Triple
T548802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mars Being Disarmed by Venus |
E12790
|
entity |
| Predicate | paintingSurface |
P15587
|
FINISHED |
| Object | canvas |
—
|
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: canvas | Statement: [Mars Being Disarmed by Venus, paintingSurface, canvas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: paintingSurface Context triple: [Mars Being Disarmed by Venus, paintingSurface, canvas]
-
A.
paintedEvery
Indicates that an entity applied paint to each and every relevant item in a specified set or domain.
-
B.
painter
Indicates that one entity creates paintings of, or is responsible for painting, another entity.
-
C.
surfaceAccess
Indicates that one entity provides a means for another entity to reach, enter, or interact with a surface or outer layer.
-
D.
draws
Indicates that one entity creates a visual representation or image of another entity.
-
E.
estimatedNumberOfPaintings
Indicates the approximate count of paintings associated with an entity, rather than an exact, verified number.
- F. None of above. chosen
Provenance (4 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_69a49334226c81908b0ea1689ef6aa3f |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49900895c819092a131c185a758bf |
completed | March 1, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69a494bae210819093c2e0d33a8ca51a |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a49858abd48190bd4b002a93e4a908 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:32 p.m.