Triple
T21819172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Museums Victoria |
E538676
|
entity |
| Predicate | hasTypeOfBuildingItUses |
P1267
|
FINISHED |
| Object | museum building |
—
|
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: museum building | Statement: [Museums Victoria, hasTypeOfBuildingItUses, museum building]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfBuildingItUses Context triple: [Museums Victoria, hasTypeOfBuildingItUses, museum building]
-
A.
containsBuildingType
Indicates that a location or area includes at least one building of the specified type.
-
B.
usesBuilding
chosen
Indicates that one entity makes use of, occupies, or operates within a particular building.
-
C.
appliedToBuildingType
Indicates that something (such as a rule, measure, or classification) is specifically applicable to a particular type of building.
-
D.
containsBuilding
Indicates that one location or area includes a building within its boundaries.
-
E.
intendedBuildingType
Indicates the type of building that something is planned or designed to be.
- 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_69e0c475038c8190abb9b1a20eb8ff50 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f07cce0b8081909e20ded72db40304 |
completed | April 28, 2026, 9:24 a.m. |
| PD | Predicate disambiguation | batch_69e6be815a108190be81d7c987d0c0d6 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:54 p.m.