Triple
T17634261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cardinal and Theological Virtues (fresco) |
E430051
|
entity |
| Predicate | languageOfIconography |
P128346
|
FINISHED |
| Object | Christian symbolism |
—
|
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: Christian symbolism | Statement: [Cardinal and Theological Virtues (fresco), languageOfIconography, Christian symbolism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfIconography Context triple: [Cardinal and Theological Virtues (fresco), languageOfIconography, Christian symbolism]
-
A.
iconographyType
Indicates the specific kind or category of visual symbolism or imagery used to represent something.
-
B.
iconographicCategory
Indicates the classification of an entity based on the type or theme of its visual or symbolic representation.
-
C.
iconographicSubject
Indicates that one entity serves as the depicted subject or theme represented in the iconography of another entity.
-
D.
iconographicForm
Indicates the specific visual or symbolic representation that an entity takes within an image or artwork.
-
E.
iconographyInfluence
Indicates that one entity’s visual symbols, motifs, or stylistic elements have shaped or informed the iconographic style or imagery of another entity.
- 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_69d889e37f308190a6aa0a69daff86c7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46ddea4688190a76a4225f268c0ac |
completed | April 19, 2026, 5:53 a.m. |
| PD | Predicate disambiguation | batch_69e3cddc87188190ac2f049b86038676 |
completed | April 18, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 5:52 a.m.