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:

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:

curl "https://api.docxcorp.us/manifest?type=legal&lang=en" -o manifest.txt
wget -i manifest.txt -P ./corpus/

Links

• Website: docxcorp.us
• GitHub: superdoc-dev/docx-corpus
• Built by: 🦋 SuperDoc