Triple
T13201804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiesa di Santa Susanna |
E314258
|
entity |
| Predicate | hasFaçadeMaterial |
P16375
|
FINISHED |
| Object | travertine |
—
|
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: travertine | Statement: [Chiesa di Santa Susanna, hasFaçadeMaterial, travertine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFaçadeMaterial Context triple: [Chiesa di Santa Susanna, hasFaçadeMaterial, travertine]
-
A.
façadeType
Indicates the specific kind or style of façade that characterizes or is applied to a building or structure.
-
B.
exteriorMaterial
Indicates the material that forms the outer surface or outer construction of an object or structure.
-
C.
featuresMaterialType
Indicates that an entity is characterized by or incorporates a specific type of material.
-
D.
frontageMaterial
chosen
Indicates the material used on the exterior front-facing surface of a structure or property.
-
E.
façadeDescription
Indicates a textual description that characterizes the appearance, style, or features of a building’s façade.
- 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_69d806aee7308190b70a237ba2a6e3e1 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc6bc108190b5a6a265bf6e9fd4 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:16 p.m.