Triple
T4322263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asian Art Museum of San Francisco |
E96545
|
entity |
| Predicate | collectionCovers |
P50441
|
FINISHED |
| Object | numerous Asian cultures |
—
|
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: numerous Asian cultures | Statement: [Asian Art Museum of San Francisco, collectionCovers, numerous Asian cultures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collectionCovers Context triple: [Asian Art Museum of San Francisco, collectionCovers, numerous Asian cultures]
-
A.
collects
Indicates that one entity gathers, accumulates, or brings together one or more other entities into its possession or control.
-
B.
notableCover
Indicates that one entity is a particularly well-known or significant cover version or adaptation of another entity.
-
C.
collectionRepository
Indicates a relationship where a repository is responsible for storing, managing, or providing access to a collection.
-
D.
collectivelyCovers
chosen
Indicates that a group of entities, taken together, fully covers or accounts for a specified set, area, or scope.
-
E.
collectionCode
Indicates the specific identifier or code assigned to the collection to which an item or resource belongs.
- 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_69b345422aac81909ddbadae437d122e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351177eb88190b89fa49a88add5e8 |
completed | March 12, 2026, 11:49 p.m. |
| PD | Predicate disambiguation | batch_69b34f4bec888190987fc2631498b637 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:12 p.m.