Triple
T1096555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sRGB |
E24283
|
entity |
| Predicate | colorGamutRelative |
P23095
|
FINISHED |
| Object | smaller than Adobe RGB (1998) |
—
|
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: smaller than Adobe RGB (1998) | Statement: [sRGB, colorGamutRelative, smaller than Adobe RGB (1998)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorGamutRelative Context triple: [sRGB, colorGamutRelative, smaller than Adobe RGB (1998)]
-
A.
colorEncoding
Indicates how the color information of an entity is represented, formatted, or encoded.
-
B.
colorEncodingMethod
Indicates the method or scheme used to represent or encode color information.
-
C.
usesColorDifferenceSignals
Indicates that one entity employs differences in color as signals to convey information or communicate.
-
D.
hasFilmColorType
Indicates that a film is associated with a particular color process or color classification (e.g., color, black-and-white).
-
E.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
- F. None of above. chosen
Provenance (4 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b99ffb3481908cd168b6c58e1c6d |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b7448c148190a3c9a4158ebd05b4 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7da38888190a118ef20ce4ae9aa |
completed | March 1, 2026, 10:04 p.m. |
Created at: March 1, 2026, 7:42 p.m.