Triple
T8929181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | quattro all-wheel drive |
E212608
|
entity |
| Predicate | typicalTorqueSplit |
P62551
|
FINISHED |
| Object | front-rear variable |
—
|
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: front-rear variable | Statement: [quattro all-wheel drive, typicalTorqueSplit, front-rear variable]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTorqueSplit Context triple: [quattro all-wheel drive, typicalTorqueSplit, front-rear variable]
-
A.
torqueDistribution
chosen
Indicates how torque or rotational force is apportioned among multiple components, such as wheels, axles, or motors, within a system.
-
B.
torque
Indicates a rotational force applied by one entity on another around a pivot or axis.
-
C.
drivingForce
Indicates a causal influence or motivating factor that propels or significantly shapes another process, event, or outcome.
-
D.
drivetrainRole
Indicates the functional role or position an entity has within a drivetrain system (e.g., input, transmission, or output component).
-
E.
drivetrainFeature
Indicates that an entity has a specific characteristic, component, or capability related to its drivetrain system.
- 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_69ca8395c438819087d7cb844ab5990c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc667470308190a75ba63de803e3a2 |
completed | April 1, 2026, 12:27 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed3286c8190a21de2ee11f2639f |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:57 p.m.