| --- |
| license: odc-by |
| task_categories: |
| - text-classification |
| language: |
| - en |
| - ru |
| - cs |
| - pl |
| - es |
| - zh |
| - lt |
| - sk |
| - fr |
| - pt |
| - de |
| - it |
| - sv |
| - nl |
| - bg |
| - uk |
| - tr |
| - ja |
| - hu |
| - ko |
| size_categories: |
| - 100K<n<1M |
| tags: |
| - docx |
| - word-documents |
| - document-classification |
| - ooxml |
| pretty_name: docx-corpus |
| --- |
| |
| # docx-corpus |
|
|
| The largest classified corpus of Word documents. 736K+ `.docx` files from the public web, classified into 10 document types and 9 topics across 76 languages. |
|
|
| ## Dataset Description |
|
|
| This dataset contains metadata for publicly available `.docx` files collected from the web. Each document has been classified by document type and topic using a two-stage pipeline: LLM labeling (Claude) of a stratified sample, followed by fine-tuned XLM-RoBERTa classifiers applied at scale. |
|
|
| ### Schema |
|
|
| | Column | Type | Description | |
| |--------|------|-------------| |
| | `id` | string | SHA-256 hash of the file (unique identifier) | |
| | `filename` | string | Original filename from the source URL | |
| | `type` | string | Document type (10 classes) | |
| | `topic` | string | Document topic (9 classes) | |
| | `language` | string | Detected language (ISO 639-1 code) | |
| | `word_count` | int | Number of words in the document | |
| | `confidence` | float | Classification confidence (min of type and topic) | |
| | `url` | string | Direct download URL for the `.docx` file | |
|
|
| ### Document Types |
|
|
| legal, forms, reports, policies, educational, correspondence, technical, administrative, creative, reference |
|
|
| ### Topics |
|
|
| government, education, healthcare, finance, legal_judicial, technology, environment, nonprofit, general |
| |
| ## Download Files |
| |
| Each row includes a `url` column pointing to the `.docx` file on our CDN. You can download files directly: |
| |
| ```python |
| from datasets import load_dataset |
| import requests |
|
|
| ds = load_dataset("superdoc-dev/docx-corpus", split="train") |
| |
| # Filter and download |
| legal_en = ds.filter(lambda x: x["type"] == "legal" and x["language"] == "en") |
| for row in legal_en: |
| resp = requests.get(row["url"]) |
| with open(f"corpus/{row['id']}.docx", "wb") as f: |
| f.write(resp.content) |
| ``` |
| |
| Or use the manifest API for bulk downloads: |
| |
| ```bash |
| curl "https://api.docxcorp.us/manifest?type=legal&lang=en" -o manifest.txt |
| wget -i manifest.txt -P ./corpus/ |
| ``` |
| |
| ## Links |
| |
| - **Website**: [docxcorp.us](https://docxcorp.us) |
| - **GitHub**: [superdoc-dev/docx-corpus](https://github.com/superdoc-dev/docx-corpus) |
| - **Built by**: [🦋 SuperDoc](https://superdoc.dev) |
| |
