Triple
T149440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Army Cadet Force |
E3399
|
entity |
| Predicate | hasUniform |
P2930
|
FINISHED |
| Object | British Army style uniform |
—
|
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: British Army style uniform | Statement: [Army Cadet Force, hasUniform, British Army style uniform]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUniform Context triple: [Army Cadet Force, hasUniform, British Army style uniform]
-
A.
usesUniform
chosen
Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
-
B.
hasStyle
Indicates that an entity possesses, exhibits, or is characterized by a particular style or manner.
-
C.
hasVariant
Indicates that one entity exists as an alternative form, version, or variation of another entity.
-
D.
hasDimension
Indicates that an entity possesses a specific measurable extent or size along one or more axes (e.g., length, width, height).
-
E.
hasSingle
Indicates that an entity possesses exactly one instance of a specified related entity or attribute.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2580ca15481909fa3e87d804a1b23 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a256599db08190a7b000b381d32ec4 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.