Triple
T594707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corvallis Municipal Airport |
E17353
|
entity |
| Predicate | hasAircraftOperationsType |
P16104
|
FINISHED |
| Object | general aviation |
—
|
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: general aviation | Statement: [Corvallis Municipal Airport, hasAircraftOperationsType, general aviation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAircraftOperationsType Context triple: [Corvallis Municipal Airport, hasAircraftOperationsType, general aviation]
-
A.
aircraftFacility
Indicates that a facility is designed, equipped, or used to support the operation, maintenance, or accommodation of aircraft.
-
B.
flightRegime
Indicates the operational conditions or phase of flight under which an aircraft or aerospace vehicle is functioning (e.g., speed, altitude, and atmospheric regime).
-
C.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
D.
hasAirportClassification
Indicates that an airport is assigned a specific classification or category based on defined criteria.
-
E.
hasAirportCodeType
Indicates that an airport code is associated with a specific classification or type (e.g., IATA, ICAO, FAA).
- F. None of above. chosen
Provenance (4 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bd280ac8190b6a530ce73da85c8 |
completed | March 1, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69a494ceeb7881909a91ed1a35d5bf0a |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a4985ada988190aaea628a9b55bca4 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:33 p.m.