Triple
T20638155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forbes Field |
E507139
|
entity |
| Predicate | hasAircraftOperations |
P51772
|
FINISHED |
| Object | general aviation operations |
—
|
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 operations | Statement: [Forbes Field, hasAircraftOperations, general aviation operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAircraftOperations Context triple: [Forbes Field, hasAircraftOperations, general aviation operations]
-
A.
hasAircraftOperationsType
Indicates the specific category or type of aircraft operations associated with an entity, such as commercial, military, or private use.
-
B.
hasRunwayOperations
Indicates that an entity conducts or is involved in operational activities on an airport runway, such as takeoffs, landings, or related ground movements.
-
C.
operatesAirport
Indicates that one entity manages and runs the operations of an airport.
-
D.
hasGeneralAviationActivity
chosen
Indicates that an entity is involved in or supports non-commercial, private, or recreational aviation operations.
-
E.
airlineOperationsType
Indicates the type or category of operational activities an airline conducts (e.g., passenger, cargo, charter, or mixed services).
- 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_69e0b4be702c8190a3d2410a881d310a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6ad1163008190aa9df36750a952d2 |
completed | April 20, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69e5a0155bd48190b3c769a12cc2c83d |
completed | April 20, 2026, 3:40 a.m. |
Created at: April 16, 2026, 11:42 a.m.