Triple

T1889744
Position Surface form Disambiguated ID Type / Status
Subject Geneva Airport E41842 entity
Predicate hubFor P423 FINISHED
Object easyJet Switzerland E6907 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: easyJet Switzerland | Statement: [Geneva Airport, hubFor, easyJet Switzerland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: easyJet Switzerland
Context triple: [Geneva Airport, hubFor, easyJet Switzerland]
  • A. easyJet chosen
    easyJet is a major British low-cost airline operating extensive domestic and European routes.
  • B. Wizz Air
    Wizz Air is a Hungarian ultra-low-cost airline known for operating an extensive network of budget flights across Europe and surrounding regions.
  • C. Ryanair
    Ryanair is a major Irish low-cost airline known for its extensive network of short-haul flights across Europe.
  • D. Eurowings
    Eurowings is a German low-cost airline and Lufthansa subsidiary that operates short- and long-haul flights across Europe and selected international destinations.
  • E. Lynx Air
    Lynx Air is a Canadian ultra-low-cost airline that operates domestic and select international flights, primarily serving major hubs such as Toronto Pearson International Airport.
  • 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_69a8864b6de0819098d089f6a1b910a7 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb142e41881908fc7335673a9dec3 completed March 7, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69addf665bd48190b08ff5159333b99b completed March 8, 2026, 8:43 p.m.
Created at: March 4, 2026, 7:34 p.m.