> ## Documentation Index
> Fetch the complete documentation index at: https://docs.spineworkspace.com/llms.txt
> Use this file to discover all available pages before exploring further.

# 06 — Classification

> How material is classified by type, domain, sensitivity, and confidence before review.

# Classification

## How Triage Classifies

Triage evaluates every incoming piece of evidence across multiple dimensions:

### Dimension 1: Source and Provenance

* Where did this come from? (MCP, conversation, agent, manual)
* Who produced it? (user, AI, system)
* Is the source trusted? (known connector vs unknown)

### Dimension 2: Semantic Category

* What type of knowledge is this?
* Categories: insight, fact, decision, action\_item, preference, relationship
* Domain: executive, product, engineering, design, sales, marketing, etc.

### Dimension 3: Entity Linking

* Which known entities does this relate to? (accounts, contacts, deals, etc.)
* Is this a new entity or an update to an existing one?
* Confidence of the link

### Dimension 4: Duplication and Conflict

* Does this duplicate existing canonical memory?
* Does it conflict with established truth?
* Is it stale (old information presented as current)?

### Dimension 5: Sensitivity and Materiality

* How sensitive is this information?
* Is it material (business-significant) or trivial?
* Does it require governance review?

### Dimension 6: Memory Scope

* Should this be personal, conversational, agent, or organizational scope?
* Does it meet the threshold for organizational memory?

## Classification Output

Every triage evaluation produces:

```json theme={null}
{
  "classification": {
    "doc_type": "lead|document|policy|code|... ",
    "workflow_type": "sales|marketing|engineering|... ",
    "intent": "description of intent"
  },
  "linking": {
    "primary_entity": "entity_id",
    "related_entities": ["entity_id_1", "entity_id_2"]
  },
  "canonical_review": {
    "is_duplicate": false,
    "has_conflict": false,
    "conflict_reason": null
  },
  "memory": {
    "scope": "organizational",
    "candidate": true
  },
  "governance": {
    "decision": "stage",
    "reason": "High-value decision with clear entity links"
  }
}
```

## Routing Decisions

| Decision | Meaning | Action |
| - | - | - |
| `stage` | Candidate for review | Write to triage\_results as pending |
| `reject` | Below threshold or spam | Terminal, no memory |
| `defer` | Needs more context | Return to review queue |
| `repair` | Incomplete, fixable | Route for repair then re-triage |

## Confidence Dimensions

Confidence is six things, and one number must never represent all six:

1. **Pattern confidence** — How well does this match known patterns?
2. **Prediction confidence** — How likely is this to be accurate?
3. **Input completeness** — How complete is the source data?
4. **Data freshness** — How current is the information?
5. **Historical precision** — How accurate has this source been?
6. **Policy eligibility** — Does this meet policy requirements?

Small samples use a named conservative lower bound, not raw accuracy. 3/3 is not better evidence than 470/500.


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