Triple

T873331
Position Surface form Disambiguated ID Type / Status
Subject Aeroflot E18861 entity
Predicate hasSubsidiary P254 FINISHED
Object Aurora Airlines E41681 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: Aurora Airlines | Statement: [Aeroflot, hasSubsidiary, Aurora Airlines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aurora Airlines
Context triple: [Aeroflot, hasSubsidiary, Aurora Airlines]
  • A. Ibex Airlines
    Ibex Airlines is a Japanese regional airline that operates domestic routes, often connecting smaller cities and regional airports within Japan.
  • B. Flair Airlines
    Flair Airlines is a Canadian ultra-low-cost carrier that operates domestic and select international flights, emphasizing budget-friendly travel options.
  • C. Sky Airline
    Sky Airline is a Chilean low-cost carrier that operates domestic and regional flights across South America.
  • D. Yamal Airlines chosen
    Yamal Airlines is a Russian regional airline based in the Yamalo-Nenets Autonomous Okrug that operates domestic and some international passenger services.
  • E. Avelo Airlines
    Avelo Airlines is a U.S. ultra-low-cost carrier known for operating point-to-point flights from secondary airports with a focus on affordability and simplicity.
  • 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_69a4938db1f081909bcd1ad2713b6096 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac97d0f88190b67fcb7fc058e4b9 completed March 1, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c01af9608190b3b735c590024f03 completed March 4, 2026, 5:16 a.m.
Created at: March 1, 2026, 7:39 p.m.