Triple

T10294644
Position Surface form Disambiguated ID Type / Status
Subject GYE E241450 entity
Predicate servesAsFocusCityFor P1655 FINISHED
Object Copa Airlines E45992 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: Copa Airlines | Statement: [GYE, servesAsFocusCityFor, Copa Airlines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Copa Airlines
Context triple: [GYE, servesAsFocusCityFor, Copa Airlines]
  • A. Copa Airlines chosen
    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.
  • B. Avianca
    Avianca is Colombia’s flagship airline and one of Latin America’s largest carriers, operating an extensive domestic and international route network.
  • C. Condor Airlines
    Condor Airlines is a German leisure airline that primarily operates holiday flights from Germany to vacation destinations worldwide.
  • D. 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.
  • 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_69d381aaafc08190af475ef58dc16aba completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2d5e0f88190be3e23ba2511a1e9 completed April 7, 2026, 9:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71d23f49081909aea149c6b219354 completed April 9, 2026, 3:29 a.m.
Created at: April 6, 2026, 11:42 a.m.