Triple

T3372696
Position Surface form Disambiguated ID Type / Status
Subject TACA Airlines E70990 entity
Predicate parentOrganization P254 FINISHED
Object Grupo TACA E70990 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: Grupo TACA | Statement: [TACA Airlines, parentOrganization, Grupo TACA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grupo TACA
Context triple: [TACA Airlines, parentOrganization, Grupo TACA]
  • A. TACA Airlines chosen
    TACA Airlines was a major Central American airline based in El Salvador that operated an extensive regional and international route network before merging with Avianca.
  • 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. 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.
  • D. Copa Holdings S.A.
    Copa Holdings S.A. is a Panamanian airline holding company best known as the owner and operator of Copa Airlines and related aviation businesses in Latin America.
  • E. TAR Aerolíneas
    TAR Aerolíneas is a Mexican regional airline that operates domestic routes connecting medium-sized cities across the country.
  • 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_69ad85a7f80c8190a05e43013f298942 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb2bdcf70819087fc7e00fbd61e0d completed March 8, 2026, 5:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3343fd8a08190bf426884ec42948c completed March 12, 2026, 9:46 p.m.
Created at: March 8, 2026, 3:13 p.m.