Triple

T35261778
Position Surface form Disambiguated ID Type / Status
Subject Nomad-Tan Ru E1018386 entity
Predicate moralityModel P54211 FINISHED
Object binary evaluation of perfection vs. imperfection 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: binary evaluation of perfection vs. imperfection | Statement: [Nomad-Tan Ru, moralityModel, binary evaluation of perfection vs. imperfection]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: moralityModel
Context triple: [Nomad-Tan Ru, moralityModel, binary evaluation of perfection vs. imperfection]
  • A. derivesMoralityFrom
    Indicates that one entity bases or grounds its moral principles, judgments, or ethical framework on another entity.
  • B. moralCriterion chosen
    Indicates that something is being evaluated or classified according to a standard of moral judgment or ethical rightness.
  • C. moralBelief
    Indicates that an agent holds a normative judgment about what is right, wrong, good, or bad in a given context.
  • D. moralTrajectory
    Indicates the direction and pattern of change in an entity’s moral behavior or ethical stance over time.
  • E. moralAttitude
    Indicates a subject’s evaluative stance or judgment about the moral rightness or wrongness of another entity, action, or situation.
  • 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_69f76de4be5c8190a51705c07612cac8 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78f6f99f8819083a6cde4e47f8e1d completed May 3, 2026, 6:09 p.m.
PD Predicate disambiguation batch_69f78e2f52e08190a77661223a96c601 completed May 3, 2026, 6:04 p.m.
Created at: May 3, 2026, 4:02 p.m.