Release v0.2.1 metadata schema update

CHANGELOG.md

@@ -1,18 +1,11 @@
 # Changelog
 
-## v0.3.0-preview (2026-06-16)
-
-- Added v0.3 quality/diversity workflow documentation: cap legal/parliamentary/official-document sources, use source-level temperature sampling, and evaluate per-source perplexity/style contamination.
-- Added source candidate review artifacts for contemporary Polish web and other possible additions.
-- Reviewed TVP Info-derived news data and blocked it until explicit upstream open-license evidence or permission is available.
-- Added European HPLT Polish web filtering workflow:
-  - `src/filter_european_hplt.py` supports chunked parquet output, explicit `HF_TOKEN`, and filtering specific HF parquet data files.
-  - `src/launch_hplt_parallel.py` launches parallel workers across the actual HF train shard list.
-- Current local HPLT candidate snapshot: 565,827 documents, 496,457,232 estimated tokens, about 1.0 GB compressed parquet output. This is not yet merged into the stable v0.2 parquet release.
-- Added `.gitignore` entries to keep large local generated candidates and logs out of git/HF commits.
-
-## v0.2.0 (2026-06-15)
-
-- Initial release: 11 openly-licensed sources, 2,490,773 docs, 6.22B tokens (tiktoken proxy).
-- Sources: eurlex, parliamentary, wikisource, wikipedia, dziennik_ustaw, wolne_lektury, wikiquote, eltec_pol, wikivoyage, wikibooks, wikinews.
-- Excluded (see README): open_subtitles_corpus, europeana_eu_pl_corpus, 1000_novels_corpus_CLARIN-PL, project_gutenberg_pl_corpus.
+## v0.2.1 (2026-06-15)
+
+- Released a stable metadata-schema update: `id, text, source, added, created, token_count, license, author`.
+- Current release totals after parquet recount: 12 sources, 2,491,773 docs, 6.28B tokens (tiktoken proxy).
+- Added `1000_novels` as a stable CC-BY-4.0 literature source.
+- Added source registry entries and PR contract for future `biblioteka_nauki` and `europeana` ingestion with per-document license/author metadata. These sources are not included in v0.2.1 parquets yet.
+- Kept raw SpeakLeash Europeana excluded unless a direct rebuild preserves per-record rights metadata.
+- Sources: eurlex, parliamentary, wikisource, wikipedia, dziennik_ustaw, wolne_lektury, 1000_novels, wikiquote, eltec_pol, wikivoyage, wikibooks, wikinews.
+- Excluded (see README): open_subtitles_corpus, europeana_eu_pl_corpus_raw_speakleash, project_gutenberg_pl_corpus.

README.md

@@ -11,8 +11,6 @@ tags:
 - polish
 - pretraining
 - dynaword
-- v0.2
-- v0.3-preview
 ---
 
 # Polish DynaWord
@@ -21,26 +19,22 @@ A continuously developed, **openly-licensed**, human-text Polish corpus — a Po
 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)).
 
-> **v0.2.0 stable** · 2,490,773 documents · **6.22B tokens** (tiktoken proxy;
-> canonical Llama-3 count at release) · 11 sources
+> **v0.2.1 stable** · 2,491,773 documents · **6.28B tokens**
+> (tiktoken proxy; canonical Llama-3 count at release) · 12 sources
 
 > **v0.3.0-preview in progress** · quality/diversity remix workflow, legal-style
-> downweighting, and filtered contemporary Polish web candidates. Current local
-> HPLT candidate run: **565,827 documents / 496.5M tokens** from
-> `ashtok897/european-hplt-v1`; not yet merged into the stable parquet release.
+> 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 |
 |---|---|---:|---:|---|
-| `v0.2.0` | stable release | 2,490,773 | 6.22B | Provenance-first corpus from 11 open/official sources. |
-| `v0.3.0-preview` | workflow + candidate data in progress | +565,827 candidate docs | +496.5M candidate tokens | Filtered European HPLT Polish web candidate, generated locally with chunked/parallel filtering; pending dedup, QA, and final mix weighting. |
-
-If the current HPLT candidate is merged as-is, the working corpus would be
-approximately **3,056,600 documents / 6.72B tokens** before dedup and mix
-reweighting. The final v0.3 release is expected to be a **training mix**, not a
-raw append: legal/parliamentary/official-document sources should be capped and
-sampled rather than allowed to dominate by raw token count.
+| `v0.2.1` | stable release | 2,491,773 | 6.28B | 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,
@@ -53,7 +47,7 @@ not the bytes**, following the Dynaword methodology:
    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`.
+   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;
@@ -79,23 +73,26 @@ as the redistributing aggregator; this release does not claim ownership of them
 | [wikipedia](data/wikipedia/wikipedia.md) | Polish Wikipedia | `CC-BY-SA-3.0` | 1,171,897 | 707.2M |
 | [dziennik_ustaw](data/dziennik_ustaw/dziennik_ustaw.md) | Dziennik Ustaw + Monitor Polski (Polish primary legislation) | `public-domain (official documents)` | 35,442 | 486.1M |
 | [wolne_lektury](data/wolne_lektury/wolne_lektury.md) | Wolne Lektury (school readings) | `CC-BY-SA-4.0 / Wolna Sztuka 1.3` | 6,141 | 103.0M |
+| [1000_novels](data/1000_novels/1000_novels.md) | 1000 Novels Corpus (CLARIN-PL) | `CC-BY-4.0` | 1,000 | 60.5M |
 | [wikiquote](data/wikiquote/wikiquote.md) | Polish Wikiquote (quotations) | `CC-BY-SA-3.0` | 30,363 | 31.9M |
 | [eltec_pol](data/eltec_pol/eltec_pol.md) | ELTeC-pol (European Literary Text Collection, Polish) | `CC-BY-4.0` | 100 | 21.5M |
 | [wikivoyage](data/wikivoyage/wikivoyage.md) | Polish Wikivoyage (travel guides) | `CC-BY-SA-3.0` | 13,645 | 17.1M |
 | [wikibooks](data/wikibooks/wikibooks.md) | Polish Wikibooks (open textbooks) | `CC-BY-SA-3.0` | 9,112 | 15.6M |
 | [wikinews](data/wikinews/wikinews.md) | Polish Wikinews | `CC-BY-2.5` | 24,386 | 12.1M |
-| **total** | | | **2,490,773** | **6,221.4M** |
+| **total** | | | **2,491,773** | **6,281.9M** |
 
 ## 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`.
+`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 raw corpus is intentionally provenance-first, but its token mix is too
+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**:
 
@@ -103,22 +100,28 @@ workflow therefore separates **source inclusion** from **training mix**:
   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, guides,
-  technical documentation/blogs, Q&A, and dialogue/instruction data;
+- 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;
-- treat GPT-2 124M as a cheap dataset probe, not proof of final model quality.
-
-Primary v0.3 web candidate: `ashtok897/european-hplt-v1`. Its card reports
-Polish `pl` coverage of **1,891,358 documents** and **~1.98B estimated tokens**
-with HPLT WDS quality scores, language confidence, URL provenance, MIME type,
-and web-register metadata. The helper `src/filter_european_hplt.py` streams this
-dataset and filters for Polish, non-machine-translated, non-boilerplate,
-domain-filtered natural web text. The dataset card marks it `CC0-1.0`, inherited
-from HPLT v3, but because it is web-crawl derived it remains subject to
-source/provenance review before a final release.
+- 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
+  v0.2.1 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:
 
@@ -126,39 +129,8 @@ Current review artifacts:
 - `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%.
-
-Current HPLT filtering status (2026-06-16):
-
-- input: `ashtok897/european-hplt-v1`, actual HF train parquet files split
-  across workers;
-- filter output generated locally under `data/european_hplt_pl_parallel_500m_v2/`;
-- kept **565,827** documents and **496,457,232** estimated tokens;
-- compressed parquet output size: about **1.0 GB**;
-- this is a candidate source snapshot, not yet a stable release artifact.
-
-Reproduce the chunked/parallel candidate run:
-
-```bash
-python3 src/launch_hplt_parallel.py \
-  --workers 4 \
-  --out-dir data/european_hplt_pl_parallel_500m_v2 \
-  --screen-prefix hplt2 \
-  --target-total-tokens 500000000
-```
-
-Monitor progress:
-
-```bash
-screen -ls
-tail -f logs/filter_european_hplt_hplt2_w0.log
-find data/european_hplt_pl_parallel_500m_v2 -maxdepth 2 -name '*.parquet' -ls
-```
-
-TVP Info-derived news data is currently **blocked**: the HF upload
-`WiktorS/polish-news` has an `apache-2.0` tag, but its README says the articles
-were obtained from `tvp.info.pl`, and no upstream TVP Info open license has been
-verified. It should only be included with explicit permission or authoritative
-upstream open-license evidence.
+- `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:
@@ -166,8 +138,7 @@ Sources we reviewed and **deliberately left out** — part of the curation:
 | source | reason |
 |---|---|
 | `open_subtitles_corpus` | Derivative of copyrighted film/TV dialogue; OpenSubtitles uploads largely unlicensed. Same copyright lesson as Danish Gigaword's OpenSubtitles (paper 2508.02271). Not openly licensed. |
-| `europeana_eu_pl_corpus` | Aggregated items with mixed per-record rights (PD / CC-BY-NC / rights-reserved). Needs per-record edm:rights filter before any inclusion. |
-| `1000_novels_corpus_CLARIN-PL` | CC-BY-4.0 label, but 'novels' likely include in-copyright contemporary works; verify titles/years on CLARIN handle 11321/312 before inclusion. |
+| `europeana_eu_pl_corpus_raw_speakleash` | Aggregated items with mixed per-record rights (PD / CC-BY-NC / rights-reserved). The raw SpeakLeash redistribution is excluded; only a direct rebuild preserving per-record rights metadata may be included. |
 | `project_gutenberg_pl_corpus` | Only 31 PL books (4.3MB) — PG is ~99% English; Polish PD literature already covered by wolne_lektury + wikisource (so near-redundant after dedup). Dropped to avoid the PD-in-EU per-work check (PG claims PD-in-US only) for negligible token gain. |
 
