SOTAB v2 Coverage Strategy

Ownership note (2026-05-09). Going forward, all ontology / vocabulary / synthetic-data work moves to Ægir. The label space conditions model pre-training directly, so it lives where the model lives. Atelier becomes the consumer of trained artifacts (H-Net/RWKV checkpoints + SVMs trained on Ægir-curated datasets). This document stays in Atelier’s docs as the specification of what we want covered; the actual TTL extensions, generators, and SOTAB integration implementation belong in ~/local/src/zndx/aegir/.

This document specifies how the BFO/CCO-grounded vocabulary should cover the SOTAB v2 Schema.org CTA label space (82 labels), so the hierarchical RWKV-7 model in Ægir can ladder predictions up from raw benchmark labels to BFO/CCO concepts.

Background

• Atelier (current): ICE trichotomy (Designative / Descriptive / Prescriptive) grounded through Common Core Ontologies into BFO 2020. 20 Schema.org subjects mapped today (11 classes, 9 properties) in src/atelier/classify/ontology/atelier-vocab.ttl. This snapshot remains operational for the existing classification pipeline during the migration window.
• Atelier (future): consumer of pre-trained model artifacts. Loads H-Net/RWKV checkpoints and SVMs trained in Ægir against ontology-grounded label spaces; uses them as evidence sources in DST fusion. No longer owns vocabulary.
• Ægir (current → future ontology home): hierarchical RWKV-7 model targeting CTA + CPA on wide tables, trained against gt-signals-dbpedia and SOTAB v2. SOTAB infrastructure already wired: scripts/download_sotab.py fetches the four canonical bundles, src/aegir/data/table_dataset.py loads sotab_v2_cta_*_set.csv reference labels. Inheriting atelier-vocab.ttl + synth generators is part of the M2 roadmap.
• Synthetic data pipeline: currently in atelier (synth_generators.py, 316+ generators). Migration target: Ægir, since the generators feed pre-training corpora directly. Atelier’s classification pipeline can consume generator output via a thin client during transition.

Authoritative SOTAB v2 label space

Verified against /raid/datasets/sotab/sotab_v2_cta_*_set.csv (union of training, validation, test, and the three robustness test sets: corner_cases, missing_values, format_heterogeneity):

82 distinct CTA labels covering 17 root entity types

Root entity types (from webdatacommons.org/structureddata/sotab/v2/, Table 2): Book, CreativeWork, Event, Hotel, JobPosting, LocalBusiness, Movie, Museum, MusicAlbum, MusicRecording, Person, Place, Product, Recipe, Restaurant, SportsEvent, TVEpisode.

The 82 labels are a mix of:

• Class names — Country, MonetaryAmount, Organization, etc.
• Entity-property pairs — Book/name, Hotel/description, JobPosting/description (the slash separates entity type from the property whose value the column carries).
• Measurement units — Distance, Duration, Energy, Mass.
• Enumeration types — BookFormatType, EventStatusType, GenderType, RestrictedDiet.
• Coded attribute types — CoordinateAT, IdentifierAT, MusicArtistAT (the AT suffix denotes “atomic type”, a SOTAB convention, not Schema.org).

Aegir’s stale _LABEL_DIMS["sotab"] = 91 comment in src/aegir/data/table_dataset.py should be reduced to 82; the extra 9 appear to be carry-over from an earlier label set draft.

Coverage analysis

Direct hits (14 of 82)

Already grounded in atelier-vocab.ttl:

Subsumption-reachable (~20 of 82)

Subclasses of types already grounded — adding them is a single rdfs:subClassOf edge under the existing CCO branch:

Schema:CreativeWork descendants (8): Book/description, Book/name, BookFormatType, Movie/description, Movie/name, Recipe/description, Recipe/name, MusicAlbum/name, MusicRecording/name, TVEpisode/name, CreativeWorkSeries, Photograph, Review.

Schema:Organization descendants (5): Hotel/description, Hotel/name, LocalBusiness/name, Museum/name, Restaurant/name, SportsTeam.

Schema:Event descendants (1): SportsEvent/name.

