Triple
T34898353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madonna dei Fusi |
E1006503
|
entity |
| Predicate | iconographicObject |
P157603
|
FINISHED |
| Object | yarnwinder as symbol of the cross |
—
|
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: yarnwinder as symbol of the cross | Statement: [Madonna dei Fusi, iconographicObject, yarnwinder as symbol of the cross]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: iconographicObject Context triple: [Madonna dei Fusi, iconographicObject, yarnwinder as symbol of the cross]
-
A.
iconographyType
Indicates the specific kind or category of visual symbolism or imagery used to represent something.
-
B.
iconographicRepresentation
chosen
Indicates that one entity serves as a visual or symbolic depiction of another, typically in an artistic, religious, or cultural context.
-
C.
iconographyFeature
Indicates a visual element or motif that appears as a distinct feature within a work’s iconography.
-
D.
iconographicSubject
Indicates that one entity serves as the depicted subject or theme represented in the iconography of another entity.
-
E.
iconographicCategory
Indicates the classification of an entity based on the type or theme of its visual or symbolic representation.
- 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_69f76dbfe5788190ad8b64f241f470c8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78710282c81909146dc0be91e983f |
completed | May 3, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f784162134819098413482ef52042f |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4 p.m.