Triple
T5820312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chevrolet Task Force |
E129090
|
entity |
| Predicate | stylingInfluence |
P44042
|
FINISHED |
| Object | classic American pickup truck look |
—
|
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: classic American pickup truck look | Statement: [Chevrolet Task Force, stylingInfluence, classic American pickup truck look]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stylingInfluence Context triple: [Chevrolet Task Force, stylingInfluence, classic American pickup truck look]
-
A.
styleTendsTo
Indicates that one style is generally inclined or likely to develop, appear, or be adopted in the direction of another style.
-
B.
fashionStyle
Indicates the characteristic way in which an entity dresses or presents themselves in terms of clothing and appearance.
-
C.
designInfluenceOn
chosen
Indicates that one design, designer, or design-related factor has an effect on shaping, guiding, or altering another design or design outcome.
-
D.
relatedStyle
Indicates that one style is associated with, similar to, or derived from another style in some relevant way.
-
E.
styleCategory
Indicates the stylistic classification or genre category that an item, work, or entity belongs to.
- 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_69c0084869e881908d7859492183ca7b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0400f1af881908d376ea4793f6dea |
completed | March 22, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69c0333fdd7081908d829265caa2ac11 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:53 p.m.