Triple

T344421
Position Surface form Disambiguated ID Type / Status
Subject easyJet E6907 entity
Predicate foundingLocation P40 FINISHED
Object London Luton Airport E15779 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 Luton Airport | Statement: [easyJet, foundingLocation, London Luton Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: London Luton Airport
Context triple: [easyJet, foundingLocation, London Luton Airport]
  • A. Luton Airport chosen
    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.
  • B. 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.
  • C. Gatwick Airport
    Gatwick Airport is a major international airport serving the London area and is one of the busiest airports in the United Kingdom.
  • D. Southend Airport
    Southend Airport is a regional international airport in Essex, England, serving the London area with passenger and cargo flights.
  • E. Manchester Airport
    Manchester Airport is a major international airport in North West England serving the Greater Manchester region and acting as a key hub for domestic and global 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_69a2e7951ba08190960e90823b5078f3 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2eb01261c81909280128b5ce75eff completed Feb. 28, 2026, 1:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4176f80488190bbee9a442a6a7076 completed March 1, 2026, 10:39 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.