Triple
T19350333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vehicle registration plates of Italy |
E483997
|
entity |
| Predicate | specialPlateColor |
P119760
|
FINISHED |
| Object | red on white for temporary plates |
—
|
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: red on white for temporary plates | Statement: [Vehicle registration plates of Italy, specialPlateColor, red on white for temporary plates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: specialPlateColor Context triple: [Vehicle registration plates of Italy, specialPlateColor, red on white for temporary plates]
-
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.
usedOnOfficialPlatesIn
Indicates that something is employed or displayed on official license plates within a specified jurisdiction or region.
-
D.
hasPlate
Indicates that one entity possesses, is equipped with, or includes a plate as part of its attributes or components.
-
E.
usesCodeOnPlates
Indicates that an entity applies or employs a specific code or coding system on plates.
- 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_69d8e8d244f8819080eb1f3491300db2 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e6190381c081909c747a22422fb02c |
completed | April 20, 2026, 12:16 p.m. |
| PD | Predicate disambiguation | batch_69e4dd12303c8190a2027c062b2dff40 |
completed | April 19, 2026, 1:48 p.m. |
Created at: April 10, 2026, 1:34 p.m.