Triple
T35917197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M-Sport Ford World Rally Team |
E1038779
|
entity |
| Predicate | usedCarModel |
P32674
|
FINISHED |
| Object | Ford Fiesta WRC |
—
|
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: Ford Fiesta WRC | Statement: [M-Sport Ford World Rally Team, usedCarModel, Ford Fiesta WRC]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedCarModel Context triple: [M-Sport Ford World Rally Team, usedCarModel, Ford Fiesta WRC]
-
A.
usedVehicleModel
Indicates that a vehicle is a pre-owned (used) instance of a particular vehicle model.
-
B.
carModel
chosen
Indicates the specific model designation of a car within a particular make or brand.
-
C.
vehicleVariant
Indicates that one vehicle is a specific version, model, or configuration variant of another related vehicle.
-
D.
listedVehicle
Indicates that a vehicle has been placed on a list, such as a registry, catalog, or inventory, as part of a tracking or management process.
-
E.
carTypeVariant
Indicates that one car type is a specific variant or version of another car type.
- 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_69f76e2320748190b7f5c4750d0cd0d3 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7be53890081909b1d93f30a8f31c6 |
completed | May 3, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f7bccacbac8190978976324c67db28 |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:07 p.m.