Triple
T28322111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trafic |
E717303
|
entity |
| Predicate | hasInnovativeVehicle |
P156398
|
FINISHED |
| Object | prototype car for an auto show |
—
|
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: prototype car for an auto show | Statement: [Trafic, hasInnovativeVehicle, prototype car for an auto show]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInnovativeVehicle Context triple: [Trafic, hasInnovativeVehicle, prototype car for an auto show]
-
A.
hasConceptVehicle
chosen
Indicates that an entity is associated with or involves a particular vehicle concept (e.g., as its subject, example, or focus).
-
B.
hasFictionalVehicle
Indicates that one entity possesses, controls, or is associated with a vehicle that exists only in a fictional or imaginary context.
-
C.
usesVehicleTechnology
Indicates that an entity employs or applies a specific vehicle-related technology in its operations, products, or activities.
-
D.
hasDrivingMotorCar
Indicates that one entity operates or drives a motor car in relation to another entity or context.
-
E.
hasVehicle
Indicates that one entity possesses, owns, or is assigned a 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_69eff6e6c3b08190ad78de6ba7f04548 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69fd7fdafbe881908a31fcb407af2c34 |
completed | May 8, 2026, 6:16 a.m. |
| PD | Predicate disambiguation | batch_69fd7ef0ea908190b5d83f71565bdb1c |
completed | May 8, 2026, 6:13 a.m. |
Created at: April 28, 2026, 12:25 a.m.