Triple

T9824150
Position Surface form Disambiguated ID Type / Status
Subject Yoshiko Morita E238610 entity
Predicate givenName P17 FINISHED
Object Yoshiko E597384 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: Yoshiko | Statement: [Yoshiko Morita, givenName, Yoshiko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yoshiko
Context triple: [Yoshiko Morita, givenName, Yoshiko]
  • A. Yoshiko chosen
    Yoshiko is a feminine Japanese given name commonly used across various generations and often associated with traditional Japanese culture.
  • B. Sachiko
    Sachiko is a Japanese feminine given name that can be written with various kanji combinations, often conveying meanings related to happiness or child.
  • C. Shigeko
    Shigeko is a Japanese feminine given name that has been borne by various notable women, including members of the imperial family.
  • D. Kazuko
    Kazuko is a Japanese feminine given name commonly borne by women, including members of the imperial family.
  • E. Chikako
    Chikako is a Japanese feminine given name that can be written with various kanji characters and is borne by several notable women in Japan.
  • 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_69ca84e0dd1881909800765d1e21f735 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb316f8948190ada3738787a5cb6a completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e519c7a88190b8776b4af4908d1f completed April 5, 2026, 10:41 p.m.
Created at: March 30, 2026, 8:31 p.m.