Triple
T2545835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loop transportation system |
E57898
|
entity |
| Predicate | vehicleControl |
P30234
|
FINISHED |
| Object | computer-controlled driving |
—
|
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: computer-controlled driving | Statement: [Loop transportation system, vehicleControl, computer-controlled driving]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleControl Context triple: [Loop transportation system, vehicleControl, computer-controlled driving]
-
A.
commandedVehicle
chosen
Indicates that one entity had authoritative control over or issued orders to another entity that is a vehicle.
-
B.
drives
Indicates that one entity operates and controls the movement of a vehicle or similar conveyance transporting themselves or others.
-
C.
drivingForce
Indicates a causal influence or motivating factor that propels or significantly shapes another process, event, or outcome.
-
D.
drivesOn
Indicates that an entity uses or travels along a particular route, surface, or roadway as its path of movement.
-
E.
vehicleUsed
Indicates that a particular vehicle is utilized or employed in performing an action, event, or activity.
- 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_69ab4a5212d88190b989ce129f2ad87f |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd2c285288190b41fc0188879623a |
completed | March 7, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69abd0c63964819092d5f578195ae8dd |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:47 p.m.