Triple

T1886624
Position Surface form Disambiguated ID Type / Status
Subject Airbus A380 E39977 entity
Predicate notableOperator P179 FINISHED
Object Asiana Airlines E52407 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: Asiana Airlines | Statement: [Airbus A380, notableOperator, Asiana Airlines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asiana Airlines
Context triple: [Airbus A380, notableOperator, Asiana Airlines]
  • A. Asiana Airlines chosen
    Asiana Airlines is a major South Korean international airline based in Seoul, operating an extensive network of passenger and cargo services across Asia, Europe, North America, and Oceania.
  • B. Korean Air
    Korean Air is South Korea’s largest airline and flag carrier, operating extensive international and domestic passenger and cargo services worldwide.
  • C. Jin Air
    Jin Air is a South Korean low-cost airline that operates domestic and international passenger flights.
  • D. Asia Pacific Airlines
    Asia Pacific Airlines is a cargo and charter airline based in Guam that primarily serves destinations across Micronesia and the Western Pacific region.
  • E. Skymark Airlines
    Skymark Airlines is a Japanese low-cost carrier based in Tokyo that operates domestic flights and some international services.
  • 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_69a88633e4fc8190b7eb40463e048ec5 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb12032c881909cd93e3601906f48 completed March 7, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3cc8d5c8190bee638183989830c completed March 8, 2026, 10:10 p.m.
Created at: March 4, 2026, 7:34 p.m.