Triple

T14151312
Position Surface form Disambiguated ID Type / Status
Subject Yohei Kono E350687 entity
Predicate child P120 FINISHED
Object Taro Kono E32470 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: Taro Kono | Statement: [Yohei Kono, child, Taro Kono]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taro Kono
Context triple: [Yohei Kono, child, Taro Kono]
  • A. Taro Kono chosen
    Taro Kono is a prominent Japanese politician and Liberal Democratic Party member known for serving in key cabinet posts such as foreign minister and defense minister and for his reformist, media-savvy profile.
  • B. Takao Kato
    Takao Kato is a Japanese automotive executive who has served as president and chief executive officer of Mitsubishi Motors Corporation.
  • C. Makoto Satō
    Makoto Satō is a Japanese actor known for his roles in mid-20th-century cinema and television.
  • D. Ryoichi Hatayama
    Ryoichi Hatayama is a Jaeger pilot in the Pacific Rim universe, known for co-piloting the Mark-6 Jaeger Guardian Bravo against kaiju threats.
  • E. Takeo
    Takeo is a Japanese given name commonly used for males and borne by various notable figures in fields such as politics, business, and the arts.
  • 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_69d8278775fc8190b0802d22ca2f495d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6124e23481909e5132a40a1d8624 completed April 14, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a2fdd7c8190b2ebf5a18c8039f2 completed May 8, 2026, 5:52 a.m.
Created at: April 10, 2026, 12:57 a.m.