Triple

T18470110
Position Surface form Disambiguated ID Type / Status
Subject UK Bribery Act 2010 E451272 entity
Predicate maximumPenaltyForOrganisations P131773 FINISHED
Object unlimited fine 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: unlimited fine | Statement: [UK Bribery Act 2010, maximumPenaltyForOrganisations, unlimited fine]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: maximumPenaltyForOrganisations
Context triple: [UK Bribery Act 2010, maximumPenaltyForOrganisations, unlimited fine]
  • A. maximumPenaltySection1
    Indicates the legal provision that specifies the highest penalty allowed under section 1 of a statute or regulation.
  • B. defaultPenalty
    Indicates that a standard or automatically applied penalty is imposed in the absence of a specific or overridden penalty.
  • C. penaltyPoints
    Indicates that a certain number of negative points or demerits are assigned to an entity as a consequence of a rule violation, error, or infraction.
  • D. penaltyRules
    Indicates the rules or conditions under which penalties are defined, applied, or enforced in a given context.
  • E. penaltyMechanism
    Indicates a relationship where a rule, system, or process imposes a negative consequence or sanction in response to certain actions or conditions.
  • F. None of above. chosen

Provenance (4 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_69d8d38465a0819099b9b42d2a662ac1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5305e349c8190925166bc3dddb320 completed April 19, 2026, 7:43 p.m.
PD Predicate disambiguation batch_69e469d05cf4819099baf1665a9cf18a completed April 19, 2026, 5:36 a.m.
PDg Predicate description generation batch_69e46d2aa72c8190a40854a7a52081e2 completed April 19, 2026, 5:50 a.m.
Created at: April 10, 2026, 11:34 a.m.