Triple
T24045249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santo Stefano |
E595499
|
entity |
| Predicate | prisonArchitecturalType |
P4631
|
FINISHED |
| Object | panopticon-style prison |
—
|
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: panopticon-style prison | Statement: [Santo Stefano, prisonArchitecturalType, panopticon-style prison]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: prisonArchitecturalType Context triple: [Santo Stefano, prisonArchitecturalType, panopticon-style prison]
-
A.
prisonType
Indicates the specific category or classification of a prison associated with an entity.
-
B.
majorPenitentiary
Indicates that an entity serves as a primary or principal penitentiary (major prison) within a given system or jurisdiction.
-
C.
architectureType
chosen
Indicates the specific style or category of architecture that characterizes or defines an entity.
-
D.
buildingType
Indicates the specific category or function that characterizes what kind of building something is.
-
E.
prisonerType
Indicates the classification or category assigned to a prisoner within a correctional or detention system.
- 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_69e288c06a908190899cad4531f32c9a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d9c9391c819095ea6232fa872d5c |
completed | April 29, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f1764345388190a3102b62ddb729b4 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 10:13 p.m.