Triple
T33406195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyundai E-GMP |
E855443
|
entity |
| Predicate | supportsVehicleToLoad |
P96313
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Hyundai E-GMP, supportsVehicleToLoad, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsVehicleToLoad Context triple: [Hyundai E-GMP, supportsVehicleToLoad, true]
-
A.
vehicleToLoad
Indicates a relationship where a vehicle is associated with, assigned to, or responsible for transporting a particular load.
-
B.
supportsVehicle
Indicates that one entity provides the necessary strength, stability, or structure to bear the weight of a vehicle.
-
C.
supportsCargoType
chosen
Indicates that one entity is capable of handling, transporting, or accommodating a specified type of cargo.
-
D.
vehicleLoadingMethod
Indicates the method or process by which a vehicle is loaded with goods, passengers, or other cargo.
-
E.
cargoVehicle
Indicates a relationship where a vehicle is used or designated for transporting cargo or goods.
- 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_69f3496f04a08190804e56ac5098b8e4 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:36 a.m.