Triple

T1856901
Position Surface form Disambiguated ID Type / Status
Subject Norwich E41722 entity
Predicate hasAirport P105 FINISHED
Object Norwich Airport E203989 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Norwich Airport | Statement: [Norwich, hasAirport, Norwich Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norwich Airport
Context triple: [Norwich, hasAirport, Norwich Airport]
  • A. Norwich Airport chosen
    Norwich Airport is a regional airport in Norwich, England, providing domestic and limited international passenger and charter flights for Norfolk and the surrounding area.
  • B. Southend Airport
    Southend Airport is a regional international airport in Essex, England, serving the London area with passenger and cargo flights.
  • C. Cotswold Airport
    Cotswold Airport is a former Royal Air Force airfield in Gloucestershire, England, now operating as a civilian airport and aviation business hub.
  • D. Cambridge Airport
    Cambridge Airport is a regional airport serving the city of Cambridge in Cambridgeshire, England, handling general aviation, business, and some commercial flights.
  • E. Luton Airport
    Luton Airport is a major international airport north of London that serves as a key hub for low-cost airlines and short-haul European flights.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a8864a83848190a4ec02721306c511 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb07fc5f08190a195a2f24d7b858a completed March 7, 2026, 4:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69addf4bda58819088adab01ca10254f completed March 8, 2026, 8:42 p.m.
Created at: March 4, 2026, 7:33 p.m.