#!/usr/bin/env python3 """Extract the authoritative SSAO term set: the membership oracle for validation. The Space Situational Awareness Ontology (Rovetto, as vendored by the NASA mission-viz project) is the target vocabulary. Every ssao: term the model emits must exist here, or it is a hallucination by construction. """ import json import pathlib from rdflib import Graph, RDF, RDFS, OWL, Namespace ROOT = pathlib.Path("/Users/fabio/projects/qwen-space-ft") KGREPO = pathlib.Path("/Users/fabio/projects/neurosymbolic-space-kg") SSAO = "https://purl.org/space-ontology/" SKOS = Namespace("http://www.w3.org/2004/02/skos/core#") g = Graph() g.parse(KGREPO / "ontology" / "SSAO_Rovetto.owl", format="turtle") def local(u): s = str(u) return s.split("#")[-1].split("/")[-1] def in_ns(u): return str(u).startswith(SSAO) classes = {} for s in set(g.subjects(RDF.type, OWL.Class)) | set(g.subjects(RDF.type, RDFS.Class)): if not in_ns(s): continue ln = local(s) label = g.value(s, RDFS.label) defn = g.value(s, SKOS.definition) or g.value(s, RDFS.comment) supers = [local(o) for o in g.objects(s, RDFS.subClassOf) if in_ns(o)] classes[ln] = { "label": str(label) if label else ln.replace("_", " "), "definition": str(defn)[:400] if defn else "", "subClassOf": supers, } props = {} for s in (set(g.subjects(RDF.type, OWL.ObjectProperty)) | set(g.subjects(RDF.type, OWL.DatatypeProperty)) | set(g.subjects(RDF.type, RDF.Property))): if not in_ns(s): continue ln = local(s) props[ln] = { "definition": str(g.value(s, SKOS.definition) or g.value(s, RDFS.comment) or "")[:300], "domain": [local(o) for o in g.objects(s, RDFS.domain) if in_ns(o)], "range": [local(o) for o in g.objects(s, RDFS.range) if in_ns(o)], } # authoritative membership set: every ssao-namespaced term appearing anywhere all_terms = sorted({local(n) for t in g for n in t if in_ns(n)}) # our own lifted catalogue vocabulary (the source side of the published alignment) kgv = Graph() kgv.parse(KGREPO / "kg" / "out" / "satcat-vocab.ttl", format="turtle") KGNS = "https://w3id.org/tesseract/space-kg/" kg_terms = sorted({local(s) for s in kgv.subjects(RDF.type, OWL.Class) if str(s).startswith(KGNS)}) vocab = { "ssao_namespace": SSAO, "kg_namespace": KGNS, "classes": classes, "properties": props, "class_names": sorted(classes), "property_names": sorted(props), "all_terms": all_terms, "kg_class_names": kg_terms, } (ROOT / "data").mkdir(exist_ok=True) (ROOT / "data" / "vocab.json").write_text(json.dumps(vocab, indent=1)) print(f"SSAO: {len(classes)} classes, {len(props)} properties, {len(all_terms)} terms total") print(f"lifted catalogue vocabulary: {len(kg_terms)} classes") print("sample classes:", ", ".join(sorted(classes)[:8]))