Triple
T28105923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poplars series paintings by Claude Monet |
E710361
|
entity |
| Predicate | seriesCountApproximate |
P80358
|
FINISHED |
| Object | about 24 paintings |
—
|
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: about 24 paintings | Statement: [Poplars series paintings by Claude Monet, seriesCountApproximate, about 24 paintings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seriesCountApproximate Context triple: [Poplars series paintings by Claude Monet, seriesCountApproximate, about 24 paintings]
-
A.
seriesSize
chosen
Indicates the total number of items or installments that make up a complete series.
-
B.
sectionCountApproximate
Indicates that the number of sections associated with an entity is known only approximately rather than as an exact count.
-
C.
numberOfSeries
Indicates the total count of distinct series associated with or contained within a given entity.
-
D.
articleCountApprox
Indicates that the relationship specifies an approximate number of articles associated with an entity.
-
E.
hasAlbumCountApprox
Indicates an approximate number of albums associated with an entity.
- 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_69ef9b71fdb081908b4a61cd7ff147c1 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 27, 2026, 9:08 p.m.