Triple
T30030328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferrari Roma |
E762995
|
entity |
| Predicate | steeringWheelFeatures |
P168366
|
FINISHED |
| Object | integrated touch controls |
—
|
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: integrated touch controls | Statement: [Ferrari Roma, steeringWheelFeatures, integrated touch controls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: steeringWheelFeatures Context triple: [Ferrari Roma, steeringWheelFeatures, integrated touch controls]
-
A.
steeringWheelType
Indicates the specific kind or design of steering wheel associated with an entity (such as a vehicle or driving setup).
-
B.
steeringType
Indicates the kind or mechanism of steering control used to direct the movement of an entity.
-
C.
hasSteering
Indicates that one entity is equipped with or possesses a steering mechanism that allows control of its direction.
-
D.
steeringWheelPosition
Indicates the relative location or orientation of a steering wheel with respect to a reference point, such as a vehicle’s interior layout or driving side.
-
E.
chassisFeature
Indicates that a particular feature, component, or characteristic is part of or associated with a chassis.
- 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_69f2246ee6e48190b69e837b913b398a |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f679af17648190bc90c5dc4afe35e4 |
completed | May 2, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69f66ec9919881908a187bfc7c4df192 |
completed | May 2, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69f67256d064819094be04fc1bbbc635 |
completed | May 2, 2026, 9:53 p.m. |
Created at: April 29, 2026, 6:49 p.m.