Triple
T7315889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naval Base Ventura County |
E168409
|
entity |
| Predicate | hasTrainingAreas |
P61879
|
FINISHED |
| Object | Seabee training facilities |
—
|
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: Seabee training facilities | Statement: [Naval Base Ventura County, hasTrainingAreas, Seabee training facilities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrainingAreas Context triple: [Naval Base Ventura County, hasTrainingAreas, Seabee training facilities]
-
A.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
B.
hasFieldTrainingComponent
Indicates that an entity includes or is associated with a component involving practical, in-the-field training activities.
-
C.
hasTrainingRole
Indicates that an entity holds or is assigned a specific role within a training or instructional context.
-
D.
hasTrainingType
Indicates that an entity is associated with or characterized by a specific type or category of training.
-
E.
hasTrainingComplex
chosen
Indicates that an entity possesses or is associated with a dedicated facility or complex used for training activities.
- 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_69c68a5251508190ad68df4151cfeb04 |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6ec04bdfc819093556aa5fa69e0e1 |
completed | March 27, 2026, 8:43 p.m. |
| PD | Predicate disambiguation | batch_69c6e7705f4881909793071dee50c557 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3:02 p.m.