Triple
T4074982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berkeley Blue |
E86741
|
entity |
| Predicate | hasColorModel |
P52856
|
FINISHED |
| Object | RGB |
—
|
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: RGB | Statement: [Berkeley Blue, hasColorModel, RGB]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasColorModel Context triple: [Berkeley Blue, hasColorModel, RGB]
-
A.
hasColorInfo
Indicates that an entity is associated with specific color-related information or attributes.
-
B.
hasColorProcess
Indicates a relationship where an entity is associated with a specific method or process used to apply, change, or manage its color.
-
C.
hasColorRange
Indicates that an entity possesses or is associated with a specific span or set of colors, rather than a single discrete color.
-
D.
hasColorReference
Indicates that one entity serves as a reference or source for determining or specifying the color associated with another entity.
-
E.
hasColorOption
Indicates that an entity offers or supports a particular color as one of its selectable options.
- 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_69aed93ebe448190a1f1686e28740ac9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc25e2e08190b3c048e1b8f85bbf |
completed | March 9, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69aef9082c2081908474f082a49bebc8 |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aef9b34dec81909bbc3def9decc71a |
completed | March 9, 2026, 4:47 p.m. |
Created at: March 9, 2026, 3:39 p.m.