Three Structural Surfaces, One Store

SERAPH is the only knowledge substrate with three distinct structural surfaces over the same content:

• Embedding field — geometric proximity (cosine similarity). Emergent from content.
• Parent tree — lineage proximity (who parented to whom at ingest time). Emergent from ingest order.
• Typed edges — explicit, user-asserted relations (cites, depends_on, causes, or any domain-specific relation). Declared, not inferred.

The first two are emergent, they fall out of the data. The third is curated, it captures directional, authoritative relations the geometry has no way to assert: citation, causal links, domain-specific structure. Two relations people often expect to live here are handled natively instead, and neither needs a typed edge: contradiction is detected from the emergent geometry (see below), and supersession is a frame-lifecycle status (Superseded, plus redirect frames on consolidation), not an edge. All three surfaces share the same provenance guarantees. Typed-edge mutations are recorded as sentinel frames in the watermark chain, they're as tamper-evident as content commits.

Emergent surfaces: agreement and disagreement. The embedding field and parent tree can agree, disagree, or partially overlap. SERAPH exposes this through a three-population model:

Population	Meaning
Consensus	Both surfaces agree — tight, well-formed concept zone.
Geometric-only	Cosine-close but lineage-distant — cross-domain analogy candidates.
Lineage-only	Same subtree but cosine-distant — concept drift within a lineage.

The ratios between populations are themselves diagnostic — no other system can compute them because no other system has both emergent surfaces. This is also how SERAPH detects contradiction: a pair that is cosine-close but whose content diverges (geometric or consensus population) is a conflict the geometry surfaces on its own, no edge required. Contradiction is a property of the geometry, read directly off these two surfaces.

Typed edges: structure the geometry can't see. An embedding can tell you two frames are semantically close. It cannot tell you one cites the other as evidence, that one causes another, or any domain-specific relation you need to author. Those are directional, authoritative claims neither the geometry nor the frame lifecycle expresses. Typed edges capture them. (Contradiction and supersession are different — contradiction SERAPH detects geometrically, and supersession is carried by frame status. A typed contradicts or supersedes edge is only for recording a curated, adjudicated assertion on top of those native mechanisms, never the primary way SERAPH knows.) Typed edges are:

• Append-only and auditable. Assertions and retractions are logged as sentinel frames — never mutated, always replayable.
• Structurally isolated. Typed edges never affect in-degree, eigenframe promotion, or similarity scoring. The emergent geometry stays pure.
• Composable with search. structural_expand chains typed-edge traversal with similarity queries — "find everything this frame cites, then expand semantically from those targets" is a single operation.
• Bidirectional when declared. A cites relation can auto-insert the reverse cited_by edge at assert time.

A vector database gives you geometric proximity. A knowledge graph gives you authored structure. SERAPH gives you both — plus their interaction — in one file, with one provenance chain.