Triple
T3163986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Barnes Foundation |
E66165
|
entity |
| Predicate | collectionSizeApproximate |
P20367
|
FINISHED |
| Object | over 4000 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: over 4000 objects | Statement: [The Barnes Foundation, collectionSizeApproximate, over 4000 objects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collectionSizeApproximate Context triple: [The Barnes Foundation, collectionSizeApproximate, over 4000 objects]
-
A.
collectionSize
Indicates the total number of items contained within a specified collection.
-
B.
hasApproximateMemberCount
chosen
Indicates that an entity is associated with a group or collection for which only an estimated or non-exact number of members is known.
-
C.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
D.
userCount
Indicates the number of users associated with or involved in a given context or entity.
-
E.
numberOfMembersReturned
Indicates the quantity of members that are provided or yielded as a result of an operation or query.
- 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_69ad85850c1481908a9e9c6242238de2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada61ba98881909106951c8ceeb959 |
completed | March 8, 2026, 4:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9dfe0a948190928f2201d671c654 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:06 p.m.