Triple
T35743092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BR-43 |
E1033093
|
entity |
| Predicate | plateColorCommercialVehicles |
P107131
|
FINISHED |
| Object | yellow background with black letters |
—
|
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: yellow background with black letters | Statement: [BR-43, plateColorCommercialVehicles, yellow background with black letters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plateColorCommercialVehicles Context triple: [BR-43, plateColorCommercialVehicles, yellow background with black letters]
-
A.
plateColorForCommercialVehicles
chosen
Indicates the color assigned to license plates specifically used on commercial vehicles.
-
B.
plateColor
Indicates that an entity has a specific color attribute associated with its plate.
-
C.
colorOfTrailMarkings
Indicates the relationship specifying what color the trail’s markings are.
-
D.
hasNationalSignageColor
Indicates that an entity uses a particular color (or set of colors) as its officially designated national signage color scheme.
-
E.
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).
- 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_69f76e119d508190a3873cb302063832 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:06 p.m.