Triple

T17533206
Position Surface form Disambiguated ID Type / Status
Subject Koizumi Kyoko E426989 entity
Predicate name P16 FINISHED
Object Koizumi Kyoko 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: Koizumi Kyoko | Statement: [Koizumi Kyoko, name, Koizumi Kyoko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Koizumi Kyoko
Context triple: [Koizumi Kyoko, name, Koizumi Kyoko]
  • A. Koizumi Kyoko chosen
    Koizumi Kyoko is a prominent Japanese singer and actress who rose to fame in the 1980s as an idol and later became acclaimed for her versatile film and television roles.
  • B. Koizumi Hanayo
    Koizumi Hanayo is a shy, rice-loving first-year student and idol-in-training from the multimedia project Love Live! School Idol Project, where she is a member of the school idol group μ's.
  • C. Kawashima Kiko
    Kawashima Kiko, better known as Princess Kiko, is a member of the Japanese imperial family and the wife of Crown Prince Fumihito (Prince Akishino).
  • D. Koyama Mihoko
    Koyama Mihoko is a Japanese philanthropist and art collector best known as the founder and patron of the Miho Museum in Shiga Prefecture, Japan.
  • E. Kodama Yōko
    Kodama Yōko is a Japanese individual notable enough to be recognized as a prominent bearer of the surname Kodama.
  • 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_69d889de677081909b22d2657b1f0292 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4536a0f588190ade91d32308897a0 completed April 19, 2026, 4 a.m.
Created at: April 10, 2026, 5:49 a.m.