Triple
T6838920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FLETC Charleston |
E157519
|
entity |
| Predicate | hasTrainingAudience |
P12602
|
FINISHED |
| Object | sworn law enforcement officers |
—
|
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: sworn law enforcement officers | Statement: [FLETC Charleston, hasTrainingAudience, sworn law enforcement officers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrainingAudience Context triple: [FLETC Charleston, hasTrainingAudience, sworn law enforcement officers]
-
A.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
B.
hasTrainingRole
Indicates that an entity holds or is assigned a specific role within a training or instructional context.
-
C.
hasTrainingType
Indicates that an entity is associated with or characterized by a specific type or category of training.
-
D.
hasEducationalAudience
chosen
Indicates that something is intended for or directed toward a specific educational audience or learner group.
-
E.
hasAudience
Indicates that an entity is intended to be received, viewed, or engaged with by a particular group of people.
- 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_69c6882c53608190b99aebef079b23bd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d67ee1c88190b82a9b6b3d1e3875 |
completed | March 27, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c6d09f90648190bc0a462c7d59de1b |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:19 p.m.