Triple
T344993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russian Museum |
E6919
|
entity |
| Predicate | hasMuseumCollectionSize |
P425
|
FINISHED |
| Object | one of the largest collections of Russian art in the world |
—
|
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: one of the largest collections of Russian art in the world | Statement: [Russian Museum, hasMuseumCollectionSize, one of the largest collections of Russian art in the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMuseumCollectionSize Context triple: [Russian Museum, hasMuseumCollectionSize, one of the largest collections of Russian art in the world]
-
A.
hasMuseumType
Indicates that an entity is classified as a museum of a specific type or category.
-
B.
numberOfExhibits
Indicates the total count of exhibits associated with a given entity or context.
-
C.
museumAt
Indicates that an entity (such as an exhibit, artifact, or event) is located at or associated with a particular museum.
-
D.
collectionSize
chosen
Indicates the total number of items contained within a specified collection.
-
E.
hasExhibits
Indicates that an entity (such as a museum, gallery, or event) displays or presents certain items, artworks, or objects as part of its collection or show.
- 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eb01261c81909280128b5ce75eff |
completed | Feb. 28, 2026, 1:17 p.m. |
| PD | Predicate disambiguation | batch_69a2e9530c98819085025efe4e04aa7e |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.