Triple
T5786234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benin Bronzes |
E128274
|
entity |
| Predicate | collectionOrExhibitionSize |
P425
|
FINISHED |
| Object | thousands of objects |
—
|
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: thousands of objects | Statement: [Benin Bronzes, collectionOrExhibitionSize, thousands of objects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collectionOrExhibitionSize Context triple: [Benin Bronzes, collectionOrExhibitionSize, thousands of objects]
-
A.
numberOfExhibits
Indicates the total count of exhibits associated with a given entity or context.
-
B.
numberOfGalleries
Indicates the total count of galleries associated with or contained by a given entity.
-
C.
collectionSize
chosen
Indicates the total number of items contained within a specified collection.
-
D.
hasExhibitionsAbout
Indicates that one entity organizes or presents exhibitions whose subject matter concerns another entity.
-
E.
museumHolds
Indicates that a museum possesses, preserves, or has custody of a particular item or collection within its holdings.
- 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_69c0084450048190bc647b649a05136b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02a1c29d48190af36cc855bb491dd |
completed | March 22, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69c021d2cd608190b98a7e3aa7001d27 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:51 p.m.