Triple

T4173098
Position Surface form Disambiguated ID Type / Status
Subject Shigeru Umebayashi E86409 entity
Predicate name P16 FINISHED
Object Shigeru Umebayashi E86409 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: Shigeru Umebayashi | Statement: [Shigeru Umebayashi, name, Shigeru Umebayashi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shigeru Umebayashi
Context triple: [Shigeru Umebayashi, name, Shigeru Umebayashi]
  • A. Shigeru Umebayashi chosen
    Shigeru Umebayashi is a Japanese composer best known internationally for his evocative film scores, particularly in collaborations with directors like Wong Kar-wai and Zhang Yimou.
  • B. Iwao Matsuda
    Iwao Matsuda was an Imperial Japanese Army general who led Japanese forces during World War II, notably in the Pacific campaigns.
  • C. Hideo Ohno
    Hideo Ohno is a Japanese physicist renowned for his pioneering work in spintronics and semiconductor physics.
  • D. Koichi Tanaka
    Koichi Tanaka is a Japanese engineer and Nobel Prize–winning chemist renowned for his pioneering work in mass spectrometry, particularly soft laser desorption ionization.
  • E. Hideo Oguni
    Hideo Oguni was a prominent Japanese screenwriter best known for his collaborations with director Akira Kurosawa on several classic films.
  • 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_69aed93de98c8190ad838ce507b77c8a completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af02e65b548190be095df62091b960 completed March 9, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69bec336e95881908c18b304b6d92411 completed March 21, 2026, 4:11 p.m.
Created at: March 9, 2026, 3:45 p.m.