Triple

T19116773
Position Surface form Disambiguated ID Type / Status
Subject Gimpo International Airport E467926 entity
Predicate previousName P65 FINISHED
Object Kimpo 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: Kimpo Airport | Statement: [Gimpo International Airport, previousName, Kimpo Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kimpo Airport
Context triple: [Gimpo International Airport, previousName, Kimpo Airport]
  • A. Neryungri Airport
    Neryungri Airport is a regional airport in the Sakha Republic of Russia that serves the town of Neryungri and its surrounding area.
  • B. Gunsan Airport
    Gunsan Airport is a regional airport in Gunsan, South Korea, serving both civilian flights and military operations.
  • C. Gimpo International Airport chosen
    Gimpo International Airport is a major airport serving the Seoul metropolitan area, primarily handling domestic flights and regional international routes.
  • 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_69d8dd06a26481908039e2a1bae8c597 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e3984bf48190818fa2b01b75decb completed April 20, 2026, 8:28 a.m.
Created at: April 10, 2026, 12:05 p.m.