Triple
T14646415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Public Garden (Arles) |
E343861
|
entity |
| Predicate | color usage |
P7182
|
FINISHED |
| Object | vivid colors |
—
|
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: vivid colors | Statement: [The Public Garden (Arles), color usage, vivid colors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: color usage Context triple: [The Public Garden (Arles), color usage, vivid colors]
-
A.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
B.
colorOftenUsed
chosen
Indicates that a particular color is frequently used or commonly applied in relation to something.
-
C.
colorTheory
Indicates a relationship where principles or concepts about how colors interact, combine, or affect perception are applied or referenced between entities.
-
D.
colorSystem
Indicates that one entity is a system or scheme used to define, organize, or represent the colors of another entity.
-
E.
color work
Indicates that an entity applies or adds color to another entity, typically as part of a creative or finishing process.
- 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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4ebe8048190a2935d00c9cfd8be |
completed | April 14, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69de657359c88190b082e3e9f86fc1d7 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:26 a.m.