Triple
T25999581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leda and the Swan (Correggio) |
E646581
|
entity |
| Predicate | usesMythologicalSubject |
P60508
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Leda and the Swan (Correggio), usesMythologicalSubject, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesMythologicalSubject Context triple: [Leda and the Swan (Correggio), usesMythologicalSubject, yes]
-
A.
hasMythologicalUsage
Indicates that something is used, referenced, or functions within a mythological context or tradition.
-
B.
usesMythOf
chosen
Indicates that one entity employs or invokes a myth or mythical narrative about another entity as part of its actions, explanations, or representations.
-
C.
hasMythologicalFeature
Indicates that an entity possesses a characteristic, attribute, or element derived from mythology or mythological beings.
-
D.
mythologicalCategory
Indicates that one entity is classified as belonging to the mythological type, group, or category represented by the other entity.
-
E.
mythologicalContent
Indicates that the subject contains, references, or is associated with myths, mythological narratives, or myth-based elements.
- 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_69e77e88cb8481908da31d4a00661f55 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f657f653448190a945b4751af8507d |
completed | May 2, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 22, 2026, 8:58 a.m.