Triple
T32975595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XY |
E843650
|
entity |
| Predicate | operatorAirlinePrimaryHubAirport |
P120243
|
FINISHED |
| Object | King Khalid International Airport |
—
|
NE NERFINISHED |
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: King Khalid International Airport | Statement: [XY, operatorAirlinePrimaryHubAirport, King Khalid International Airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatorAirlinePrimaryHubAirport Context triple: [XY, operatorAirlinePrimaryHubAirport, King Khalid International Airport]
-
A.
associatedAirportPrimaryHubFor
chosen
Indicates that an airport serves as the primary hub for a particular airline or transportation operator.
-
B.
airlineHub
Indicates that a particular location (typically an airport or city) serves as a central hub or primary operational base for an airline.
-
C.
primaryHubAirline
Indicates that an airline serves as the main or principal hub carrier for a particular airport or location.
-
D.
operatorPrimaryHubAirportCode
Indicates the airport code of the main or primary hub used by the operator.
-
E.
associatedAirlineHeadquarters
Indicates that an airline is connected to or based at a particular headquarters location.
- 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_69f3494b9fc48190bb61c955ba471275 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a00512437d48190ad20324968ead5f4 |
completed | May 10, 2026, 9:34 a.m. |
| PD | Predicate disambiguation | batch_6a0050227350819099f41369c3d168be |
completed | May 10, 2026, 9:30 a.m. |
Created at: May 1, 2026, 1:22 a.m.