Triple
T27582116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SVGA |
E699609
|
entity |
| Predicate | maximumColorsSupported |
P30793
|
FINISHED |
| Object | 16777216 |
—
|
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: 16777216 | Statement: [SVGA, maximumColorsSupported, 16777216]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumColorsSupported Context triple: [SVGA, maximumColorsSupported, 16777216]
-
A.
maxColorsOnScreen
chosen
Indicates the maximum number of distinct colors that can be displayed on the screen at the same time.
-
B.
hasNumberOfColors
Indicates the quantity of distinct colors associated with an entity.
-
C.
colorDepth
Indicates the bit-depth used to represent the color information of an image or display, defining how many distinct colors can be shown.
-
D.
supportsColorSampling
Indicates that one entity can perform or accommodate color sampling operations on another entity or its data.
-
E.
supportsAlphaBitDepth
Indicates that one entity is capable of handling or providing image or video data with an alpha (transparency) channel at a specified bit depth.
- 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_69f6a28c7c148190bfc980aad9f678ca |
completed | May 3, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69f69fe1e3c88190830bb2e9f407357e |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 27, 2026, 2:03 p.m.