Triple

T12839699
Position Surface form Disambiguated ID Type / Status
Subject Shuji Nakamura E307015 entity
Predicate sharesNobelPrizeWith P1859 FINISHED
Object Hiroshi Amano E59837 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: Hiroshi Amano | Statement: [Shuji Nakamura, sharesNobelPrizeWith, Hiroshi Amano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hiroshi Amano
Context triple: [Shuji Nakamura, sharesNobelPrizeWith, Hiroshi Amano]
  • A. Hiroshi Amano chosen
    Hiroshi Amano is a Japanese physicist and Nobel laureate renowned for his pioneering work on blue light-emitting diodes (LEDs) and semiconductor technology.
  • B. Norio Miyaura
    Norio Miyaura is a Japanese chemist renowned for co-developing the Suzuki–Miyaura cross-coupling reaction, a pivotal method in organic synthesis.
  • C. Shogo Akiyama
    Shogo Akiyama is a Japanese professional baseball outfielder known for his standout career in Nippon Professional Baseball and later stint in Major League Baseball.
  • D. Noboru Kawazoe
    Noboru Kawazoe was a Japanese architect and critic closely associated with the Metabolism movement, contributing to its theoretical foundations and promotion.
  • E. Masanobu Takayanagi
    Masanobu Takayanagi is a Japanese cinematographer known for his work on acclaimed films such as Silver Linings Playbook, Spotlight, and Warrior.
  • 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_69d7bdf52b94819096d6f0ba4ab50a98 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96ff11b4481909fb2f92c46186853 completed April 10, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68edd30e881909062e8f91f614990 completed May 2, 2026, 11:55 p.m.
Created at: April 9, 2026, 5:35 p.m.