Triple
T25745844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | F performance division |
E648341
|
entity |
| Predicate | vehicleLayoutFocus |
P5253
|
FINISHED |
| Object | all-wheel drive performance |
—
|
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: all-wheel drive performance | Statement: [F performance division, vehicleLayoutFocus, all-wheel drive performance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleLayoutFocus Context triple: [F performance division, vehicleLayoutFocus, all-wheel drive performance]
-
A.
vehicleLayout
chosen
Indicates how the components or seating within a vehicle are arranged or configured relative to each other.
-
B.
vehicleTypeFocus
Indicates that the relationship or action specifically concerns or emphasizes a particular type or category of vehicle.
-
C.
drivingFocus
Indicates that one entity serves as the primary motivating force, priority, or central concern guiding another entity’s actions or decisions.
-
D.
hostVehicle
Indicates that one entity serves as the primary or reference vehicle in relation to another entity or context.
-
E.
focusesOnSide
Indicates that an action, attention, or analysis is directed specifically toward one particular side or aspect of something.
- 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_69e7ab306eec8190b05c312c6ab186b8 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f5fd1e9dd081908c70074c8aa49e51 |
completed | May 2, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69f5afec3e94819080d9ba86cf8c866e |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 22, 2026, 3:51 a.m.