Triple
T36956846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rad |
E914209
|
entity |
| Predicate | hasVisualTone |
P125598
|
FINISHED |
| Object | neon post-apocalyptic aesthetic |
—
|
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: neon post-apocalyptic aesthetic | Statement: [Rad, hasVisualTone, neon post-apocalyptic aesthetic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVisualTone Context triple: [Rad, hasVisualTone, neon post-apocalyptic aesthetic]
-
A.
visualTone
chosen
Indicates how the visual style, mood, or aesthetic quality of one entity relates to or affects another.
-
B.
hasToneContrast
Indicates a relationship where two tones differ in pitch, contour, or phonological features such that they form a perceptible tonal contrast.
-
C.
hasVisuals
Indicates that one entity includes, displays, or is associated with visual elements or imagery related to another entity.
-
D.
haveTone
Indicates that an entity possesses or exhibits a particular tone, such as a specific attitude, mood, or quality of expression.
-
E.
hasVisualCharacter
Indicates that one entity possesses or exhibits a particular visual appearance, style, or graphical characteristic defined by another 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_69f76e8b28848190abd81fe7a7374910 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd8ccbd4c88190b13aae0673b3c821 |
completed | May 8, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69fd8ae2227c819089546f5c3629799e |
completed | May 8, 2026, 7:04 a.m. |
Created at: May 3, 2026, 4:13 p.m.