Triple

T10343522
Position Surface form Disambiguated ID Type / Status
Subject Vickers Viscount E243683 entity
Predicate operator P179 FINISHED
Object Cubana de Aviación E25422 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: Cubana de Aviación | Statement: [Vickers Viscount, operator, Cubana de Aviación]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cubana de Aviación
Context triple: [Vickers Viscount, operator, Cubana de Aviación]
  • A. Cubana de Aviación chosen
    Cubana de Aviación is the national flag carrier airline of Cuba, operating domestic and international flights primarily from its Havana hub.
  • B. Condor Airlines
    Condor Airlines is a German leisure airline that primarily operates holiday flights from Germany to vacation destinations worldwide.
  • C. Boliviana de Aviación
    Boliviana de Aviación is Bolivia’s state-owned flag carrier airline, operating domestic and international passenger and cargo services.
  • D. 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.
  • 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e92105888190a08104deb9d0cf1c completed April 7, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d75077dfbc81908de29aac1a3bb19f completed April 9, 2026, 7:08 a.m.
Created at: April 6, 2026, 11:55 a.m.