Triple

T17673989
Position Surface form Disambiguated ID Type / Status
Subject FRA E440597 entity
Predicate hubFor P423 FINISHED
Object Condor Airlines NE NERFINISHED

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: Condor Airlines | Statement: [FRA, hubFor, Condor Airlines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Condor Airlines
Context triple: [FRA, hubFor, Condor Airlines]
  • A. Condor Airlines chosen
    Condor Airlines is a German leisure airline that primarily operates holiday flights from Germany to vacation destinations worldwide.
  • B. Boliviana de Aviación
    Boliviana de Aviación is Bolivia’s state-owned flag carrier airline, operating domestic and international passenger and cargo services.
  • 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. Cronos Airlines
    Cronos Airlines is an Equatorial Guinea-based carrier that uses Malabo International Airport as its primary hub for regional and possibly limited international flights.
  • 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 (2 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_69d8b9e87e18819087104a44dc4dc5b1 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e46f6ba22081909e2099490c047378 completed April 19, 2026, 6 a.m.
Created at: April 10, 2026, 10 a.m.