Triple
T20027249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alfa DNA driving mode selector |
E495015
|
entity |
| Predicate | DynamicModeEffect |
P106972
|
FINISHED |
| Object | sharper throttle response |
—
|
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: sharper throttle response | Statement: [Alfa DNA driving mode selector, DynamicModeEffect, sharper throttle response]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: DynamicModeEffect Context triple: [Alfa DNA driving mode selector, DynamicModeEffect, sharper throttle response]
-
A.
visualEffect
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
-
B.
ultimateEffect
Indicates the final or overall outcome that results from a preceding action, condition, or sequence of events.
-
C.
usesEffectType
Indicates that an entity employs or is associated with a particular type or category of effect in its operation or behavior.
-
D.
specialEffectsBy
Indicates that the special effects for something (such as a film, scene, or shot) are created or provided by a particular person or entity.
-
E.
providesEffect
chosen
Indicates that one entity causes, delivers, or produces a particular effect or outcome on another 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6628e1eec81908e4c9b2b0b68f0e4 |
completed | April 20, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69e54ce752748190a0a1ffddd0372271 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:35 p.m.