Triple

T20227758
Position Surface form Disambiguated ID Type / Status
Subject Privy Councillor (Japan) E495435 entity
Predicate typicalOfficeHolderBackground P9583 FINISHED
Object former cabinet minister 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: former cabinet minister | Statement: [Privy Councillor (Japan), typicalOfficeHolderBackground, former cabinet minister]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typicalOfficeHolderBackground
Context triple: [Privy Councillor (Japan), typicalOfficeHolderBackground, former cabinet minister]
  • A. officeHolderBackground
    Indicates that one entity’s background, such as prior roles, experience, or qualifications, is associated with or characterizes the office holder of another entity.
  • B. officeHoldersAreUsually chosen
    Indicates that individuals holding a particular office or position are typically or generally characterized by a specified property or role.
  • C. officeHolderTypicallyFrom
    Indicates that the person holding a particular office is typically drawn from or originates from a specified group, region, or category.
  • D. officeHolderUsually
    Indicates that an entity is the person who typically or customarily holds a particular office or position.
  • E. officeHolderOccupation
    Indicates that the occupation describes the role or job held by an office holder.
  • 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_69da626cff80819097b530718a7c98b6 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66fda9428819098467e7e8c547a07 completed April 20, 2026, 6:26 p.m.
PD Predicate disambiguation batch_69e55b18609481909ab28bc8750a642f completed April 19, 2026, 10:45 p.m.
Created at: April 11, 2026, 11:39 p.m.