Triple

T895304
Position Surface form Disambiguated ID Type / Status
Subject Kakuei Tanaka E19330 entity
Predicate givenName P17 FINISHED
Object Kakuei E19330 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: Kakuei | Statement: [Kakuei Tanaka, givenName, Kakuei]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kakuei
Context triple: [Kakuei Tanaka, givenName, Kakuei]
  • A. Kume Kunitake
    Kume Kunitake was a Meiji-era Japanese scholar, historian, and statesman best known for documenting the Iwakura Mission’s journey and for his influential writings on Japan’s modernization.
  • B. Andō Rikichi
    Andō Rikichi was a Japanese military officer and colonial administrator who served in prominent leadership roles in Taiwan during the period of Japanese rule.
  • C. Koji Sato
    Koji Sato is a Japanese automotive executive who serves as the president and CEO of Toyota Motor Corporation.
  • D. Kakuei Tanaka chosen
    Kakuei Tanaka was a powerful and controversial Japanese prime minister and political kingmaker who dominated postwar politics through his influence within the Liberal Democratic Party.
  • E. Ishizuka Eizō
    Ishizuka Eizō was a Japanese colonial administrator who served as a high-ranking official in Taiwan during the period of Japanese rule.
  • 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_69a4939d37188190848be3d426ebc9ae completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ad23d6e88190a2fb5e1e168a7b44 completed March 1, 2026, 9:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad0e56e7fc8190a81cbd97e20fd0e6 completed March 8, 2026, 5:51 a.m.
Created at: March 1, 2026, 7:39 p.m.