Triple
T17918416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Randolph Air Force Base |
E447997
|
entity |
| Predicate | hasAircraftOperationType |
P16104
|
FINISHED |
| Object | training flights |
—
|
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: training flights | Statement: [Randolph Air Force Base, hasAircraftOperationType, training flights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAircraftOperationType Context triple: [Randolph Air Force Base, hasAircraftOperationType, training flights]
-
A.
hasAircraftOperationsType
chosen
Indicates the specific category or type of aircraft operations associated with an entity, such as commercial, military, or private use.
-
B.
aircraftOperationType
Indicates the specific manner or purpose for which an aircraft is being operated (e.g., commercial, private, military, training).
-
C.
hasRunwayOperations
Indicates that an entity conducts or is involved in operational activities on an airport runway, such as takeoffs, landings, or related ground movements.
-
D.
airlineOperationsType
Indicates the type or category of operational activities an airline conducts (e.g., passenger, cargo, charter, or mixed services).
-
E.
previouslyOperatedWithAircraftType
Indicates that an entity has, at some time in the past, conducted operations using a specified type of 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a30844548190b7a43c2f093f35d7 |
completed | April 19, 2026, 9:40 a.m. |
| PD | Predicate disambiguation | batch_69e3d8ec2f6881909d7f54b878cbed37 |
completed | April 18, 2026, 7:18 p.m. |
Created at: April 10, 2026, 10:20 a.m.