Triple
T14091746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nigerian Defence Academy |
E339147
|
entity |
| Predicate | hasTrainingDuration |
P82629
|
FINISHED |
| Object | multi‑year cadetship programme |
—
|
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: multi‑year cadetship programme | Statement: [Nigerian Defence Academy, hasTrainingDuration, multi‑year cadetship programme]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrainingDuration Context triple: [Nigerian Defence Academy, hasTrainingDuration, multi‑year cadetship programme]
-
A.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
B.
hasTrainingTrack
Indicates that an entity is associated with or assigned to a specific training track or program.
-
C.
hasCourseLength
chosen
Indicates that an entity (such as a course) is associated with a specific duration or length.
-
D.
hasTrainingType
Indicates that an entity is associated with or characterized by a specific type or category of training.
-
E.
trainingProvidedAt
Indicates that a training activity or program is conducted or delivered at a specific location or venue.
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5ee3213c8190af2853a2a5b302a2 |
completed | April 14, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69de05b0e6c88190a819eeba0028981f |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:21 p.m.