Triple

T1494631
Position Surface form Disambiguated ID Type / Status
Subject Gimhae International Airport E29657 entity
Predicate focusCityFor P164 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: [Gimhae International Airport, focusCityFor, Asiana Airlines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asiana Airlines
Context triple: [Gimhae International Airport, focusCityFor, 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. EVA Air
    EVA Air is a major Taiwanese international airline known for its extensive global route network, high service standards, and innovative themed flights such as its Hello Kitty jets.
  • 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_69a498dba1d8819093b46a3a8d2485f1 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c6c78c9481909b210b845aa6e9df completed March 1, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad308bf1048190bc15a712e5ee0caa completed March 8, 2026, 8:17 a.m.
Created at: March 1, 2026, 8:12 p.m.