--- license: - gfdl - cc-by-sa-3.0 language: - de task_categories: - text-generation - fill-mask size_categories: - 1M | | 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//dewiki--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 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 > (), 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 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.