Triple
T29447645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 6 Hours of Fuji |
E746892
|
entity |
| Predicate | numberOfDriversPerCar |
P157305
|
FINISHED |
| Object | 2–3 drivers |
—
|
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: 2–3 drivers | Statement: [6 Hours of Fuji, numberOfDriversPerCar, 2–3 drivers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfDriversPerCar Context triple: [6 Hours of Fuji, numberOfDriversPerCar, 2–3 drivers]
-
A.
minimumDriversPerCar
chosen
Indicates the minimum number of drivers that must be assigned to or available for each car.
-
B.
numberOfDriversPerTeam
Indicates the quantity of drivers associated with each team.
-
C.
numberOfRidersPerVehicle
Indicates the quantity of riders associated with each individual vehicle in the relationship.
-
D.
numberOfCarsPerUnit
Indicates the quantity of cars associated with each single unit of a specified measure (such as time, distance, or entity).
-
E.
quantityPerCar
Indicates the amount or number of a specified item associated with each individual car.
- 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_69f0a7a230488190b44a97fe3d16f731 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fff328ddc0819080642334a41fcf95 |
completed | May 10, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69fff2e0971c819081aa66f4a6a34b28 |
completed | May 10, 2026, 2:52 a.m. |
Created at: April 28, 2026, 3:29 p.m.