Triple

T344331
Position Surface form Disambiguated ID Type / Status
Subject Manchester Airports Group E6905 entity
Predicate operates P24 FINISHED
Object London Stansted Airport E15363 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 Stansted Airport | Statement: [Manchester Airports Group, operates, London Stansted Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: London Stansted Airport
Context triple: [Manchester Airports Group, operates, London Stansted Airport]
  • A. Stansted Airport chosen
    Stansted Airport is a major international airport serving the London area, particularly known as a hub for low-cost and European short-haul flights.
  • B. 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.
  • 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. London International Airport
    London International Airport is a regional airport serving the city of London and surrounding areas in southwestern Ontario, Canada.
  • 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_69a3e85ff5248190848e7c390d550c59 completed March 1, 2026, 7:18 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.