Triple
T31729253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sonnenflammen |
E809810
|
entity |
| Predicate | hasSymbolistElements |
P103297
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Sonnenflammen, hasSymbolistElements, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSymbolistElements Context triple: [Sonnenflammen, hasSymbolistElements, true]
-
A.
incorporatesSymbolismFrom
chosen
Indicates that one entity includes or integrates symbolic elements, motifs, or meanings derived from another entity.
-
B.
symbolismIn
Indicates that one entity functions as a symbol or representation within the context, meaning, or interpretive framework of another entity.
-
C.
hasSymbolicImagery
Indicates that one entity incorporates or is associated with symbolic visual elements representing ideas, concepts, or themes related to another entity.
-
D.
languageOfSymbolism
Indicates that one entity is the language in which the symbolic meaning or symbolism of another entity is expressed or encoded.
-
E.
hasSpiritualImagery
Indicates that something contains or employs imagery related to spiritual, religious, or transcendent themes.
- 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_69f348e0e4908190a884582eca646fb7 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6ab1d46a4819098cbd250564c7d85 |
completed | May 3, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69f6aa20a1588190a53533fc9764efb2 |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 11:21 p.m.