Triple
T1972900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Piazza della Rotonda |
E42840
|
entity |
| Predicate | hasBuildingTypeAround |
P13155
|
FINISHED |
| Object | palazzi |
—
|
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: palazzi | Statement: [Piazza della Rotonda, hasBuildingTypeAround, palazzi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBuildingTypeAround Context triple: [Piazza della Rotonda, hasBuildingTypeAround, palazzi]
-
A.
containsBuilding
Indicates that one location or area includes a building within its boundaries.
-
B.
hasNearbyLandUse
Indicates that one land area is located close to another area characterized by a specific type of land use.
-
C.
hasBuildingHeightType
Indicates the classification or type used to characterize the height of a building in the relationship.
-
D.
hasSurroundings
chosen
Indicates that an entity is located within or encircled by a particular environment, context, or set of surrounding elements.
-
E.
hasNearbySquare
Indicates that one entity has at least one square-shaped entity located close to it in space.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3f477988190b0165fc46b1cccfd |
completed | March 7, 2026, 5:13 a.m. |
| PD | Predicate disambiguation | batch_69abaff7d4a48190ab0d51aefb1c4e31 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.