 ## Personal & sensitive data
@@ -214,43 +185,145 @@ python3 src/make_docs.py
 
 ## Corpus phrase frequency (normalized by tokens)
 
-To show how frequent legal and discourse markers are across the corpus, we can report counts normalized by token count per source and globally. Raw counts + percentages are generated from the current parquet data and source token counts:
+Raw counts and token-normalized shares are regenerated from the current parquet files with `src/pattern_frequency_report.py`.
 
-```bash
-python3 src/pattern_frequency_report.py --data-root . \
-  --out-md pattern_frequency_report.md \
-  --out-hf artifacts/pattern_frequency_hf_snippet.md \
-  --out-png artifacts/pattern_frequency.png
-```
+## Phrase frequency in corpus (token-normalized)
 
-`pattern_frequency_report.md` contains full source-by-source breakdown.
-`artifacts/pattern_frequency_hf_snippet.md` is the exact block for Hugging Face model card.
+- Total token count (tiktoken proxy): **6,281,911,234**
 
-| pattern | count | share of all corpus tokens |
+| Pattern | Count | Share of all tokens |
 |---|---:|---:|
-| `w roku` | 434,882 | 0.0070% |
-| `klasyfikacji` | 129,963 | 0.0021% |
-| `ustawa` | 586,803 | 0.0094% |
-| `artykuł` | 2,035,630 | 0.0327% |
-| `parlament` | 1,201,401 | 0.0193% |
-| `rozporządzenie` | 1,490,399 | 0.0240% |
-| `w pobliżu` | 77,561 | 0.0012% |
-| `mieszkańców` | 240,332 | 0.0039% |
-| `Dz.U.` | 939,966 | 0.0151% |
+| `w roku` | 435,541 | 0.0069% |
+| `klasyfikacji` | 129,977 | 0.0021% |
+| `ustawa` | 587,459 | 0.0094% |
+| `artykuł` | 2,036,359 | 0.0324% |
+| `parlament` | 1,201,641 | 0.0191% |
+| `rozporządzenie` | 1,490,464 | 0.0237% |
+| `w pobliżu` | 78,823 | 0.0013% |
+| `mieszkańców` | 241,200 | 0.0038% |
+| `Dz.U.` | 939,966 | 0.0150% |
+
+### Per-source shares
+
+| source | pattern | count | share of source tokens |
+|---|---|---:|---:|
+| `1000_novels` | `w roku` | 659 | 0.00109% |
+| `1000_novels` | `klasyfikacji` | 14 | 0.00002% |
+| `1000_novels` | `ustawa` | 656 | 0.00108% |
+| `1000_novels` | `artykuł` | 729 | 0.00120% |
+| `1000_novels` | `parlament` | 240 | 0.00040% |
+| `1000_novels` | `rozporządzenie` | 65 | 0.00011% |
+| `1000_novels` | `w pobliżu` | 1,262 | 0.00209% |
+| `1000_novels` | `mieszkańców` | 868 | 0.00143% |
+| `1000_novels` | `Dz.U.` | 0 | 0.00000% |
+| `dziennik_ustaw` | `w roku` | 33,096 | 0.00681% |
+| `dziennik_ustaw` | `klasyfikacji` | 10,896 | 0.00224% |
+| `dziennik_ustaw` | `ustawa` | 77,376 | 0.01592% |
+| `dziennik_ustaw` | `artykuł` | 27,773 | 0.00571% |
+| `dziennik_ustaw` | `parlament` | 42,338 | 0.00871% |
+| `dziennik_ustaw` | `rozporządzenie` | 166,383 | 0.03423% |
+| `dziennik_ustaw` | `w pobliżu` | 1,087 | 0.00022% |
+| `dziennik_ustaw` | `mieszkańców` | 8,025 | 0.00165% |
+| `dziennik_ustaw` | `Dz.U.` | 158 | 0.00003% |
+| `eltec_pol` | `w roku` | 108 | 0.00050% |
+| `eltec_pol` | `klasyfikacji` | 1 | 0.00000% |
+| `eltec_pol` | `ustawa` | 153 | 0.00071% |
+| `eltec_pol` | `artykuł` | 173 | 0.00081% |
+| `eltec_pol` | `parlament` | 95 | 0.00044% |
+| `eltec_pol` | `rozporządzenie` | 35 | 0.00016% |
+| `eltec_pol` | `w pobliżu` | 246 | 0.00114% |
+| `eltec_pol` | `mieszkańców` | 214 | 0.00100% |
+| `eltec_pol` | `Dz.U.` | 0 | 0.00000% |
+| `eurlex` | `w roku` | 40,009 | 0.00168% |
+| `eurlex` | `klasyfikacji` | 59,428 | 0.00250% |
+| `eurlex` | `ustawa` | 30,368 | 0.00128% |
+| `eurlex` | `artykuł` | 1,774,958 | 0.07464% |
+| `eurlex` | `parlament` | 780,286 | 0.03281% |
+| `eurlex` | `rozporządzenie` | 1,202,658 | 0.05057% |
+| `eurlex` | `w pobliżu` | 6,088 | 0.00026% |
+| `eurlex` | `mieszkańców` | 9,441 | 0.00040% |
+| `eurlex` | `Dz.U.` | 915,707 | 0.03851% |
+| `parliamentary` | `w roku` | 198,192 | 0.01203% |
+| `parliamentary` | `klasyfikacji` | 12,637 | 0.00077% |
+| `parliamentary` | `ustawa` | 459,179 | 0.02788% |
+| `parliamentary` | `artykuł` | 182,038 | 0.01105% |
+| `parliamentary` | `parlament` | 309,695 | 0.01881% |
+| `parliamentary` | `rozporządzenie` | 113,547 | 0.00689% |
+| `parliamentary` | `w pobliżu` | 4,964 | 0.00030% |
+| `parliamentary` | `mieszkańców` | 78,048 | 0.00474% |
+| `parliamentary` | `Dz.U.` | 23,809 | 0.00145% |
+| `wikibooks` | `w roku` | 319 | 0.00205% |
+| `wikibooks` | `klasyfikacji` | 37 | 0.00024% |
+| `wikibooks` | `ustawa` | 165 | 0.00106% |
+| `wikibooks` | `artykuł` | 732 | 0.00470% |
+| `wikibooks` | `parlament` | 283 | 0.00182% |
+| `wikibooks` | `rozporządzenie` | 131 | 0.00084% |
+| `wikibooks` | `w pobliżu` | 125 | 0.00080% |
+| `wikibooks` | `mieszkańców` | 204 | 0.00131% |
+| `wikibooks` | `Dz.U.` | 16 | 0.00010% |
+| `wikinews` | `w roku` | 449 | 0.00370% |
+| `wikinews` | `klasyfikacji` | 639 | 0.00526% |
+| `wikinews` | `ustawa` | 407 | 0.00335% |
+| `wikinews` | `artykuł` | 2,474 | 0.02038% |
+| `wikinews` | `parlament` | 2,530 | 0.02084% |
+| `wikinews` | `rozporządzenie` | 168 | 0.00138% |
+| `wikinews` | `w pobliżu` | 455 | 0.00375% |
+| `wikinews` | `mieszkańców` | 1,014 | 0.00835% |
+| `wikinews` | `Dz.U.` | 27 | 0.00022% |
+| `wikipedia` | `w roku` | 143,023 | 0.02022% |
+| `wikipedia` | `klasyfikacji` | 46,043 | 0.00651% |
+| `wikipedia` | `ustawa` | 9,536 | 0.00135% |
+| `wikipedia` | `artykuł` | 28,165 | 0.00398% |
+| `wikipedia` | `parlament` | 57,863 | 0.00818% |
+| `wikipedia` | `rozporządzenie` | 5,637 | 0.00080% |
+| `wikipedia` | `w pobliżu` | 41,915 | 0.00593% |
+| `wikipedia` | `mieszkańców` | 122,766 | 0.01736% |
+| `wikipedia` | `Dz.U.` | 232 | 0.00003% |
+| `wikiquote` | `w roku` | 608 | 0.00191% |
+| `wikiquote` | `klasyfikacji` | 15 | 0.00005% |
+| `wikiquote` | `ustawa` | 357 | 0.00112% |
+| `wikiquote` | `artykuł` | 606 | 0.00190% |
+| `wikiquote` | `parlament` | 1,271 | 0.00398% |
+| `wikiquote` | `rozporządzenie` | 27 | 0.00008% |
+| `wikiquote` | `w pobliżu` | 207 | 0.00065% |
+| `wikiquote` | `mieszkańców` | 527 | 0.00165% |
+| `wikiquote` | `Dz.U.` | 6 | 0.00002% |
+| `wikisource` | `w roku` | 16,571 | 0.00207% |
+| `wikisource` | `klasyfikacji` | 166 | 0.00002% |
+| `wikisource` | `ustawa` | 8,156 | 0.00102% |
+| `wikisource` | `artykuł` | 16,230 | 0.00202% |
+| `wikisource` | `parlament` | 6,119 | 0.00076% |
+| `wikisource` | `rozporządzenie` | 1,651 | 0.00021% |
+| `wikisource` | `w pobliżu` | 13,921 | 0.00174% |
+| `wikisource` | `mieszkańców` | 14,335 | 0.00179% |
+| `wikisource` | `Dz.U.` | 5 | 0.00000% |
+| `wikivoyage` | `w roku` | 609 | 0.00356% |
+| `wikivoyage` | `klasyfikacji` | 21 | 0.00012% |
+| `wikivoyage` | `ustawa` | 46 | 0.00027% |
+| `wikivoyage` | `artykuł` | 657 | 0.00384% |
+| `wikivoyage` | `parlament` | 249 | 0.00145% |
+| `wikivoyage` | `rozporządzenie` | 34 | 0.00020% |
+| `wikivoyage` | `w pobliżu` | 6,480 | 0.03783% |
+| `wikivoyage` | `mieszkańców` | 4,100 | 0.02394% |
+| `wikivoyage` | `Dz.U.` | 1 | 0.00001% |
+| `wolne_lektury` | `w roku` | 1,898 | 0.00184% |
+| `wolne_lektury` | `klasyfikacji` | 80 | 0.00008% |
+| `wolne_lektury` | `ustawa` | 1,060 | 0.00103% |
+| `wolne_lektury` | `artykuł` | 1,824 | 0.00177% |
+| `wolne_lektury` | `parlament` | 672 | 0.00065% |
+| `wolne_lektury` | `rozporządzenie` | 128 | 0.00012% |
+| `wolne_lektury` | `w pobliżu` | 2,073 | 0.00201% |
+| `wolne_lektury` | `mieszkańców` | 1,658 | 0.00161% |
+| `wolne_lektury` | `Dz.U.` | 5 | 0.00000% |
 
