Atlas Coarse Types for LLM Extraction
======================================

Use these 12 types when prompting a cheap/small LLM for entity type suggestion.
The suggested type is a hint to the entity resolver for candidate ranking — not
a final classification. Pass 2 (Wikidata QID lookup) promotes to the fine-grained
subtype from the full ontology.


COARSE TYPES
------------

Person
Organization
Location
CreativeWork
Event
Product
FinancialInstrument
Animal
Disease
Building
FictionalCharacter
Other


PASS 2 PROMOTION MAP
--------------------

Person              -> Person

Organization        -> Organization
                       PoliticalParty
                       MilitaryUnit
                       MediaOrganization

Location            -> Location
                       Continent
                       Country
                       Region
                       PopulatedPlace
                       Neighbourhood
                       NaturalFeature
                       AdministrativeArea

CreativeWork        -> CreativeWork
                       Film
                       Book
                       MusicAlbum
                       TVSeries
                       VideoGame

Event               -> Event

Product             -> Product
                       Drug
                       Food

FinancialInstrument -> FinancialInstrument
                       PublicCompany
                       StockIndex
                       Commodity
                       Cryptocurrency
                       Currency

Animal              -> Animal

Disease             -> Disease

Building            -> Building

FictionalCharacter  -> FictionalCharacter

Other               -> Other
                       Award
                       Sport
                       EthnicGroup
                       Concept


NOTES
-----

- Animal and Disease are kept separate because confusing them with Product
  or Concept causes hard resolution failures.

- Building is kept separate because landmarks (Eiffel Tower, White House)
  resolve very differently from cities or countries.

- FictionalCharacter is kept separate because confusing a fictional entity
  with a real person is a hard failure, not a soft one.

- Award, Sport, EthnicGroup and Concept fall into Other at the coarse level.
  A small model will mis-classify these anyway; the QID lookup in pass 2
  recovers the correct fine-grained type reliably.
