Canonical corpus freeze v0.1.0

README.md

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+---
+pretty_name: PT-BR Creative Corpus
+language:
+- pt
+license: other
+task_categories:
+- text-generation
+tags:
+- pt-br
+- brazilian-portuguese
+- creative-writing
+- literature
+- pretraining
+- continued-pretraining
+configs:
+- config_name: corpus
+  default: true
+  data_files:
+  - split: corpus
+    path: "data/corpus/*.parquet"
+- config_name: documents
+  data_files:
+  - split: documents
+    path: "data/documents/*.parquet"
+- config_name: review_inventory
+  data_files:
+  - split: review
+    path: "data/review_inventory/*.parquet"
+- config_name: curation_lineage
+  data_files:
+  - split: lineage
+    path: "data/curation_lineage/*.parquet"
+- config_name: audit_metrics
+  data_files:
+  - split: audit
+    path: "data/audit_metrics/*.parquet"
+---
+
+# PT-BR Creative Corpus v0.1.0
+
+A curated Brazilian-Portuguese creative-writing corpus for continued pretraining / midtraining research.
+
+## Status
+
+This is the **canonical corpus freeze**, not a final model-specific training build.
+
+- Canonical text units: **1,354**
+- Document/edition entities: **803**
+- Characters: **82,538,439**
+- Words (whitespace count): **13,929,410**
+- Historical project estimate: **18,339,188 chars/4.5 tokens**, retained only in the `audit_metrics` config.
+
+The canonical `corpus` config deliberately contains **no generic token-count column**. Exact token counts belong to tokenizer-specific CPT builds.
+
+## Load a small sample without loading the corpus
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("oliveirabruno01/ptbr-creative-cpt", "corpus", split="corpus", streaming=True)
+for row in ds.take(100):
+    ...
+```
+
+## Load the full canonical corpus
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("oliveirabruno01/ptbr-creative-cpt", "corpus", split="corpus")
+```
+
+For CPT, derive a model/run-specific training build from this corpus:
+
+```text
+canonical corpus
+  -> work/author-level benchmark holdout + decontamination
+  -> target model tokenizer
+  -> EOS/document-boundary policy
+  -> sequence packing for chosen context length
+  -> trainer-specific binary/memmap format
+```
+
+Tokenized/packed sequences are intentionally **not** baked into this repository.
+
+## Text-unit model
+
+Most corpus rows are complete selected works/documents. FE-Unicamp is intentionally different: modern scholarly editions were segmented and only blocks classified as primary historical creative literature were retained. Those rows use `unit_kind="selected_segment"` and point to a real parent edition through `parent_document_id`.
+
+For FE, `primary_authors` refers to the historical literary writer; modern scholarly editors are kept separately in `editors`.
+
+## Orthography
+
+`text_variant="original"` means the extracted source orthography is preserved. Any future AO90-normalized material must be released as a separate derived variant, never as a replacement for original text.
+
+## Rights
+
+Rights vary by source and are recorded per row with `rights_tier`, `license`, `license_url`, and `rights_evidence`.
+
+Important caveat: the `ptbr-books-publicos` backbone is upstream-released under CC0-1.0 and described as public-domain, but this project did **not** independently establish per-item rights for every backbone book. The corpus therefore records that as a source-dataset claim rather than silently converting it into per-item legal provenance.
+
+BBM scan-derived text is not included in `corpus`; it remains in the review/deferred inventory.
+
+## Auxiliary configs
+
+- `documents`: document/edition hierarchy.
+- `review_inventory`: deferred and review queues, without training text.
+- `curation_lineage`: acceptance/dedup/curation lineage for canonical units.
+- `audit_metrics`: historical project accounting metrics. These are audit artifacts, not canonical token counts.
+
+## Data architecture references
+
+This repository keeps canonical text separate from tokenizer-specific training preprocessing, following the general architecture used by open pretraining projects such as Dolma/OLMo.
+
+- Dolma data format: https://github.com/allenai/dolma/blob/main/docs/data-format.md
+- OLMo memmap preprocessing: https://github.com/allenai/OLMo/blob/main/scripts/prepare_memmap_dataset.py
+- Hugging Face manual dataset configs: https://huggingface.co/docs/hub/datasets-manual-configuration

data/audit_metrics/audit_metrics.parquet

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data/curation_lineage/curation_lineage.parquet

