Triple

T2780521
Position Surface form Disambiguated ID Type / Status
Subject Tijuana International Airport E61680 entity
Predicate servesAsHubFor P423 FINISHED
Object Volaris E45592 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: Volaris | Statement: [Tijuana International Airport, servesAsHubFor, Volaris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Volaris
Context triple: [Tijuana International Airport, servesAsHubFor, Volaris]
  • A. Volaris chosen
    Volaris is a Mexican low-cost airline that operates domestic and international flights, primarily serving routes across Mexico, the United States, and Central America.
  • B. 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.
  • C. Sky Airline
    Sky Airline is a Chilean low-cost carrier that operates domestic and regional flights across South America.
  • D. 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.
  • E. 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.
  • 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_69ab4b7e43c48190997b8fc8fb1663ab completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd997ebc8190bff88fe549827615 completed March 7, 2026, 8:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc05cf84881908e771471dbda4c8d completed March 10, 2026, 6:55 a.m.
Created at: March 6, 2026, 9:57 p.m.