Triple
T1367186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sala Regia |
E30029
|
entity |
| Predicate | ceilingDecoration |
P8228
|
FINISHED |
| Object | stucco and gilded ornament |
—
|
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: stucco and gilded ornament | Statement: [Sala Regia, ceilingDecoration, stucco and gilded ornament]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ceilingDecoration Context triple: [Sala Regia, ceilingDecoration, stucco and gilded ornament]
-
A.
ceilingMaterial
Indicates the material from which a ceiling is constructed or finished.
-
B.
decoration
Indicates that one entity serves as an ornament or embellishing element for another entity, enhancing its appearance or style.
-
C.
decorations
chosen
Indicates that one entity adds, provides, or serves as ornamental or decorative elements for another entity.
-
D.
throneDecoration
Indicates that one entity serves as a decorative element or ornamentation for a throne associated with another entity.
-
E.
ceilingHeight
Indicates the vertical distance from the floor to the ceiling in a given 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_69a498f912008190a376a98b207b2071 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c2d33d2081908008494b5f56bf56 |
completed | March 1, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69a4befb08b88190be966fa1aadd4bcd |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:57 p.m.