ssao-space-instruct

Instruction data teaching a language model to write valid RDF Turtle in the Space Situational Awareness Ontology (SSAO) for real space objects, and to judge proposed catalogue-to-ontology alignments using instance evidence.

1,245 examples: 1,072 train, 74 validation, 99 test. Built by Tesseract Academy.

The construction principle

No example asserts anything a validator cannot check. Every Turtle target is generated from a real CelesTrak SATCAT record by applying a published, argued SATCAT-to-SSAO alignment, so the ontology terms are correct by derivation rather than by authorship. A fail-closed vocabulary gate refuses to emit the dataset at all if any ssao: term in any target is missing from the ontology's authoritative 554-term set.

That gate earned its place immediately: the first builder version invented ssao:hasOrbit and ssao:hasInclination, which SSAO does not define (the real names are has_Orbit, has_Orbital_Inclination). Shipping those would have taught fluent hallucination in a domain whose ontology cannot reject it, which is exactly the failure mode the accompanying study measures.

Task families

Family	n (approx)	What it teaches
T1 record to Turtle	900	Catalogue fields to SSAO-typed Turtle with correct prefixes
T2 term lookup	60	Domain question to the correct SSAO class, with SSAO's definition
T3 alignment judgement	55	Accept or refuse a proposed correspondence, with argument and witness counts
T4 orbit regime	200	Orbital elements to regime class, with the deciding threshold cited
T5 refusal	30	Explicit refusal where the catalogue cannot determine the answer

T3 is the unusual one. Positive rows come from a curated crosswalk; negative rows come from its asserted non-mappings plus mappings that were empirically refuted by counting counter-instances in the catalogue, with the witness counts quoted as the justification. For example, refusing kg:RegimeGEORegion = ssao:Geostationary_Orbit cites 1,007 of 1,734 geosynchronous-band residents whose inclination exceeds 5 degrees. We are not aware of another public dataset covering alignment judgement with extensional evidence.

Sources and provenance

• CelesTrak SATCAT, snapshot 2026-07-29, pinned by sha256. 70,122 objects; T1 and T4 draw on a random sample. Data courtesy of T.S. Kelso.
• Space Situational Awareness Ontology by Robert J. Rovetto, in the copy vendored by the NASA mission-viz project (351 classes, 150 properties).
• The alignment and the witness counts come from neurosymbolic-space-kg, which contains the builder, the validator, the vocabulary gate and the measurements. Everything regenerates from source.

Format

Chat-formatted JSONL, one object per line, with a fixed system prompt:

{"messages": [
  {"role": "system", "content": "You are a space-domain knowledge engineer..."},
  {"role": "user", "content": "Express this catalogue record as SSAO Turtle...."},
  {"role": "assistant", "content": "@prefix ssao: <https://purl.org/space-ontology/> ...."}
]}

Known limitations

• Property coverage is deliberately narrow: only the SSAO properties the catalogue can populate honestly (COSPAR number, country of origin, launch date, orbit, inclination, period, perigee, apogee). Most of SSAO's 150 properties are untouched.
• Status codes are operator-reported and can be stale; T1 targets inherit that.
• Derived orbit regimes rest on stated thresholds (2000 km for LEO, a 1400 to 1500 minute geosynchronous band, 5 degrees for geostationary candidacy). They are conventions, printed in the builder and adjustable; a sensitivity sweep of their influence is published in the repository.
• The alignment judgements are a curated position, reviewable and arguable, not ground truth.
• Roughly 72 percent of examples are one task family (T1), so a model trained on this alone will be strongest at record-to-Turtle.

License

CC BY 4.0. SATCAT data courtesy of CelesTrak; SSAO by Robert J. Rovetto. Please attribute both alongside this dataset.