 ![Overall pattern counts](artifacts/pattern_frequency_overall.png)
 
-Per-source normalized shares:
-- [w roku](artifacts/pattern_frequency_w_roku.png)
-- [klasyfikacji](artifacts/pattern_frequency_klasyfikacji.png)
-- [ustawa](artifacts/pattern_frequency_ustawa.png)
-- [artykuł](artifacts/pattern_frequency_artykul.png)
-- [parlament](artifacts/pattern_frequency_parlament.png)
-- [rozporządzenie](artifacts/pattern_frequency_rozporządzenie.png)
-- [w pobliżu](artifacts/pattern_frequency_w_pobliżu.png)
-- [mieszkańców](artifacts/pattern_frequency_mieszkańców.png)
-- [Dz.U.](artifacts/pattern_frequency_dzu.png)
-
-### Hugging Face Model Card block
-
-Wklej dokładnie `artifacts/pattern_frequency_hf_snippet.md` do sekcji **Results** w model card (`README.md` repozytorium na HF).
+![w roku by source](artifacts/pattern_frequency_w_roku.png)
+![klasyfikacji by source](artifacts/pattern_frequency_klasyfikacji.png)
+![ustawa by source](artifacts/pattern_frequency_ustawa.png)
+![artykuł by source](artifacts/pattern_frequency_artykul.png)
+![parlament by source](artifacts/pattern_frequency_parlament.png)
+![rozporządzenie by source](artifacts/pattern_frequency_rozporządzenie.png)
+![w pobliżu by source](artifacts/pattern_frequency_w_pobliżu.png)
+![mieszkańców by source](artifacts/pattern_frequency_mieszkańców.png)
+![Dz.U. by source](artifacts/pattern_frequency_dzu.png)

artifacts/bartek_source_ingestion_plan_2026-07-02.md

@@ -0,0 +1,73 @@
+# Bartek source ingestion plan
+
+## Decision
+
+Accept the two extra columns in the main parquet schema:
+
+`id, text, source, added, created, token_count, license, author`
+
+Reason: `license` and `author` are document-level provenance fields. Keeping them
+inside the parquet means they survive shuffling, filtering, deduplication, and
+training-mix extraction. A separate sidecar file is useful for audit exports, but
+it should not be the only place where rights metadata lives.
+
+## Contract for the PR
+
+Bartek should provide:
+
+- normalized parquet/jsonl.zst files for `biblioteka_nauki` and `europeana`, or
+  a script that regenerates them from the upstream services;
+- per-record `license` and `author` fields where upstream metadata exists;
+- per-source stats: documents, characters, token count, license distribution,
+  author coverage, dropped-record counts;
+- enough source notes to reproduce the exact upstream query/API/interface and the
+  license decision logic.
+
+The project-side scripts now support the expanded schema and will regenerate:
+
+- per-source datasheets in `data/<source>/<source>.md`;
+- the README source table and totals;
+- the changelog source list.
+
+## Source policy
+
+### Biblioteka Nauki
+
+Include as `biblioteka_nauki` only through the direct upstream rebuild. Do not
+treat the old SpeakLeash aggregate as sufficient evidence. Each record should
+carry its upstream license and author/creator metadata when available.
+
+Suggested source description:
+
+Biblioteka Nauki is a Polish academic-text source fetched directly from the
+upstream site/interface. Records are accepted only when a reusable license is
+available in the upstream metadata. Per-document license and author metadata are
+preserved in the corpus.
+
+### Europeana
+
+Include as `europeana` only through the direct upstream rebuild preserving
+per-record rights statements. The raw SpeakLeash aggregate remains excluded
+because it is mixed-rights and insufficiently traceable.
+
+Release split:
+
+- `created/published < 1929`: conservative public release slice for US-sensitive
+  downstream users;
+- `created/published >= 1929` or unknown date: keep separately labeled, or hold
+  until legal review confirms the release scope.
+
+Dataset-card wording should say that Europeana rights statements are evaluated
+primarily for Poland/EU and that public-domain status can depend on jurisdiction.
+
+## Checklist before merge
+
+- Run the source rebuild or ingest script.
+- Validate parquet schema has the eight canonical columns.
+- Recompute token counts and stats from the generated files.
+- Run `python3 src/make_docs.py`.
+- Inspect the README totals and source datasheets.
+- Confirm Europeana is either split at 1929 or explicitly marked as
+  jurisdiction-sensitive.
+- Keep raw SpeakLeash Europeana excluded unless per-record rights metadata is
+  preserved.

artifacts/pattern_frequency_hf_snippet.md

@@ -1,136 +1,140 @@
-## Phrase frequency (token-normalized)
+## Phrase frequency in corpus (token-normalized)
 
-### Global corpus totals
+- Total token count (tiktoken proxy): **6,281,911,234**
 
-Token counts are computed with the same tiktoken proxy used in source stats (`cl100k_base`).
-
-| Pattern | Count | Share of total tokens |
+| Pattern | Count | Share of all tokens |
 |---|---:|---:|
-| `w roku` | 434,882 | 0.0070% |
-| `klasyfikacji` | 129,963 | 0.0021% |
-| `ustawa` | 586,803 | 0.0094% |
-| `artykuł` | 2,035,630 | 0.0327% |
-| `parlament` | 1,201,401 | 0.0193% |
-| `rozporządzenie` | 1,490,399 | 0.0240% |
-| `w pobliżu` | 77,561 | 0.0012% |
-| `mieszkańców` | 240,332 | 0.0039% |
-| `Dz.U.` | 939,966 | 0.0151% |
-
-![overall-pattern-frequency](artifacts/pattern_frequency_overall.png)
-
-### Per-source token-normalized shares
+| `w roku` | 435,541 | 0.0069% |
+| `klasyfikacji` | 129,977 | 0.0021% |
+| `ustawa` | 587,459 | 0.0094% |
+| `artykuł` | 2,036,359 | 0.0324% |
+| `parlament` | 1,201,641 | 0.0191% |
+| `rozporządzenie` | 1,490,464 | 0.0237% |
+| `w pobliżu` | 78,823 | 0.0013% |
+| `mieszkańców` | 241,200 | 0.0038% |
+| `Dz.U.` | 939,966 | 0.0150% |
 
