Triple

T1301807
Position Surface form Disambiguated ID Type / Status
Subject Ciampino–G. B. Pastine International Airport E27780 entity
Predicate servedBy P82 FINISHED
Object Wizz Air E95554 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: Wizz Air | Statement: [Ciampino–G. B. Pastine International Airport, servedBy, Wizz Air]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wizz Air
Context triple: [Ciampino–G. B. Pastine International Airport, servedBy, Wizz Air]
  • A. Wizz Air chosen
    Wizz Air is a Hungarian ultra-low-cost airline known for operating an extensive network of budget flights across Europe and surrounding regions.
  • B. Ryanair
    Ryanair is a major Irish low-cost airline known for its extensive network of short-haul flights across Europe.
  • C. 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.
  • D. Eurowings
    Eurowings is a German low-cost airline and Lufthansa subsidiary that operates short- and long-haul flights across Europe and selected international destinations.
  • E. Lynx Air
    Lynx Air is a Canadian ultra-low-cost airline that operates domestic and select international flights, primarily serving major hubs such as Toronto Pearson International Airport.
  • 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_69a496d6682881909ba658f1c1e0e2b0 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c115ba64819081c55fa6807e19ef completed March 1, 2026, 10:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc622dac88190b6ecdc62c7f26dc5 completed March 8, 2026, 12:43 a.m.
Created at: March 1, 2026, 7:51 p.m.