Triple
T5170650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MCI |
E116667
|
entity |
| Predicate | hasGeneralAviationOperations |
P51772
|
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: [MCI, hasGeneralAviationOperations, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGeneralAviationOperations Context triple: [MCI, hasGeneralAviationOperations, yes]
-
A.
hasGeneralAviationActivity
chosen
Indicates that an entity is involved in or supports non-commercial, private, or recreational aviation operations.
-
B.
hasGeneralAviationFacilities
Indicates that a location or airport provides facilities and services specifically for general aviation operations.
-
C.
hasAircraftOperationsType
Indicates the specific category or type of aircraft operations associated with an entity, such as commercial, military, or private use.
-
D.
hasRunwayOperations
Indicates that an entity conducts or is involved in operational activities on an airport runway, such as takeoffs, landings, or related ground movements.
-
E.
isPartOfAviationSystem
Indicates that something functions as a component or subsystem within a broader aviation system or infrastructure.
- 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_69bd445ff97c81909a2615cc56235470 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd794f44248190a3a90c92208104a7 |
completed | March 20, 2026, 4:43 p.m. |
| PD | Predicate disambiguation | batch_69bd77b36c008190b91011a9fa52b3d2 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:45 p.m.