Triple

T1556822
Position Surface form Disambiguated ID Type / Status
Subject Taro Kono E33223 entity
Predicate familyName P18 FINISHED
Object Kono E33223 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: Kono | Statement: [Taro Kono, familyName, Kono]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kono
Context triple: [Taro Kono, familyName, Kono]
  • A. Kono chosen
    Kono is a Japanese surname most prominently associated with politician Taro Kono, a leading figure in contemporary Japanese politics.
  • B. Kuni
    Kuni is the Japanese noble family name of Empress Kōjun, consort of Emperor Shōwa (Hirohito) and mother of Emperor Emeritus Akihito.
  • C. Kyojin
    Kyojin is the popular nickname of the Yomiuri Giants, one of Japan’s most historic and successful professional baseball teams.
  • D. Kanuma
    Kanuma is a regional harvest festival celebrated mainly in Andhra Pradesh and Telangana as part of the multi-day Makar Sankranti festivities, focusing on cattle worship and agricultural prosperity.
  • E. Kunis
    Kunis is the surname of actress Mila Kunis, a Ukrainian-born American performer known for roles in "That '70s Show," "Black Swan," and as the voice of Meg Griffin on "Family Guy."
  • 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_69a885ef9cf48190b0af0f5ce3d02231 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a908704d208190937af41c6454df4e completed March 5, 2026, 4:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad370e10248190b060a0209b979ef9 completed March 8, 2026, 8:45 a.m.
Created at: March 4, 2026, 7:27 p.m.