Triple
T27582062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Video Graphics Array |
E699608
|
entity |
| Predicate | maxColorsAt320×200 |
P121142
|
FINISHED |
| Object | 256 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: 256 colors | Statement: [Video Graphics Array, maxColorsAt320×200, 256 colors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maxColorsAt320×200 Context triple: [Video Graphics Array, maxColorsAt320×200, 256 colors]
-
A.
maxColorsOnScreen
Indicates the maximum number of distinct colors that can be displayed on the screen at the same time.
-
B.
graphicsModeColorsAt640x200
Indicates the number or type of colors available when operating in a graphics display mode with a resolution of 640 by 200 pixels.
-
C.
hasNumberOfColors
chosen
Indicates the quantity of distinct colors associated with an entity.
-
D.
paletteSize
Indicates the number of distinct colors included in a given color palette.
-
E.
colorDepth
Indicates the bit-depth used to represent the color information of an image or display, defining how many distinct colors can be shown.
- 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_69ef6a4cb8b881909b3a8d630fd89df2 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6359e3d3c81909814e2f0a7fb0ea9 |
completed | May 2, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f631871c888190bf29466fe4254e51 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 2:03 p.m.