Triple

T17790072
Position Surface form Disambiguated ID Type / Status
Subject Hiroshi Satō E444134 entity
Predicate hasDiacriticVariant P457 FINISHED
Object Hiroshi Satō 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: Hiroshi Satō | Statement: [Hiroshi Satō, hasDiacriticVariant, Hiroshi Satō]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hiroshi Satō
Context triple: [Hiroshi Satō, hasDiacriticVariant, Hiroshi Satō]
  • A. Hiroshi Satō chosen
    Hiroshi Satō is a Japanese given name commonly borne by men across various professions, including business, sports, and the arts.
  • B. Akira Satō
    Akira Satō is a Japanese personal name shared by multiple notable individuals across fields such as politics, sports, and the arts.
  • C. Yasutaka Nakasone
    Yasutaka Nakasone is a Japanese politician and member of the prominent Nakasone political family.
  • D. Shigeru Satō
    Shigeru Satō is a Japanese individual notable enough to be specifically distinguished among people sharing the surname Satō.
  • E. Masakazu Nakasone
    Masakazu Nakasone is a Japanese politician who serves as the mayor of the city of Uruma in Okinawa Prefecture.
  • 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_69d8b9ef17708190bdf7e2adbf14ddc2 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4879688908190a5428b1fa7525f62 completed April 19, 2026, 7:43 a.m.
Created at: April 10, 2026, 10:13 a.m.