-Plots:
-- [w roku](artifacts/pattern_frequency_w_roku.png)
-- [klasyfikacji](artifacts/pattern_frequency_klasyfikacji.png)
-- [ustawa](artifacts/pattern_frequency_ustawa.png)
-- [artykuł](artifacts/pattern_frequency_artykul.png)
-- [parlament](artifacts/pattern_frequency_parlament.png)
-- [rozporządzenie](artifacts/pattern_frequency_rozporządzenie.png)
-- [w pobliżu](artifacts/pattern_frequency_w_pobliżu.png)
-- [mieszkańców](artifacts/pattern_frequency_mieszkańców.png)
-- [Dz.U.](artifacts/pattern_frequency_dzu.png)
-
-### Source-level full table
+### Per-source shares
 
 | source | pattern | count | share of source tokens |
 |---|---|---:|---:|
-| dziennik_ustaw | `w roku` | 33,096 | 0.00681% |
-| dziennik_ustaw | `klasyfikacji` | 10,896 | 0.00224% |
-| dziennik_ustaw | `ustawa` | 77,376 | 0.01592% |
-| dziennik_ustaw | `artykuł` | 27,773 | 0.00571% |
-| dziennik_ustaw | `parlament` | 42,338 | 0.00871% |
-| dziennik_ustaw | `rozporządzenie` | 166,383 | 0.03423% |
-| dziennik_ustaw | `w pobliżu` | 1,087 | 0.00022% |
-| dziennik_ustaw | `mieszkańców` | 8,025 | 0.00165% |
-| dziennik_ustaw | `Dz.U.` | 158 | 0.00003% |
-| eltec_pol | `w roku` | 108 | 0.00050% |
-| eltec_pol | `klasyfikacji` | 1 | 0.00000% |
-| eltec_pol | `ustawa` | 153 | 0.00071% |
-| eltec_pol | `artykuł` | 173 | 0.00081% |
-| eltec_pol | `parlament` | 95 | 0.00044% |
-| eltec_pol | `rozporządzenie` | 35 | 0.00016% |
-| eltec_pol | `w pobliżu` | 246 | 0.00114% |
-| eltec_pol | `mieszkańców` | 214 | 0.00100% |
-| eltec_pol | `Dz.U.` | 0 | 0.00000% |
-| eurlex | `w roku` | 40,009 | 0.00168% |
-| eurlex | `klasyfikacji` | 59,428 | 0.00250% |
-| eurlex | `ustawa` | 30,368 | 0.00128% |
-| eurlex | `artykuł` | 1,774,958 | 0.07464% |
-| eurlex | `parlament` | 780,286 | 0.03281% |
-| eurlex | `rozporządzenie` | 1,202,658 | 0.05057% |
-| eurlex | `w pobliżu` | 6,088 | 0.00026% |
-| eurlex | `mieszkańców` | 9,441 | 0.00040% |
-| eurlex | `Dz.U.` | 915,707 | 0.03851% |
-| parliamentary | `w roku` | 198,192 | 0.01203% |
-| parliamentary | `klasyfikacji` | 12,637 | 0.00077% |
-| parliamentary | `ustawa` | 459,179 | 0.02788% |
-| parliamentary | `artykuł` | 182,038 | 0.01105% |
-| parliamentary | `parlament` | 309,695 | 0.01881% |
-| parliamentary | `rozporządzenie` | 113,547 | 0.00689% |
-| parliamentary | `w pobliżu` | 4,964 | 0.00030% |
-| parliamentary | `mieszkańców` | 78,048 | 0.00474% |
-| parliamentary | `Dz.U.` | 23,809 | 0.00145% |
-| wikibooks | `w roku` | 319 | 0.00205% |
-| wikibooks | `klasyfikacji` | 37 | 0.00024% |
-| wikibooks | `ustawa` | 165 | 0.00106% |
-| wikibooks | `artykuł` | 732 | 0.00470% |
-| wikibooks | `parlament` | 283 | 0.00182% |
-| wikibooks | `rozporządzenie` | 131 | 0.00084% |
-| wikibooks | `w pobliżu` | 125 | 0.00080% |
-| wikibooks | `mieszkańców` | 204 | 0.00131% |
-| wikibooks | `Dz.U.` | 16 | 0.00010% |
-| wikinews | `w roku` | 449 | 0.00370% |
-| wikinews | `klasyfikacji` | 639 | 0.00526% |
-| wikinews | `ustawa` | 407 | 0.00335% |
-| wikinews | `artykuł` | 2,474 | 0.02038% |
-| wikinews | `parlament` | 2,530 | 0.02084% |
-| wikinews | `rozporządzenie` | 168 | 0.00138% |
-| wikinews | `w pobliżu` | 455 | 0.00375% |
-| wikinews | `mieszkańców` | 1,014 | 0.00835% |
-| wikinews | `Dz.U.` | 27 | 0.00022% |
-| wikipedia | `w roku` | 143,023 | 0.02022% |
-| wikipedia | `klasyfikacji` | 46,043 | 0.00651% |
-| wikipedia | `ustawa` | 9,536 | 0.00135% |
-| wikipedia | `artykuł` | 28,165 | 0.00398% |
-| wikipedia | `parlament` | 57,863 | 0.00818% |
-| wikipedia | `rozporządzenie` | 5,637 | 0.00080% |
-| wikipedia | `w pobliżu` | 41,915 | 0.00593% |
-| wikipedia | `mieszkańców` | 122,766 | 0.01736% |
-| wikipedia | `Dz.U.` | 232 | 0.00003% |
-| wikiquote | `w roku` | 608 | 0.00191% |
-| wikiquote | `klasyfikacji` | 15 | 0.00005% |
-| wikiquote | `ustawa` | 357 | 0.00112% |
-| wikiquote | `artykuł` | 606 | 0.00190% |
-| wikiquote | `parlament` | 1,271 | 0.00398% |
-| wikiquote | `rozporządzenie` | 27 | 0.00008% |
-| wikiquote | `w pobliżu` | 207 | 0.00065% |
-| wikiquote | `mieszkańców` | 527 | 0.00165% |
-| wikiquote | `Dz.U.` | 6 | 0.00002% |
-| wikisource | `w roku` | 16,571 | 0.00207% |
-| wikisource | `klasyfikacji` | 166 | 0.00002% |
-| wikisource | `ustawa` | 8,156 | 0.00102% |
-| wikisource | `artykuł` | 16,230 | 0.00202% |
-| wikisource | `parlament` | 6,119 | 0.00076% |
-| wikisource | `rozporządzenie` | 1,651 | 0.00021% |
-| wikisource | `w pobliżu` | 13,921 | 0.00174% |
-| wikisource | `mieszkańców` | 14,335 | 0.00179% |
-| wikisource | `Dz.U.` | 5 | 0.00000% |
-| wikivoyage | `w roku` | 609 | 0.00356% |
-| wikivoyage | `klasyfikacji` | 21 | 0.00012% |
-| wikivoyage | `ustawa` | 46 | 0.00027% |
-| wikivoyage | `artykuł` | 657 | 0.00384% |
-| wikivoyage | `parlament` | 249 | 0.00145% |
-| wikivoyage | `rozporządzenie` | 34 | 0.00020% |
-| wikivoyage | `w pobliżu` | 6,480 | 0.03783% |
-| wikivoyage | `mieszkańców` | 4,100 | 0.02394% |
-| wikivoyage | `Dz.U.` | 1 | 0.00001% |
-| wolne_lektury | `w roku` | 1,898 | 0.00184% |
-| wolne_lektury | `klasyfikacji` | 80 | 0.00008% |
-| wolne_lektury | `ustawa` | 1,060 | 0.00103% |
-| wolne_lektury | `artykuł` | 1,824 | 0.00177% |
-| wolne_lektury | `parlament` | 672 | 0.00065% |
-| wolne_lektury | `rozporządzenie` | 128 | 0.00012% |
-| wolne_lektury | `w pobliżu` | 2,073 | 0.00201% |
-| wolne_lektury | `mieszkańców` | 1,658 | 0.00161% |
-| wolne_lektury | `Dz.U.` | 5 | 0.00000% |
+| `1000_novels` | `w roku` | 659 | 0.00109% |
+| `1000_novels` | `klasyfikacji` | 14 | 0.00002% |
+| `1000_novels` | `ustawa` | 656 | 0.00108% |
+| `1000_novels` | `artykuł` | 729 | 0.00120% |
+| `1000_novels` | `parlament` | 240 | 0.00040% |
+| `1000_novels` | `rozporządzenie` | 65 | 0.00011% |
+| `1000_novels` | `w pobliżu` | 1,262 | 0.00209% |
+| `1000_novels` | `mieszkańców` | 868 | 0.00143% |
