Triple
T25339014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Doors |
E635355
|
entity |
| Predicate | originalPanelsDisplayedAt |
P178251
|
FINISHED |
| Object | Museo dell’Opera del Duomo, Florence |
—
|
NE NERFINISHED |
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: Museo dell’Opera del Duomo, Florence | Statement: [South Doors, originalPanelsDisplayedAt, Museo dell’Opera del Duomo, Florence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalPanelsDisplayedAt Context triple: [South Doors, originalPanelsDisplayedAt, Museo dell’Opera del Duomo, Florence]
-
A.
numberOfPanels
Indicates the total count of distinct panels associated with or contained within a given entity.
-
B.
hasNumberOfInscribedPanels
Indicates the relationship that specifies how many inscribed panels are associated with a given entity.
-
C.
hasNumberOfPaintedPanels
Indicates the relationship specifying how many panels in an object or structure are painted.
-
D.
hasInformationPanels
Indicates that an entity is equipped with or accompanied by informational panels that provide explanatory or descriptive content.
-
E.
numberOfStainedGlassPanels
Indicates the count of stained glass panels associated with a given entity or object.
- F. None of above. chosen
Provenance (4 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_69e75a99bd6481909476115b35b9a8e4 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
| PDg | Predicate description generation | batch_69f70e854b9c8190a3416e2189e17742 |
completed | May 3, 2026, 8:59 a.m. |
Created at: April 21, 2026, 1:32 p.m.