Triple

T19639718
Position Surface form Disambiguated ID Type / Status
Subject Nagako E471498 entity
Predicate givenName P17 FINISHED
Object Nagako 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: Nagako | Statement: [Nagako, givenName, Nagako]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nagako
Context triple: [Nagako, givenName, Nagako]
  • A. Nagako chosen
    Nagako, better known as Empress Kōjun, was the long-serving consort of Emperor Shōwa (Hirohito) and the mother of Emperor Emeritus Akihito of Japan.
  • B. Ayako
    Ayako is a Japanese feminine given name commonly used for women and girls in Japan.
  • C. Yuriko
    Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
  • D. 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.
  • E. Chiyoko
    Chiyoko is the Japanese given name of singer and actress Pat Suzuki, reflecting her Japanese heritage.
  • 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_69d8e511f28481909f4bc3ea9191e54a completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e641215df48190926b38e6502bb83e completed April 20, 2026, 3:07 p.m.
Created at: April 10, 2026, 1:44 p.m.