Triple

T1305484
Position Surface form Disambiguated ID Type / Status
Subject FR E27865 entity
Predicate associatedAirlineName P12809 FINISHED
Object Ryanair E4144 NE FINISHED

How this triple was built (3 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: Ryanair | Statement: [FR, associatedAirlineName, Ryanair]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ryanair
Context triple: [FR, associatedAirlineName, Ryanair]
  • A. Ryanair chosen
    Ryanair is a major Irish low-cost airline known for its extensive network of short-haul flights across Europe.
  • 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. Aer Lingus
    Aer Lingus is the flag carrier airline of Ireland, operating international flights primarily between Ireland, Europe, and North America.
  • D. Flybe
    Flybe was a British regional airline that operated short-haul flights across the UK and Europe before ceasing operations.
  • 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.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedAirlineName
Context triple: [FR, associatedAirlineName, Ryanair]
  • A. associatedWithIATAAirlineCode
    Indicates that an entity is linked to or identified by a specific IATA airline code.
  • B. servesAirline
    Indicates that a transportation facility or location provides service for, or is regularly used by, a specified airline.
  • C. associatedAirlineHeadquarters
    Indicates that an airline is connected to or based at a particular headquarters location.
  • D. airlineInvolved chosen
    Indicates that a specific airline is directly associated with, or plays a role in, a particular event, situation, or context.
  • E. linkedAirlineCountry
    Indicates that there is an association between an airline and a country, such as the country where the airline is based, registered, or primarily operates.
  • F. None of above.

Provenance (4 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_69a496d7d83481908f83085854e51328 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c13524d481909e8f5bb2ab91f6e4 completed March 1, 2026, 10:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad08a5b5fc81909b75f07b620447cd completed March 8, 2026, 5:27 a.m.
PD Predicate disambiguation batch_69a4bee8544c8190874efd9bae9bccf9 completed March 1, 2026, 10:34 p.m.
Created at: March 1, 2026, 7:51 p.m.