Triple
T26133599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Museum Bank Indonesia |
E659315
|
entity |
| Predicate | occupiesBuildingPreviouslyUsedBy |
P58676
|
FINISHED |
| Object | Bank Indonesia |
—
|
NE NERFINISHED |
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: Bank Indonesia | Statement: [Museum Bank Indonesia, occupiesBuildingPreviouslyUsedBy, Bank Indonesia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupiesBuildingPreviouslyUsedBy Context triple: [Museum Bank Indonesia, occupiesBuildingPreviouslyUsedBy, Bank Indonesia]
-
A.
occupiesFormerBuilding
chosen
Indicates that one entity is currently using or located in a building that was previously used or occupied by another entity.
-
B.
previousBuildingUse
Indicates that a building previously served a specified use or function before its current one.
-
C.
formerOccupant
Indicates that an entity previously occupied a position, role, or place but no longer does so.
-
D.
hasFormerBuilding
Indicates that an entity previously occupied or used a different building, which is identified as its former building.
-
E.
laterOccupant
Indicates that one entity occupied or held a position in a place or role after another entity had previously done so.
- 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_69ee5bc3c20c8190bf2cf272f4170e95 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f62d89b89c8190afb372a8172111e7 |
completed | May 2, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69f62c1379f08190836c3e02b0c892df |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 26, 2026, 8:16 p.m.