Triple
T30187391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gatineau-Ottawa Executive Airport |
E767372
|
entity |
| Predicate | supportsBusinessAviation |
P71775
|
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: [Gatineau-Ottawa Executive Airport, supportsBusinessAviation, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsBusinessAviation Context triple: [Gatineau-Ottawa Executive Airport, supportsBusinessAviation, yes]
-
A.
supportsBusiness
Indicates that one entity provides assistance, resources, or services that help another entity operate, grow, or succeed in its business activities.
-
B.
supportsCommercialFlights
Indicates that the subject provides the necessary facilities, services, or conditions for regular commercial passenger or cargo flights to operate.
-
C.
hasCorporateAviation
Indicates that an entity operates, owns, or utilizes aircraft or aviation services for corporate or business purposes.
-
D.
servesAviationType
chosen
Indicates that one entity provides services or functions specifically for a particular type or category of aviation.
-
E.
supportsAircraft
Indicates that one entity is capable of accommodating, carrying, or enabling the operation of an aircraft.
- 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_69f2247cc3d88190811dec3face94bf5 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e0f3d88190a4ee7b0673f1ef90 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 7:27 p.m.