polish-dynaword / src /make_docs.py
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#!/usr/bin/env python3
"""Generate Dynaword documentation: per-source datasheets + README + CHANGELOG + LICENSE.
Reads sources.py + data/<source>/<source>.stats.json (written by build_dynaword.py).
Implements the "Documented" principle (datasheets, Gebru et al. 2021) and the
aggregate README table (paper 2508.02271).
"""
from __future__ import annotations
import json, sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parent))
from sources import SOURCES, EXCLUDED, ADDED
ROOT = Path(__file__).resolve().parent.parent
VERSION = "0.2.1"
CONTACT = "k.wikiel@gmail.com" # notice-and-takedown / data-removal requests
# Dupochron: documented good-faith provenance + no-warranty + takedown + PII.
DISCLAIMER = f"""## Personal & sensitive data
This corpus contains **only** text that its upstream sources already published
under open licenses or as official public-domain record. It therefore includes
names and statements of **public figures acting in a public capacity** — e.g.
parliamentary speakers (PPC), authorities named in legal acts (EUR-Lex), and
people described in encyclopedic articles (Wikipedia/Wikisource). No private,
non-public personal data was collected or added. If you are a data subject and
want content concerning you removed, contact **{CONTACT}** — it will be dropped
from the next version (see retroactive-removal policy below).
## Disclaimer & legal
- **Provenance in good faith.** Per-source licenses are reproduced *as documented
by the upstream sources and by SpeakLeash* (the intermediate aggregator), to the
best of our knowledge. We make no independent legal warranty about the copyright
status of any individual document.
- **No ownership claim.** This release is a *curated, license-reviewed, documented
aggregation*. We claim no ownership of the underlying texts; rights remain with
the original authors/rightsholders under their respective licenses.
- **Provided "as is"**, without warranty of any kind, express or implied. This is
not legal advice.
- **Your compliance is yours.** Downstream users must satisfy each upstream
license themselves — in particular **CC-BY-SA-4.0 attribution and share-alike**
for derivatives of this dataset, and attribution to the upstream sources and to
SpeakLeash.
- **Notice-and-takedown.** Any source or rightsholder raising a substantiated
objection can have material removed: contact **{CONTACT}**; it is dropped from
the next version and recorded in the CHANGELOG. Removal is retroactive
going-forward (prior immutable snapshots/commits may persist).
"""
def load_stats(name):
f = ROOT / "data" / name / f"{name}.stats.json"
return json.loads(f.read_text()) if f.exists() else None
def datasheet(name, cfg, st):
license_rows = ""
licenses = st.get("licenses") or {}
if licenses:
top = sorted(licenses.items(), key=lambda item: -item[1])[:20]
license_rows = "\n\n## Per-document license metadata\n| license | documents |\n|---|---:|\n"
license_rows += "\n".join(f"| `{k or 'UNKNOWN'}` | {v:,} |" for k, v in top)
author_note = ""
if "authors_with_value" in st:
author_note = (
f"\n\nAuthor metadata present for **{st.get('authors_with_value', 0):,}** "
"documents. Empty values mean the upstream record did not expose a "
"machine-readable author field."
)
legal_note = cfg.get("legal_note", "")
if legal_note:
legal_note = f"\n\n## Legal scope note\n{legal_note}"
source_note = ""
if st.get("stats_recomputed_from_parquet"):
source_note = "\n\nStatistics were recomputed directly from the released parquet file."
return f"""# {name}
{cfg['pretty']}
## Dataset description
- **Source (upstream):** {cfg['upstream']}
- **Domain:** {cfg['domain']}
- **Language:** Polish (pl)
- **License:** `{cfg['license']}`
- **Created (range):** {cfg['created']}
- **Added:** {ADDED}
## Licensing — traceable basis
{cfg['traceable']}
## Provenance
{cfg.get('provenance', f"Pulled from SpeakLeash's public redistribution "
f"(`speakleash-ds-pub`, key `{cfg.get('speakleash_key')}`) of the upstream source "
f"above. SpeakLeash credited as intermediate aggregator; upstream "
f"license/attribution preserved.")}
## Statistics
| documents | characters | tokens (tiktoken proxy) |
|---:|---:|---:|
| {st['kept']:,} | {st['chars']:,} | {st['tokens']:,} |
{license_rows}{author_note}{legal_note}{source_note}
## Filters applied (build_dynaword.py)
Minimal, per Dynaword guidelines (heavy filtering left to downstream use):
- drop documents < 200 chars: **{st.get('drop_short', 0):,}**
- drop non-Polish (diacritic ratio): **{st.get('drop_lang', 0):,}**
- exact cross-source dedup (sha1): **{st.get('drop_dup', 0):,}**
- OCR alpha-ratio < 0.70 (OCR sources only): **{st.get('drop_ocr', 0):,}**
- read {st.get('read', st['kept']):,} → kept {st['kept']:,}
Token counts are a fast tiktoken (cl100k) proxy (~1% off Llama-3); the canonical
Llama-3 count is computed at release.
