Triple
T8055523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lotus Cars |
E187987
|
entity |
| Predicate | vehicleTypeSpecialization |
P27118
|
FINISHED |
| Object | high‑performance road 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: high‑performance road cars | Statement: [Lotus Cars, vehicleTypeSpecialization, high‑performance road cars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleTypeSpecialization Context triple: [Lotus Cars, vehicleTypeSpecialization, high‑performance road cars]
-
A.
vehicleType
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
-
B.
vehicleTypeFocus
chosen
Indicates that the relationship or action specifically concerns or emphasizes a particular type or category of vehicle.
-
C.
vehicleFamily
Indicates that two vehicles belong to the same family or category based on shared design, platform, or lineage.
-
D.
vehicleStandard
Indicates that something complies with, or is defined according to, a specified vehicle-related standard or regulatory specification.
-
E.
appliedToVehicleType
Indicates that something (such as a rule, restriction, or condition) is specifically applicable to a particular type or category of vehicle.
- 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.