Triple
T20671762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TBU |
E508042
|
entity |
| Predicate | vehicleTypeCoverage |
P23423
|
FINISHED |
| Object | passenger 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: passenger cars | Statement: [TBU, vehicleTypeCoverage, passenger cars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleTypeCoverage Context triple: [TBU, vehicleTypeCoverage, passenger cars]
-
A.
vehiclePolicy
Indicates a relationship where a policy governs, regulates, or defines rules and conditions for the use, operation, or management of a vehicle.
-
B.
vehicleType
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
-
C.
typeOfCoverage
Indicates the specific kind or category of coverage that applies in a given context (such as insurance, service, or protection).
-
D.
appliedToVehicleType
chosen
Indicates that something (such as a rule, restriction, or condition) is specifically applicable to a particular type or category of vehicle.
-
E.
vehicleEligibility
Indicates whether a given vehicle satisfies the required conditions or criteria to be considered eligible for a specified purpose or program.
- 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_69e0b4c1164881909a3bf1e3ddb2bc32 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b5c92aa8819096fbe0ca5101d01b |
completed | April 20, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69e5c03caee881908be4dd25796a03d5 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:44 a.m.