Triple

T34672611
Position Surface form Disambiguated ID Type / Status
Subject The Squickerwonkers E890414 entity
Predicate hasMoralLessons P57332 FINISHED
Object yes 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: yes | Statement: [The Squickerwonkers, hasMoralLessons, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMoralLessons
Context triple: [The Squickerwonkers, hasMoralLessons, yes]
  • A. hasMoralMessage chosen
    Indicates that something conveys or embodies a lesson, value, or guidance about what is right or wrong behavior.
  • B. hasMoralizingFunction
    Indicates that something serves to convey, reinforce, or promote moral norms, values, or judgments within a context or interaction.
  • C. hasMoralPerspective
    Indicates that an entity holds or applies a particular moral or ethical viewpoint in evaluating actions, situations, or other entities.
  • D. hasMoralFraming
    Indicates that something is presented or interpreted in terms of moral values, judgments, or ethical considerations.
  • E. hasMoralCode
    Indicates that an entity adheres to or is guided by a set of moral principles or ethical rules.
  • 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_69f349d9c59481908b36baa0be093aea completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69fed6da0390819096b88ef4714b144e completed May 9, 2026, 6:40 a.m.
PD Predicate disambiguation batch_69fed53517d081909966f31707625f1a completed May 9, 2026, 6:33 a.m.
Created at: May 1, 2026, 2:05 a.m.