# Enrichment PILOT — sign-off required before full-corpus scaling

**Date:** 2026-05-29. Pilot covers **34 activities** (the STOP gate from `HANDOFF.md`
step 3, guarding ~6–8k LLM calls across the full corpus).

## Pipeline integrity (all green)

| Hop | Expected | Actual |
|-----|----------|--------|
| prompts emitted | 34 | 34 |
| part files on disk (valid JSON, key matches filename) | 34 | 34 |
| `enrichment.json` entries after `--collect` | 34 | 34 |
| rebuild overlay: `matched` / `orphaned` | 34 / 0 | **34 / 0** |

No leak at any hop. `orphaned 0` confirms the content_key the rebuild computes
matches what `run_enrichment` emitted (no dedup rep-selection drift).

## Pilot composition

Deliberately mixed to exercise BOTH operations (corpus is 7076 EN / 2465 RO, so
en→ro translation is the dominant + highest-risk path):

- **26** rows from `teambuilding_corbu` — all Romanian → **ro→ro polish**
- **8** rows from `d3959920_outdoor_games` — all English → **en→ro translation**

Result: ~7 genuine en→ro translations + ~27 ro→ro polish.

## Field population (stated vs estimated)

```
age_group_max     : 0 stated / 30 estimated
age_group_min     : 0 / 34
duration_max      : 3 / 29
duration_min      : 4 / 28
indoor_outdoor    : 12 / 22
participants_max  : 0 / 24
participants_min  : 4 / 30
space_needed      : 2 / 32
```

Almost everything is estimated — sources rarely state ages/durations explicitly.
The pipeline marks every inferred field in `estimated_fields`, and the UI shows an
`(estimat)` marker, so estimates are transparent to end users.

## What to evaluate (the three sign-off axes)

1. **Translation fidelity (en→ro)** — e.g. *Labels → Etichete*, *Ships in a Fog →
   Nave în ceață*, *Spot the Colours → Găsește culorile*. Game rules preserved,
   no moralizing added, proper terms kept.
2. **Description fidelity / expansion** — ro→ro rows fold in setup/material detail
   that IS in the source chunk (e.g. *Găsește-ți fratele și sora* adds "carton A6"
   + "la semnal, toți încep simultan"; *Ce-mi place?* folds in the character-traits
   discussion). No invented steps observed.
3. **Estimation plausibility** — mostly reasonable. **Weak spots to judge:** a few
   age ranges are very wide/defaulted (e.g. *Găsește-ți fratele și sora* → age
   10–99). If wide age defaults are unacceptable, tighten the ENRICHMENT_PROMPT
   guidance before scaling.

## Inspect the data yourself

```bash
sqlite3 data/activities.db "select name, name_ro, language, indoor_outdoor, space_needed, estimated_fields from activities where name_ro is not null;"
# raw overlay: data/enrichment.json (34 entries)
# per-activity parts: data/enrichment_parts/*.json
```

## After sign-off (do NOT auto-proceed)

Scale in waves of ~8–16 Sonnet subagents over the rest of the corpus
(`run_enrichment.py` is additive + resumable — skips already-enriched keys),
`--collect`, then final `build_database.py --rebuild --enrichment`.