Triple
T16773902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angra Mainyu |
E407672
|
entity |
| Predicate | moralTeachingFunction |
P25343
|
FINISHED |
| Object | serves as warning against evil choices |
—
|
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: serves as warning against evil choices | Statement: [Angra Mainyu, moralTeachingFunction, serves as warning against evil choices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralTeachingFunction Context triple: [Angra Mainyu, moralTeachingFunction, serves as warning against evil choices]
-
A.
moralTheme
chosen
Indicates that a work, event, or situation embodies or conveys a particular ethical lesson, value, or moral principle.
-
B.
moralInfluenceOnCharacter
Indicates that one entity exerts a moral influence that shapes, guides, or alters the character or ethical disposition of another entity.
-
C.
derivesMoralityFrom
Indicates that one entity bases or grounds its moral principles, judgments, or ethical framework on another entity.
-
D.
moralCriterion
Indicates that something is being evaluated or classified according to a standard of moral judgment or ethical rightness.
-
E.
moralConcept
Indicates that one entity represents or embodies a moral or ethical concept in relation to another.
- 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_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. |
Created at: April 10, 2026, 5:22 a.m.