Triple

T10567131
Position Surface form Disambiguated ID Type / Status
Subject Kentarō E249378 entity
Predicate scriptFormExample P20268 FINISHED
Object ケンタロウ E249378 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: ケンタロウ | Statement: [Kentarō, scriptFormExample, ケンタロウ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ケンタロウ
Context triple: [Kentarō, scriptFormExample, ケンタロウ]
  • A. Kentarō chosen
    Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
  • B. Kenjirō
    Kenjirō is a Japanese masculine given name that can be written with various kanji combinations and is borne by multiple notable individuals in fields such as sports, arts, and entertainment.
  • C. Shintaro
    Shintaro is a Japanese given name commonly used for males and borne by various notable figures in sports, entertainment, and politics.
  • D. Shinpei
    Shinpei is a Japanese given name commonly used for males and borne by various notable figures in politics, arts, and entertainment.
  • E. Keisuke
    Keisuke is a Japanese given name commonly used for males and borne by numerous notable figures in fields such as sports, entertainment, and politics.
  • 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_69d381c8bd708190acf3d275c908251e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d5280da8bc8190a2a7c90dbc17ea70 completed April 7, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3c7b89a808190af9b2d4f37ad9012 completed April 18, 2026, 6:04 p.m.
Created at: April 6, 2026, 12:36 p.m.