Triple
T1956475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Cruise |
E42280
|
entity |
| Predicate | controlInterface |
P17356
|
FINISHED |
| Object | steering wheel controls |
—
|
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: steering wheel controls | Statement: [Super Cruise, controlInterface, steering wheel controls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: controlInterface Context triple: [Super Cruise, controlInterface, steering wheel controls]
-
A.
exportControl
Indicates that an entity is subject to rules or restrictions governing the transfer or export of goods, services, or information across borders.
-
B.
controlSurfaces
Indicates that one entity functions as a control surface or set of control surfaces used to influence, steer, or regulate the behavior or state of another entity.
-
C.
robotControlSystem
Indicates a relationship where a system monitors, directs, and coordinates the actions and behaviors of one or more robots.
-
D.
canControl
Indicates that one entity has the ability or authority to direct, manage, or influence the behavior or state of another entity.
-
E.
controlUnitType
chosen
Indicates the specific kind or category of control unit associated with or assigned to an entity.
- 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_69a8870eea088190a38781990812a9bc |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb37b4a38819099f98be92be91ade |
completed | March 7, 2026, 5:11 a.m. |
| PD | Predicate disambiguation | batch_69abaff3eda88190b643994cb4dfb8df |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.