# dev.uapf.semantic-document-analysis — Overview

**UAPF v1.1 SSOT-conformant** Level 4 process package for semantic
document analysis.

## What

A six-node BPMN process that, given free-text document content:

1. **Detect and redact PII** (`ai.redact@1`) — masks PII and returns the
   deterministic regex signal set (personas kods / IBAN / contact data /
   category count).
2. **Assess personal-data risk** (DMN `assess-personal-data-risk`) —
   ranked rules map the signal set to `personalDataRisk`.
3. **Decide GDPR processing route** (DMN `gdpr-processing-route`) —
   `personalDataRisk` x `allowCentralization` -> CENTRAL/LOCAL,
   anonymisation and redaction level.
4. **Extract semantic metadata** (`ai.extract@1`) — the one model step;
   produces VDVC v1.1 structured metadata.
5. **Determine validation status** (DMN `human-validation-gate`) —
   confidence thresholds + PII re-scan -> REJECTED / PENDING_REVIEW /
   APPROVED_AUTO.
6. **Emit** `document.semantic-analysis.completed.v1` (`event.emit@1`).

## Why this shape

The previous 1.x package was a single `ai.extract` call wrapped in
BPMN. The decision logic — risk, routing, validation gating — lived
invisibly in host code. Version 2.0 extracts that logic into three
versioned DMN decision tables. The algorithm is now in the package:
inspectable, diff-able, portable. The host supplies inference for one
bounded step only.

## What's portable

- The BPMN flow (the process shape)
- Three DMN decision tables (the algorithm and its weights)
- The VDVC output JSON Schema (the extraction contract)
- The resource mapping and the guardrails policy

## How to consume

Drop this `.uapf` into any UAPF-conformant runtime and run
`Process_SemanticDocumentAnalysis`. The runtime evaluates the DMN
decisions itself and resolves the resource mapping for the three
capability-backed service tasks.