Triple
T11872127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kirby Krackle |
E282428
|
entity |
| Predicate | artisticEffect |
P16366
|
FINISHED |
| Object | abstract representation of energy |
—
|
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: abstract representation of energy | Statement: [Kirby Krackle, artisticEffect, abstract representation of energy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: artisticEffect Context triple: [Kirby Krackle, artisticEffect, abstract representation of energy]
-
A.
visualEffect
chosen
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
-
B.
artisticFunction
Indicates that one entity serves a creative, expressive, or aesthetic role or purpose in relation to another entity.
-
C.
artisticStyle
Indicates the artistic movement, style, or aesthetic approach that characterizes how something is created or visually expressed.
-
D.
contrastEffect
Indicates that one entity’s characteristics are perceived or evaluated differently because they are compared or juxtaposed with another entity.
-
E.
artUse
Indicates that one entity uses, applies, or employs another entity within an artistic or creative context.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d39d2934819093b9f7006f45e5cb |
completed | April 10, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69d8bb272f88819090c37c944c5a60ab |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:43 p.m.