Triple
T23310788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerrit Dou |
E590575
|
entity |
| Predicate | paintingFormat |
P13218
|
FINISHED |
| Object | small cabinet pictures |
—
|
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: small cabinet pictures | Statement: [Gerrit Dou, paintingFormat, small cabinet pictures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: paintingFormat Context triple: [Gerrit Dou, paintingFormat, small cabinet pictures]
-
A.
paintingSettingOf
Indicates that a painting depicts or provides the visual setting or background context for another entity or scene.
-
B.
paintsFor
Indicates that one entity creates paintings or artwork on behalf of, or under commission from, another entity.
-
C.
typicalPictureFormat
chosen
Indicates the standard or most commonly used picture format associated with an entity (such as a device, medium, or context).
-
D.
paints
Indicates that one entity applies paint to create, cover, or decorate another entity.
-
E.
paintingPractice
Indicates engaging in the activity of practicing or improving skills in painting.
- 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_69e25d1d32188190948eb76909d1dcc3 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1972acad08190bb56541b822555cd |
completed | April 29, 2026, 5:29 a.m. |
| PD | Predicate disambiguation | batch_69effcf8ca2c8190887d4f4656617d21 |
completed | April 28, 2026, 12:19 a.m. |
Created at: April 17, 2026, 5:06 p.m.