Triple
T3662029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Air Force ROTC |
E77670
|
entity |
| Predicate | trainingLocationType |
P50226
|
FINISHED |
| Object | college campus |
—
|
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: college campus | Statement: [Air Force ROTC, trainingLocationType, college campus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingLocationType Context triple: [Air Force ROTC, trainingLocationType, college campus]
-
A.
trainingFacilityLocation
Indicates the place or site where a training facility is situated or operates.
-
B.
springTrainingLocation
Indicates the location where an entity conducts its spring training activities.
-
C.
trainingGround
Indicates a location or context where entities engage in practice, drills, or preparation activities to develop or improve skills.
-
D.
trainingCity
Indicates the city where an entity receives or conducts training.
-
E.
trainingGroundFor
Indicates that one entity serves as a place or context where another entity is trained, prepared, or developed.
- 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3d826d88190b0b50e8592088a36 |
completed | March 8, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69adb847e9d881909dad2ffd0f3b6c15 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb97cdb788190a5ce96b21bd157ab |
completed | March 8, 2026, 6:01 p.m. |
Created at: March 8, 2026, 3:25 p.m.