Triple

T11864950
Position Surface form Disambiguated ID Type / Status
Subject Child Support Act 1991 E282256 entity
Predicate enforcementMechanismsInclude P79850 FINISHED
Object deductions from earnings 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: deductions from earnings | Statement: [Child Support Act 1991, enforcementMechanismsInclude, deductions from earnings]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: enforcementMechanismsInclude
Context triple: [Child Support Act 1991, enforcementMechanismsInclude, deductions from earnings]
  • A. enforcement
    Indicates the act of compelling compliance with rules, laws, or agreements through monitoring, pressure, or sanctions.
  • B. enforcementModel chosen
    Indicates the method or framework by which rules, policies, or constraints are applied, monitored, and enforced within a system or interaction.
  • C. supervisionMechanism
    Indicates that one entity oversees, monitors, or regulates the actions or behavior of another through a defined control or guidance process.
  • D. enforcementStrength
    Indicates the degree or intensity with which rules, laws, or policies are applied and enforced in a given context.
  • E. enforcedOn
    Indicates that a rule, policy, or constraint is applied with authority to a particular target or subject.
  • 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_69d6ab2945d081908a5851c916cbcfb5 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a73883508190a78b5f4ba4a220df completed April 10, 2026, 7:31 a.m.
PD Predicate disambiguation batch_69d8a2589f0c8190ad82ff11acabae93 completed April 10, 2026, 7:10 a.m.
Created at: April 8, 2026, 9:43 p.m.