Triple
T6228854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | flag of the Netherlands (tricolour concept) |
E139301
|
entity |
| Predicate | visualSimplicity |
P69029
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [flag of the Netherlands (tricolour concept), visualSimplicity, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visualSimplicity Context triple: [flag of the Netherlands (tricolour concept), visualSimplicity, high]
-
A.
visualElements
Indicates that one entity contains, uses, or is characterized by specific visual components or graphical features associated with another entity.
-
B.
visualForm
Indicates the visual appearance, shape, or structural pattern that characterizes how something looks.
-
C.
isEasierToSeeThan
Indicates that one entity is more visually noticeable or discernible than another under comparable viewing conditions.
-
D.
graphics
Indicates a relationship where one entity is responsible for creating, providing, or handling visual representations or graphical content for another entity or context.
-
E.
visualEffect
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
- F. None of above. chosen
Provenance (4 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_69c008afd3148190b71e9eaa60420dd1 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062d841a88190b67a8045cdaadf44 |
completed | March 22, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69c055ffdf54819086d987d646e44ff5 |
completed | March 22, 2026, 8:50 p.m. |
| PDg | Predicate description generation | batch_69c056c965ac8190b938502fa8c74e1b |
completed | March 22, 2026, 8:53 p.m. |
Created at: March 22, 2026, 4:22 p.m.