Triple
T2274069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford D2C platform (fifth generation) |
E50727
|
entity |
| Predicate | automotiveClassSupported |
P37628
|
FINISHED |
| Object | pony car |
—
|
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: pony car | Statement: [Ford D2C platform (fifth generation), automotiveClassSupported, pony car]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: automotiveClassSupported Context triple: [Ford D2C platform (fifth generation), automotiveClassSupported, pony car]
-
A.
appliedToVehicleType
Indicates that something (such as a rule, restriction, or condition) is specifically applicable to a particular type or category of vehicle.
-
B.
vehicleStandard
Indicates that something complies with, or is defined according to, a specified vehicle-related standard or regulatory specification.
-
C.
vehicleManufacturerHosted
Indicates that a vehicle manufacturer organized, sponsored, or served as the host for a particular event or activity.
-
D.
carModel
Indicates the specific model designation of a car within a particular make or brand.
-
E.
associatedVehicleWeightClass
Indicates the weight classification category that is linked or assigned to a particular vehicle.
- F. None of above. chosen
Provenance (4 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_69a88b05910c8190a9a2b1ff230c85f9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc39c6ff0819081a07696f1c29990 |
completed | March 7, 2026, 6:20 a.m. |
| PD | Predicate disambiguation | batch_69abbdb7719081909143efa8f48df4e4 |
completed | March 7, 2026, 5:55 a.m. |
| PDg | Predicate description generation | batch_69abc39b2f548190a38f604e0d36db3a |
completed | March 7, 2026, 6:20 a.m. |
Created at: March 4, 2026, 7:48 p.m.