Schema:PostalAddress sub-properties (4): addressLocality, addressRegion, postalCode, streetAddress.

Schema:QuantitativeValue measurement subtypes (4 + 1): Distance, Duration, Energy, Mass, weight (column-as-property).

Missing — requires new vocab work (~48 of 82)

Grouped by extension target:

Three-tier extension strategy

Tier-A — measurement zoo (lowest effort, highest leverage)

Add ~10 schema:QuantitativeValue subclasses under cco:DescriptiveICE:

schema:Distance       rdfs:subClassOf cco:ont00000853 .  # Descriptive ICE
schema:Duration       rdfs:subClassOf cco:ont00000853 .
schema:Energy         rdfs:subClassOf cco:ont00000853 .
schema:Mass           rdfs:subClassOf cco:ont00000853 .
schema:Speed          rdfs:subClassOf cco:ont00000853 .
schema:Temperature    rdfs:subClassOf cco:ont00000853 .

Plus property-level: unitCode, unitText, weight.

Implementation: ~10 lines in atelier-vocab.ttl, ~5 generators in synth_generators.py (already have NUMERIC.* generators that can be re-keyed to schema URIs).

SOTAB labels covered: 10 (Distance, Duration, Energy, Mass, weight, unitCode, unitText, Number, Boolean, plus one ancillary).

Tier-B — subclass plumbing (CreativeWork + Organization + Event subtrees)

Single-edge additions for entity types already grounded at parent level:

schema:Book           rdfs:subClassOf schema:CreativeWork .
schema:Movie          rdfs:subClassOf schema:CreativeWork .
schema:Recipe         rdfs:subClassOf schema:CreativeWork .
schema:MusicAlbum     rdfs:subClassOf schema:CreativeWork .
schema:MusicRecording rdfs:subClassOf schema:CreativeWork .
schema:TVEpisode      rdfs:subClassOf schema:CreativeWork .
schema:Photograph     rdfs:subClassOf schema:CreativeWork .
schema:Review         rdfs:subClassOf schema:CreativeWork .
schema:Hotel          rdfs:subClassOf schema:Organization .
schema:LocalBusiness  rdfs:subClassOf schema:Organization .
schema:Museum         rdfs:subClassOf schema:Organization .
schema:Restaurant     rdfs:subClassOf schema:Organization .
schema:SportsTeam     rdfs:subClassOf schema:Organization .
schema:SportsEvent    rdfs:subClassOf schema:Event .

Implementation: ~14 lines in atelier-vocab.ttl, ~14 SSSOM annotation blocks, ~14 generators in synth_generators.py.

SOTAB labels covered: ~20 (entity-property pairs cascade through parent’s name/description mappings).

Tier-C — Product branch + JobPosting + economics

Largest single addition; introduces cco:Artifact lineage:

schema:Product        rdfs:subClassOf cco:Artifact .       # NEW branch
schema:ProductModel   rdfs:subClassOf cco:ArtifactModel .  # NEW
schema:Brand          rdfs:subClassOf cco:DesignativeICE . # NEW
schema:JobPosting     rdfs:subClassOf cco:DescriptiveICE . # NEW

Plus property-level mappings: price, priceRange, currency, paymentAccepted, DeliveryMethod, ItemAvailability, OfferItemCondition, workHours, OccupationalExperienceRequirements, EducationalOccupationalCredential.

Plus temporal refinements: Date, DateTime, Time, DayOfWeek as subproperties of existing TIMESTAMP lineage.

Plus enumerations: CategoryCode, EventStatusType, EventAttendanceModeEnumeration, GenderType, RestrictedDiet, BookFormatType (~6 enumeration classes).

Implementation: ~30 lines in atelier-vocab.ttl, comparable SSSOM annotation overhead, ~25 new synth generators (Product family is its own generator pack: SKU, brand, model, GTIN, etc.).

SOTAB labels covered: remaining ~48.

Cumulative coverage after all three tiers

100% of the 82 SOTAB v2 Schema.org CTA labels mapped to BFO/CCO grounding, with provenance trails (SSSOM sssom:object_label axioms) for every mapping.

