Triple
T4727612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of London Police |
E104923
|
entity |
| Predicate | wearsUniformStyle |
P22715
|
FINISHED |
| Object | British police 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 police uniform | Statement: [City of London Police, wearsUniformStyle, British police uniform]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wearsUniformStyle Context triple: [City of London Police, wearsUniformStyle, British police uniform]
-
A.
wearsOnUniform
Indicates that an item is part of and is worn as a component of a uniform.
-
B.
wearsUniformSimilarTo
chosen
Indicates that one entity wears a uniform that is similar in appearance or style to the uniform worn by another entity.
-
C.
modernUniformDesigner
Indicates that an entity is the designer responsible for creating or developing a modern-style uniform for another entity.
-
D.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
-
E.
uniformStyle
Indicates that the related entities share the same or a consistent style, pattern, or formatting.
- 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_69bd43ed84648190ae0b7ee8e8d00482 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd67c9c3c08190a6c4944cdd1362a8 |
completed | March 20, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69bd6220071881909670c89d072ffb6d |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:18 p.m.