Triple
T30142505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | wordmark quattro |
E766165
|
entity |
| Predicate | visualElementOf |
P29429
|
FINISHED |
| Object | Audi quattro badge |
—
|
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: Audi quattro badge | Statement: [wordmark quattro, visualElementOf, Audi quattro badge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visualElementOf Context triple: [wordmark quattro, visualElementOf, Audi quattro badge]
-
A.
visualElements
chosen
Indicates that one entity contains, uses, or is characterized by specific visual components or graphical features associated with another entity.
-
B.
visualizedIn
Indicates that something is represented or depicted within a particular visual medium, view, or visualization.
-
C.
visualizationLibrary
Indicates that an entity uses, depends on, or is implemented with a particular visualization library for rendering or displaying visual data.
-
D.
visualizationMethod
Indicates the technique or approach used to visually represent data, information, or concepts.
-
E.
visualMetaphor
Indicates a relationship where one entity conceptually represents or explains another through a visual analogy or symbolic imagery.
- 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_69f2247909048190ae86c2160cf8b566 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b7b03488190b1db5fde4c7dd6e5 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 7:18 p.m.