Triple
T812030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyundai Kona Electric |
E17565
|
entity |
| Predicate | hasDriveType |
P4169
|
FINISHED |
| Object | electric front-wheel 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: electric front-wheel drive | Statement: [Hyundai Kona Electric, hasDriveType, electric front-wheel drive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDriveType Context triple: [Hyundai Kona Electric, hasDriveType, electric front-wheel drive]
-
A.
driveType
chosen
Indicates the type or configuration of the drive mechanism used to power or propel an entity.
-
B.
drivesOn
Indicates that an entity uses or travels along a particular route, surface, or roadway as its path of movement.
-
C.
hasVehicle
Indicates that one entity possesses, owns, or is assigned a vehicle.
-
D.
hasMotivePowerType
Indicates that an entity (such as a vehicle or machine) operates using a specified type of motive power (e.g., electric, diesel, steam).
-
E.
hasInternalHardDrive
Indicates that one entity possesses an internal hard drive as a built-in storage component.
- 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab4c7418819085cb64c6bf5fa70c |
completed | March 1, 2026, 9:10 p.m. |
| PD | Predicate disambiguation | batch_69a4aa73df08819096d0553a4b2509de |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.