Triple
T23489721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Officers Training Academy |
E570635
|
entity |
| Predicate | hasTrainingComponents |
P24513
|
FINISHED |
| Object | physical training |
—
|
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: physical training | Statement: [Officers Training Academy, hasTrainingComponents, physical training]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrainingComponents Context triple: [Officers Training Academy, hasTrainingComponents, physical training]
-
A.
hasFieldTrainingComponent
Indicates that an entity includes or is associated with a component involving practical, in-the-field training activities.
-
B.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
C.
hasTrainingComplex
Indicates that an entity possesses or is associated with a dedicated facility or complex used for training activities.
-
D.
hasTrainingType
chosen
Indicates that an entity is associated with or characterized by a specific type or category of training.
-
E.
hasTrainingTrack
Indicates that an entity is associated with or assigned to a specific training track or program.
- 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_69e245b0b01481908f636939bedd804c |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a7dba7388190a322ab059bb6522a |
completed | April 29, 2026, 6:40 a.m. |
| PD | Predicate disambiguation | batch_69f0620ac3608190b36916261ea50f54 |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 6:04 p.m.