Triple
T28858481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volkswagen Caddy |
E728798
|
entity |
| Predicate | longWheelbaseName |
P33596
|
FINISHED |
| Object | Caddy Maxi |
—
|
NE NERFINISHED |
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: Caddy Maxi | Statement: [Volkswagen Caddy, longWheelbaseName, Caddy Maxi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: longWheelbaseName Context triple: [Volkswagen Caddy, longWheelbaseName, Caddy Maxi]
-
A.
wheelbase
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
chosen
Indicates the classification of a vehicle based on the length or category of its wheelbase.
-
E.
hasLeadingWheelArrangement
Indicates the specific configuration of the leading (front) wheels in a vehicle’s or locomotive’s wheel arrangement.
- 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_69f0319f4e5481909e4c439dbe8be940 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f65a14eaa081908113d246dbaf86dd |
completed | May 2, 2026, 8:09 p.m. |
| PD | Predicate disambiguation | batch_69f65762b5e481908a30ca963dcba4be |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 6:46 a.m.