Triple
T8540965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenya Airports Authority |
E202191
|
entity |
| Predicate | typeOfAirportManaged |
P16113
|
FINISHED |
| Object | international airports |
—
|
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 airports | Statement: [Kenya Airports Authority, typeOfAirportManaged, international airports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfAirportManaged Context triple: [Kenya Airports Authority, typeOfAirportManaged, international airports]
-
A.
isLocatedAtAirportType
Indicates that one entity is situated at, or associated with, an airport of a specified type (e.g., international, regional, military).
-
B.
isCivilAirport
Indicates that an airport is designated and used primarily for civilian (non-military) aviation operations.
-
C.
isPublicAirport
Indicates that an airport is open for use by the general public rather than restricted to private or military operations.
-
D.
hasAirfieldType
Indicates that an airfield is classified as having a particular type or category of airfield.
-
E.
associatedWithAirportType
chosen
Indicates that an entity has a connection or linkage to a specific category or type of airport.
- 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_69ca832461e88190a654c5e44e233aa8 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe6e10bc081909a7210c577b807fb |
completed | March 31, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69cbd111bf988190be98c92a607c6456 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:18 p.m.