Triple
T5302468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ginevra de' Benci |
E120013
|
entity |
| Predicate | depictsElement |
P46781
|
FINISHED |
| Object | juniper bush background |
—
|
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: juniper bush background | Statement: [Ginevra de' Benci, depictsElement, juniper bush background]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsElement Context triple: [Ginevra de' Benci, depictsElement, juniper bush background]
-
A.
depictionElement
chosen
Indicates that one entity is an element or component that appears within the visual or representational depiction of another entity.
-
B.
depictsAttribute
Indicates that one entity visually represents or illustrates a specific attribute or characteristic of another entity.
-
C.
depicts
Indicates that one entity visually represents, portrays, or shows another entity.
-
D.
depictsClass
Indicates that one entity visually represents or portrays a particular class or category of entities.
-
E.
depictsName
Indicates that something visually represents or portrays the name of an entity.
- 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_69bd44704be88190acdb2ac481b0ff55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8e44e7c881909b241b2fec366038 |
completed | March 20, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69bd845097ac81909678624c4907fda4 |
completed | March 20, 2026, 5:30 p.m. |
Created at: March 20, 2026, 1:53 p.m.