Triple

T32582735
Position Surface form Disambiguated ID Type / Status
Subject Grand Cross of the Order of Leopold E832832 entity
Predicate hasOrderDivision P195361 FINISHED
Object civil division 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: civil division | Statement: [Grand Cross of the Order of Leopold, hasOrderDivision, civil division]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasOrderDivision
Context triple: [Grand Cross of the Order of Leopold, hasOrderDivision, civil division]
  • A. hasOrder
    Indicates that one entity possesses, is associated with, or is characterized by a specific order, sequence, or arrangement relative to others.
  • B. hasDivisionCode
    Indicates that an entity is associated with a specific division identifier or code within an organizational or classification structure.
  • C. hasDivisionRule
    Indicates that one entity is governed, organized, or separated according to a specified rule or method of division defined by another entity.
  • D. containsDivision
    Indicates that one entity includes or encompasses a subdivision or internal division of another entity.
  • E. hasShowDivision
    Indicates that one entity is divided into or organized by another entity for the purpose of presenting or structuring a show or performance.
  • 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_69f349289adc81909f4374a58ec35a39 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69fdbc5ef46c8190bbcfb9798f4615b7 completed May 8, 2026, 10:35 a.m.
PD Predicate disambiguation batch_69fdbb270338819082ce3f73903e884f completed May 8, 2026, 10:29 a.m.
PDg Predicate description generation batch_69fdbc5da9988190b95234bce4cc2062 completed May 8, 2026, 10:35 a.m.
Created at: May 1, 2026, 1:04 a.m.