Triple
T30147050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No. 2 Service Dress |
E766283
|
entity |
| Predicate | isUniformOf |
P2930
|
FINISHED |
| Object | British Army land forces |
—
|
NE NERFINISHED |
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 land forces | Statement: [No. 2 Service Dress, isUniformOf, British Army land forces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUniformOf Context triple: [No. 2 Service Dress, isUniformOf, British Army land forces]
-
A.
isUniform
Indicates that all elements or parts within a given set, structure, or context share the same characteristics or value.
-
B.
areUniform
Indicates that all elements in a given set or collection share the same value, property, or characteristic.
-
C.
isUniformVariant
Indicates that one entity is a stylistic or formatting variant of another while preserving the same underlying content or structure.
-
D.
requiresUniformity
Indicates that one entity imposes a condition that another entity (or set of entities) must be consistent or identical in a specified aspect.
-
E.
usesUniform
chosen
Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
- 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_69f2247909048190ae86c2160cf8b566 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67e8d025c8190aacc621e932e381e |
completed | May 2, 2026, 10:45 p.m. |
| PD | Predicate disambiguation | batch_69f673c7a4588190837854f3ef61e6bf |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 7:19 p.m.