Triple
T9834927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swedish Police Authority |
E239074
|
entity |
| Predicate | policeUniformColor |
P74357
|
FINISHED |
| Object | dark blue |
—
|
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: dark blue | Statement: [Swedish Police Authority, policeUniformColor, dark blue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policeUniformColor Context triple: [Swedish Police Authority, policeUniformColor, dark blue]
-
A.
wearsUniformColor
chosen
Indicates that an entity regularly uses or is associated with a specific uniform color as part of its standard attire or dress code.
-
B.
corpsColour
Indicates the specific color associated with a military corps or unit.
-
C.
wearsUniformSimilarTo
Indicates that one entity wears a uniform that is similar in appearance or style to the uniform worn by another entity.
-
D.
wearsOnUniform
Indicates that an item is part of and is worn as a component of a uniform.
-
E.
peakUniformedPersonnel
Indicates the maximum number of uniformed personnel present or deployed at any point in time within a given context or operation.
- 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_69ca84e314108190978324a4bdb959f8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb339aa1c8190901d8e660cef49c5 |
completed | April 2, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69cd03e30bc08190816c0a6d29c21b0f |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:32 p.m.