Triple

T1654147
Position Surface form Disambiguated ID Type / Status
Subject Navy Ministry of Japan E35758 entity
Predicate hadMinisterialPosition P1827 FINISHED
Object Minister of the Navy 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: Minister of the Navy | Statement: [Navy Ministry of Japan, hadMinisterialPosition, Minister of the Navy]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hadMinisterialPosition
Context triple: [Navy Ministry of Japan, hadMinisterialPosition, Minister of the Navy]
  • A. hasMinister
    Indicates that one entity serves as the minister (political, religious, or administrative official) responsible for or associated with another entity.
  • B. hasMinisterialSeat
    Indicates that a governmental or administrative body holds its official ministerial seat or headquarters at a particular location.
  • C. servedInCabinetOf
    Indicates that one person held a position as a member of the governmental cabinet led by another person.
  • D. hasMinisterialPortfolios
    Indicates that a person holds one or more official ministerial roles or portfolios within a government or similar authority.
  • E. servedAs chosen
    Indicates that one entity held and performed the role, position, or function associated with another entity for some period of time.
  • 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_69a8860568888190a32cd9f70acbba42 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aaf3359ce48190803b322db8ad6027 completed March 6, 2026, 3:31 p.m.
PD Predicate disambiguation batch_69a907cff53c8190b424f088478d3e2c completed March 5, 2026, 4:34 a.m.
Created at: March 4, 2026, 7:29 p.m.