Triple
T15689087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Horn |
E380277
|
entity |
| Predicate | availableDrivetrains |
P4169
|
FINISHED |
| Object | rear-wheel drive |
—
|
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: rear-wheel drive | Statement: [Big Horn, availableDrivetrains, rear-wheel drive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: availableDrivetrains Context triple: [Big Horn, availableDrivetrains, rear-wheel drive]
-
A.
drivetrainFeature
Indicates that an entity has a specific characteristic, component, or capability related to its drivetrain system.
-
B.
drivetrainRole
Indicates the functional role or position an entity has within a drivetrain system (e.g., input, transmission, or output component).
-
C.
supportsDrivetrainFeature
Indicates that an entity provides or is compatible with a specified drivetrain-related capability or function.
-
D.
driveType
chosen
Indicates the type or configuration of the drive mechanism used to power or propel an entity.
-
E.
numberOfAxlesDriven
Indicates the count of axles on a vehicle that are actively powered or driven by the propulsion system.
- 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f4cee5481908699fbb2b7bdd2f6 |
completed | April 16, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69deda8c856c8190882330114f9a1a5f |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:44 a.m.