Triple
T13920176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mercedes-AMG A 35 |
E334720
|
entity |
| Predicate | hasOptionalFeature |
P23744
|
FINISHED |
| Object | adaptive suspension |
—
|
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: adaptive suspension | Statement: [Mercedes-AMG A 35, hasOptionalFeature, adaptive suspension]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOptionalFeature Context triple: [Mercedes-AMG A 35, hasOptionalFeature, adaptive suspension]
-
A.
hasFeature
Indicates that an entity possesses, exhibits, or includes a particular characteristic, attribute, or component.
-
B.
hasOptionalSection
chosen
Indicates that an entity includes a section or component that is not mandatory and may or may not be present.
-
C.
hasFeatureCode
Indicates that an entity is associated with a specific feature identifier or code that characterizes one of its properties or attributes.
-
D.
hasFeatureStatus
Indicates that an entity possesses a particular feature along with its current state or condition.
-
E.
hasPrimaryFeature
Indicates that an entity possesses a main or most characteristic feature that defines or distinguishes it.
- 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_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2aa428ac819084e7c4b244d15f20 |
completed | April 14, 2026, 11:53 a.m. |
| PD | Predicate disambiguation | batch_69de059e4ba881908554f72e889719fa |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:16 p.m.