Triple

T2498539
Position Surface form Disambiguated ID Type / Status
Subject Asiana Airlines E52407 entity
Predicate callsign P1565 FINISHED
Object ASIANA 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 | Statement: [Asiana Airlines, callsign, ASIANA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ASIANA
Context triple: [Asiana Airlines, callsign, ASIANA]
  • 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. 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.
  • C. Korean Air
    Korean Air is South Korea’s largest airline and flag carrier, operating extensive international and domestic passenger and cargo services worldwide.
  • D. Jin Air
    Jin Air is a South Korean low-cost airline that operates domestic and international passenger flights.
  • 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_69ab4957b3a88190adf968ae0c1b931c completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd1ae9040819091b3ca5b98659e99 completed March 7, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1f9ed13c81909856db636bfb2e9e completed March 9, 2026, 7:29 p.m.
Created at: March 6, 2026, 9:46 p.m.