Triple
T1096577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sRGB |
E24283
|
entity |
| Predicate | colorManagementRole |
P17747
|
FINISHED |
| Object | baseline color space for non-color-managed content |
—
|
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: baseline color space for non-color-managed content | Statement: [sRGB, colorManagementRole, baseline color space for non-color-managed content]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorManagementRole Context triple: [sRGB, colorManagementRole, baseline color space for non-color-managed content]
-
A.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
B.
displayRole
chosen
Indicates the role or position an entity holds in the context of how it is presented or shown in a display.
-
C.
colorEncoding
Indicates how the color information of an entity is represented, formatted, or encoded.
-
D.
hasFilmColorType
Indicates that a film is associated with a particular color process or color classification (e.g., color, black-and-white).
-
E.
colorEncodingMethod
Indicates the method or scheme used to represent or encode color information.
- 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_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. |
Created at: March 1, 2026, 7:42 p.m.