Triple

T10870650
Position Surface form Disambiguated ID Type / Status
Subject VB E256639 entity
Predicate assignedToAirline P41156 FINISHED
Object Viva Aerobus E48204 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: Viva Aerobus | Statement: [VB, assignedToAirline, Viva Aerobus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viva Aerobus
Context triple: [VB, assignedToAirline, Viva Aerobus]
  • A. Viva Aerobus chosen
    Viva Aerobus is a Mexican low-cost airline known for offering budget-friendly domestic and regional flights across Mexico and select international destinations.
  • B. Volaris
    Volaris is a Mexican low-cost airline that operates domestic and international flights, primarily serving routes across Mexico, the United States, and Central America.
  • C. Aeroméxico
    Aeroméxico is Mexico’s flagship airline, operating domestic and international flights across the Americas, Europe, and Asia from its main hub in Mexico City.
  • D. Copa Airlines
    Copa Airlines is the flag carrier of Panama and a major Latin American airline known for its extensive route network centered on its hub in Panama City.
  • E. Interjet
    Interjet was a Mexican low-cost airline known for operating domestic and international routes across the Americas before ceasing operations in 2020.
  • 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_69d6aa83d1448190a66d93c32394d21f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7518610e48190bee50db71ae0ca3e completed April 9, 2026, 7:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69dff7d9ce3c8190afeb2a27fb82b594 completed April 15, 2026, 8:40 p.m.
Created at: April 8, 2026, 9:20 p.m.