F.R.A.C.C. Distributed Matrix

Technical Brief

F.R.A.C.C. translates a sentence into a deterministic semantic profile. It classifies each input across seven arcs: essence, form, action, frame, intent, relation, and value.

Each arc is scored across three processing phases, combined into a triadic sum, and ranked into a final weighted output. The result is a reproducible synthesis payload rather than a freeform interpretation layer.

• Input model: tokenized natural language with arc-specific lexicon matching.
• Processing model: three-phase scoring with bounded polarity and magnitude weighting.
• Output model: ranked semantic primitives for downstream synthesis and inspection.