Triple
T27582061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Video Graphics Array |
E699608
|
entity |
| Predicate | maxColorsAtMaxResolution |
P30793
|
FINISHED |
| Object | 16 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: 16 colors | Statement: [Video Graphics Array, maxColorsAtMaxResolution, 16 colors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maxColorsAtMaxResolution Context triple: [Video Graphics Array, maxColorsAtMaxResolution, 16 colors]
-
A.
maxColorsOnScreen
chosen
Indicates the maximum number of distinct colors that can be displayed on the screen at the same time.
-
B.
maximumResolution
Indicates the highest level of detail or fineness at which something (such as an image, display, or measurement) can be represented or processed.
-
C.
hasNumberOfColors
Indicates the quantity of distinct colors associated with an entity.
-
D.
maximumBrightness
Indicates the highest level of brightness that an entity can reach or exhibit.
-
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_69f63016cc1481908862c906df769a43 |
completed | May 2, 2026, 5:10 p.m. |
| PD | Predicate disambiguation | batch_69f62c1921008190a62675a31f66a875 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 2:03 p.m.