Triple
T1096540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sRGB |
E24283
|
entity |
| Predicate | colorModel |
P60
|
FINISHED |
| Object | RGB |
E24283
|
NE 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: RGB | Statement: [sRGB, colorModel, RGB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RGB Context triple: [sRGB, colorModel, RGB]
-
A.
BGR
BGR is the three-letter ISO 3166-1 alpha-3 country code assigned to Bulgaria.
-
B.
sRGB
chosen
sRGB is a standard RGB color space widely used for digital images, displays, and the web to ensure consistent color reproduction across devices.
-
C.
CYMX
CYMX is the ICAO airport code for Montréal–Mirabel International Airport, a major cargo and aerospace hub located northwest of Montreal, Quebec, Canada.
-
D.
Composition with Red, Blue and Yellow
Composition with Red, Blue and Yellow is a 1930 primary-color grid painting by Dutch De Stijl artist Piet Mondrian, exemplifying his mature abstract style of intersecting black lines and rectangular color fields.
-
E.
Red
Red is the famous nickname of Arnold "Red" Auerbach, the legendary Boston Celtics coach and executive known for his pivotal role in building an NBA dynasty.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4c3bb31881908768a909ce56a95d |
completed | March 7, 2026, 4:03 p.m. |
Created at: March 1, 2026, 7:42 p.m.