refactor: migrate to deck-based vocabulary curation

Database Schema:
- Add decks table for curated word lists (A1, Most Common, etc.)
- Add deck_terms join table with position ordering
- Link rooms to decks via rooms.deck_id FK
- Remove frequency_rank from terms (now deck-scoped)
- Change users.id to uuid, add openauth_sub for auth mapping
- Add room_players.left_at for disconnect tracking
- Add rooms.updated_at for stale room recovery
- Add CHECK constraints for data integrity (pos, status, etc.)

Extraction Script:
- Rewrite extract.py to mirror complete OMW dataset
- Extract all 25,204 bilingual noun synsets (en-it)
- Remove frequency filtering and block lists
- Output all lemmas per synset for full synonym support
- Seed data now uncurated; decks handle selection

Architecture:
- Separate concerns: raw OMW data in DB, curation in decks
- Enables user-created decks and multiple difficulty levels
- Rooms select vocabulary by choosing a deck

scripts/requirements.txt

@@ -1 +1 @@
-nltk>=3.8
+wn==1.1.0