Triple
T564370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vision After the Sermon |
E13521
|
entity |
| Predicate | hasColorCharacteristic |
P274
|
FINISHED |
| Object | non-naturalistic color scheme |
—
|
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: non-naturalistic color scheme | Statement: [Vision After the Sermon, hasColorCharacteristic, non-naturalistic color scheme]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasColorCharacteristic Context triple: [Vision After the Sermon, hasColorCharacteristic, non-naturalistic color scheme]
-
A.
hasColorOption
Indicates that an entity offers or supports a particular color as one of its selectable options.
-
B.
hasCharacteristic
chosen
Indicates that an entity possesses, exhibits, or is defined by a particular attribute, feature, or quality.
-
C.
hasFilmColorType
Indicates that a film is associated with a particular color process or color classification (e.g., color, black-and-white).
-
D.
hasCrossColor
Indicates that an entity possesses a cross-shaped marking or pattern of a specified color.
-
E.
hasRouteColorStandard
Indicates that a route is associated with a standardized color designation used for identification or classification.
- 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49a735b2881908293ad21ad41cdd6 |
completed | March 1, 2026, 7:58 p.m. |
| PD | Predicate disambiguation | batch_69a494c044648190a98589ab18935216 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.