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README.md

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+---
+license: other
+license_name: odatl-1.0
+language:
+  - en
+  - de
+  - fr
+  - ru
+  - es
+  - it
+  - ja
+  - zh
+  - pt
+  - ar
+  - fa
+  - tr
+  - pl
+  - nl
+  - id
+  - ko
+  - vi
+  - uk
+  - ca
+  - hu
+  - fi
+  - cs
+  - ro
+  - sv
+size_categories:
+  - 1M<n<10M
+task_categories:
+  - text-generation
+  - feature-extraction
+tags:
+  - wikipedia
+  - corpus
+  - cleaned
+  - pretraining
+pretty_name: Scraped-Data (Cleaned Wikipedia Corpus)
+---
+
+# Scraped-Data
+
+A multi-language corpus of **~8.8 million** cleaned Wikipedia article records,
+scraped, parsed, and cleaned at scale on a CPU-only Google Colab session.
+
+## Files
+
+| File | Size | Contents |
+|---|---|---|
+| `corpus_batch1.clean.zip` | 4.80 GB | ~2.9M docs |
+| `corpus_batch2.clean.zip` | 4.85 GB | ~2.5M docs |
+| `corpus_batch3.clean.zip` | 4.91 GB | ~2.3M docs |
+
+Each archive contains a single JSONL file (`clean.jsonl`), one JSON object per line.
+
+## Schema
+
+```json
+{"src": "wiki", "url": "...", "title": "...", "chars": 1234, "text": "..."}
+```
+
+- `src` — source type (`wiki`)
+- `url` — canonical article URL
+- `title` — article title (trimmed)
+- `chars` — character count of `text`
+- `text` — cleaned plain-text body
+
+## Provenance
+
+Sourced from the official `wikimedia/wikipedia` dump snapshot `20231101`
+(parquet shards), which itself derives from Wikipedia dumps published by the
+Wikimedia Foundation. Underlying articles are © their respective Wikipedia
+contributors and are dual-licensed under CC-BY-SA; this compilation is
+additionally distributed under ODATL-1.0 (below). Attribution for upstream
+content must be preserved by downstream users in accordance with both
+licenses.
+
+## Cleaning pipeline
+
+1. Segmented parallel HTTP download of source shards (~200 Mbps sustained)
+2. Multi-process zstd/parquet decode with orjson serialization
+3. Per-record cleaning: control-character stripping, tab/NBSP removal,
+   CRLF normalization, blank-line collapse, email redaction (`[email]`)
+4. Minimum length gate (280 chars), empty-text drop
+5. Title+URL exact-duplicate removal across each batch
+6. Validation pass: every emitted record is valid UTF-8 JSON
+
+## License
+
+This dataset is released under the **Open Data Attribution Training
+Disclosure License (ODATL-1.0)**, reproduced in full below.
+
+---
+
+# Open Data Attribution Training Disclosure License (ODATL-1.0)
+
+Version 1.0 — July 2026
+
+A permissive open-data license requiring attribution and mandatory disclosure of AI training use.
+
+## SECTION 1 — DEFINITIONS
+
+**1.1** "Dataset" refers to the collection of data, files, metadata, annotations, structures, or any other materials distributed under this License, including any updates, subsets, or modified versions.
+
+**1.2** "Licensor" refers to the entity or individual who releases the Dataset under this License.
+
+**1.3** "Licensee" refers to any person, organization, or system that accesses, uses, modifies, redistributes, or incorporates the Dataset.
+
+**1.4** "Model" refers to any machine learning system, artificial intelligence system, algorithm, statistical model, or computational process trained, fine-tuned, evaluated, or otherwise developed using the Dataset.
+
+**1.5** "Public Notice" refers to a clear, visible, and publicly accessible statement acknowledging use of the Dataset.
+
+**1.6** "Derivative Dataset" refers to any dataset created by modifying, transforming, filtering, augmenting, or otherwise altering the original Dataset.
+
+**1.7** "Derivative Model" refers to any Model whose training data includes the Dataset or any Derivative Dataset.
+
+## SECTION 2 — GRANT OF RIGHTS
+
+**2.1** The Licensor grants the Licensee a worldwide, royalty-free, non-exclusive, irrevocable permission to:
+- Use, copy, and redistribute the Dataset for any purpose.
