Triple

T11622966
Position Surface form Disambiguated ID Type / Status
Subject Tadahiko Mizuno E276185 entity
Predicate familyName P18 FINISHED
Object Mizuno E756826 NE 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: Mizuno | Statement: [Tadahiko Mizuno, familyName, Mizuno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mizuno
Context triple: [Tadahiko Mizuno, familyName, Mizuno]
  • A. Mizuno chosen
    Mizuno is a Japanese sports equipment and sportswear company known for producing high-quality gear and apparel for a wide range of sports.
  • B. Onitsuka Tiger
    Onitsuka Tiger is a Japanese athletic footwear and apparel brand known for its retro-styled sneakers and as the predecessor to the modern ASICS corporation.
  • C. Yonex
    Yonex is a Japanese sports equipment manufacturer best known for its high-quality badminton, tennis, and golf products used by many professional athletes.
  • D. Slazenger
    Slazenger is a British sports equipment brand best known for its long-standing association with tennis and other racket sports.
  • E. Babolat
    Babolat is a French sports equipment company best known for its high-performance tennis racquets and strings used by many top professional players.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d6aafa51148190ab84940694c00235 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a122a3708190ab6513dad4c4fde7 completed April 10, 2026, 7:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee8762586481909a4b563c827487e0 completed April 26, 2026, 9:45 p.m.
Created at: April 8, 2026, 9:39 p.m.