Ownership flow (post-migration)

During the migration window (until ontology fully relocates), atelier keeps its operational atelier-vocab.ttl snapshot. The concrete contract Ægir publishes to atelier becomes a vocab_label_map.json (IRI + BFO ancestry per SOTAB label) plus the trained model checkpoints themselves.

Aegir touchpoints (informative, not prescriptive)

The work in Ægir, in roadmap terms, lands inside its M2 milestone (“external-baseline harness, ontology editor with Postgres write paths, per-class F1 bars”):

• src/aegir/data/table_dataset.py — fix the stale _LABEL_DIMS["sotab"] = 91 to 82; add a label_to_iri resolver that consumes the shared sotab_label_map.json.
• scripts/sotab_diagnostic.py — extend representation-collapse diagnostics to surface per-tier (A/B/C) coverage of predictions, so we can see whether collapses correlate with vocab gaps.
• Leaderboard gateway (src/aegir/gateway/app.py) — /api/ontology endpoint already exists; extend its response to include the BFO ancestry of each predicted label.
• src/aegir/models/heads.py::AegirForColumnAnnotation — no model change needed for tier work; the head already operates on a (num_labels,) output, and 82 vs 91 is just a config delta.

The pretraining work documented in aegir/docs/notes/2026-04-19/234700_sotab_diagnostic_representation_collapse.md (model collapses to single embedding point on SOTAB-small) is orthogonal to this strategy — it’s a model issue, not a vocabulary issue. Vocab extension proceeds independently and should improve the post-collapse ceiling once representations are healthy.

Synthetic data pipeline implications

The synth framework (synth_generators.py, 316+ hand-coded generators plus the three-layer registry) migrates to Ægir with the rest of the ontology work. Ægir-resident synth gives pre-training direct access to generator output without crossing repo boundaries. After Tier-A/B/C extensions:

• Tier-A adds measurement generators — DURATION (ISO-8601 strings), MASS (with unit suffix), DISTANCE, ENERGY — these are mostly numeric with unit annotations. Existing NUMERIC.* generators can be re-keyed.
• Tier-B adds entity-name generators — BOOK_TITLE, MOVIE_TITLE, RECIPE_NAME, HOTEL_NAME, etc. Cascade through the registry’s template priority (priority 2): once Ægir has ~50 real Book/name samples from SOTAB itself, the registry generates plausible book titles via perturbation.
• Tier-C adds product attribute generators — SKU, Brand, GTIN, ProductModel. Domain-specific; benefit from hand-coded generators (priority 1) seeded with realistic patterns.

Atelier’s classification pipeline, post-migration, can either (a) call into Ægir’s synth via a thin client during local dev, or (b) bundle a generator snapshot at release time. The decision depends on whether Atelier’s BDD/pytest scenarios remain self-contained or are content to require Ægir as a sibling repo.

Verification

Coverage is mechanically verifiable via SPARQL totality:

PREFIX cco: <https://www.commoncoreontologies.org/>
PREFIX schema: <https://schema.org/>

# Every SOTAB label must have a path to cco:InformationContentEntity (or descendant).
SELECT ?label WHERE {
  VALUES ?label { schema:Distance schema:Duration schema:Mass ... }  # all 82
  FILTER NOT EXISTS {
    ?label rdfs:subClassOf+ cco:ont00000958 .  # cco:InformationContentEntity
  }
}
# Empty result == 100% coverage.

This goes in src/atelier/classify/ontology/sparql/sotab_totality.rq once Tier-A lands.

Status

• Strategy doc: this file (2026-05-09).
• Ownership migration: Ægir takes over ontology / vocab / synth.
• Tier-A implementation: Ægir M2 — vocab edits + SSSOM annotations + SPARQL totality query + measurement generators.
• Tier-B implementation: Ægir M2.
• Tier-C implementation: Ægir M3.

Atelier’s contribution post-migration is consumption-side: load Ægir’s trained checkpoints as DST evidence sources, surface BFO ancestry via the gateway/UI, integrate predictions into the existing belief/plausibility fusion machinery. The vocabulary itself, and the work to extend it, lives next to the model that uses it.