"""
def main():
rows, tot_doc, tot_tok, tot_chr = [], 0, 0, 0
for name, cfg in SOURCES.items():
st = load_stats(name)
if not st:
print(f" ! no stats for {name}"); continue
(ROOT / "data" / name / f"{name}.md").write_text(datasheet(name, cfg, st))
rows.append((name, cfg, st))
tot_doc += st["kept"]; tot_tok += st["tokens"]; tot_chr += st["chars"]
rows.sort(key=lambda r: -r[2]["tokens"])
tbl = "\n".join(
f"| [{n}](data/{n}/{n}.md) | {c['pretty']} | `{c['license']}` | "
f"{s['kept']:,} | {s['tokens']/1e6:,.1f}M |"
for n, c, s in rows)
excl = "\n".join(f"| `{k}` | {v} |" for k, v in EXCLUDED.items())
phrase_frequency = ""
phrase_path = ROOT / "artifacts" / "pattern_frequency_hf_snippet.md"
if phrase_path.exists():
snippet = phrase_path.read_text().replace(
"## Phrase frequency in corpus (token-normalized)\n\n", ""
)
phrase_frequency = (
"\n## Results\n\n"
"### Corpus phrase frequency (normalized by tokens)\n\n"
"Raw counts and token-normalized shares are regenerated from the "
"current parquet files with `src/pattern_frequency_report.py`.\n\n"
f"{snippet}"
)
readme = f"""---
license: cc-by-sa-4.0
language:
- pl
pretty_name: Polish DynaWord
task_categories:
- text-generation
size_categories:
- 1M<n<10M
tags:
- polish
- pretraining
- dynaword
---
# Polish DynaWord
A continuously developed, **openly-licensed**, human-text Polish corpus — a Polish
edition in the [Dynaword](https://huggingface.co/datasets/danish-foundation-models/danish-dynaword)
family (Enevoldsen et al., [arXiv:2508.02271](https://arxiv.org/abs/2508.02271)).
> **v{VERSION} stable** · {tot_doc:,} documents · **{tot_tok/1e9:.2f}B tokens**
> (tiktoken proxy; canonical Llama-3 count at release) · {len(rows)} sources
> Updated: **{ADDED}**
> **v0.3.0-preview in progress** · quality/diversity remix workflow, legal-style
> downweighting, and filtered contemporary Polish web candidates. Biblioteka
> Nauki and Europeana are prepared as source-ingestion PR targets with
> per-document `license` and `author` metadata, but they are not part of this
> stable parquet release yet.
## Versions
| version | status | documents | tokens | notes |
|---|---|---:|---:|---|
| `v0.2.1` | stable release | {tot_doc:,} | {tot_tok/1e9:.2f}B | 12-source stable corpus with `license` and `author` metadata columns; adds `1000_novels`. |
| `v0.2.0` | previous stable | 2,490,773 | 6.22B | Provenance-first corpus from 11 open/official sources. |
| `v0.3.0-preview` | workflow + candidate data in progress | candidate-only | TBD | Biblioteka Nauki, Europeana, and HPLT/Common Corpus style expansion pending per-source QA, dedup, and legal review. |
## What this dataset contributes
The raw texts come from existing open corpora (redistributed via SpeakLeash and,
where applicable, fetched from upstream). **The value added here is the curation,
not the bytes**, following the Dynaword methodology:
1. **License review per source** — each source vetted for an *openly-licensed,
traceable* legal basis (documented in its datasheet); sources that fail the
review are **excluded with a stated reason** (see table below), not silently
kept. This is the core editorial work.
2. **Filtering & normalization** — minimal, reproducible gates (short-doc,
non-Polish, exact cross-source dedup, OCR garble) applied uniformly to one
clean schema: `id, text, source, added, created, token_count, license, author`.
3. **Documentation** — a datasheet per source (Gebru et al. 2021) + this card,
so provenance and licensing are auditable rather than assumed.
4. **Reproducibility & versioning** — `src/` rebuilds the corpus from sources;
new sources and removals are tracked in the CHANGELOG.
Credit for the underlying texts belongs to the upstream sources and to SpeakLeash
as the redistributing aggregator; this release does not claim ownership of them
(see Disclaimer).
## Contributors
- **Kacper Wikieł** — corpus curation, release engineering, documentation, and
reproducible build workflow.
- **Bart Kobyliński** — source expansion work for Biblioteka Nauki and Europeana,
including per-document license/author metadata collection and rebuild planning.
## Guiding principles
1. **Open & traceable licensing** — every source is *openly licensed* with a documented
legal basis (see each datasheet's "traceable basis"), not a vague "public domain".
2. **Reproducibility** — `src/build_dynaword.py` rebuilds the corpus from sources.
3. **Documented** — a datasheet per source under `data/<source>/`.
4. **Extensibility** — versioned; new sources via PR.
## Sources
| source | description | license | documents | tokens |
|---|---|---|---:|---:|
{tbl}
| **total** | | | **{tot_doc:,}** | **{tot_tok/1e6:,.1f}M** |
## Method
Only **human-authored** text — no synthetic, machine-translated, or auto-transcribed
data. Gates are intentionally minimal (drop short docs, non-Polish, exact duplicates,
OCR garble); heavy quality filtering and mix-weighting are left to downstream training.
