Triple

T4223101
Position Surface form Disambiguated ID Type / Status
Subject VIR E94387 entity
Predicate airlineFocusCityOfIdentifiedAirline P1295 FINISHED
Object London City Airport E16417 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: London City Airport | Statement: [VIR, airlineFocusCityOfIdentifiedAirline, London City Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: London City Airport
Context triple: [VIR, airlineFocusCityOfIdentifiedAirline, London City Airport]
  • A. London City Airport chosen
    London City Airport is a small, centrally located international airport in East London that primarily serves business travelers with short-haul European and domestic flights.
  • B. London International Airport
    London International Airport is a regional airport serving the city of London and surrounding areas in southwestern Ontario, Canada.
  • C. Heathrow Airport
    Heathrow Airport is the United Kingdom’s largest and busiest international airport, serving as a major global aviation hub for London.
  • D. Gatwick Airport
    Gatwick Airport is a major international airport serving the London area and is one of the busiest airports in the United Kingdom.
  • E. Stansted Airport
    Stansted Airport is a major international airport serving the London area, particularly known as a hub for low-cost and European short-haul 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_69b3453700a08190ae88792e3dc63207 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34f7d20b48190a404638c68c31026 completed March 12, 2026, 11:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b6721dcf28819080b6a265152059e9 completed March 15, 2026, 8:47 a.m.
Created at: March 12, 2026, 11:04 p.m.