Triple
T14608685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BMW M Performance (for i4 M50) |
E342898
|
entity |
| Predicate | chassisOptionsInclude |
P114171
|
FINISHED |
| Object | sport suspension components |
—
|
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: sport suspension components | Statement: [BMW M Performance (for i4 M50), chassisOptionsInclude, sport suspension components]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chassisOptionsInclude Context triple: [BMW M Performance (for i4 M50), chassisOptionsInclude, sport suspension components]
-
A.
chassisFeature
chosen
Indicates that a particular feature, component, or characteristic is part of or associated with a chassis.
-
B.
chassisConstruction
Indicates how the chassis of an object is built or assembled, specifying the construction method or structural design used.
-
C.
chassis
Indicates that one entity serves as the structural frame or supporting base (chassis) for another entity.
-
D.
supportsChassisType
Indicates that one entity is compatible with and can be used to support or accommodate a specified chassis type.
-
E.
chassisMaterialFeature
Indicates that an entity has a chassis characterized by a specific material-related feature or property.
- 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb44d327c8190a8d20568429d0f80 |
completed | April 14, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69de656f9f4c81909f815b6629a9ee39 |
completed | April 14, 2026, 4:03 p.m. |
Created at: April 10, 2026, 1:25 a.m.