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data/documents/documents.parquet

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data/review_inventory/review_inventory.parquet

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schema.json

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+{
+  "version": "0.1.0",
+  "corpus_columns": {
+    "id": "stable canonical text-unit identifier",
+    "text": "self-contained accepted text",
+    "unit_kind": "book/article/cordel/selected_segment/etc.",
+    "parent_document_id": "parent edition/document ID when unit is a selected segment",
+    "segment_index": "stable segment index within parent document",
+    "title": "source title; FE segments retain parent edition title",
+    "primary_authors": "creators of the literary text",
+    "editors": "modern editors/compilers where applicable",
+    "genre": "curated/model-assisted broad genre",
+    "year": "source/edition year when available",
+    "date_label": "human-readable historical content period when available",
+    "language": "language code",
+    "source": "specific source",
+    "source_family": "coarse source family",
+    "source_collection": "collection/journal/source subcollection",
+    "source_id": "stable source-specific identifier",
+    "landing_url": "provenance landing page",
+    "source_file_url": "upstream source-file URL for provenance; not needed to use frozen corpus",
+    "rights_tier": "project rights tier",
+    "license": "human-readable license/public-domain label",
+    "license_url": "license URL when available",
+    "rights_evidence": "why this unit was admitted",
+    "text_variant": "original; AO90 normalization is future separate derivative",
+    "orthography_hint": "historical/contemporary hint; original text is never overwritten",
+    "extraction_method": "how text was originally extracted or assembled",
+    "quality_label": "source-stage quality label",
+    "text_sha256": "SHA-256 of exact UTF-8 canonical text string",
+    "char_count": "Python Unicode character count of canonical text",
+    "word_count": "whitespace-split word count; not a tokenizer token count"
+  },
+  "auxiliary_tables": {
+    "documents": "document/edition hierarchy and parent metadata",
+    "review_inventory": "deferred/review queues; contains no training text",
+    "curation_lineage": "acceptance/dedup/curation provenance",
+    "audit_metrics": "legacy project token estimates/hashes kept out of canonical schema"
+  }
+}

stats.json

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+{
+  "version": "0.1.0",
+  "schema_version": "0.1.0",
+  "canonical_units": 1354,
+  "document_entities": 803,
+  "characters": 82538439,
+  "words": 13929410,
+  "legacy_audit_est_tokens_4p5": 18339188,
+  "legacy_metric_warning": "Historical chars/4.5 project estimate retained only in audit_metrics. Canonical corpus intentionally contains no tokenizer-dependent token count.",
+  "source_families": [
+    {
+      "source_family": "Conta pra Mim",
+      "units": 1,
+      "characters": 6365,
+      "words": 1036
+    },
+    {
+      "source_family": "FCRB",
+      "units": 65,
+      "characters": 761029,
+      "words": 138351
+    },
+    {
+      "source_family": "FE-Unicamp",
+      "units": 556,
+      "characters": 3155902,
+      "words": 535932
+    },
+    {
+      "source_family": "OJS",
+      "units": 318,
+      "characters": 2114092,
+      "words": 351649
+    },
+    {
+      "source_family": "OMP/Open Books",
+      "units": 14,
+      "characters": 831288,
+      "words": 140721
+    },
+    {
+      "source_family": "UEMA",
+      "units": 1,
+      "characters": 106498,
+      "words": 18292
+    },
+    {
+      "source_family": "backbone_books",
+      "units": 399,
+      "characters": 75563265,
+      "words": 12743429
+    }
+  ],
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+}