Triple
T35010002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President Dick Richardson |
E1009916
|
entity |
| Predicate | moralAlignmentInLore |
P22459
|
FINISHED |
| Object | 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: evil | Statement: [President Dick Richardson, moralAlignmentInLore, evil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralAlignmentInLore Context triple: [President Dick Richardson, moralAlignmentInLore, evil]
-
A.
characterAlignment
chosen
Indicates the moral or ethical stance a character holds, typically along axes such as good–evil and lawful–chaotic.
-
B.
hasMoralArchetype
Indicates that an entity exemplifies or is characterized by a particular moral pattern, role, or ethical archetype.
-
C.
speciesAlignment
Indicates how closely related or compatible two species are in terms of traits, behavior, or evolutionary relationship.
-
D.
isMoralFoilFor
Indicates that one entity serves as a contrasting counterpart whose differing moral qualities highlight or emphasize the moral traits of another entity.
-
E.
primaryRaceAlignment
Indicates how an entity’s main racial identity or classification is aligned, categorized, or associated within a defined racial framework or system.
- 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_69f76dcc3ac8819096a3ed52f5fa2523 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78ce78b508190955848e133398dc8 |
completed | May 3, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69f78b8f4cc08190b49fccd798cb25d7 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:01 p.m.