+| `1000_novels` | `Dz.U.` | 0 | 0.00000% |
+| `dziennik_ustaw` | `w roku` | 33,096 | 0.00681% |
+| `dziennik_ustaw` | `klasyfikacji` | 10,896 | 0.00224% |
+| `dziennik_ustaw` | `ustawa` | 77,376 | 0.01592% |
+| `dziennik_ustaw` | `artykuł` | 27,773 | 0.00571% |
+| `dziennik_ustaw` | `parlament` | 42,338 | 0.00871% |
+| `dziennik_ustaw` | `rozporządzenie` | 166,383 | 0.03423% |
+| `dziennik_ustaw` | `w pobliżu` | 1,087 | 0.00022% |
+| `dziennik_ustaw` | `mieszkańców` | 8,025 | 0.00165% |
+| `dziennik_ustaw` | `Dz.U.` | 158 | 0.00003% |
+| `eltec_pol` | `w roku` | 108 | 0.00050% |
+| `eltec_pol` | `klasyfikacji` | 1 | 0.00000% |
+| `eltec_pol` | `ustawa` | 153 | 0.00071% |
+| `eltec_pol` | `artykuł` | 173 | 0.00081% |
+| `eltec_pol` | `parlament` | 95 | 0.00044% |
+| `eltec_pol` | `rozporządzenie` | 35 | 0.00016% |
+| `eltec_pol` | `w pobliżu` | 246 | 0.00114% |
+| `eltec_pol` | `mieszkańców` | 214 | 0.00100% |
+| `eltec_pol` | `Dz.U.` | 0 | 0.00000% |
+| `eurlex` | `w roku` | 40,009 | 0.00168% |
+| `eurlex` | `klasyfikacji` | 59,428 | 0.00250% |
+| `eurlex` | `ustawa` | 30,368 | 0.00128% |
+| `eurlex` | `artykuł` | 1,774,958 | 0.07464% |
+| `eurlex` | `parlament` | 780,286 | 0.03281% |
+| `eurlex` | `rozporządzenie` | 1,202,658 | 0.05057% |
+| `eurlex` | `w pobliżu` | 6,088 | 0.00026% |
+| `eurlex` | `mieszkańców` | 9,441 | 0.00040% |
+| `eurlex` | `Dz.U.` | 915,707 | 0.03851% |
+| `parliamentary` | `w roku` | 198,192 | 0.01203% |
+| `parliamentary` | `klasyfikacji` | 12,637 | 0.00077% |
+| `parliamentary` | `ustawa` | 459,179 | 0.02788% |
+| `parliamentary` | `artykuł` | 182,038 | 0.01105% |
+| `parliamentary` | `parlament` | 309,695 | 0.01881% |
+| `parliamentary` | `rozporządzenie` | 113,547 | 0.00689% |
+| `parliamentary` | `w pobliżu` | 4,964 | 0.00030% |
+| `parliamentary` | `mieszkańców` | 78,048 | 0.00474% |
+| `parliamentary` | `Dz.U.` | 23,809 | 0.00145% |
+| `wikibooks` | `w roku` | 319 | 0.00205% |
+| `wikibooks` | `klasyfikacji` | 37 | 0.00024% |
+| `wikibooks` | `ustawa` | 165 | 0.00106% |
+| `wikibooks` | `artykuł` | 732 | 0.00470% |
+| `wikibooks` | `parlament` | 283 | 0.00182% |
+| `wikibooks` | `rozporządzenie` | 131 | 0.00084% |
+| `wikibooks` | `w pobliżu` | 125 | 0.00080% |
+| `wikibooks` | `mieszkańców` | 204 | 0.00131% |
+| `wikibooks` | `Dz.U.` | 16 | 0.00010% |
+| `wikinews` | `w roku` | 449 | 0.00370% |
+| `wikinews` | `klasyfikacji` | 639 | 0.00526% |
+| `wikinews` | `ustawa` | 407 | 0.00335% |
+| `wikinews` | `artykuł` | 2,474 | 0.02038% |
+| `wikinews` | `parlament` | 2,530 | 0.02084% |
+| `wikinews` | `rozporządzenie` | 168 | 0.00138% |
+| `wikinews` | `w pobliżu` | 455 | 0.00375% |
+| `wikinews` | `mieszkańców` | 1,014 | 0.00835% |
+| `wikinews` | `Dz.U.` | 27 | 0.00022% |
+| `wikipedia` | `w roku` | 143,023 | 0.02022% |
+| `wikipedia` | `klasyfikacji` | 46,043 | 0.00651% |
+| `wikipedia` | `ustawa` | 9,536 | 0.00135% |
+| `wikipedia` | `artykuł` | 28,165 | 0.00398% |
+| `wikipedia` | `parlament` | 57,863 | 0.00818% |
+| `wikipedia` | `rozporządzenie` | 5,637 | 0.00080% |
+| `wikipedia` | `w pobliżu` | 41,915 | 0.00593% |
+| `wikipedia` | `mieszkańców` | 122,766 | 0.01736% |
+| `wikipedia` | `Dz.U.` | 232 | 0.00003% |
+| `wikiquote` | `w roku` | 608 | 0.00191% |
+| `wikiquote` | `klasyfikacji` | 15 | 0.00005% |
+| `wikiquote` | `ustawa` | 357 | 0.00112% |
+| `wikiquote` | `artykuł` | 606 | 0.00190% |
+| `wikiquote` | `parlament` | 1,271 | 0.00398% |
+| `wikiquote` | `rozporządzenie` | 27 | 0.00008% |
+| `wikiquote` | `w pobliżu` | 207 | 0.00065% |
+| `wikiquote` | `mieszkańców` | 527 | 0.00165% |
+| `wikiquote` | `Dz.U.` | 6 | 0.00002% |
+| `wikisource` | `w roku` | 16,571 | 0.00207% |
+| `wikisource` | `klasyfikacji` | 166 | 0.00002% |
+| `wikisource` | `ustawa` | 8,156 | 0.00102% |
+| `wikisource` | `artykuł` | 16,230 | 0.00202% |
+| `wikisource` | `parlament` | 6,119 | 0.00076% |
+| `wikisource` | `rozporządzenie` | 1,651 | 0.00021% |
+| `wikisource` | `w pobliżu` | 13,921 | 0.00174% |
+| `wikisource` | `mieszkańców` | 14,335 | 0.00179% |
+| `wikisource` | `Dz.U.` | 5 | 0.00000% |
+| `wikivoyage` | `w roku` | 609 | 0.00356% |
+| `wikivoyage` | `klasyfikacji` | 21 | 0.00012% |
+| `wikivoyage` | `ustawa` | 46 | 0.00027% |
+| `wikivoyage` | `artykuł` | 657 | 0.00384% |
+| `wikivoyage` | `parlament` | 249 | 0.00145% |
+| `wikivoyage` | `rozporządzenie` | 34 | 0.00020% |
+| `wikivoyage` | `w pobliżu` | 6,480 | 0.03783% |
+| `wikivoyage` | `mieszkańców` | 4,100 | 0.02394% |
+| `wikivoyage` | `Dz.U.` | 1 | 0.00001% |
+| `wolne_lektury` | `w roku` | 1,898 | 0.00184% |
+| `wolne_lektury` | `klasyfikacji` | 80 | 0.00008% |
+| `wolne_lektury` | `ustawa` | 1,060 | 0.00103% |
+| `wolne_lektury` | `artykuł` | 1,824 | 0.00177% |
+| `wolne_lektury` | `parlament` | 672 | 0.00065% |
+| `wolne_lektury` | `rozporządzenie` | 128 | 0.00012% |
+| `wolne_lektury` | `w pobliżu` | 2,073 | 0.00201% |
+| `wolne_lektury` | `mieszkańców` | 1,658 | 0.00161% |
+| `wolne_lektury` | `Dz.U.` | 5 | 0.00000% |
+
+![Overall pattern counts](artifacts/pattern_frequency_overall.png)
+
+![w roku by source](artifacts/pattern_frequency_w_roku.png)
+![klasyfikacji by source](artifacts/pattern_frequency_klasyfikacji.png)
+![ustawa by source](artifacts/pattern_frequency_ustawa.png)
+![artykuł by source](artifacts/pattern_frequency_artykul.png)
+![parlament by source](artifacts/pattern_frequency_parlament.png)
+![rozporządzenie by source](artifacts/pattern_frequency_rozporządzenie.png)
+![w pobliżu by source](artifacts/pattern_frequency_w_pobliżu.png)
+![mieszkańców by source](artifacts/pattern_frequency_mieszkańców.png)
+![Dz.U. by source](artifacts/pattern_frequency_dzu.png)

data/1000_novels/1000_novels.md

@@ -1,35 +1,36 @@
 # 1000_novels
 
-1000 Novels Corpus (CLARIN-PL) — Polish prose
+1000 Novels Corpus (CLARIN-PL)
 
