Triple
T6066275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pyongyang Sunan International Airport |
E135167
|
entity |
| Predicate | hasApronForAircraftParking |
P40806
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Pyongyang Sunan International Airport, hasApronForAircraftParking, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApronForAircraftParking Context triple: [Pyongyang Sunan International Airport, hasApronForAircraftParking, yes]
-
A.
hasParkingApron
chosen
Indicates that a location or facility includes a designated parking apron area for vehicles or aircraft.
-
B.
hasApron
Indicates that one entity possesses or is wearing an apron in relation to another context or entity.
-
C.
hasMilitaryApron
Indicates that a location or facility includes a designated apron area specifically used for military aircraft operations.
-
D.
hasApronType
Indicates that an entity is associated with or characterized by a specific type or category of apron.
-
E.
hasBaggageSystem
Indicates that an entity is equipped with or utilizes a baggage handling system.
- 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_69c00878d06881909ee78e88913bf890 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0573df7508190bbb5b496188b2f3e |
completed | March 22, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69c049f031408190b08b2766237c5dd0 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:10 p.m.