Triple
T16774166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faravahar |
E407678
|
entity |
| Predicate | streamerSymbolism |
P124582
|
FINISHED |
| Object | choice between good and evil |
—
|
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: choice between good and evil | Statement: [Faravahar, streamerSymbolism, choice between good and evil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: streamerSymbolism Context triple: [Faravahar, streamerSymbolism, choice between good and evil]
-
A.
shapeSymbolism
Indicates how a particular shape is associated with or conveys symbolic meaning within a given context.
-
B.
symbolismFocus
Indicates that the primary emphasis of a work, element, or representation is on its symbolic meaning rather than its literal or functional aspects.
-
C.
starMeaning
Indicates that one entity represents or conveys the symbolic or interpretive significance of a star associated with another entity.
-
D.
dreamsSignified
Indicates that one entity’s dreams symbolically represent, foreshadow, or convey information about another entity or situation.
-
E.
cosmicSymbolism
Indicates a relationship where one entity symbolically represents or embodies cosmic, universal, or celestial principles in relation to another.
- F. None of above. chosen
Provenance (4 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b038d0608190be15c758427bb664 |
completed | April 18, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69e319cf691c819083e39225f5777ef0 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326bac94481908c082117553320f8 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:22 a.m.