Triple

T29855850
Position Surface form Disambiguated ID Type / Status
Subject Kebang E758185 entity
Predicate justiceModel P40179 FINISHED
Object restorative rather than punitive 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: restorative rather than punitive | Statement: [Kebang, justiceModel, restorative rather than punitive]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: justiceModel
Context triple: [Kebang, justiceModel, restorative rather than punitive]
  • A. typeOfJusticeMechanism chosen
    Indicates the kind or category of justice mechanism that characterizes how justice is pursued or administered in a given context.
  • B. legalSystem
    Indicates the formal framework of laws, rules, and institutions that governs how legal matters are defined, interpreted, and enforced within a society or jurisdiction.
  • C. legalCase
    Indicates a relationship where a formal legal dispute or proceeding exists between parties, typically adjudicated by a court or similar authority.
  • D. hasJustice
    Indicates that an entity possesses, upholds, or embodies justice in its actions, qualities, or governing principles.
  • E. legalCaseAlongside
    Indicates that two or more legal cases are proceeding in parallel or in coordination, such that they are related or handled together in some aspect of the legal process.
  • 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_69f2245a82cc8190a387e7d0118d710b completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f6764be1fc8190a474af62f40a95a5 completed May 2, 2026, 10:10 p.m.
PD Predicate disambiguation batch_69f66ec5bf508190ad088b89455252bd completed May 2, 2026, 9:38 p.m.
Created at: April 29, 2026, 5:46 p.m.