Triple
T11969055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quinta del Sordo |
E284867
|
entity |
| Predicate | BlackPaintingsTransferredToCanvas |
P102563
|
FINISHED |
| Object | 1874 |
—
|
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: 1874 | Statement: [Quinta del Sordo, BlackPaintingsTransferredToCanvas, 1874]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: BlackPaintingsTransferredToCanvas Context triple: [Quinta del Sordo, BlackPaintingsTransferredToCanvas, 1874]
-
A.
paintedIn
Indicates that an artwork or object was created or executed using paint within a specific time period or at a particular location.
-
B.
paintedOn
Indicates that one entity has been applied as paint onto the surface of another entity.
-
C.
paintedEvery
Indicates that an entity applied paint to each and every relevant item in a specified set or domain.
-
D.
estimatedNumberOfPaintings
Indicates the approximate count of paintings associated with an entity, rather than an exact, verified number.
-
E.
paintingPractice
Indicates engaging in the activity of practicing or improving skills in painting.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9037bee54819085242a3ef3e286f9 |
completed | April 10, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69d8bb40f30c8190a0e0719bd67542bf |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8dd0ba0f88190b7d5e358c27ca184 |
completed | April 10, 2026, 11:20 a.m. |
Created at: April 8, 2026, 9:46 p.m.