Triple
T19350337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vehicle registration plates of Italy |
E483997
|
entity |
| Predicate | motorcyclePlateSize |
P135528
|
FINISHED |
| Object | 177 mm × 177 mm |
—
|
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: 177 mm × 177 mm | Statement: [Vehicle registration plates of Italy, motorcyclePlateSize, 177 mm × 177 mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: motorcyclePlateSize Context triple: [Vehicle registration plates of Italy, motorcyclePlateSize, 177 mm × 177 mm]
-
A.
hasPlate
Indicates that one entity possesses, is equipped with, or includes a plate as part of its attributes or components.
-
B.
numberOfPlates
Indicates the quantity of plates associated with or involved in a particular entity, event, or context.
-
C.
tireSize
Indicates the specific size of a tire associated with an object or vehicle.
-
D.
isOnRearPlate
Indicates that one entity is positioned on or attached to the rear plate of another entity.
-
E.
plateNumberOf
Indicates the license plate number that is assigned to or associated with a particular vehicle.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69e4df51ac6c819091ce72b07790ffa6 |
completed | April 19, 2026, 1:57 p.m. |
Created at: April 10, 2026, 1:34 p.m.