Triple
T444210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Art of Painting |
E10180
|
entity |
| Predicate | perspectiveTechnique |
P3047
|
FINISHED |
| Object | linear perspective with deep interior space |
—
|
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: linear perspective with deep interior space | Statement: [The Art of Painting, perspectiveTechnique, linear perspective with deep interior space]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: perspectiveTechnique Context triple: [The Art of Painting, perspectiveTechnique, linear perspective with deep interior space]
-
A.
perspectiveOf
Indicates that something is expressed, depicted, or understood from the viewpoint or standpoint of a particular entity.
-
B.
observingTechnique
Indicates the method or procedure used to carry out an observation.
-
C.
hasFieldOfView
Indicates that one entity possesses a visual coverage area within which it can perceive or detect other entities or regions.
-
D.
filmingTechnique
Indicates the specific method or style used to capture visual content during the filming process.
-
E.
hasTechnique
chosen
Indicates that an entity employs, utilizes, or is associated with a particular method, procedure, or technique.
- 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.