Triple
T1774669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Commodore Amiga 1000 |
E38950
|
entity |
| Predicate | graphicsColors |
P60
|
FINISHED |
| Object | up to 32 colors from 4096-color palette |
—
|
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: up to 32 colors from 4096-color palette | Statement: [Commodore Amiga 1000, graphicsColors, up to 32 colors from 4096-color palette]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: graphicsColors Context triple: [Commodore Amiga 1000, graphicsColors, up to 32 colors from 4096-color palette]
-
A.
colors
chosen
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
B.
originalColors
Indicates that something retains or is associated with its initial, unaltered set of colors.
-
C.
colorVarietyOf
Indicates that one entity represents a specific color variant or color option of another entity.
-
D.
colorTheory
Indicates a relationship where principles or concepts about how colors interact, combine, or affect perception are applied or referenced between entities.
-
E.
colorOftenUsed
Indicates that a particular color is frequently used or commonly applied in relation to something.
- 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab17e368048190b7b73d156400f772 |
completed | March 6, 2026, 6:07 p.m. |
| PD | Predicate disambiguation | batch_69aa61cd4c1c8190a8dff391f5642bfe |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.