Triple
T36108981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ERS (MGU-K and MGU-H) |
E1044437
|
entity |
| Predicate | MGU-KFunction |
P132490
|
FINISHED |
| Object | recovers kinetic energy under braking |
—
|
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: recovers kinetic energy under braking | Statement: [ERS (MGU-K and MGU-H), MGU-KFunction, recovers kinetic energy under braking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: MGU-KFunction Context triple: [ERS (MGU-K and MGU-H), MGU-KFunction, recovers kinetic energy under braking]
-
A.
usesKERS
Indicates that one entity employs or relies on a Kinetic Energy Recovery System (KERS) as part of its operation or functionality.
-
B.
mechanicalFunction
chosen
Indicates that one entity serves as the mechanical role, operation, or function performed by another entity or system.
-
C.
drivingForce
Indicates a causal influence or motivating factor that propels or significantly shapes another process, event, or outcome.
-
D.
hasKinetics
Indicates that one entity is associated with the kinetic properties or rate-related behavior of another entity in a process or reaction.
-
E.
fuelMeteringMethod
Indicates how fuel is measured, controlled, or delivered within a system or process.
- 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_69f76e344a4c8190af3858c6d78ba88f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b69b333081909cadbed3fcb8ecf5 |
completed | May 3, 2026, 8:56 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c2a5f8819094ad4621d7b97e0c |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:08 p.m.