Triple
T15146303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palazzo del Governo (Turin) |
E361816
|
entity |
| Predicate | hasInteriorUse |
P6655
|
FINISHED |
| Object | offices |
—
|
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: offices | Statement: [Palazzo del Governo (Turin), hasInteriorUse, offices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInteriorUse Context triple: [Palazzo del Governo (Turin), hasInteriorUse, offices]
-
A.
hasInteriorFeature
chosen
Indicates that an entity contains or includes a specific feature within its interior space.
-
B.
hasFloorUse
Indicates that a particular floor or level of a building is designated for a specific function, activity, or type of use.
-
C.
hasIndoorType
Indicates that an entity is associated with a specific type or category of indoor environment or indoor feature.
-
D.
hasIndoorArea
Indicates that an entity possesses or includes an area or space that is located indoors or within a building.
-
E.
hasCentralAreaUse
Indicates that an entity’s central area is used or designated for a particular function or purpose.
- 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005c825a481909d00098b0e743365 |
completed | April 15, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69deb9713fe881909dec2fd3f6c84b39 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:07 a.m.