-archive/pages/cia_mkultra.parquet")
 ```
 
-## Data Sources
-
-All documents are public record obtained from:
-- National Archives (NARA)
-- CIA FOIA Reading Room
-- Congress.gov
-- Library of Congress
+## Methodology
 
-## Citation
+- **OCR**: Tesseract + PyMuPDF
+- **NER**: spaCy `en_core_web_lg`
+- **Topics**: BART-large-MNLI (zero-shot) + BERTopic (unsupervised)
+- **Embeddings**: sentence-transformers/all-MiniLM-L6-v2 (384-dim) and OpenAI text-embedding-3-small (1536-dim) per page
+- **Redaction detection**: OpenCV contour analysis on PDF-rendered pages
+- **Entity relationships**: page-window co-occurrence with distance weighting
 
-```bibtex
-@misc{rubin2026researcharchive,
-  author = {Rubin, Theodore},
-  title = {Research Document Archive: ML Pipeline for Declassified U.S. Government Documents},
-  year = {2026},
-  publisher = {HuggingFace},
-  url = {https://huggingface.co/datasets/datamatters24/research-document-archive}
-}
-```
+Code: https://github.com/tedrubin80/Massivedata-Pull

dataset-metadata.json

@@ -0,0 +1,6 @@
+{
+  "title": "Research Document Archive",
+  "id": "theodorerubin/research-document-archive",
+  "licenses": [{"name": "CC0-1.0"}],
+  "keywords": ["declassified", "government", "ocr", "nlp", "entities", "embeddings", "historical"]
+}

document_dates.parquet

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document_events.parquet

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document_features.parquet

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document_keywords.parquet

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document_topics.parquet

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documents.parquet

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entities/cia_declassified.parquet

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entities/cia_mkultra.parquet

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entities/cia_stargate.parquet

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entities/doj_disclosures.parquet

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entities/house_resolutions.parquet

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entities/lincoln_archives.parquet

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entity_relationships.parquet

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