Triple
T35101359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leda and the Swan |
E1013025
|
entity |
| Predicate | hasParentageTheme |
P180532
|
FINISHED |
| Object | divine paternity |
—
|
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: divine paternity | Statement: [Leda and the Swan, hasParentageTheme, divine paternity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParentageTheme Context triple: [Leda and the Swan, hasParentageTheme, divine paternity]
-
A.
hasThemeRelationship
Indicates a relationship where one entity is thematically related to, or centered around, another entity as its main subject or topic.
-
B.
hasFamilyTheme
Indicates that something involves, centers on, or prominently features themes related to family relationships or family life.
-
C.
hasThemeType
Indicates that something is associated with or characterized by a particular thematic category or type.
-
D.
hasAncestorDescendantTheme
chosen
Indicates a thematic relationship where one element is treated as an ancestor and another as its descendant, emphasizing lineage, heritage, or generational connection between them.
-
E.
usesThemeFrom
Indicates that one work incorporates, references, or is based on the thematic material of another work.
- 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_69f76dd556248190808b4c4f43debebb |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ffb1f0b03c81909ddb81f07ce74e88 |
completed | May 9, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69ffb1662b2481908582e0612744f4c5 |
completed | May 9, 2026, 10:12 p.m. |
Created at: May 3, 2026, 4:01 p.m.