Triple
T2920309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moffat Museum |
E78703
|
entity |
| Predicate | hasTypeOfBuildingUse |
P1844
|
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: [Moffat Museum, hasTypeOfBuildingUse, museum building]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfBuildingUse Context triple: [Moffat Museum, hasTypeOfBuildingUse, museum building]
-
A.
buildingType
chosen
Indicates the specific category or function that characterizes what kind of building something is.
-
B.
landUseIncludes
Indicates that a specified land area contains or permits the specified type(s) of land use within its boundaries.
-
C.
appliesToBuildingComplex
Indicates that something (such as a rule, condition, attribute, or action) is relevant or applicable to an entire building complex rather than to individual buildings or units.
-
D.
containsBuilding
Indicates that one location or area includes a building within its boundaries.
-
E.
hasBuildingHeightType
Indicates the classification or type used to characterize the height of a building in the relationship.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97fd89d88190bc7db4b39058ae3a |
completed | March 8, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9603ddd88190b8bf91bc7517cc21 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:54 p.m.