Initial dataset release — MagTina350m pretrain corpus slice

README.md

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+---
+license: cc0-1.0
+language:
+- pt
+pretty_name: Diário Oficial da União 2025-2026 (DO1 + DO1E)
+size_categories:
+- 10K<n<100K
+task_categories:
+- text-generation
+tags:
+- pt-br
+- brazilian-portuguese
+- government
+- legal
+- dou
+- diario-oficial
+- pretraining
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/*.parquet
+---
+
+# Diário Oficial da União 2025-2026 (DO1 + DO1E)
+
+Part of the **MagTina350m pretrain corpus release** by [Dataseek](https://dataseek.com.br)
+under the Magestic.ai brand. This is one of nine silver-layer datasets that fed
+[`dataseek/magtina350m-base`](https://huggingface.co/dataseek/magtina350m-base).
+
+## Summary
+
+20 K articles from the Brazilian Official Federal Gazette covering 2025-2026 — sections DO1 (regular edition) and DO1E (extra edition). Rich structured metadata: publication date, edition, page, PDF URL, ementa (summary), full text. Small corpus but high signal for legal/admin PT-BR.
+
+## Source and collection method
+
+Source: INLABS portal — https://inlabs.in.gov.br/ → daily ZIP downloads → XML parse → DO1 + DO1E section filter → dedup by `id_materia`.
+
+**ETL script (in the MagTina1B repository):** [`scripts/etl/09_dou_2026_v1.py`](https://huggingface.co/dataseek/magtina350m-base) *(public release of the ETL scripts is on the roadmap; until then the data card below documents the recipe in full).*
+
+## Filters and deduplication
+
+The following filters were applied before this dataset reached its silver
+(release-ready) state:
+
+- Sections DO1 (regular) and DO1E (extra) only
+- Dedup by `id_materia`
+
+Global URL-normalised deduplication was applied across all web-derived corpora
+(`webpages`, `news`, `blogs`) so the same article does not appear twice across
+those three datasets.
+
+## Schema
+
+| Column | Type | Description |
+|---|---|---|
+| `id_materia` | `string` | INLABS materia identifier. |
+| `article_id` | `string` | Per-article id within materia. |
+| `pub_name` | `string` | Publication identifier (e.g. 'DO1'). |
+| `pub_date` | `timestamp` | Publication date. |
+| `art_type` | `string` | Article type. |
+| `art_category` | `string` | Article category. |
+| `art_class` | `string` | Article subclass. |
+| `edition_number` | `string` | Edition number. |
+| `page_number` | `string` | Page in the printed edition. |
+| `pdf_url` | `string` | URL to the official PDF. |
+| `identifica` | `string` | Short identifier line (e.g. ato number). |
+| `titulo` | `string` | Article title. |
+| `ementa` | `string` | Official summary (when present). |
+| `text` | `string` | Full article body. |
+| `n_chars` | `int32` | Character count of `text`. |
+| `n_words` | `int32` | Word count of `text`. |
+
+Columns dropped at export (kept private as ETL internals): *none*
+
+## Size statistics
+
+| Metric | Value |
+|---|---:|
+| Rows | 20.1 K (20,124) |
+| Characters | 75.63 M (75,633,413) |
+| Estimated tokens (PT-BR, chars / 4.5) | 16.81 M |
+| Compressed Parquet on disk | ~0.04 GB |
+
+**Used in MagTina350m pretrain:** 0.017 B tokens
+(0.1 % of MagTina350m's 17.39 B-token pretrain budget).
+
+## How to load
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("dataseek/ptbr-dou", split="train", streaming=True)
+for row in ds.take(5):
+    print(row["text"][:200])
+```
+
+Streaming is recommended for the larger configs. For the smaller datasets
+(`ptbr-dou`, `ptbr-books-publicos`) eager loading is fine.
+
+## Licensing
+
+CC0 1.0 / Public Domain. Official acts of the Brazilian federal government are not protected by copyright (Lei 9.610/98 art. 8 § I). Freely redistributable.
+
+**Upstream attribution:** INLABS / Imprensa Nacional — https://inlabs.in.gov.br/ (Brazilian Federal Press Office)
+
+## Citation
+
+If you use this dataset, please cite both the upstream source and MagTina350m:
+
+```bibtex
+@misc{magtina350m_pretrain_2026,
+  title  = {MagTina350m pretrain corpus — Diário Oficial da União 2025-2026 (DO1 + DO1E)},
+  author = {Frasson, Ricardo and {Dataseek Team}},
+  year   = 2026,
+  publisher = {Hugging Face},
+  url    = {https://huggingface.co/datasets/dataseek/ptbr-dou}
+}
+```
+
+Please also honour the upstream license terms — for CC-BY-derived data,
+attribution to the upstream creators is mandatory; for CC-BY-SA, downstream
+derivatives must remain CC-BY-SA-compatible.
+
+## Intended use
+
+- Pre-training, continued pre-training, or domain-adapting of Brazilian Portuguese
+  language models.
+- PT-BR NLP research where statistically representative public-web / academic /
+  legal / encyclopedic data is needed.
+- Reproducing or improving on the MagTina350m result.
+
+## Known limitations and PII statement
+
+- **Text was NOT PII-scrubbed.** URLs, emails, phone numbers and personal names
+  that occurred in the source data may still be present. We strip zero-width
+  characters and normalise Unicode but we do not run an NER pass.
+- **Crawled data carries upstream biases** of CommonCrawl, Wikipedia, news outlets
+  and academic institutions present in the source. We have not audited these.
+- **No safety filtering** beyond langid and basic alpha-ratio gates. Hate-speech,
+  spam and adult content present in the source remain unless caught incidentally.
+- **Provenance preserved at row level.** Every row has either a `url`, `source` or
+  `doc_id` column that points back to upstream — this is intentional, so consumers
+  can re-license, redact or filter.
+
+## Related releases
+
+- **Model:** [`dataseek/magtina350m-base`](https://huggingface.co/dataseek/magtina350m-base) (354.6 M params, pretrained on this corpus + 8 sibling datasets)
+- **Instruct model:** [`dataseek/magtina350m-instruct`](https://huggingface.co/dataseek/magtina350m-instruct)
+- **Sibling datasets:** see `dataseek/ptbr-*` for all nine corpora
+
+## License
+
+[cc0-1.0](https://spdx.org/licenses/cc0-1.0.html)

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