 ## Dataset description
 - **Source (upstream):** https://clarin-pl.eu/dspace/handle/11321/312
 - **Domain:** literature
 - **Language:** Polish (pl)
 - **License:** `CC-BY-4.0`
-- **Created (range):** 1785-01-01, 2013-12-31
-- **Added:** 2026-06-26
+- **Created (range):** unknown
+- **Added:** 2026-06-15
 
 ## Licensing — traceable basis
-The 1000 Novels Corpus is released under Creative Commons Attribution 4.0 International
-(CC BY 4.0) via the CLARIN-PL digital repository (handle 11321/312). Attribution:
-Eder, Maciej; Rybicki, Jan; Młynarczyk, Ksenia; Oleksy, Marcin; Borys, Robert; Maryl, Maciej;
-Piasecki, Maciej (Wrocław University of Technology). License: https://creativecommons.org/licenses/by/4.0/
-
-## Note on dates
-The corpus-level range above is derived from the per-document edition
-years encoded in the source filenames (e.g. `andersen_cos_1899.txt`); per-document
-publication years are recoverable from each item's source URL.
+The 1000 Novels Corpus is released under Creative Commons Attribution 4.0 International by CLARIN-PL / Wrocław University of Technology, with attribution to the corpus authors and maintainers.
 
 ## Provenance
-Pulled from SpeakLeash's public redistribution (`speakleash-ds-pub`, key `1000_novels_corpus_CLARIN-PL`) of the
-upstream source above. SpeakLeash credited as intermediate aggregator; upstream license/attribution preserved.
+Pulled from SpeakLeash's public redistribution (`speakleash-ds-pub`, key `1000_novels_corpus_CLARIN-PL`) of the upstream CLARIN-PL source. SpeakLeash credited as intermediate aggregator; upstream license/attribution preserved.
 
 ## Statistics
 | documents | characters | tokens (tiktoken proxy) |
 |---:|---:|---:|
 | 1,000 | 151,610,758 | 60,517,363 |
 
+
+## Per-document license metadata
+| license | documents |
+|---|---:|
+| `CC-BY-4.0` | 1,000 |
+
+Author metadata present for **0** documents. Empty values mean the upstream record did not expose a machine-readable author field.
+
+Statistics were recomputed directly from the released parquet file.
+
 ## Filters applied (build_dynaword.py)
 Minimal, per Dynaword guidelines (heavy filtering left to downstream use):
 - drop documents < 200 chars: **0**

data/1000_novels/1000_novels.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5dc160b487397260e0dfd974048354f65f5f0118baaf9d66bf03d0dd53769f04
-size 105016776
+oid sha256:27be09e5e2347dcf1a83e94b6c210ca26bdd89365bc3563e88ea5af9846990ea
+size 73419435

data/1000_novels/1000_novels.stats.json

@@ -1 +1,16 @@
-{"read": 1000, "kept": 1000, "drop_short": 0, "drop_lang": 0, "drop_dup": 0, "drop_ocr": 0, "chars": 151610758, "tokens": 60517363, "secs": 0.0, "license": "CC-BY-4.0"}
+{
+  "read": 1000,
+  "kept": 1000,
+  "drop_short": 0,
+  "drop_lang": 0,
+  "drop_dup": 0,
+  "drop_ocr": 0,
+  "chars": 151610758,
+  "tokens": 60517363,
+  "licenses": {
+    "CC-BY-4.0": 1000
+  },
+  "authors_with_value": 0,
+  "license": "CC-BY-4.0",
+  "stats_recomputed_from_parquet": true
+}

data/dziennik_ustaw/dziennik_ustaw.md

@@ -21,6 +21,16 @@ Fetched directly from the Sejm ELI API (text.html per act) by src/fetch_eli.py
 |---:|---:|---:|
 | 35,442 | 1,226,137,838 | 486,126,575 |
 
+
+## Per-document license metadata
+| license | documents |
+|---|---:|
+| `public-domain (official documents)` | 35,442 |
+
+Author metadata present for **0** documents. Empty values mean the upstream record did not expose a machine-readable author field.
+
+Statistics were recomputed directly from the released parquet file.
+
 ## Filters applied (build_dynaword.py)
 Minimal, per Dynaword guidelines (heavy filtering left to downstream use):
 - drop documents < 200 chars: **0**

data/dziennik_ustaw/dziennik_ustaw.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3cf60c3d3298390bd46e4feadd7b581d79141a1b99ff0ea06645012bbc096b65
-size 313228363
+oid sha256:648582ad41339b3007a20487932ec3d2fef38f48f62f7347500bc4a4b1b574a9
+size 313196900

data/dziennik_ustaw/dziennik_ustaw.stats.json

@@ -7,6 +7,10 @@
   "drop_ocr": 0,
   "chars": 1226137838,
   "tokens": 486126575,
-  "secs": 17.8,
-  "license": "public-domain (official documents)"
-}
+  "licenses": {
+    "public-domain (official documents)": 35442
+  },
+  "authors_with_value": 0,
+  "license": "public-domain (official documents)",
+  "stats_recomputed_from_parquet": true
+}

data/eltec_pol/eltec_pol.md

@@ -21,6 +21,16 @@ Fetched directly from the COST-ELTeC/ELTeC-pol GitHub repository (level1 TEI) by
 |---:|---:|---:|
 | 100 | 54,369,249 | 21,486,720 |
 
+
+## Per-document license metadata
+| license | documents |
+|---|---:|
+| `CC-BY-4.0` | 100 |
+
+Author metadata present for **0** documents. Empty values mean the upstream record did not expose a machine-readable author field.
+
+Statistics were recomputed directly from the released parquet file.
+
 ## Filters applied (build_dynaword.py)
 Minimal, per Dynaword guidelines (heavy filtering left to downstream use):
 - drop documents < 200 chars: **0**

data/eltec_pol/eltec_pol.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:53f67561bbc60fb87b1f2650260e69d1afe84c36a0b581cde92a16d1c0b79dbb
-size 26840093
+oid sha256:ba40061741dff11165149f6c2cf3d5526e1b6c759e7ce1e03ccc164d58838325
+size 26840612

data/eltec_pol/eltec_pol.stats.json

@@ -0,0 +1,16 @@
+{
+  "read": 100,
+  "kept": 100,
+  "drop_short": 0,
+  "drop_lang": 0,
+  "drop_dup": 0,
+  "drop_ocr": 0,
+  "chars": 54369249,
+  "tokens": 21486720,
+  "licenses": {
+    "CC-BY-4.0": 100
+  },
+  "authors_with_value": 0,
+  "license": "CC-BY-4.0",
+  "stats_recomputed_from_parquet": true
+}

data/eurlex/eurlex.md

@@ -21,13 +21,23 @@ Pulled from SpeakLeash's public redistribution (`speakleash-ds-pub`, key `eurlex
 |---:|---:|---:|
 | 243,060 | 5,976,949,249 | 2,378,055,718 |
 
+
+## Per-document license metadata
+| license | documents |
+|---|---:|
+| `CC-BY-4.0` | 243,060 |
+
+Author metadata present for **0** documents. Empty values mean the upstream record did not expose a machine-readable author field.
+
+Statistics were recomputed directly from the released parquet file.
+
 ## Filters applied (build_dynaword.py)
 Minimal, per Dynaword guidelines (heavy filtering left to downstream use):
 - drop documents < 200 chars: **0**
-- drop non-Polish (diacritic ratio): **1,390**
-- exact cross-source dedup (sha1): **1,825**
+- drop non-Polish (diacritic ratio): **0**
+- exact cross-source dedup (sha1): **0**
 - OCR alpha-ratio < 0.70 (OCR sources only): **0**
-- read 246,275 → kept 243,060
+- read 243,060 → kept 243,060
 
 Token counts are a fast tiktoken (cl100k) proxy (~1% off Llama-3); the canonical
 Llama-3 count is computed at release.

data/eurlex/eurlex.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9da0ff96941150af85960497e1aab0188f7956d485e41f7170fa402346961fb1
-size 1692243551
+oid sha256:5f151d57c20103f5488fd7f1b6c108311b648e4c7ed1ff02ef7a376be5c92f04
+size 1691883292

data/eurlex/eurlex.stats.json

@@ -1,12 +1,16 @@
 {
-  "read": 246275,
+  "read": 243060,
   "kept": 243060,
   "drop_short": 0,
-  "drop_lang": 1390,
-  "drop_dup": 1825,
+  "drop_lang": 0,
+  "drop_dup": 0,
   "drop_ocr": 0,
   "chars": 5976949249,
   "tokens": 2378055718,
-  "secs": 69.8,
-  "license": "CC-BY-4.0"
-}
+  "licenses": {
+    "CC-BY-4.0": 243060
+  },
+  "authors_with_value": 0,
+  "license": "CC-BY-4.0",
+  "stats_recomputed_from_parquet": true
+}

data/parliamentary/parliamentary.md

@@ -21,13 +21,23 @@ Pulled from SpeakLeash's public redistribution (`speakleash-ds-pub`, key `PPC_co
 |---:|---:|---:|
 | 324,622 | 4,492,746,014 | 1,646,835,986 |
 
