Triple

T7406992
Position Surface form Disambiguated ID Type / Status
Subject RKPK E170895 entity
Predicate alternateName P39 FINISHED
Object Busan Gimhae International Airport E29657 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: Busan Gimhae International Airport | Statement: [RKPK, alternateName, Busan Gimhae International Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Busan Gimhae International Airport
Context triple: [RKPK, alternateName, Busan Gimhae International Airport]
  • A. Gimhae International Airport chosen
    Gimhae International Airport is the main international airport serving the Busan metropolitan area in South Korea.
  • B. Gwangju Airport
    Gwangju Airport is a regional airport in Gwangju, South Korea, serving domestic flights and limited military operations.
  • C. Jeju International Airport
    Jeju International Airport is the main airport serving South Korea’s Jeju Island, handling extensive domestic traffic and a growing number of international flights for this major tourist destination.
  • D. Daegu International Airport
    Daegu International Airport is a regional airport in Daegu, South Korea, serving both domestic and limited international flights.
  • E. Sacheon Airport
    Sacheon Airport is a regional airport in South Korea serving the city of Jinju and the surrounding Gyeongsangnam-do area with domestic flights.
  • 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_69c68a6010108190925e5284de022660 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f298f2388190afc944c9bc78749a completed March 27, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83c4dc1c08190876eb0e70f387b77 completed March 28, 2026, 8:38 p.m.
Created at: March 27, 2026, 3:10 p.m.