Triple

T22572683
Position Surface form Disambiguated ID Type / Status
Subject Aso family E558114 entity
Predicate hasNotableMember P304 FINISHED
Object Taro Aso 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: Taro Aso | Statement: [Aso family, hasNotableMember, Taro Aso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taro Aso
Context triple: [Aso family, hasNotableMember, Taro Aso]
  • A. Taro Aso chosen
    Taro Aso is a Japanese politician of the Liberal Democratic Party who has served as Prime Minister and long-time senior cabinet member, including as Deputy Prime Minister and Finance Minister.
  • B. Hulusi Akar
    Hulusi Akar is a Turkish general and politician who served as Chief of the General Staff and later as Turkey’s Minister of National Defense.
  • C. Takeo Doi
    Takeo Doi was a Japanese aeronautical engineer best known for designing several World War II fighter aircraft for the Imperial Japanese Army Air Service.
  • D. Hiroshi Satō
    Hiroshi Satō is a Japanese given name commonly borne by men across various professions, including business, sports, and the arts.
  • E. Koji Hashimoto
    Koji Hashimoto was a Japanese film director and assistant director best known for his work on the Godzilla franchise and other Toho science fiction films.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e5ae4ac8190b1f503457603d969 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15fe958e881909b58a5439f2c6a35 completed April 29, 2026, 1:33 a.m.
Created at: April 16, 2026, 8:52 p.m.