Triple
T35859864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tayside Police |
E1036915
|
entity |
| Predicate | usedUniformColour |
P46425
|
FINISHED |
| Object | black and white |
—
|
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: black and white | Statement: [Tayside Police, usedUniformColour, black and white]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedUniformColour Context triple: [Tayside Police, usedUniformColour, black and white]
-
A.
usedUniformColor
chosen
Indicates that multiple entities share or employed the same uniform color in a given context.
-
B.
usesUniform
Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
-
C.
colorUse
Indicates that one entity uses, applies, or is associated with a particular color in its appearance, design, or representation.
-
D.
uniformAccentColor
Indicates that multiple elements share the same accent color, creating a consistent visual highlight across them.
-
E.
uniformColorFeature
Indicates that the related entities share or exhibit the same uniform color characteristic.
- 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_69f76e1d279c8190843e5b64a0a12c3f |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aa3883d48190b05e3d2da7a017ae |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d435288190b30b1991fb003121 |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:06 p.m.