add splits

README.md

@@ -36,6 +36,7 @@ definitions. The full category catalog remains in the source collection.
 | `data/topic-provenance.jsonl.gz` | Frozen initial/final assignments and review status for all Full IDs. | 127,895 |
 | `data/noow.csv` | Whole-document text and ordered normalized VW features. | 1,118,455,706 |
 | `data/bow.csv` | The same documents with counted VW features. | 875,143,956 |
+| `data/splits.json` | Optional fit/calibration/validation memberships by article ID. | 291,038 |
 
 [SHA256SUMS](SHA256SUMS) covers this repository's published data. Preparation code,
 environment locks and source/output pins are maintained once in the
@@ -94,7 +95,8 @@ are not thereby certified correct.
 
 The original JSON records have no NLP preprocessing or model scoring. The
 optional preparation workflow below produces separate NLP CSV files without a
-research train/test split. The `corpus` split is a storage partition. Source text
+research train/test split; a fixed reference partition is supplied separately in
+`data/splits.json`. The `corpus` split is a storage partition. Source text
 has not been shortened or rewritten for subject selection. No exact duplicate source text was
 removed. This collection is not a representative sample of Russian writing.
 
@@ -161,6 +163,51 @@ required: these files are not additional YAML configurations, because combining
 JSON and CSV builders in one repository configuration did not load reliably.
 The published CSV files have been fully read with Hugging Face Datasets.
 
+### Optional reference splits
+
+[data/splits.json](data/splits.json) maps each partition name to an ordered list
+of article IDs. The lists are disjoint and together cover all 17,251 articles:
+
+| Partition | Documents | Intended use |
+| --- | ---: | --- |
+| `fit` | 10,342 | Fit models and training-dependent vocabularies or statistics. |
+| `calibration` | 3,434 | Tune parameters and make development decisions. |
+| `validation` | 3,475 | Evaluate the selected procedure on held-out documents. |
+
+The partition uses multilabel group stratification with approximate proportions
+60/20/20 and seeds 20260824 and 20260825 for the two successive splits.
+Near-duplicate articles, identified by Jaccard similarity ≥0.9 between sets of
+five-word shingles, stay in the same partition. The procedure found one such
+pair; both articles are in `fit`. No articles were removed.
+
+The same IDs occur in `articles`, `noow.csv`, `bow.csv` and `labels.json`.
+The Hugging Face split `corpus` still contains the whole collection; use the
+stored memberships when you want this reference partition. After loading
+`articles` above, run from the root of a downloaded repository:
+
+```python
+import json
+from pathlib import Path
+from datasets import DatasetDict
+
+splits = json.loads(Path("data/splits.json").read_text(encoding="utf-8"))
+index = {doc_id: i for i, doc_id in enumerate(articles["id"])}
+partitioned = DatasetDict({
+    name: articles.select([index[doc_id] for doc_id in ids])
+    for name, ids in splits.items()
+})
+print({name: len(part) for name, part in partitioned.items()})
+# {'calibration': 3434, 'fit': 10342, 'validation': 3475}
+```
+
+For either CSV representation, replace `articles` with the loaded `noow` or
+`bow` dataset. Selection preserves the order recorded in `splits.json`.
+The shared corpus/NLP preparation workflow does not generate this supplementary
+partition. Its published ngrams use all article bodies, so applying the
+memberships does not make those features training-only; see the NLP preparation
+section below. Text-only modeling can use `@word` and fit any further vocabulary
+or statistics on `fit` alone.
+
 To export one VW document per line without loading the CSV into memory, run this
 from the downloaded repository. Choose an output path outside the repository:
 
@@ -545,8 +592,9 @@ sample of Russian writing or an evenly balanced subject collection. Quality
 status does not guarantee accuracy, neutrality, completeness or suitability for
 any downstream application. Articles can contain sensitive, biased, outdated or
 offensive material. The partial subject labels described here do not establish a complete reference
-annotation. Further downstream preprocessing, deduplication policy and research
-splits must be specified separately.
+annotation. The optional reference splits above provide one document partition;
+further downstream preprocessing, deduplication and any alternative split policy
+must be specified for each study.
 
 ## File verification
 
@@ -556,7 +604,7 @@ Run from this downloaded repository's root:
 sha256sum -c SHA256SUMS
 ```
 
-[SHA256SUMS](SHA256SUMS) covers all six data files, excluding this README and
+[SHA256SUMS](SHA256SUMS) covers all seven data files, excluding this README and
 Git/service metadata. Full has its own manifest for its data and shared
 preparation files. The shared corpus contract independently pins expected
 published reconstruction payloads. A successful local checksum check establishes

SHA256SUMS

@@ -4,3 +4,4 @@ e7ceacd69d76601df24bb42e6d0177f46142d0b8ac1bf6e8c22ad4d5a0b0ca70  data/labels.js
 2c71aa6b5a327ebe924f5f0160eaf6f923a86da1a3a7fe8c68aa67f8858f8b6b  data/noow.csv
 c8cf602a924f18255e155cdcaa9357907461851e849113c72051c2b89484f22c  data/topics.jsonl.gz
 f5749b942b8028f955863cea1afc44d06bc0b36eaf83dc9071e11913029b807f  data/topic-provenance.jsonl.gz
+798a38e397af640901e7f832694d69457d4d6d2982d435fe2d5756e2e5e4aa0b  data/splits.json