Triple
T9291577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L’Atelier rouge |
E223528
|
entity |
| Predicate | depictionTechnique |
P14965
|
FINISHED |
| Object | use of line to define objects within a flat color field |
—
|
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: use of line to define objects within a flat color field | Statement: [L’Atelier rouge, depictionTechnique, use of line to define objects within a flat color field]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictionTechnique Context triple: [L’Atelier rouge, depictionTechnique, use of line to define objects within a flat color field]
-
A.
artisticTechnique
chosen
Indicates the method, style, or process used to create or execute an artistic work.
-
B.
depictionType
Indicates the specific manner or style in which something is visually represented or depicted.
-
C.
artisticDepiction
Indicates that one entity visually represents, portrays, or illustrates another in an artistic medium.
-
D.
depictionDetail
Indicates that one depiction provides additional detail, refinement, or a closer view of what is shown in another depiction.
-
E.
depictionAction
Indicates an action in which one entity visually represents, illustrates, or portrays another entity.
- 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_69ca8422ddf881908a3f8f876c9f53aa |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd0866ff608190a07afac4afd0ec09 |
completed | April 1, 2026, 11:58 a.m. |
| PD | Predicate disambiguation | batch_69cc7a5aeb748190afb89c6bbd2a6d6f |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:35 p.m.