# ReviewIQ v3.2 Design Decisions

> Fast context-recovery document — all key decisions without the full spec.

---

## 1. Markpoint

```
ID:       reviewiq-v32-span-layer-2026-01-24-001
Status:   v3.2 span layer complete
Based on: v3.1.2 (commit f998277)
```

---

## 2. Core Design Decisions

| Decision | Choice | Rationale |
|----------|--------|-----------|
| Span granularity | Clause/topic-level | Preserves multi-domain signal |
| span_id format | ULID (TEXT) | Survives re-segmentation |
| Span offsets | Required (NOT NULL) | Deterministic reconstruction |
| Offsets reference | reviews_enriched.text | Not text_normalized |
| Span → Issue mapping | One-to-one (UNIQUE span_id) | Atomic unit per issue |
| Primary span enforcement | Partial unique index | Exactly one per review version |
| Primary selection | I3>I2>I1, V->V±>V0>V+, span_index | Deterministic, stable |
| Reprocessing strategy | Soft-switch with is_active | No transient empty states |
| Span overlap | GiST exclusion constraint | Non-overlapping ranges enforced |
| Secondary codes | Array with cardinality ≤ 2 | Could normalize to link table later |
| Causal chain storage | JSONB | Flexibility, normalize later if needed |
| relation_type vs causal_chain | Separate concerns | relation = within-review, causal = root cause |
| Dimension columns | Postgres ENUMs | Type safety, storage efficiency |
| Trust score floor | 0.2 (GREATEST clamp) | Prevent multiplicative collapse |
| Issue routing key | (business_id, place_id, urt_primary, entity_normalized) | Deterministic, entity-aware |
| Issue ID generation | SHA256 via pgcrypto | Deterministic, collision-resistant |
| Text validation trigger | Conditional via session setting | Performance: skip in bulk loads |
| Relation validation | Application-level post-insert | Handles insertion order |

---

## 3. Extensions Required

| Extension | Purpose |
|-----------|---------|
| `btree_gist` | Exclusion constraint for non-overlapping spans |
| `pgcrypto` | SHA256-based issue ID generation |

---

## 4. New Tables

| Table | Purpose |
|-------|---------|
| `review_spans` | Span-level URT classification |
| `review_span_secondary_codes` | (Optional) Normalized secondary codes |

---

## 5. Modified Tables

| Table | Changes |
|-------|---------|
| `issue_spans` | Added `span_id` FK (NOT NULL), removed direct review FK as canonical |

---

## 6. New ENUM Types

**Valence & Intensity:**
- `urt_valence` — V-, V±, V0, V+
- `urt_intensity` — I1, I2, I3

**Specificity & Actionability:**
- `urt_specificity` — S1, S2, S3
- `urt_actionability` — A1, A2, A3

**Context & Evidence:**
- `urt_temporal` — TC (current), TR (recent), TH (historical), TF (future)
- `urt_evidence` — ES (stated), EI (inferred), EC (contextual)
- `urt_comparative` — CR-N (none), CR-B (better), CR-W (worse), CR-S (same)

**Classification:**
- `urt_profile` — lite, core, standard, full
- `urt_confidence` — low, medium, high
- `urt_relation` — cause_of, effect_of, contrast, resolution
- `urt_entity_type` — location, staff, product, process, time, other

---

## 7. Key Functions

| Function | Purpose |
|----------|---------|
| `urt_validate_causal_chain()` | Validates causal JSONB structure |
| `validate_review_relations()` | Ensures related_span_id same-parent |
| `validate_active_spans()` | Ensures valid active span set |
| `set_primary_span()` | Deterministic primary selection |
| `generate_issue_id()` | SHA256-based issue ID |

---

## 8. Key Triggers

| Trigger | Purpose |
|---------|---------|
| `review_spans_validate_bounds` | span_end ≤ text length |
| `review_spans_validate_text` | span_text matches substring |
| `review_spans_validate_causal_chain` | causal_chain JSONB valid |

---

## 9. USN Format

```
Standard: URT:S:{codes}:{V}{I}:{S}{A}{T}.{E}.{CR}
Full:     URT:F:{codes}:{V}{I}:{S}{A}{T}.{E}.{CR}:{causal}
```

**Examples:**
- `URT:S:SVC.SPD:V-I3:S3A3T2.E2.CR1` — Specific service speed complaint
- `URT:F:PRD.QUA:V+I2:S2A1T1.E3.CR2:staff→training` — Product quality praise with causal chain

---

## 10. Span Boundary Rules

1. **Split on contrasting conjunctions** — "but", "however", "although"
2. **Split on topic/target change** — Different entity or aspect
3. **Split on valence change** — Positive → Negative or vice versa
4. **Split on domain change** — SVC → PRD → AMB
5. **Keep cause→effect together** — Causal chain stays in one span

---

## 11. Deferred to v3.3+

| Item | Reason |
|------|--------|
| Entity extraction implementation | Requires NER pipeline |
| Trust-weighted fact aggregation | Needs more span data |
| Secondary domain enforcement | App-level validation sufficient |
| Span-based fact counting | Currently review-based, optimize later |

---

## 12. Open Questions Resolved

| Question | Resolution |
|----------|------------|
| Span → Issue cardinality? | **One-to-one** (not many-to-many) |
| Offsets nullable for LLM-inferred? | **No** — required, NOT NULL |
| Reprocessing strategy? | **Soft-switch** with is_active flag |
| TEXT vs ENUM for dimensions? | **ENUMs** — committed to Postgres |

---

## Quick Reference

### Primary Span Selection Algorithm

```
ORDER BY:
  1. intensity DESC (I3 > I2 > I1)
  2. valence ASC (V- > V± > V0 > V+)
  3. span_index ASC (first wins ties)
```

### Issue Routing Key

```sql
(business_id, place_id, urt_primary, entity_normalized)
```

### Trust Score Calculation

```sql
GREATEST(0.2, base_trust * modifiers)  -- Floor prevents collapse
```

---

*Last updated: 2026-01-24*