Triple

T6893876
Position Surface form Disambiguated ID Type / Status
Subject KE E159119 entity
Predicate airlineCallsign P13478 FINISHED
Object KOREANAIR E30717 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: KOREANAIR | Statement: [KE, airlineCallsign, KOREANAIR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KOREANAIR
Context triple: [KE, airlineCallsign, KOREANAIR]
  • A. Korean Air chosen
    Korean Air is South Korea’s largest airline and flag carrier, operating extensive international and domestic passenger and cargo services worldwide.
  • B. Asiana Airlines
    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.
  • C. Jeju Air
    Jeju Air is a South Korean low-cost airline that operates extensive domestic and international routes, particularly serving leisure and regional markets in East Asia.
  • 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_69c6883568c8819081db6407e892cccc completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d931da24819096b9b205f2c0ebb0 completed March 27, 2026, 7:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7511fbe808190bc3dfb7c34a7cbb6 completed March 28, 2026, 3:55 a.m.
Created at: March 27, 2026, 2:24 p.m.