Triple
T24438608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clark |
E616190
|
entity |
| Predicate | isAllegoricalCharacterIn |
P24039
|
FINISHED |
| Object | allegory of Nazi rise to power |
—
|
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: allegory of Nazi rise to power | Statement: [Clark, isAllegoricalCharacterIn, allegory of Nazi rise to power]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isAllegoricalCharacterIn Context triple: [Clark, isAllegoricalCharacterIn, allegory of Nazi rise to power]
-
A.
hasAllegoricalFigures
chosen
Indicates that a work, scene, or element includes figures that symbolically represent abstract ideas, concepts, or moral qualities.
-
B.
hasAllegoricalDepictionsBy
Indicates that one entity is represented through allegorical depictions created by another entity.
-
C.
isFictionalCharacter
Indicates that the subject is a character that exists only in fiction rather than in real life.
-
D.
allegoricalRoleInInferno
Indicates a symbolic or allegorical function that an entity fulfills within the narrative framework of Dante’s Inferno.
-
E.
symbolInFiction
Indicates that something functions as a symbolic element within a fictional work or narrative.
- 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_69e2d7ec44b081909ccaf1f3bbec0641 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f297891f108190a98e55c900494d30 |
completed | April 29, 2026, 11:43 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:16 a.m.