Triple
T9413059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gimpo |
E226749
|
entity |
| Predicate | airportInstanceOf |
P86085
|
FINISHED |
| Object | international airport |
—
|
LITERAL 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: international airport | Statement: [Gimpo, airportInstanceOf, international airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportInstanceOf Context triple: [Gimpo, airportInstanceOf, international airport]
-
A.
airportStation
Indicates a location functions as an airport facility where air transport operations occur.
-
B.
airportOwner
Indicates that one entity owns, controls, or holds primary legal responsibility for an airport.
-
C.
airportTypePresent
chosen
Indicates that a specific type or category of airport is present or exists in relation to the referenced entity.
-
D.
airportUse
Indicates that an airport is used or utilized by a particular entity, such as an airline, organization, or service.
-
E.
airportOfficialName
Indicates the officially designated full name of an airport as recognized by authorities or governing bodies.
- F. None of above.
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. |
| PD | Predicate disambiguation | batch_69cca54c37f88190bddccf28e5fe5c84 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:47 p.m.