Triple

T586151
Position Surface form Disambiguated ID Type / Status
Subject Amsterdam Airport Schiphol E15161 entity
Predicate isFocusCityFor P1295 FINISHED
Object easyJet 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 | Statement: [Amsterdam Airport Schiphol, isFocusCityFor, easyJet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: easyJet
Context triple: [Amsterdam Airport Schiphol, isFocusCityFor, easyJet]
  • A. easyJet chosen
    easyJet is a major British low-cost airline operating extensive domestic and European routes.
  • B. Ryanair
    Ryanair is a major Irish low-cost airline known for its extensive network of short-haul flights across Europe.
  • C. TUI Airways
    TUI Airways is a British charter and scheduled airline that primarily serves leisure destinations across Europe and worldwide as part of the TUI Group.
  • D. Jet2.com
    Jet2.com is a British low-cost leisure airline that operates scheduled and charter flights across Europe from multiple UK bases.
  • E. Vueling
    Vueling is a Spanish low-cost airline that operates extensive domestic and European routes, particularly around major hubs such as Barcelona and other key cities.
  • 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_69a4935783b8819082b77726ec10cc42 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49b9a46388190a094b9ebf8dec397 completed March 1, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69a50e273f508190bbbec5da99cb8a42 completed March 2, 2026, 4:12 a.m.
Created at: March 1, 2026, 7:33 p.m.