Triple
T35859865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tayside Police |
E1036915
|
entity |
| Predicate | usedVehicleLivery |
P21786
|
FINISHED |
| Object | Battenburg markings |
—
|
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: Battenburg markings | Statement: [Tayside Police, usedVehicleLivery, Battenburg markings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedVehicleLivery Context triple: [Tayside Police, usedVehicleLivery, Battenburg markings]
-
A.
hasLivery
chosen
Indicates that one entity bears or displays the distinctive colors, markings, or branding (livery) associated with another entity.
-
B.
liveryFeature
Indicates a characteristic or design element that is part of a specific livery or external appearance scheme.
-
C.
liveryColors
Indicates the specific set of colors used as the official or characteristic color scheme associated with an entity (such as a brand, organization, or vehicle).
-
D.
usesVehicleVariant
Indicates that one entity performs an action or function by employing a specific variant or version of a vehicle.
-
E.
liveryInspiredBy
Indicates that one livery’s design, colors, or overall appearance is based on, influenced by, or pays homage to another livery.
- 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.