Triple
T6727203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hieronymus Bosch |
E153545
|
entity |
| Predicate | numberOfSurvivingPaintings |
P5764
|
FINISHED |
| Object | approximately 25 |
—
|
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: approximately 25 | Statement: [Hieronymus Bosch, numberOfSurvivingPaintings, approximately 25]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSurvivingPaintings Context triple: [Hieronymus Bosch, numberOfSurvivingPaintings, approximately 25]
-
A.
estimatedNumberOfPaintings
chosen
Indicates the approximate count of paintings associated with an entity, rather than an exact, verified number.
-
B.
numberOfPaintingsCreated
Indicates the total count of paintings that an entity has created.
-
C.
numberOfPaintedSculptures
Indicates the quantity of sculptures that have been painted in a given context or collection.
-
D.
paintedIn
Indicates that an artwork or object was created or executed using paint within a specific time period or at a particular location.
-
E.
paintedEvery
Indicates that an entity applied paint to each and every relevant item in a specified set or domain.
- 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_69c6880afb988190ad88011b48ecfcba |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d354177481908ab3cf5437c095e2 |
completed | March 27, 2026, 6:58 p.m. |
| PD | Predicate disambiguation | batch_69c6d08e8a2c8190ae4e8d8c039be7ce |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:08 p.m.