Triple

T13354005
Position Surface form Disambiguated ID Type / Status
Subject Jobs E318140 entity
Predicate editedBy P1954 FINISHED
Object Robert Komatsu E59783 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: Robert Komatsu | Statement: [Jobs, editedBy, Robert Komatsu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Robert Komatsu
Context triple: [Jobs, editedBy, Robert Komatsu]
  • A. Robert Komatsu chosen
    Robert Komatsu is a film and television editor known for his work on projects such as the 2013 biographical drama "Jobs."
  • B. Hiroshi Kikuchi
    Hiroshi Kikuchi was a prominent Japanese author and editor, best known as the founder of the major publishing company Bungeishunjū and the creator of the Akutagawa and Naoki literary prizes.
  • C. Gunichi Mikawa
    Gunichi Mikawa was an admiral in the Imperial Japanese Navy during World War II, best known for leading Japanese cruiser forces in several major Pacific naval engagements.
  • D. Kazuyuki Matsushita
    Kazuyuki Matsushita is a Japanese designer best known for creating the iconic International Fountain at Seattle Center.
  • E. Toshio Fukuda
    Toshio Fukuda is a Japanese media executive best known for his leadership role at Nippon Television Network, one of Japan’s major commercial broadcasters.
  • 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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99e8d520881908aa23c7102b72b72 completed April 11, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f71f49e5548190b14d09daea628e6b completed May 3, 2026, 10:11 a.m.
Created at: April 9, 2026, 9:32 p.m.