Triple

T3081500
Position Surface form Disambiguated ID Type / Status
Subject Jotaro Kawakami E64266 entity
Predicate givenName P17 FINISHED
Object Jotaro E64266 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: Jotaro | Statement: [Jotaro Kawakami, givenName, Jotaro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jotaro
Context triple: [Jotaro Kawakami, givenName, Jotaro]
  • A. Jotaro Kawakami chosen
    Jotaro Kawakami was a prominent Japanese socialist politician who served as a leading figure in the Japan Socialist Party during the mid-20th century.
  • B. Kiyoshi Katsuki
    Kiyoshi Katsuki was an Imperial Japanese Army general who played a leading role in Japan’s early Second Sino-Japanese War campaigns, including high-level command during the Battle of Shanghai in 1937.
  • C. Gojo
    Gojo is a small city in Japan’s Nara Prefecture known for its traditional townscape and proximity to the Yoshino River.
  • D. Shizuo
    Shizuo is a Japanese masculine given name borne by several notable figures, including mathematicians and artists.
  • E. Gojo Ohashi
    Gojo Ohashi is a notable bridge in Kyoto, Japan, spanning the Kamo River and serving as an important local thoroughfare.
  • 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_69ad857bb4c88190a4cf27893fcabed8 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada1aaf6d48190af4f9106965589b0 completed March 8, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1f89443a4819091dafc560b45cc26 completed March 11, 2026, 11:19 p.m.
Created at: March 8, 2026, 3:03 p.m.