Triple
T444305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Girl Reading a Letter at an Open Window |
E10182
|
entity |
| Predicate | hasColorPalette |
P60
|
FINISHED |
| Object | muted earth tones with strong highlights |
—
|
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: muted earth tones with strong highlights | Statement: [Girl Reading a Letter at an Open Window, hasColorPalette, muted earth tones with strong highlights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasColorPalette Context triple: [Girl Reading a Letter at an Open Window, hasColorPalette, muted earth tones with strong highlights]
-
A.
colors
chosen
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
B.
hasCrossColor
Indicates that an entity possesses a cross-shaped marking or pattern of a specified color.
-
C.
hasRouteColorStandard
Indicates that a route is associated with a standardized color designation used for identification or classification.
-
D.
hasBottleColor
Indicates that an entity is associated with a bottle characterized by a specific color.
-
E.
hasFieldColor
Indicates that an entity possesses a field whose color is specified by another entity or value.
- 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_69a2e8465ef481909655c681b01e2986 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2ef459800819083cd9eef3e7b5295 |
completed | Feb. 28, 2026, 1:36 p.m. |
| PD | Predicate disambiguation | batch_69a2edde2b9c8190bd20b582eb4c5065 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.