Triple
T9413033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gimpo |
E226749
|
entity |
| Predicate | servedBy |
P82
|
FINISHED |
| Object | Gimpo International Airport |
E105451
|
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: Gimpo International Airport | Statement: [Gimpo, servedBy, Gimpo International Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gimpo International Airport Context triple: [Gimpo, servedBy, Gimpo International Airport]
-
A.
Gimpo International Airport
chosen
Gimpo International Airport is a major airport serving the Seoul metropolitan area, primarily handling domestic flights and regional international routes.
-
B.
Gwangju Airport
Gwangju Airport is a regional airport in Gwangju, South Korea, serving domestic flights and limited military operations.
-
C.
Neryungri Airport
Neryungri Airport is a regional airport in the Sakha Republic of Russia that serves the town of Neryungri and its surrounding area.
-
D.
Daegu International Airport
Daegu International Airport is a regional airport in Daegu, South Korea, serving both domestic and limited international flights.
-
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_69ca843280488190bc65600e843ef9e6 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd5258f7e081908d48600409181fdb |
completed | April 1, 2026, 5:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d12228d8148190814646881e1f2d98 |
completed | April 4, 2026, 2:37 p.m. |
Created at: March 30, 2026, 7:47 p.m.