Triple
T19232033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Subaru SVX |
E480893
|
entity |
| Predicate | driveTypeInJapanBaseModels |
P4169
|
FINISHED |
| Object | front-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: front-wheel-drive | Statement: [Subaru SVX, driveTypeInJapanBaseModels, front-wheel-drive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: driveTypeInJapanBaseModels Context triple: [Subaru SVX, driveTypeInJapanBaseModels, front-wheel-drive]
-
A.
driveType
chosen
Indicates the type or configuration of the drive mechanism used to power or propel an entity.
-
B.
carModel
Indicates the specific model designation of a car within a particular make or brand.
-
C.
rideModel
Indicates that one entity is a specific model or type designation of a ride associated with another entity.
-
D.
wheelbaseVariantOf
Indicates a relationship where one vehicle’s wheelbase configuration is a variant or modified version of another vehicle’s wheelbase.
-
E.
carTypeVariant
Indicates that one car type is a specific variant or version of another car type.
- 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_69d8e8ccb8f48190ad420098e74fb1db |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fa9db56081908f50d318d7fc9eaa |
completed | April 20, 2026, 10:06 a.m. |
| PD | Predicate disambiguation | batch_69e4dcfae6f081909cc173cf71a5005c |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:25 p.m.