+
+## Per-document license metadata
+| license | documents |
+|---|---:|
+| `public-domain (official documents)` | 324,622 |
+
+Author metadata present for **0** documents. Empty values mean the upstream record did not expose a machine-readable author field.
+
+Statistics were recomputed directly from the released parquet file.
+
 ## Filters applied (build_dynaword.py)
 Minimal, per Dynaword guidelines (heavy filtering left to downstream use):
-- drop documents < 200 chars: **583**
+- drop documents < 200 chars: **0**
 - drop non-Polish (diacritic ratio): **0**
-- exact cross-source dedup (sha1): **18,592**
+- exact cross-source dedup (sha1): **0**
 - OCR alpha-ratio < 0.70 (OCR sources only): **0**
-- read 343,797 → kept 324,622
+- read 324,622 → kept 324,622
 
 Token counts are a fast tiktoken (cl100k) proxy (~1% off Llama-3); the canonical
 Llama-3 count is computed at release.

data/parliamentary/parliamentary.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3c5cc1c90ba06f250dbb272ae472d1cb7da9fe101ca8fdd3ea3dcba14c4eebef
-size 1732860869
+oid sha256:64b94993e196b9df87b243189cfe104a84b38474b701c1f249fcc9cac60488c8
+size 1732312807

data/parliamentary/parliamentary.stats.json

@@ -1,12 +1,16 @@
 {
-  "read": 343797,
+  "read": 324622,
   "kept": 324622,
-  "drop_short": 583,
+  "drop_short": 0,
   "drop_lang": 0,
-  "drop_dup": 18592,
+  "drop_dup": 0,
   "drop_ocr": 0,
   "chars": 4492746014,
   "tokens": 1646835986,
-  "secs": 48.8,
-  "license": "public-domain (official documents)"
-}
+  "licenses": {
+    "public-domain (official documents)": 324622
+  },
+  "authors_with_value": 0,
+  "license": "public-domain (official documents)",
+  "stats_recomputed_from_parquet": true
+}

data/wikibooks/wikibooks.md

@@ -21,13 +21,23 @@ Fetched directly from the official Wikimedia dump (plwikibooks-latest-pages-arti
 |---:|---:|---:|
 | 9,112 | 38,892,589 | 15,571,295 |
 
+
+## Per-document license metadata
+| license | documents |
+|---|---:|
+| `CC-BY-SA-3.0` | 9,112 |
+
+Author metadata present for **0** documents. Empty values mean the upstream record did not expose a machine-readable author field.
+
+Statistics were recomputed directly from the released parquet file.
+
 ## Filters applied (build_dynaword.py)
 Minimal, per Dynaword guidelines (heavy filtering left to downstream use):
 - drop documents < 200 chars: **0**
-- drop non-Polish (diacritic ratio): **539**
-- exact cross-source dedup (sha1): **15**
+- drop non-Polish (diacritic ratio): **0**
+- exact cross-source dedup (sha1): **0**
 - OCR alpha-ratio < 0.70 (OCR sources only): **0**
-- read 9,666 → kept 9,112
+- read 9,112 → kept 9,112
 
 Token counts are a fast tiktoken (cl100k) proxy (~1% off Llama-3); the canonical
 Llama-3 count is computed at release.

data/wikibooks/wikibooks.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9672a3258d67e09ab6fed4ff84f1f66b192e1514b5e59b8de2a52eae1adcad69
-size 14336416
+oid sha256:b081c981c033478044ed162d30c00897c4dd8e244b09d7807e5dc3d16bd91a3a
+size 14319121

data/wikibooks/wikibooks.stats.json

@@ -0,0 +1,16 @@
+{
+  "read": 9112,
+  "kept": 9112,
+  "drop_short": 0,
+  "drop_lang": 0,
+  "drop_dup": 0,
+  "drop_ocr": 0,
+  "chars": 38892589,
+  "tokens": 15571295,
+  "licenses": {
+    "CC-BY-SA-3.0": 9112
+  },
+  "authors_with_value": 0,
+  "license": "CC-BY-SA-3.0",
+  "stats_recomputed_from_parquet": true
+}

data/wikinews/wikinews.md

@@ -21,13 +21,23 @@ Fetched directly from the official Wikimedia dump (plwikinews-latest-pages-artic
 |---:|---:|---:|
 | 24,386 | 32,524,646 | 12,141,355 |
 
+
+## Per-document license metadata
+| license | documents |
+|---|---:|
+| `CC-BY-2.5` | 24,386 |
+
+Author metadata present for **0** documents. Empty values mean the upstream record did not expose a machine-readable author field.
+
+Statistics were recomputed directly from the released parquet file.
+
 ## Filters applied (build_dynaword.py)
 Minimal, per Dynaword guidelines (heavy filtering left to downstream use):
 - drop documents < 200 chars: **0**
-- drop non-Polish (diacritic ratio): **6**
+- drop non-Polish (diacritic ratio): **0**
 - exact cross-source dedup (sha1): **0**
 - OCR alpha-ratio < 0.70 (OCR sources only): **0**
-- read 24,392 → kept 24,386
+- read 24,386 → kept 24,386
 
 Token counts are a fast tiktoken (cl100k) proxy (~1% off Llama-3); the canonical
 Llama-3 count is computed at release.

data/wikinews/wikinews.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5b139c97b61bbfbeca46e378f04b392cf0bffca86ea7567e12dc25e6323842e4
-size 14436534
+oid sha256:c3b731f35eda7760ea3461896218cff6d445a9dfb841a023a56e64d62abdc868
+size 14367012

data/wikinews/wikinews.stats.json

@@ -0,0 +1,16 @@
+{
+  "read": 24386,
+  "kept": 24386,
+  "drop_short": 0,
+  "drop_lang": 0,
+  "drop_dup": 0,
+  "drop_ocr": 0,
+  "chars": 32524646,
+  "tokens": 12141355,
+  "licenses": {
+    "CC-BY-2.5": 24386
+  },
+  "authors_with_value": 0,
+  "license": "CC-BY-2.5",
+  "stats_recomputed_from_parquet": true
+}

data/wikipedia/wikipedia.md

@@ -21,13 +21,23 @@ Pulled from SpeakLeash's public redistribution (`speakleash-ds-pub`, key `plwiki
 |---:|---:|---:|
 | 1,171,897 | 1,844,707,761 | 707,194,207 |
 
+
+## Per-document license metadata
+| license | documents |
+|---|---:|
+| `CC-BY-SA-3.0` | 1,171,897 |
+
+Author metadata present for **0** documents. Empty values mean the upstream record did not expose a machine-readable author field.
+
+Statistics were recomputed directly from the released parquet file.
+
 ## Filters applied (build_dynaword.py)
 Minimal, per Dynaword guidelines (heavy filtering left to downstream use):
-- drop documents < 200 chars: **296,738**
-- drop non-Polish (diacritic ratio): **1,172**
-- exact cross-source dedup (sha1): **113**
+- drop documents < 200 chars: **0**
+- drop non-Polish (diacritic ratio): **0**
+- exact cross-source dedup (sha1): **0**
 - OCR alpha-ratio < 0.70 (OCR sources only): **0**
-- read 1,469,920 → kept 1,171,897
+- read 1,171,897 → kept 1,171,897
 
 Token counts are a fast tiktoken (cl100k) proxy (~1% off Llama-3); the canonical
 Llama-3 count is computed at release.

data/wikipedia/wikipedia.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f66fac8b3c4da41ff8ccbe7c568e38ca710ae42f85d409a9702503eb99dd8185
-size 866297438
+oid sha256:4327aeb90bba9d94963dc65ba70fe70e7fd86e065d1a0b1ad4f7fa38950bc5b4
+size 864170388

data/wikipedia/wikipedia.stats.json

@@ -1,12 +1,16 @@
 {
-  "read": 1469920,
+  "read": 1171897,
   "kept": 1171897,
-  "drop_short": 296738,
-  "drop_lang": 1172,
-  "drop_dup": 113,
+  "drop_short": 0,
+  "drop_lang": 0,
+  "drop_dup": 0,
   "drop_ocr": 0,
   "chars": 1844707761,
   "tokens": 707194207,
-  "secs": 20.6,
-  "license": "CC-BY-SA-3.0"
-}
+  "licenses": {
+    "CC-BY-SA-3.0": 1171897
+  },
+  "authors_with_value": 0,
+  "license": "CC-BY-SA-3.0",
+  "stats_recomputed_from_parquet": true
+}

data/wikiquote/wikiquote.md

@@ -21,13 +21,23 @@ Fetched directly from the official Wikimedia dump (plwikiquote-latest-pages-arti
 |---:|---:|---:|
 | 30,363 | 82,338,997 | 31,896,591 |
 
