Triple
T16941240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garda Síochána |
E410953
|
entity |
| Predicate | vehicleLivery |
P21786
|
FINISHED |
| Object | blue and yellow battenburg markings |
—
|
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: blue and yellow battenburg markings | Statement: [Garda Síochána, vehicleLivery, blue and yellow battenburg markings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleLivery Context triple: [Garda Síochána, vehicleLivery, blue and yellow battenburg markings]
-
A.
hasLivery
chosen
Indicates that one entity bears or displays the distinctive colors, markings, or branding (livery) associated with another entity.
-
B.
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).
-
C.
liveryFeature
Indicates a characteristic or design element that is part of a specific livery or external appearance scheme.
-
D.
plateColorForCommercialVehicles
Indicates the color assigned to license plates specifically used on commercial vehicles.
-
E.
repaintedColor
Indicates that an entity’s color has been changed from its original color to a new one.
- 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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cfadec70819095ec0048ebc71016 |
completed | April 18, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_69e32b9aa8748190b248890aca86753d |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:31 a.m.