Triple
T13315396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deutsche Tourenwagen Meisterschaft |
E317176
|
entity |
| Predicate | eligibleCars |
P93378
|
FINISHED |
| Object | production-based touring cars |
—
|
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: production-based touring cars | Statement: [Deutsche Tourenwagen Meisterschaft, eligibleCars, production-based touring cars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eligibleCars Context triple: [Deutsche Tourenwagen Meisterschaft, eligibleCars, production-based touring cars]
-
A.
vehicleEligibility
chosen
Indicates whether a given vehicle satisfies the required conditions or criteria to be considered eligible for a specified purpose or program.
-
B.
affectedCars
Indicates that certain cars are impacted or influenced by a particular event, condition, or action.
-
C.
shortlistedVehicle
Indicates that a vehicle has been selected as a candidate option from a larger set, typically for further consideration or evaluation.
-
D.
recommendedVehicle
Indicates that one entity suggests or endorses a particular vehicle as suitable or preferable for another entity or purpose.
-
E.
appliedToVehicleType
Indicates that something (such as a rule, restriction, or condition) is specifically applicable to a particular type or category of vehicle.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6babd88190a5d529df9584b9a4 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:29 p.m.