Triple

T10413959
Position Surface form Disambiguated ID Type / Status
Subject Copa ConnectMiles Gold E245467 entity
Predicate airline P9049 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: [Copa ConnectMiles Gold, airline, Copa Airlines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Copa Airlines
Context triple: [Copa ConnectMiles Gold, airline, 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_69d381be340c8190b05998703d42d224 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4ea0ec6fc8190a71af759226a3cba completed April 7, 2026, 11:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69d87e9b86648190b83eb5261c9a7b97 completed April 10, 2026, 4:37 a.m.
Created at: April 6, 2026, 12:10 p.m.