Triple
T16789903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyundai Ioniq 6 |
E408078
|
entity |
| Predicate | ADASFeature |
P57273
|
FINISHED |
| Object | Highway Driving Assist |
—
|
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: Highway Driving Assist | Statement: [Hyundai Ioniq 6, ADASFeature, Highway Driving Assist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ADASFeature Context triple: [Hyundai Ioniq 6, ADASFeature, Highway Driving Assist]
-
A.
hasDriverAssistance
chosen
Indicates that an entity is equipped with or supports driver assistance features or systems.
-
B.
CAVFeature
Indicates a relationship where an entity possesses or is characterized by a specific feature, attribute, or property within the CAV (context-aware/controlled) framework.
-
C.
driveAssistFeature
Indicates that one entity provides an assistance feature that helps another entity perform driving-related tasks.
-
D.
hasVehicleFeature
Indicates that a vehicle possesses, includes, or is equipped with a specific feature or characteristic.
-
E.
hasTrafficFeature
Indicates that an entity possesses or is associated with a specific traffic-related characteristic, element, or infrastructure feature.
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2a50e18819090a30e1f38e520e0 |
completed | April 18, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69e319cf691c819083e39225f5777ef0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:22 a.m.