Evaluation-set decontamination is applied/marked separately. Schema:
`id, text, source, added, created, token_count, license, author`. The `license`
and `author` columns are per-document metadata when upstream exposes them; older
sources use the source-level license and an empty author field.
## v0.3 quality roadmap and current status
The v0.2.x raw corpus is intentionally provenance-first, but its token mix is too
heavy in legal/parliamentary language for natural general pretraining. The v0.3
workflow therefore separates **source inclusion** from **training mix**:
- cap `eurlex + parliamentary + dziennik_ustaw` to roughly **10-20%** of training
tokens combined;
- use source-level temperature sampling (`sqrt`, alpha `0.5`) instead of raw
token-proportional sampling;
- add traceably licensed contemporary/natural Polish: open web, academic prose,
cultural heritage text, guides, technical documentation/blogs, Q&A, and
dialogue/instruction data;
- run aggressive exact, normalized, and near-duplicate removal;
- reserve the final **5-15%** of training for higher-quality sources rather than
the largest sources;
- evaluate per-source perplexity and style contamination, not only global loss.
Current v0.3 source-ingestion status:
- `biblioteka_nauki`: prepared in the source registry as a direct-upstream
rebuild target with per-document license and author metadata; not included in
v{VERSION} parquets yet.
- `europeana`: prepared in the source registry as a direct-upstream rebuild
target with per-record rights statements and creator metadata; raw SpeakLeash
Europeana remains excluded.
- Europeana release policy: split conservatively at pre-1929 records for
US-sensitive downstream reuse, and keep later/unknown records separately
labeled or held until legal review.
- `ashtok897/european-hplt-v1`: candidate workflow exists, but web-crawl
provenance, dedup, QA, and final mix weighting are still pending before stable
inclusion.
Current review artifacts:
- `configs/source_candidates_v0_3.json` — candidate decisions and license policy.
- `artifacts/source_license_review_v0_3.md` — source-by-source license review.
- `artifacts/source_candidate_audit_v0_3.md` — generated Hugging Face metadata audit.
- `artifacts/training_mix_v0_3.md` — example 1B-token training mix with legal sources capped at 15%.
- `artifacts/bartek_source_ingestion_plan_2026-07-02.md` — PR contract for
Biblioteka Nauki and Europeana ingestion.
## Excluded sources (transparency)
Sources we reviewed and **deliberately left out** — part of the curation:
| source | reason |
|---|---|
{excl}
{DISCLAIMER}
## License & attribution
Released under **CC-BY-SA-4.0** (copyleft inherited from CC-BY-SA sources such as
Wikipedia/Wikisource/Wolne Lektury). Attribution due to each upstream (see datasheets)
and to **SpeakLeash** as the intermediate aggregator. Retroactive-removal policy: a
source that raises an objection is dropped from subsequent versions, recorded in the
CHANGELOG.
## Reproduce
```bash
python3 src/build_dynaword.py --all --speakleash-dir <speakleash_zst_dir> --out .
python3 src/make_docs.py
```
{phrase_frequency}
"""
(ROOT / "README.md").write_text(readme)
(ROOT / "CHANGELOG.md").write_text(
f"# Changelog\n\n## v{VERSION} ({ADDED})\n\n"
f"- Released a stable metadata-schema update: "
f"`id, text, source, added, created, token_count, license, author`.\n"
f"- Current release totals after parquet recount: {len(rows)} sources, "
f"{tot_doc:,} docs, {tot_tok/1e9:.2f}B tokens (tiktoken proxy).\n"
f"- Added `1000_novels` as a stable CC-BY-4.0 literature source.\n"
f"- Added source registry entries and PR contract for future "
f"`biblioteka_nauki` and `europeana` ingestion with per-document "
f"license/author metadata. These sources are not included in v{VERSION} "
f"parquets yet.\n"
f"- Credited Bart Kobyliński for source expansion work on Biblioteka "
f"Nauki and Europeana metadata/rebuild preparation.\n"
f"- Kept raw SpeakLeash Europeana excluded unless a direct rebuild "
f"preserves per-record rights metadata.\n"
f"- Sources: {', '.join(n for n, _, _ in rows)}.\n"
f"- Excluded (see README): {', '.join(EXCLUDED)}.\n")
(ROOT / "LICENSE").write_text(
"Polish DynaWord is released under Creative Commons Attribution-ShareAlike 4.0\n"
"International (CC-BY-SA-4.0): https://creativecommons.org/licenses/by-sa/4.0/\n\n"
"Per-source upstream licenses and attribution are documented in each\n"
"data/<source>/<source>.md datasheet.\n")
print(f"docs written: README + CHANGELOG + LICENSE + {len(rows)} datasheets")
print(f"TOTAL {tot_doc:,} docs | {tot_tok/1e9:.2f}B tok | {tot_chr/1e9:.1f}B chars")
if __name__ == "__main__":
main()