Triple

T1319081
Position Surface form Disambiguated ID Type / Status
Subject Milan Bergamo Airport E28173 entity
Predicate hasPrimaryAirline P12356 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: [Milan Bergamo Airport, hasPrimaryAirline, Ryanair]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ryanair
Context triple: [Milan Bergamo Airport, hasPrimaryAirline, 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: hasPrimaryAirline
Context triple: [Milan Bergamo Airport, hasPrimaryAirline, Ryanair]
  • A. servesAirline chosen
    Indicates that a transportation facility or location provides service for, or is regularly used by, a specified airline.
  • B. hasUnderlyingAirlineCallsign
    Indicates that an airline-related entity is associated with a specific underlying airline callsign used for identification in air traffic communications.
  • C. servesAirlineType
    Indicates that a service provider (such as an airport, terminal, or facility) accommodates or operates flights for a specified type or category of airline.
  • D. airlineType
    Indicates the classification or category of an airline based on its operational or service characteristics.
  • E. airline
    Indicates that an entity operates as a commercial air transport carrier providing flight services between locations.
  • 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_69a498532c3481909223b74af2e578df completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c1780be8819083a9365b8a49305d completed March 1, 2026, 10:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69ada0ba8f608190a5f1fcc5ebcee9e5 completed March 8, 2026, 4:15 p.m.
PD Predicate disambiguation batch_69a4beebcb348190964bd7215811942c completed March 1, 2026, 10:34 p.m.
Created at: March 1, 2026, 7:55 p.m.