Triple
T8055507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lotus Cars |
E187987
|
entity |
| Predicate | vehicleLayoutSpecialization |
P5253
|
FINISHED |
| Object | mid‑engine sports cars |
—
|
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: mid‑engine sports cars | Statement: [Lotus Cars, vehicleLayoutSpecialization, mid‑engine sports cars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleLayoutSpecialization Context triple: [Lotus Cars, vehicleLayoutSpecialization, mid‑engine sports cars]
-
A.
vehicleLayout
chosen
Indicates how the components or seating within a vehicle are arranged or configured relative to each other.
-
B.
featuresVehicle
Indicates that one entity includes, presents, or prominently incorporates a particular vehicle as part of its content, composition, or offering.
-
C.
carTypeVariant
Indicates that one car type is a specific variant or version of another car type.
-
D.
wheelbaseVariantOf
Indicates a relationship where one vehicle’s wheelbase configuration is a variant or modified version of another vehicle’s wheelbase.
-
E.
wheelArrangementSystem
Indicates the specific configuration or system by which the wheels of a vehicle or rolling stock are arranged and organized.
- 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_69ca82b2f68881908c50560697e210da |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3fa16804819094926ff2ff053c80 |
completed | March 31, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69cb049a1b9c8190811c396421ebf9c9 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:25 p.m.