Triple

T703842
Position Surface form Disambiguated ID Type / Status
Subject George Best Belfast City Airport E14056 entity
Predicate hasFocusCityFor 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: [George Best Belfast City Airport, hasFocusCityFor, easyJet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: easyJet
Context triple: [George Best Belfast City Airport, hasFocusCityFor, 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_69a493494ec48190ae6751683625a9ba completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a533fa788190bba0f55655469c46 completed March 1, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a654dcbb688190ab997a3d31ec729a completed March 3, 2026, 3:26 a.m.
Created at: March 1, 2026, 7:36 p.m.