Triple

T2605937
Position Surface form Disambiguated ID Type / Status
Subject Universal Credit E58657 entity
Predicate sanctionMechanism P18137 FINISHED
Object reduction of payment for non-compliance 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: reduction of payment for non-compliance | Statement: [Universal Credit, sanctionMechanism, reduction of payment for non-compliance]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: sanctionMechanism
Context triple: [Universal Credit, sanctionMechanism, reduction of payment for non-compliance]
  • A. sanction
    Indicates the imposition of an official penalty or restrictive measure by an authority in response to certain actions or behaviors.
  • B. typeOfSanction chosen
    Indicates the specific category or kind of sanction that is applied in a given situation.
  • C. receivedSanctionFrom
    Indicates that one entity has been subjected to a formal penalty, restriction, or disciplinary measure imposed by another entity.
  • D. canImposeSanctions
    Indicates that one entity has the authority or power to apply punitive or restrictive measures (sanctions) against another entity.
  • E. typeOfJusticeMechanism
    Indicates the kind or category of justice mechanism that characterizes how justice is pursued or administered in a given context.
  • 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_69ab4ac3523881909679750c9f8c2dec completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8def9bc8190b2e013abffc7b191 completed March 7, 2026, 7:50 a.m.
PD Predicate disambiguation batch_69abd80ab7248190ba06ba14fe4c5638 completed March 7, 2026, 7:47 a.m.
Created at: March 6, 2026, 9:49 p.m.