Triple
T38490499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford Granada (European) |
E918040
|
entity |
| Predicate | wheelbaseMk2 |
P4167
|
FINISHED |
| Object | 2770 mm |
—
|
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: 2770 mm | Statement: [Ford Granada (European), wheelbaseMk2, 2770 mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wheelbaseMk2 Context triple: [Ford Granada (European), wheelbaseMk2, 2770 mm]
-
A.
wheelbase
chosen
Indicates the distance between the centers of the front and rear wheels of a vehicle.
-
B.
wheelbaseComparedTo
Indicates a comparison between the distances between the front and rear wheel axles (wheelbases) of two entities, specifying how one wheelbase relates in size or length to the other.
-
C.
wheelbaseVariantOf
Indicates a relationship where one vehicle’s wheelbase configuration is a variant or modified version of another vehicle’s wheelbase.
-
D.
wheelbaseClass
Indicates the classification of a vehicle based on the length or category of its wheelbase.
-
E.
wheelHeightApprox
Indicates that the height of a wheel is approximately equal to a specified value or to the height of another wheel.
- 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_69f76e9894208190a129a553a60ca58c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcdaa36f90819093f8661969990c7d |
completed | May 7, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fefc588190b063d7ea1ec87b07 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:31 p.m.