Triple
T18796602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chevrolet front‑wheel‑drive passenger cars |
E459649
|
entity |
| Predicate | typicalDriveConfiguration |
P68759
|
FINISHED |
| Object | left‑hand drive |
—
|
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: left‑hand drive | Statement: [Chevrolet front‑wheel‑drive passenger cars, typicalDriveConfiguration, left‑hand drive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDriveConfiguration Context triple: [Chevrolet front‑wheel‑drive passenger cars, typicalDriveConfiguration, left‑hand drive]
-
A.
driveType
Indicates the type or configuration of the drive mechanism used to power or propel an entity.
-
B.
typicalPickupConfiguration
Indicates the usual or standard arrangement or setup used for picking up or collecting something in a given context.
-
C.
typicalTractionType
Indicates the usual or most common type of traction mechanism associated with an entity (such as how it is typically powered or driven).
-
D.
drivesOn
Indicates that an entity uses or travels along a particular route, surface, or roadway as its path of movement.
-
E.
drivetrainFeature
chosen
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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a01ed3c08190890d9518ed69fdee |
completed | April 20, 2026, 3:40 a.m. |
| PD | Predicate disambiguation | batch_69e48d16dd34819096e096d0c0e4c15c |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:53 a.m.