README.md

---
license:
  - gfdl
  - cc-by-sa-3.0
language:
  - de
task_categories:
  - text-generation
  - fill-mask
size_categories:
  - 1M<n<10M
tags:
  - wikipedia
  - german
  - language-modeling
  - pretraining
  - cleaned
pretty_name: German Wikipedia (Cleaned)
---

# German Wikipedia (Cleaned)

A cleaned, plain-text version of the German Wikipedia for language model
pre-training. Each line is a single article; wiki markup, references, and
boilerplate navigation sections have been removed.

| | |
|---|---|
| Articles | ~2,000,000 |
| Size | ~10 GB (UTF-8 plain text) |
| Format | JSONL, one `{"text": "..."}` object per line |
| Source dump | `dewiki-20260601-pages-articles-multistream.xml.bz2` |
| Source URL | <https://dumps.wikimedia.org/dewiki/20260601/> |
| License | GFDL + CC-BY-SA 3.0 (inherited) |
| Language | German (`de`) |

## What's in this dataset

Plain-text article bodies. Section structure (headers, paragraphs) is
preserved as line breaks; wiki markup, templates, infoboxes, tables,
image captions, magic words, references, and the standard
end-of-article navigation sections are stripped.

Every record is a single article. The corpus is suitable for:

- Continued pre-training of base language models on German
- Causal language modeling from scratch
- Masked language modeling (BERT-style)
- Domain-adaptive pre-training for German-heavy applications

## What was filtered out

The following pages from the raw MediaWiki dump are excluded:

- **Non-article namespaces** — `Wikipedia:`, `Portal:`, `Hilfe:`,
  `Kategorie:`, `Vorlage:`, `Modul:`, `MediaWiki:` (any namespace != 0)
- **Redirects**
- **Stubs** — articles with fewer than 1500 characters after markup
  stripping
- **Oversized articles** — articles longer than 80,000 characters after
  cleanup (typically list-articles and bot-generated entries)
- **Disambiguation pages** — titles containing "(Begriffsklärung)" or
  "(disambiguation)"
- **List pages** — titles starting with "Liste " or "List "

Within retained articles, the following residual cleanup is applied:

- Lines beginning with `mini|` are removed (leftover cells from stripped
  Infobox templates)
- Runs of three or more consecutive newlines are collapsed to two

## How to use

Load with the `datasets` library:

```python
from datasets import load_dataset

ds = load_dataset("gmrrh/de-wiki", split="train")

# ds[i]["text"] is the full article body as a single string

# Iterate for training
for ex in ds:
    text = ex["text"]
    # tokenize, pack into chunks, train
```

Streaming for environments where the ~10 GB download is inconvenient:

```python
from datasets import load_dataset

ds = load_dataset(
    "gmrrh/de-wiki",
    split="train",
    streaming=True,
)
for ex in ds:
    text = ex["text"]
    # ...
```

## Data fields

| Field | Type | Description |
|---|---|---|
| `text` | `string` | Article body, plain text, UTF-8, line-broken by section |

There is a single `train` split. No held-out splits are provided; this is
a pre-training corpus, not an evaluation benchmark.

## How this dataset was built

The pipeline is reproducible from public sources. Source code for the
cleaning scripts is published alongside this dataset.

1. **Download the raw dump** from
   `https://dumps.wikimedia.org/dewiki/<YYYYMMDD>/dewiki-<YYYYMMDD>-pages-articles-multistream.xml.bz2`.
   The dump used for the current version is `20260601`.
2. **Stream-parse** the MediaWiki XML with `mwxml` (forward-only
   `iterparse`, no full XML tree in memory).
3. **Drop** pages by namespace, redirect status, and title patterns
   before any expensive text processing.
4. **Strip wiki markup** with `mwparserfromhell.parse(text).strip_code(normalize=True, collapse=True)`,
   which removes templates, tables, wiki links, magic words, etc.
5. **Post-clean** the resulting plain text: drop residual `mini|` lines,
   collapse whitespace runs.
6. **Length-filter** to a 1,500–80,000 character band.
7. **Stream-write** to JSONL, one article per line.

A 7.6 GB compressed `.xml.bz2` produces a ~10 GB cleaned JSONL of
approximately 1.8 million articles, with an end-to-end runtime of roughly
2–4 hours on a single CPU.

## License and attribution

This dataset is derived from Wikipedia content, which is dual-licensed
under the **GNU Free Documentation License (GFDL)** and the
**Creative Commons Attribution-ShareAlike 3.0 License
(CC-BY-SA 3.0)**. See <https://dumps.wikimedia.org/legal.html> for
the full text.

If you build on top of this dataset and redistribute the derivative
work, the share-alike clause applies: the resulting work must be
released under a compatible license.

Required attribution when using this dataset:

> Contains modified data from Wikipedia, the free encyclopedia
> (<https://de.wikipedia.org/>), used under CC-BY-SA 3.0 / GFDL.

## Known limitations

- **Residual markup artifacts.** Markup stripping is heuristic. A small
  fraction of articles may retain table cells, list fragments, or
  template-rendered text that `mwparserfromhell` did not fully collapse.
- **Knowledge cutoff.** Coverage ends at the snapshot date of the source
  dump (`20260601` in this version). Events after that date are not
  present.
- **Wikipedia biases.** The corpus inherits the topical, demographic,
  and editorial biases of the German-language Wikipedia community.
  See <https://en.wikipedia.org/wiki/Wikipedia:Systemic_bias> for
  background.
- **German only.** No multilingual alignment is provided; cross-lingual
  training will require additional data sources.
- **Repetitive boilerplate.** End-of-article sections ("Literatur",
  "Siehe auch", "Kategorien", "Weblinks") are stripped, but
  introduction-style infobox cells may still appear in some articles.

## Intended use

- Pre-training and continued pre-training of German language models.
- Research on German-language NLP.

## Out-of-scope use

- Use as an authoritative reference for facts. Wikipedia is editable by
  anyone and contains errors; consult primary sources for citation.
- Production systems where factual accuracy is safety-critical.
- Any use that violates the GFDL or CC-BY-SA 3.0 terms, including
  redistribution under a more restrictive license.

## Citation

If you use this dataset in academic work, please cite the underlying
Wikipedia source:

```bibtex
@misc{wikimedia_2026_dump,
  author       = {{Wikimedia Foundation}},
  title        = {Wikimedia Downloads},
  howpublished = {\url{https://dumps.wikimedia.org}},
  note         = {German Wikipedia dump, snapshot 20260601},
  year         = {2026}
}
```

## Changelog

- **v1** — Initial release. ~2.0M articles, German Wikipedia dump
  snapshot `20260601`. Pipeline: `mwxml` stream-parse →
  `mwparserfromhell.strip_code()` → `mini|` regex → length filter
  1,500–80,000 chars.