Triple
T20547804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian vehicle registration plate system |
E504517
|
entity |
| Predicate | highSecurityPlateColor |
P119760
|
FINISHED |
| Object | black letters on white background for private vehicles |
—
|
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 letters on white background for private vehicles | Statement: [Indian vehicle registration plate system, highSecurityPlateColor, black letters on white background for private vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: highSecurityPlateColor Context triple: [Indian vehicle registration plate system, highSecurityPlateColor, black letters on white background for private vehicles]
-
A.
plateColorForCommercialVehicles
Indicates the color assigned to license plates specifically used on commercial vehicles.
-
B.
plateColor
chosen
Indicates that an entity has a specific color attribute associated with its plate.
-
C.
roadSignColor
Indicates the color attribute associated with a particular road sign.
-
D.
hasPlate
Indicates that one entity possesses, is equipped with, or includes a plate as part of its attributes or components.
-
E.
usedOnOfficialPlatesIn
Indicates that something is employed or displayed on official license plates within a specified jurisdiction or region.
- 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_69e0b4b52c048190952b4d0f430813a3 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a2991ac8819089b8c2d70eb88952 |
completed | April 20, 2026, 10:03 p.m. |
| PD | Predicate disambiguation | batch_69e59fe5592c8190bb6122b784496d02 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:38 a.m.