Triple
T11651696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KHI |
E276917
|
entity |
| Predicate | airportHasPassengerTerminal |
P34629
|
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: [KHI, airportHasPassengerTerminal, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportHasPassengerTerminal Context triple: [KHI, airportHasPassengerTerminal, Yes]
-
A.
hasNumberOfPassengerTerminalsAtAirport
Indicates the relationship that specifies how many passenger terminals are present at a given airport.
-
B.
airportHasTerminals
chosen
Indicates that a particular airport includes or is composed of one or more terminal facilities.
-
C.
hasPassengerTerminal
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
-
D.
hasPassengerTerminalFacilities
Indicates that an entity provides facilities or infrastructure specifically intended for handling and serving passengers.
-
E.
isPassengerAirport
Indicates that an airport primarily serves commercial passenger air traffic rather than cargo or other specialized operations.
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a2d01f9c8190849f252f22519550 |
completed | April 10, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69d85ddc780481909a3bc63832fe2bd2 |
completed | April 10, 2026, 2:18 a.m. |
Created at: April 8, 2026, 9:39 p.m.