Triple

T23538342
Position Surface form Disambiguated ID Type / Status
Subject Ann Harada E577668 entity
Predicate name P16 FINISHED
Object Ann Harada 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: Ann Harada | Statement: [Ann Harada, name, Ann Harada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ann Harada
Context triple: [Ann Harada, name, Ann Harada]
  • A. Ann Harada chosen
    Ann Harada is an American actress and singer best known for her comedic and character roles on Broadway and in television, including her work in musical theater and sketch comedy.
  • B. Ayumi Nakamura
    Ayumi Nakamura is a Japanese rock singer and songwriter known for her powerful vocals and energetic performances since the 1980s.
  • C. Adele Yoshioka
    Adele Yoshioka is an actress best known for her role in the 1973 Clint Eastwood crime film "Magnum Force."
  • D. Okamura Mika
    Okamura Mika is a Japanese individual notable enough to be specifically distinguished as a bearer of the surname Okamura.
  • E. Seiko Matsuda
    Seiko Matsuda is a hugely popular Japanese pop singer and idol, especially famous in the 1980s, known for her numerous hit songs and enduring influence on J-pop culture.
  • 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_69e245f9d5d08190a4a20004e1784e20 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1ae19473881909aa65f9d36744502 completed April 29, 2026, 7:07 a.m.
Created at: April 17, 2026, 6:10 p.m.