Triple
T13505094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PSA PF2 platform (early generations) |
E320995
|
entity |
| Predicate | usedForVehicleClass |
P97747
|
FINISHED |
| Object | compact car |
—
|
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: compact car | Statement: [PSA PF2 platform (early generations), usedForVehicleClass, compact car]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedForVehicleClass Context triple: [PSA PF2 platform (early generations), usedForVehicleClass, compact car]
-
A.
intendedVehicleClass
chosen
Indicates that one entity is designed or specified to be used with, or is appropriate for, a particular class or category of vehicle.
-
B.
appliedToVehicleType
Indicates that something (such as a rule, restriction, or condition) is specifically applicable to a particular type or category of vehicle.
-
C.
vehicleEligibility
Indicates whether a given vehicle satisfies the required conditions or criteria to be considered eligible for a specified purpose or program.
-
D.
mainVehicleClass
Indicates the primary category or type of vehicle to which an entity chiefly belongs.
-
E.
associatedVehicleWeightClass
Indicates the weight classification category that is linked or assigned to a particular 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf810e248190a060481004503f96 |
completed | April 12, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69dbae0b63748190b5e207f84b2532ea |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:43 p.m.