Triple

T19341480
Position Surface form Disambiguated ID Type / Status
Subject Advanced Quantum Mechanics E483765 entity
Predicate author P4 FINISHED
Object Jun John Sakurai NE NERFINISHED

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: Jun John Sakurai | Statement: [Advanced Quantum Mechanics, author, Jun John Sakurai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jun John Sakurai
Context triple: [Advanced Quantum Mechanics, author, Jun John Sakurai]
  • A. Jun John Sakurai chosen
    Jun John Sakurai was a prominent Japanese-American theoretical physicist renowned for his influential work in quantum mechanics and particle physics, as well as for authoring widely used graduate-level textbooks.
  • B. Hitoshi Takagi
    Hitoshi Takagi is a Japanese voice actor best known for voicing the character Totoro in Studio Ghibli’s animated film "My Neighbor Totoro."
  • C. Hitoshi Yamada
    Hitoshi Yamada is a Japanese individual notable enough to be specifically distinguished from others sharing the given name Hitoshi.
  • D. Hitoshi Sugai
    Hitoshi Sugai is a Japanese individual notable enough to be specifically distinguished from others sharing the given name Hitoshi.
  • E. Hitoshi Sato
    Hitoshi Sato is a Japanese former professional cyclist known for competing in national and international road racing events.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d244f8819080eb1f3491300db2 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e6185795bc8190a63061ca794c0d67 completed April 20, 2026, 12:13 p.m.
Created at: April 10, 2026, 1:33 p.m.