Triple

T4308116
Position Surface form Disambiguated ID Type / Status
Subject SEN E94005 entity
Predicate isPartOf P10 FINISHED
Object London airport system E93744 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 airport system | Statement: [SEN, isPartOf, London airport system]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: London airport system
Context triple: [SEN, isPartOf, London airport system]
  • A. London airport system chosen
    The London airport system is the network of major international and regional airports serving the Greater London area, including hubs such as Heathrow, Gatwick, Stansted, Luton, and London City.
  • 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. London City Airport
    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.
  • E. London Oxford Airport
    London Oxford Airport is a regional airport in Oxfordshire, England, serving general aviation, business, and limited commercial flights for the Oxford area.
  • 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_69b3451886588190a3dd1305ea7c58dc completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b350d2af088190ad7cb035d6e0f8c2 completed March 12, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c756809c8190af90c91ec7883e55 completed March 14, 2026, 8:38 p.m.
Created at: March 12, 2026, 11:11 p.m.