Triple
T14122320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mickey Mouse Clubhouse |
E339933
|
entity |
| Predicate | includesVisualStyle |
P61564
|
FINISHED |
| Object | bright colorful 3D graphics |
—
|
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: bright colorful 3D graphics | Statement: [Mickey Mouse Clubhouse, includesVisualStyle, bright colorful 3D graphics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesVisualStyle Context triple: [Mickey Mouse Clubhouse, includesVisualStyle, bright colorful 3D graphics]
-
A.
typicalVisualStyle
chosen
Indicates the characteristic or commonly observed visual appearance or aesthetic style associated with an entity.
-
B.
hasSignatureVisualStyle
Indicates that an entity is characterized by a distinctive and recognizable visual style that sets it apart from others.
-
C.
visualizedIn
Indicates that something is represented or depicted within a particular visual medium, view, or visualization.
-
D.
usesAsStyleOf
Indicates that one entity adopts or applies another entity as a stylistic model, method, or manner of expression.
-
E.
structuralStyle
Indicates the architectural or design style that characterizes the structure or form of an entity.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de6095548881908a9e66adccca92d2 |
completed | April 14, 2026, 3:43 p.m. |
| PD | Predicate disambiguation | batch_69de05b5e7a08190a16be9ad8b92b80c |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:22 p.m.