Triple
T12729411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gimhae |
E304192
|
entity |
| Predicate | hasAirport |
P105
|
FINISHED |
| Object | 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: Gimhae International Airport | Statement: [Gimhae, hasAirport, Gimhae International Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gimhae International Airport Context triple: [Gimhae, hasAirport, 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.
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.
Gunsan Airport
Gunsan Airport is a regional airport in Gunsan, South Korea, serving both civilian flights and military operations.
-
E.
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.
- 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_69d7bdf1426c8190a4402e1c4cdec33a |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d964172490819080cd022ff8290b6e |
completed | April 10, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c8a4b7c8190a514b623a7364fd7 |
completed | May 2, 2026, 10:36 p.m. |
Created at: April 9, 2026, 5:25 p.m.