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README.md

@@ -4,10 +4,10 @@ configs:
   data_files:
   - split: train
     path: epo_patents/*.parquet
-- config_name: wikidata_triples
+- config_name: wikidata_seed
   data_files:
   - split: train
-    path: wikidata_triples/*.parquet
+    path: wikidata_seed/*.parquet
 - config_name: personas
   data_files:
   - split: train
@@ -22,7 +22,7 @@ Volumes below describe what is available beyond these samples.
 | Config | Sample | Available |
 |---|---|---|
 | `epo_patents` | 107 sections / 7 patents | 1.08M patents processed (2020-2025); 8.25M-document full-text backfile 1978-2025 (5.49M with description/claims, ~48B words) |
-| `wikidata_triples` | 2.37M triples / 48.8k subjects | 558M triples, 2,369 shards, ~34.5 GB |
+| `wikidata_seed` | 2M triples / 849k subjects | 558M triples, ~34.5 GB |
 | `personas` | 100k personas / 108 countries | 57.3M personas |
 
 More configs to follow: financial regulation (24 regulators, 12+ jurisdictions), 3GPP
@@ -43,22 +43,28 @@ so `identifier` is the publication number and supplementary fields sit in `metad
 `date` is the publication year. Note that some documents are republications after opposition,
 where the original grant year differs — that year is preserved in `metadata`.
 
-## wikidata_triples
+## wikidata_seed
 
 Wikidata statements parsed into subject-property-value triples with labels resolved and
-qualifiers attached (~30% of statements carry a qualifier). `value_type` distinguishes entity
-references from strings, quantities, times, coordinates, and monolingual text.
+qualifiers attached. `value_type` distinguishes entity references from strings, quantities,
+times, coordinates, and monolingual text.
+
+This sample is drawn across shards spread through the corpus and shuffled. It is a **curated
+seed** rather than a raw dump: database cross-reference properties (external identifiers such as
+Commons category, VIAF, GeoNames, Freebase) are removed, as are Wikimedia-internal subjects
+(categories, templates, disambiguation pages) and auto-generated numeric items. Unit references
+inside quantity values are resolved to labels. Cleaning retains ~73% of source rows.
 
 ## personas
 
 Synthetic population personas across 108 countries, demographically grounded: name, sex, age,
-region and place (with coordinates and settlement tier), marital status, education, employment
-status, occupation, religion, monthly income in PPP dollars, and health conditions.
+place (with coordinates and settlement tier), marital status, education, employment status,
+occupation, religion, monthly income in PPP dollars, and health conditions.
 
-Location is given as place name with coordinates and settlement tier (administrative
-subdivision codes are not included). This sample is drawn across the full corpus and shuffled; per-country counts stay proportional
-to the underlying population weighting. `persona_id` is globally unique (`country`-`id`);
-`country_row_id` preserves the original per-country identifier.
+Location is given as place name with coordinates and settlement tier (administrative subdivision
+codes are not included). This sample is drawn across the full corpus and shuffled; per-country
+counts stay proportional to the underlying population weighting. `persona_id` is globally unique
+(`country`-`id`).
 
 ## Licensing