Triple

T23537260
Position Surface form Disambiguated ID Type / Status
Subject Party Cove E577632 entity
Predicate regulationConcern P31131 FINISHED
Object boating safety enforcement 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: boating safety enforcement | Statement: [Party Cove, regulationConcern, boating safety enforcement]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: regulationConcern
Context triple: [Party Cove, regulationConcern, boating safety enforcement]
  • A. regulatoryIssues chosen
    Indicates that there are regulatory concerns, non-compliance, or potential violations associated with the related entity or activity.
  • B. regulationAtIssue
    Indicates that a specific regulation is the subject of concern, dispute, or analysis in the given context.
  • C. relatedRegulation
    Indicates that there exists a regulatory rule, law, or directive that is associated with, governs, or is otherwise relevant to the referenced entity or activity.
  • D. regulationImpact
    Indicates how a regulation influences, constrains, or alters the behavior, performance, or outcomes associated with the related entities.
  • E. associatedWithRegulation
    Indicates a relationship where something is linked to, governed by, or relevant to a specific regulation or regulatory framework.
  • 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_69e245f9d5d08190a4a20004e1784e20 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1ae1831688190ac06b84729bce160 completed April 29, 2026, 7:07 a.m.
PD Predicate disambiguation batch_69f118afabd88190bd88f49597d120e8 completed April 28, 2026, 8:29 p.m.
Created at: April 17, 2026, 6:10 p.m.