Triple
T38207064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nokia E61 |
E1009228
|
entity |
| Predicate | hasDisplayColorDepth |
P30796
|
FINISHED |
| Object | 16 million 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 million colors | Statement: [Nokia E61, hasDisplayColorDepth, 16 million colors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDisplayColorDepth Context triple: [Nokia E61, hasDisplayColorDepth, 16 million colors]
-
A.
colorDepth
chosen
Indicates the bit-depth used to represent the color information of an image or display, defining how many distinct colors can be shown.
-
B.
hasColorDisplay
Indicates that an entity is equipped with a display capable of showing colors rather than only monochrome output.
-
C.
hasColorModel
Indicates that an entity uses or is associated with a particular color representation model (such as RGB, CMYK, or HSV) for defining its colors.
-
D.
graphicsCapabilities
Indicates the level or type of graphical processing features or performance that an entity supports or provides.
-
E.
hasDisplayBacklightColor
Indicates that an entity’s display uses a specific backlight color.
- 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_69f76dc94fcc8190bd2f55e81f9d6527 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ffb82be8148190a1c870d467a28c80 |
completed | May 9, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69ffb7bbd550819094052e9a0d0ae320 |
completed | May 9, 2026, 10:39 p.m. |
Created at: May 3, 2026, 4:30 p.m.