Triple
T13160215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landscape at the Bois d’Amour |
E312703
|
entity |
| Predicate | color approach |
P29804
|
FINISHED |
| Object | Cloisonnist influence |
—
|
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: Cloisonnist influence | Statement: [Landscape at the Bois d’Amour, color approach, Cloisonnist influence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: color approach Context triple: [Landscape at the Bois d’Amour, color approach, Cloisonnist influence]
-
A.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
B.
colorTheory
chosen
Indicates a relationship where principles or concepts about how colors interact, combine, or affect perception are applied or referenced between entities.
-
C.
colorTreatment
Indicates that an entity has undergone a process or action that changes, enhances, or assigns its color.
-
D.
color work
Indicates that an entity applies or adds color to another entity, typically as part of a creative or finishing process.
-
E.
colorSystem
Indicates that one entity is a system or scheme used to define, organize, or represent the colors of 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_69d806ac3ee081909b2fd27d060aa974 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bbd1d088190b7c69f37fc6eeb64 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:12 p.m.