Triple
T12236153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sergei Shchukin |
E291596
|
entity |
| Predicate | artCollectionSize |
P5764
|
FINISHED |
| Object | over 200 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: over 200 paintings | Statement: [Sergei Shchukin, artCollectionSize, over 200 paintings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: artCollectionSize Context triple: [Sergei Shchukin, artCollectionSize, over 200 paintings]
-
A.
hasArtCollection
Indicates that an entity possesses, maintains, or is associated with a collection of artworks.
-
B.
estimatedNumberOfPaintings
chosen
Indicates the approximate count of paintings associated with an entity, rather than an exact, verified number.
-
C.
collectionSize
Indicates the total number of items contained within a specified collection.
-
D.
artCollectionFocus
Indicates that an art collection is primarily centered around or devoted to a particular theme, style, period, subject, or type of artwork.
-
E.
numberOfGalleries
Indicates the total count of galleries associated with or contained by a given 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d924a3973c8190a882046963b320fb |
completed | April 10, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69d91c41bcbc81909782f4e3c571b218 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:51 p.m.