Triple
T30619473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | General Motors Super Cruise |
E779405
|
entity |
| Predicate | SAELevel |
P169627
|
FINISHED |
| Object | Level 2 driver assistance |
—
|
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: Level 2 driver assistance | Statement: [General Motors Super Cruise, SAELevel, Level 2 driver assistance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: SAELevel Context triple: [General Motors Super Cruise, SAELevel, Level 2 driver assistance]
-
A.
hasVehicularActivityLevel
Indicates the degree or intensity of vehicular activity associated with an entity, such as traffic volume or frequency of vehicle use.
-
B.
intendedVehicleClass
Indicates that one entity is designed or specified to be used with, or is appropriate for, a particular class or category of vehicle.
-
C.
hasLevelOfTraffic
Indicates the degree or intensity of traffic present in or affecting a given entity or location.
-
D.
designedSpeedKmH
Indicates the maximum speed in kilometers per hour that something is intended or engineered to achieve under its design specifications.
-
E.
includesVehicleLevel
Indicates that something encompasses or applies to a specific level or category associated with a vehicle.
- F. None of above. chosen
Provenance (4 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_69f224a3307081909a6dca8ca75dbf48 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f689ed5b9c81909976d061f71d782a |
completed | May 2, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69f67e448a9c8190b591374d98799fe3 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f67f0353c88190a05b2db449abe0f4 |
completed | May 2, 2026, 10:47 p.m. |
Created at: April 29, 2026, 8:26 p.m.