Triple
T28227016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camille Monet in Japanese Costume |
E711615
|
entity |
| Predicate | depictsArtStyle |
P1851
|
FINISHED |
| Object | Japanese art |
—
|
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: Japanese art | Statement: [Camille Monet in Japanese Costume, depictsArtStyle, Japanese art]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsArtStyle Context triple: [Camille Monet in Japanese Costume, depictsArtStyle, Japanese art]
-
A.
artisticDepiction
Indicates that one entity visually represents, portrays, or illustrates another in an artistic medium.
-
B.
fieldOfDepiction
Indicates that one entity serves as the subject matter or thematic focus depicted within another entity, such as an image, artwork, or representation.
-
C.
depictionType
Indicates the specific manner or style in which something is visually represented or depicted.
-
D.
artisticStyle
chosen
Indicates the artistic movement, style, or aesthetic approach that characterizes how something is created or visually expressed.
-
E.
isDepictedInArtMovement
Indicates that an entity is portrayed or represented within artworks associated with a particular art movement.
- 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_69efb51dfb048190ada79b745c33b363 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 27, 2026, 10:50 p.m.