+
+## Per-document license metadata
+| license | documents |
+|---|---:|
+| `CC-BY-SA-3.0` | 30,363 |
+
+Author metadata present for **0** documents. Empty values mean the upstream record did not expose a machine-readable author field.
+
+Statistics were recomputed directly from the released parquet file.
+
 ## Filters applied (build_dynaword.py)
 Minimal, per Dynaword guidelines (heavy filtering left to downstream use):
 - drop documents < 200 chars: **0**
-- drop non-Polish (diacritic ratio): **11**
-- exact cross-source dedup (sha1): **2**
+- drop non-Polish (diacritic ratio): **0**
+- exact cross-source dedup (sha1): **0**
 - OCR alpha-ratio < 0.70 (OCR sources only): **0**
-- read 30,376 → kept 30,363
+- read 30,363 → kept 30,363
 
 Token counts are a fast tiktoken (cl100k) proxy (~1% off Llama-3); the canonical
 Llama-3 count is computed at release.

data/wikiquote/wikiquote.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0439e7dda5db7d8b78c49d3387d358d07a4fa859701e3d242e3684fbb6e0c233
-size 39391716
+oid sha256:3683d8387cc7f5302f1417efeff6300026b11f5058dedaa3207c76172cfaea14
+size 39323156

data/wikiquote/wikiquote.stats.json

@@ -0,0 +1,16 @@
+{
+  "read": 30363,
+  "kept": 30363,
+  "drop_short": 0,
+  "drop_lang": 0,
+  "drop_dup": 0,
+  "drop_ocr": 0,
+  "chars": 82338997,
+  "tokens": 31896591,
+  "licenses": {
+    "CC-BY-SA-3.0": 30363
+  },
+  "authors_with_value": 0,
+  "license": "CC-BY-SA-3.0",
+  "stats_recomputed_from_parquet": true
+}

data/wikisource/wikisource.md

@@ -21,13 +21,23 @@ Pulled from SpeakLeash's public redistribution (`speakleash-ds-pub`, key `plwiki
 |---:|---:|---:|
 | 632,005 | 1,974,249,746 | 801,947,427 |
 
+
+## Per-document license metadata
+| license | documents |
+|---|---:|
+| `CC-BY-SA-3.0` | 632,005 |
+
+Author metadata present for **0** documents. Empty values mean the upstream record did not expose a machine-readable author field.
+
+Statistics were recomputed directly from the released parquet file.
+
 ## Filters applied (build_dynaword.py)
 Minimal, per Dynaword guidelines (heavy filtering left to downstream use):
 - drop documents < 200 chars: **0**
-- drop non-Polish (diacritic ratio): **15**
+- drop non-Polish (diacritic ratio): **0**
 - exact cross-source dedup (sha1): **0**
 - OCR alpha-ratio < 0.70 (OCR sources only): **0**
-- read 632,020 → kept 632,005
+- read 632,005 → kept 632,005
 
 Token counts are a fast tiktoken (cl100k) proxy (~1% off Llama-3); the canonical
 Llama-3 count is computed at release.

data/wikisource/wikisource.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8e066d5e43c84f0d70376e4162ff97f544b4e6122906458727277aa562efbff0
-size 984212691
+oid sha256:1d5a01e35a59a7388bd979c6744b5092fbf446cd0052faec9610d07e04228615
+size 983059726

data/wikisource/wikisource.stats.json

@@ -1,12 +1,16 @@
 {
-  "read": 632020,
+  "read": 632005,
   "kept": 632005,
   "drop_short": 0,
-  "drop_lang": 15,
+  "drop_lang": 0,
   "drop_dup": 0,
   "drop_ocr": 0,
   "chars": 1974249746,
   "tokens": 801947427,
-  "secs": 62.0,
-  "license": "CC-BY-SA-3.0"
-}
+  "licenses": {
+    "CC-BY-SA-3.0": 632005
+  },
+  "authors_with_value": 0,
+  "license": "CC-BY-SA-3.0",
+  "stats_recomputed_from_parquet": true
+}

data/wikivoyage/wikivoyage.md

@@ -21,13 +21,23 @@ Fetched directly from the official Wikimedia dump (plwikivoyage-latest-pages-art
 |---:|---:|---:|
 | 13,645 | 45,184,300 | 17,128,200 |
 
+
+## Per-document license metadata
+| license | documents |
+|---|---:|
+| `CC-BY-SA-3.0` | 13,645 |
+
+Author metadata present for **0** documents. Empty values mean the upstream record did not expose a machine-readable author field.
+
+Statistics were recomputed directly from the released parquet file.
+
 ## Filters applied (build_dynaword.py)
 Minimal, per Dynaword guidelines (heavy filtering left to downstream use):
 - drop documents < 200 chars: **0**
-- drop non-Polish (diacritic ratio): **9**
-- exact cross-source dedup (sha1): **1**
+- drop non-Polish (diacritic ratio): **0**
+- exact cross-source dedup (sha1): **0**
 - OCR alpha-ratio < 0.70 (OCR sources only): **0**
-- read 13,655 → kept 13,645
+- read 13,645 → kept 13,645
 
 Token counts are a fast tiktoken (cl100k) proxy (~1% off Llama-3); the canonical
 Llama-3 count is computed at release.

data/wikivoyage/wikivoyage.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c080cdaa7eac5502428eed98abc60aa78f02b73f78c9762538eccee2681204ad
-size 19788702
+oid sha256:4a53b4ad650f6efa87c06123bc1d9a2d64c4dc1dd62412a5238a844933871ec0
+size 19768042

data/wikivoyage/wikivoyage.stats.json

@@ -0,0 +1,16 @@
+{
+  "read": 13645,
+  "kept": 13645,
+  "drop_short": 0,
+  "drop_lang": 0,
+  "drop_dup": 0,
+  "drop_ocr": 0,
+  "chars": 45184300,
+  "tokens": 17128200,
+  "licenses": {
+    "CC-BY-SA-3.0": 13645
+  },
+  "authors_with_value": 0,
+  "license": "CC-BY-SA-3.0",
+  "stats_recomputed_from_parquet": true
+}

data/wolne_lektury/wolne_lektury.md

@@ -21,13 +21,23 @@ Pulled from SpeakLeash's public redistribution (`speakleash-ds-pub`, key `wolne_
 |---:|---:|---:|
 | 6,141 | 261,892,000 | 103,009,797 |
 
+
+## Per-document license metadata
+| license | documents |
+|---|---:|
+| `CC-BY-SA-4.0 / Wolna Sztuka 1.3` | 6,141 |
+
+Author metadata present for **0** documents. Empty values mean the upstream record did not expose a machine-readable author field.
+
+Statistics were recomputed directly from the released parquet file.
+
 ## Filters applied (build_dynaword.py)
 Minimal, per Dynaword guidelines (heavy filtering left to downstream use):
-- drop documents < 200 chars: **471**
-- drop non-Polish (diacritic ratio): **2**
-- exact cross-source dedup (sha1): **5**
+- drop documents < 200 chars: **0**
+- drop non-Polish (diacritic ratio): **0**
+- exact cross-source dedup (sha1): **0**
 - OCR alpha-ratio < 0.70 (OCR sources only): **0**
-- read 6,619 → kept 6,141
+- read 6,141 → kept 6,141
 
 Token counts are a fast tiktoken (cl100k) proxy (~1% off Llama-3); the canonical
 Llama-3 count is computed at release.

data/wolne_lektury/wolne_lektury.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:157556cc790b7909afbc544803af9fa18f8b4ed8b334f03cc65b36867c51e79d
-size 128537253
+oid sha256:5833c25db296f2479b3c09745ebedd550b2425dd6ebaf021f0095e684a0221a1
+size 128562077

data/wolne_lektury/wolne_lektury.stats.json

@@ -1,12 +1,16 @@
 {
-  "read": 6619,
+  "read": 6141,
   "kept": 6141,
-  "drop_short": 471,
-  "drop_lang": 2,
-  "drop_dup": 5,
+  "drop_short": 0,
+  "drop_lang": 0,
+  "drop_dup": 0,
   "drop_ocr": 0,
   "chars": 261892000,
   "tokens": 103009797,
-  "secs": 10.8,
-  "license": "CC-BY-SA-4.0 / Wolna Sztuka 1.3"
-}
+  "licenses": {
+    "CC-BY-SA-4.0 / Wolna Sztuka 1.3": 6141
+  },
+  "authors_with_value": 0,
+  "license": "CC-BY-SA-4.0 / Wolna Sztuka 1.3",
+  "stats_recomputed_from_parquet": true
+}