Triple
T1144644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Captain Frans Banning Cocq |
E23534
|
entity |
| Predicate | paintingFeatures |
P16367
|
FINISHED |
| Object | black costume with red sash in "The Night Watch" |
—
|
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: black costume with red sash in "The Night Watch" | Statement: [Captain Frans Banning Cocq, paintingFeatures, black costume with red sash in "The Night Watch"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: paintingFeatures Context triple: [Captain Frans Banning Cocq, paintingFeatures, black costume with red sash in "The Night Watch"]
-
A.
artisticCharacteristic
chosen
Indicates that one entity possesses or exhibits a particular artistic quality, style, or trait in relation to another.
-
B.
paintedEvery
Indicates that an entity applied paint to each and every relevant item in a specified set or domain.
-
C.
artisticMedium
Indicates the material or technique used to create an artwork or artistic expression.
-
D.
artisticTechnique
Indicates the method, style, or process used to create or execute an artistic work.
-
E.
artisticDepiction
Indicates that one entity visually represents, portrays, or illustrates another in an artistic medium.
- 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_69a493ef399c8190b04b9146d2314f59 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc5008d8819095c1ffb5db5b4911 |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4d4104819084027a043c6118cb |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.