Triple

T3300497
Position Surface form Disambiguated ID Type / Status
Subject Avios E69318 entity
Predicate usedBy P260 FINISHED
Object Vueling Club E28556 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: Vueling Club | Statement: [Avios, usedBy, Vueling Club]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vueling Club
Context triple: [Avios, usedBy, Vueling Club]
  • A. Vueling chosen
    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.
  • B. Blue Air
    Blue Air is a Romanian low-cost airline that operated scheduled passenger flights across Europe.
  • C. Smartavia
    Smartavia is a Russian low-cost airline that operates domestic and regional flights, using Moscow Domodedovo International Airport as one of its main bases.
  • D. Ibex Airlines
    Ibex Airlines is a Japanese regional airline that operates domestic routes, often connecting smaller cities and regional airports within Japan.
  • E. Viva Aerobus
    Viva Aerobus is a Mexican low-cost airline known for offering budget-friendly domestic and regional flights across Mexico and select international destinations.
  • 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_69ad859e529c8190a404273f53cb487d completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb0a66fcc819093931fe7a6507723 completed March 8, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2f3db14ac819083182f56c60b61b2 completed March 12, 2026, 5:11 p.m.
Created at: March 8, 2026, 3:11 p.m.