Triple

T33091384
Position Surface form Disambiguated ID Type / Status
Subject Niue High Court E846790 entity
Predicate canApplyLawOf P90195 FINISHED
Object New Zealand NE NERFINISHED

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: New Zealand | Statement: [Niue High Court, canApplyLawOf, New Zealand]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: canApplyLawOf
Context triple: [Niue High Court, canApplyLawOf, New Zealand]
  • A. appliesLawThrough
    Indicates that one entity enforces, implements, or carries out a law or legal rule by means of another entity or mechanism.
  • B. linearLawAppliesTo
    Indicates that a specific linear law or linear relationship is applicable to, or governs, the referenced entity or situation.
  • C. usesLawTo
    Indicates that one entity applies or relies on a specific law as a means or tool to affect, regulate, or influence another entity or situation.
  • D. legalCodeAppliesTo chosen
    Indicates that a particular legal code or statute is applicable to, or governs, a specified subject, situation, or entity.
  • E. appliesToFieldOfLaw
    Indicates that something is relevant or applicable to a particular field or branch of law.
  • 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_69f3495590dc8190aa04f3dec74ce976 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d6a6b04c8190bee4cf9c00665ef7 completed May 3, 2026, 5:01 a.m.
PD Predicate disambiguation batch_69f6d27120988190aacec621cf2bf0e8 completed May 3, 2026, 4:43 a.m.
Created at: May 1, 2026, 1:26 a.m.