Triple

T8574659
Position Surface form Disambiguated ID Type / Status
Subject Shintaro Abe E203017 entity
Predicate givenName P17 FINISHED
Object Shintaro E201810 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: Shintaro | Statement: [Shintaro Abe, givenName, Shintaro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shintaro
Context triple: [Shintaro Abe, givenName, Shintaro]
  • A. Shintaro chosen
    Shintaro is a Japanese given name commonly used for males and borne by various notable figures in sports, entertainment, and politics.
  • B. Kentarō
    Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
  • C. Takahito
    Takahito, better known by his title Prince Mikasa, was a member of the Japanese imperial family and the youngest son of Emperor Taishō.
  • D. 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.
  • E. Shinpei
    Shinpei is a Japanese given name commonly used for males and borne by various notable figures in politics, arts, and entertainment.
  • 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_69ca8328ebe481909a8c038fa79959b4 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbea947f188190af469babaa73ddf6 completed March 31, 2026, 3:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69d065ac77c08190af1c13cce87e0991 completed April 4, 2026, 1:13 a.m.
Created at: March 30, 2026, 6:21 p.m.