Triple
T34838208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lewis University |
E1004258
|
entity |
| Predicate | hasFlightTrainingFacility |
P182299
|
FINISHED |
| Object | Lewis University Airport |
—
|
NE NERFINISHED |
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: Lewis University Airport | Statement: [Lewis University, hasFlightTrainingFacility, Lewis University Airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFlightTrainingFacility Context triple: [Lewis University, hasFlightTrainingFacility, Lewis University Airport]
-
A.
hasFlightTrainingActivity
Indicates that an entity is involved in or associated with a flight training activity.
-
B.
hasFixedWingTrainingRole
Indicates that an entity serves in a training capacity specifically related to the operation or use of fixed-wing aircraft.
-
C.
tookFlightTrainingIn
Indicates that an entity received or completed flight training at or through a specified organization, location, or program.
-
D.
hasGeneralAviationFacilities
Indicates that a location or airport provides facilities and services specifically for general aviation operations.
-
E.
hasFixedWingTraining
Indicates that an entity has received training in operating or working with fixed-wing aircraft.
- 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_69f76db97714819099b5bed36fd64e9d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7886be6d8819095ec62e4f2cee858 |
completed | May 3, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69f7841440f48190b4346c08855951d2 |
completed | May 3, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69f7886b27f08190ab4580f949222c93 |
completed | May 3, 2026, 5:39 p.m. |
Created at: May 3, 2026, 4 p.m.