Ten production-grade slices drawn from a live operational graph — joined, canonicalised, pseudonymised, provenance-back-linked, and shipped with three orthogonal privacy gauges in a signed manifest.
Every entity carries a JSON-LD @type array. Every passage carries a PROV-O back-link. Every edge carries (t_valid, t_invalid, t_created, t_expired) — contradictions invalidate rather than overwrite.
25.5K contacts · 6.2K companies · 87 deals across HubSpot, Salesforce, Asana and Jira — joined into one canonical knowledge graph with HMAC-keyed pseudonyms.
~38 GB · ~4.5B markdown characters from Drive and iCloud. 7,326 organisations and 4,044 persons extracted with provenance back to source URIs.
70,019 mapping edges across 15 ontologies — BFO, FIBO, UFO, PROV-O, SDLC, CWE, OWASP — on 110 repos. 43% of latest-revision functions carry ≥ 1 mapping.
6,698 unique trace IDs · 21,117 embedded passages. Every passage carries a PROV-O back-link to its source document URI.
A reviewer audits any slice without re-running the pipeline: recompute SHA-256 over the bytes, confirm the gauge band matches the value, verify the operator's ed25519 signature against the published fingerprint.
Per-slice keys rotated per release. Canonical URIs never leave the resolver — only HMAC-derived pseudonym IDs ship in the pack.
Each slice carries a band — tight / moderate / wide — for distributional distance from the held-out reference. Villani 2009; scipy bootstrap CI.
Likelihood-ratio attack at FPR = 10⁻³ against a shadow model. We ship the band, not the raw score. Carlini et al. 2022.
Secret-Sharer canaries planted at controlled rarity; we publish the 95th-percentile exposure as an upper bound. Carlini 2019 + 2021.
FULL BIBLIOGRAPHY IN THE DECK APPENDIX
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