+- Modify, transform, or build upon the Dataset.
+- Create Derivative Datasets.
+- Train, fine-tune, evaluate, or otherwise use the Dataset for machine learning or AI development.
+- Create Derivative Models based on the Dataset.
+
+**2.2** These rights are intended to be compatible with open-source and open-data principles, including but not limited to CC-BY, ODC-BY, and other permissive data licenses.
+
+**2.3** No patent rights are granted or implied by this License.
+
+## SECTION 3 — MANDATORY ATTRIBUTION
+
+**3.1** Any public use, redistribution, publication, or derivative work involving the Dataset must include the following attribution:
+
+> "This work uses data provided under the Open Data Attribution Training Disclosure License (ODATL-1.0)."
+
+**3.2** Attribution must appear in:
+- Documentation
+- Research papers
+- Model cards
+- Public datasets
+- Product descriptions
+- Any public-facing material referencing the Dataset
+
+**3.3** Attribution must remain intact and may not be removed, obscured, or altered.
+
+## SECTION 4 — MANDATORY TRAINING DISCLOSURE
+
+**4.1** If the Dataset is used to train, fine-tune, evaluate, or otherwise develop any Model, the Licensee must provide a Public Notice stating:
+
+> "This model was trained using data provided under the Open Data Attribution Training Disclosure License (ODATL-1.0)."
+
+**4.2** This disclosure must appear in:
+- Model cards
+- Public releases of the Model
+- Research publications
+- Technical documentation
+- Product descriptions
+- Any public announcement or description of the Model
+
+**4.3** Disclosure must be truthful, visible, and accessible to the general public.
+
+**4.4** Failure to provide this disclosure immediately terminates all rights granted under this License.
+
+## SECTION 5 — REDISTRIBUTION REQUIREMENTS
+
+**5.1** If the Licensee redistributes the Dataset or any Derivative Dataset, the Licensee must:
+- Include this License in full.
+- Clearly indicate any modifications made.
+- Preserve all attribution and disclosure requirements.
+
+**5.2** Derivative Datasets may be dual-licensed under other open-data licenses, provided this License remains included and enforceable.
+
+## SECTION 6 — OPEN-SOURCE COMPATIBILITY
+
+**6.1** This License is designed to be compatible with:
+- Open Data Commons Attribution (ODC-BY)
+- Creative Commons Attribution (CC-BY)
+- Open-source AI research workflows
+- Open-data distribution platforms
+
+**6.2** Redistribution through open-source repositories (e.g., GitHub, HuggingFace, Kaggle) is permitted and encouraged.
+
+**6.3** Licensees may combine the Dataset with other open datasets, provided attribution and training disclosure obligations remain intact.
+
+## SECTION 7 — PROHIBITED USES
+
+**7.1** The Licensee may not:
+- Claim exclusive ownership of the Dataset.
+- Remove or alter attribution or disclosure requirements.
+- Use the Dataset in violation of applicable laws or regulations.
+- Misrepresent the origin, nature, or licensing of the Dataset.
+
+**7.2** The Licensee may not apply technical or legal measures that restrict others from exercising rights granted under this License.
+
+## SECTION 8 — NO WARRANTY
+
+**8.1** The Dataset is provided "as-is," without warranty of any kind, express or implied.
+
+**8.2** The Licensor is not liable for any damages, losses, or claims arising from use of the Dataset or any Derivative Model.
+
+## SECTION 9 — TERMINATION
+
+**9.1** Rights under this License automatically terminate if the Licensee:
+- Fails to provide required attribution.
+- Fails to provide required training disclosure.
+- Violates any other term of this License.
+
+**9.2** Rights may be reinstated upon correction of the violation, unless the Licensor explicitly revokes permission.
+
+## SECTION 10 — ACCEPTANCE
+
+**10.1** By accessing or using the Dataset, the Licensee agrees to be bound by the terms of this License.
+
+**10.2** Continued use of the Dataset constitutes ongoing acceptance of all terms.
+
+## SECTION 11 — CONTACT
+
+**11.1** For permissions beyond this License, contact the Licensor.