Triple

T11238019
Position Surface form Disambiguated ID Type / Status
Subject LifeMiles E265994 entity
Predicate operator P179 FINISHED
Object Avianca E52987 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: Avianca | Statement: [LifeMiles, operator, Avianca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Avianca
Context triple: [LifeMiles, operator, Avianca]
  • A. Avianca chosen
    Avianca is Colombia’s flagship airline and one of Latin America’s largest carriers, operating an extensive domestic and international route network.
  • B. Caribbean Airlines
    Caribbean Airlines is the state-owned flag carrier of Trinidad and Tobago, operating regional and international flights throughout the Caribbean and to North and South America.
  • 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. AeroCaribbean
    AeroCaribbean was a Cuban regional airline that operated domestic and Caribbean routes, primarily serving as a subsidiary of Cubana de Aviación.
  • E. LATAM Airlines Group
    LATAM Airlines Group is a major Latin American airline holding company formed by the merger of LAN Airlines and TAM Airlines, operating an extensive network of domestic and international routes across the Americas and beyond.
  • 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e918375081908c2a7ccb50cbf331 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e603a1acc08190816db1ff13708e79 completed April 20, 2026, 10:44 a.m.
Created at: April 8, 2026, 9:30 p.m.