Triple
T6230897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Army officer cadets |
E139348
|
entity |
| Predicate | hasResponsibilityDuringTraining |
P41566
|
FINISHED |
| Object | leading small teams |
—
|
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: leading small teams | Statement: [British Army officer cadets, hasResponsibilityDuringTraining, leading small teams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasResponsibilityDuringTraining Context triple: [British Army officer cadets, hasResponsibilityDuringTraining, leading small teams]
-
A.
hasTrainingRole
chosen
Indicates that an entity holds or is assigned a specific role within a training or instructional context.
-
B.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
C.
hasTrainingType
Indicates that an entity is associated with or characterized by a specific type or category of training.
-
D.
hasTrained
Indicates that one entity has provided training or instruction to another entity.
-
E.
requiresTraining
Indicates that one entity can only be properly or legitimately used, performed, or engaged with if the other entity has first received appropriate training.
- 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_69c008afd3148190b71e9eaa60420dd1 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062ec5be4819084d6df2e8dd2a542 |
completed | March 22, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69c05601de6481909d0880048fd7b49a |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:22 p.m.