Triple

T5940096
Position Surface form Disambiguated ID Type / Status
Subject Cape Town International Airport E132144 entity
Predicate hasHubAirline P423 FINISHED
Object CemAir E459947 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: CemAir | Statement: [Cape Town International Airport, hasHubAirline, CemAir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CemAir
Context triple: [Cape Town International Airport, hasHubAirline, CemAir]
  • A. CemAir chosen
    CemAir is a South African regional and domestic airline operating scheduled and charter flights to various destinations within South Africa and neighboring countries.
  • B. J-Air
    J-Air is a Japanese regional airline operating domestic feeder and short-haul routes on behalf of Japan Airlines.
  • C. CEMO
    CEMO is a research center focused on advancing educational measurement, assessment, and related methodologies.
  • D. Equair
    Equair is an Ecuadorian airline that operated domestic passenger flights, notably serving routes from Guayaquil and Quito.
  • E. Cargojet
    Cargojet is a Canadian cargo airline specializing in time-sensitive overnight air freight services across North America and select international routes.
  • 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_69c0085c55dc8190aa90e242c956e2fa completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c038f101c081908fb530d2f1f358fc completed March 22, 2026, 6:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c0748c888190b41326eddc76db62 completed March 23, 2026, 4:24 a.m.
Created at: March 22, 2026, 4:01 p.m.