Triple

T3297559
Position Surface form Disambiguated ID Type / Status
Subject Empress Michiko E69251 entity
Predicate givenName P17 FINISHED
Object Michiko E4280 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: Michiko | Statement: [Empress Michiko, givenName, Michiko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michiko
Context triple: [Empress Michiko, givenName, Michiko]
  • A. Michiko chosen
    Michiko is the former Empress of Japan and the wife of Emperor Emeritus Akihito, known for being the first commoner to marry into the Japanese imperial family.
  • B. Totsuko
    Totsuko is the former abbreviated name of Tokyo Tsushin Kogyo, the Japanese company that later became Sony.
  • C. Kazuko
    Kazuko is a Japanese feminine given name commonly borne by women, including members of the imperial family.
  • D. Kumiko
    Kumiko is the introspective Japanese woman at the center of the film "Kumiko, the Treasure Hunter," whose obsession with a fictional movie treasure drives her on a quixotic journey to America.
  • E. Aiko, Princess Toshi
    Aiko, Princess Toshi is the only child of Emperor Naruhito and Empress Masako of Japan and a member of the Japanese imperial family.
  • 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_69ad859e529c8190a404273f53cb487d completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb0a2f4708190821edb9700f62d2f completed March 8, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2f3d35c448190a4ca50ae31639e65 completed March 12, 2026, 5:11 p.m.
Created at: March 8, 2026, 3:10 p.m.