| | --- |
| | language: |
| | - es |
| | license: cc-by-4.0 |
| | tags: |
| | - history |
| | - spain |
| | - 23-F |
| | - declassified-documents |
| | - transcripts |
| | - coup-attempt |
| | - education |
| | - spanish-transition |
| | - document-ai |
| | - ocr |
| | task_categories: |
| | - image-to-text |
| | - text-generation |
| | - question-answering |
| | pretty_name: "Expediente 23-F: Declassified Documents from the 1981 Spanish Coup Attempt" |
| | size_categories: |
| | - 1K<n<10K |
| | --- |
| | |
| | # Expediente 23-F: Declassified Documents from the 1981 Spanish Coup Attempt |
| |
|
| | A page-level multimodal dataset of declassified Spanish government documents related to the failed coup d'etat of February 23, 1981 (known as 23-F). Each row contains a rendered page image paired with its extracted text, sourced from official state archives. |
| |
|
| | ## Historical Context |
| |
|
| | On February 23, 1981, Lieutenant Colonel Antonio Tejero stormed the Spanish Congress of Deputies with armed Guardia Civil officers during the investiture vote of Prime Minister Leopoldo Calvo-Sotelo. The coup failed after King Juan Carlos I publicly opposed it in a televised address. These documents were declassified and published by the Spanish Government through the *Portal de Archivos Estatales*. |
| |
|
| | ## Dataset Schema |
| |
|
| | | Column | Type | Description | |
| | |---|---|---| |
| | | `image` | `Image` | Rendered page image (150 DPI) | |
| | | `pdf_source` | `string` | Relative path to the original PDF or image file | |
| | | `page_number` | `int32` | Page number within the source document (1-indexed) | |
| | | `text` | `string` | Extracted text for the page (OCR or pdf-parse) | |
| | | `ministry` | `string` | Originating ministry (`interior`, `exteriores`, `defensa`) | |
| | | `archive_id` | `string` | Archival signature (e.g., `AGA-83-07633`, `AGMAE-R39017`) | |
| |
|
| | ## Dataset Statistics |
| |
|
| | | Metric | Value | |
| | |---|---| |
| | | **Total rows (pages)** | 1,224 | |
| | | **Source documents** | 167 | |
| | | **Text coverage** | 100% (all pages have extracted text) | |
| | | **Total extracted text** | ~12.6 million characters | |
| | | **File types** | 155 PDFs (92.8%), 12 JPGs (7.2%) | |
| |
|
| | ### Documents by Ministry |
| |
|
| | | Ministry | Documents | Description | |
| | |---|---|---| |
| | | `defensa` | 108 | Military intelligence reports (CESID/CNI), internal memos | |
| | | `exteriores` | 31 | Diplomatic cables, embassy communications, verbal notes | |
| | | `interior` | 28 | Wiretap transcripts from the Guardia Civil, phone intercepts between conspirators | |
| |
|
| | ### Document Characteristics |
| |
|
| | | Property | Breakdown | |
| | |---|---| |
| | | **Format** | 90 typed, 73 scanned, 4 handwritten | |
| | | **Classification level** | 88 *secreto*, 77 *reservado*, 2 *confidencial* | |
| | | **Pages per document** | Min: 1, Max: 312, Mean: 7.3 | |
| | | **Text length per document** | Min: 130 chars, Median: 26.8K chars, Max: 3.45M chars | |
| |
|
| | ## Data Processing Pipeline |
| |
|
| | ### Image Rendering |
| | - **Tool:** `pdf2image` + Poppler |
| | - **Resolution:** 150 DPI (PNG) |
| | - **JPG documents** are loaded directly as single-page images |
| |
|
| | ### Text Extraction |
| | Two extraction methods were used depending on document type: |
| |
|
| | 1. **pdf-parse** (typed documents): Direct text extraction from digitally-created PDFs |
| | 2. **Vision-Language OCR** (scanned/handwritten documents): |
| | - **Model:** [`mlx-community/GLM-OCR-bf16`](https://huggingface.co/mlx-community/GLM-OCR-bf16) running on Apple Silicon via MLX |
| | - **Input resolution:** 200 DPI |
| | - **Max tokens per page:** 8,192 |
| | - **Post-processing:** Whitespace normalization, paragraph structure preservation |
| |
|
| | The `isOcrText` field in the source metadata indicates which method was used per document. |
| |
|
| | ## Usage |
| |
|
| | ```python |
| | from datasets import load_dataset |
| | |
| | ds = load_dataset("JorgeAV/23f-expediente") |
| | |
| | # Display a page |
| | print(ds["train"][0]["text"]) |
| | ds["train"][0]["image"].show() |
| | |
| | # Filter by ministry |
| | interior = ds["train"].filter(lambda x: x["ministry"] == "interior") |
| | |
| | # Get all pages from a specific document |
| | doc_pages = ds["train"].filter(lambda x: x["pdf_source"] == "interior/guardia-civil/23F_1_conversacion_gc_tejero.pdf") |
| | ``` |
| |
|
| | ## Intended Uses |
| |
|
| | - **Historical research** on the Spanish Transition to democracy |
| | - **Document AI** benchmarking: OCR, layout analysis, and document understanding on Spanish historical documents |
| | - **NLP in Spanish**: text extraction quality evaluation, named entity recognition on official/archival language |
| | - **Educational projects** about 20th-century European political history |
| |
|
| | ## Limitations |
| |
|
| | - OCR quality is lower on handwritten documents (4 out of 167) |
| | - Some scanned pages may contain text artifacts or recognition errors |
| | - Text extraction from multi-column layouts may not preserve reading order perfectly |
| | - All text is in Spanish; no translations are provided |
| |
|
| | ## Source & License |
| |
|
| | - **Original documents:** Public domain (declassified records from the Spanish Government, published via the *Portal de Archivos Estatales*) |
| | - **Structured dataset:** [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/) |
| |
|
| | ## Associated Project |
| |
|
| | This dataset powers [23f-expediente](https://github.com/JorgeAV/23f-expediente), an interactive educational web application with an FBI/spy case-file aesthetic for exploring the 23-F documents. |
| |
|
