Triple
T4623884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CFB Halifax |
E101048
|
entity |
| Predicate | hasTrainingFunction |
P57493
|
FINISHED |
| Object | sailor professional development |
—
|
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: sailor professional development | Statement: [CFB Halifax, hasTrainingFunction, sailor professional development]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrainingFunction Context triple: [CFB Halifax, hasTrainingFunction, sailor professional development]
-
A.
hasTrained
Indicates that one entity has provided training or instruction to another entity.
-
B.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
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.
trainingMethod
Indicates the specific approach, technique, or procedure used to train an entity (such as a person, model, or system).
- 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_69bd43d0497c8190ac23c65c5804846a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a06d6248190a613be9784dd1ef4 |
completed | March 20, 2026, 2:30 p.m. |
| PD | Predicate disambiguation | batch_69bd5231db7c8190b38d4fdbad8bf842 |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd56b5f4648190834eafa666d53caa |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:13 p.m.