Triple

T703843
Position Surface form Disambiguated ID Type / Status
Subject George Best Belfast City Airport E14056 entity
Predicate hasFocusCityFor P1295 FINISHED
Object Loganair E17455 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: Loganair | Statement: [George Best Belfast City Airport, hasFocusCityFor, Loganair]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loganair
Context triple: [George Best Belfast City Airport, hasFocusCityFor, Loganair]
  • A. Loganair chosen
    Loganair is a Scottish regional airline that operates domestic and short-haul international flights across the United Kingdom and nearby destinations.
  • B. Ibex Airlines
    Ibex Airlines is a Japanese regional airline that operates domestic routes, often connecting smaller cities and regional airports within Japan.
  • C. Flair Airlines
    Flair Airlines is a Canadian ultra-low-cost carrier that operates domestic and select international flights, emphasizing budget-friendly travel options.
  • D. Cape Air
    Cape Air is a U.S.-based regional airline known for operating short-haul commuter flights, primarily in the Northeast, Midwest, Montana, the Caribbean, and Micronesia.
  • E. Ryanair
    Ryanair is a major Irish low-cost airline known for its extensive network of short-haul flights across Europe.
  • 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_69a76d71a25c81908de9b9e59affb79f completed March 3, 2026, 11:23 p.m.
Created at: March 1, 2026, 7:36 p.m.