Triple

T4366249
Position Surface form Disambiguated ID Type / Status
Subject Katerina Mikhailovna Maslova E98778 entity
Predicate characterDevelopmentFocus P20798 FINISHED
Object conscience and forgiveness 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: conscience and forgiveness | Statement: [Katerina Mikhailovna Maslova, characterDevelopmentFocus, conscience and forgiveness]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: characterDevelopmentFocus
Context triple: [Katerina Mikhailovna Maslova, characterDevelopmentFocus, conscience and forgiveness]
  • A. developmentCharacter
    Indicates a relationship where one entity contributes to or influences the growth, formation, or evolution of another entity’s characteristics or qualities.
  • B. characterArc chosen
    Indicates the developmental journey or transformation a character undergoes over the course of a narrative.
  • C. characterArcElement
    Indicates that one element is a component or stage within a character’s overall developmental arc or transformation.
  • D. character1
    Indicates that the subject is identified as the first or primary character in a narrative or context.
  • E. protagonistCharacteristic
    Indicates that a characteristic, trait, or defining quality is attributed to the protagonist in a narrative or scenario.
  • 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_69b3454c772081908e20173e379e8ebe completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35200263081909bb326a4d7a8db99 completed March 12, 2026, 11:53 p.m.
PD Predicate disambiguation batch_69b34f53e3cc8190bf5d4dbe2413bf65 completed March 12, 2026, 11:42 p.m.
Created at: March 12, 2026, 11:17 p.m.