Triple

T17811889
Position Surface form Disambiguated ID Type / Status
Subject Cheongju E444728 entity
Predicate hasAirport P105 FINISHED
Object Cheongju International Airport NE NERFINISHED

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: Cheongju International Airport | Statement: [Cheongju, hasAirport, Cheongju International Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cheongju International Airport
Context triple: [Cheongju, hasAirport, Cheongju International Airport]
  • A. Cheongju International Airport chosen
    Cheongju International Airport is a major regional airport in central South Korea that serves both domestic and international flights for the city of Cheongju and the surrounding Chungcheong region.
  • B. Gunsan Airport
    Gunsan Airport is a regional airport in Gunsan, South Korea, serving both civilian flights and military operations.
  • C. 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.
  • D. Gwangju Airport
    Gwangju Airport is a regional airport in Gwangju, South Korea, serving domestic flights and limited military operations.
  • E. Wonsan Kalma International Airport
    Wonsan Kalma International Airport is a modern civilian and military airport in Wonsan, North Korea, known for its extensive reconstruction and role in the country’s tourism and strategic infrastructure plans.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f0de78819099395b14db75a8a6 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4887b5e50819098506f0b92d709b5 completed April 19, 2026, 7:47 a.m.
Created at: April 10, 2026, 10:14 a.m.