Triple
T4706547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joint Force Training Centre |
E104400
|
entity |
| Predicate | trainingScope |
P28135
|
FINISHED |
| Object | joint operations |
—
|
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: joint operations | Statement: [Joint Force Training Centre, trainingScope, joint operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingScope Context triple: [Joint Force Training Centre, trainingScope, joint operations]
-
A.
trainingDomain
chosen
Indicates that an entity is associated with or operates within a particular field, area, or domain of training.
-
B.
trainingComponent
Indicates that one entity functions as a training-related part, module, or element within a larger training process or system involving another entity.
-
C.
trainingUse
Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
-
D.
training
Indicates that one entity is teaching, coaching, or otherwise helping another entity acquire or improve a skill, behavior, or capability.
-
E.
trainingSystem
Indicates a system or framework used to train, instruct, or develop skills or knowledge in a target entity.
- 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_69bd43eac3c08190af7e4020c6c3704c |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd650ad0f88190844bfcb46b3071c2 |
completed | March 20, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69bd621ba7448190a53ab1e2897acf71 |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:17 p.m.