Triple

T2022227
Position Surface form Disambiguated ID Type / Status
Subject 300 E44130 entity
Predicate cinematographer P1953 FINISHED
Object Larry Fong E203698 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: Larry Fong | Statement: [300, cinematographer, Larry Fong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Larry Fong
Context triple: [300, cinematographer, Larry Fong]
  • A. Larry Fong chosen
    Larry Fong is an American cinematographer known for his visually striking work on major films such as "300," "Watchmen," and "Batman v Superman: Dawn of Justice."
  • B. Victor Wong
    Victor Wong was an American character actor known for his distinctive presence in films such as "The Last Emperor," "Big Trouble in Little China," and "Tremors."
  • C. Charles C. Tan
    Charles C. Tan was a notable benefactor and alumnus of the University of California, Berkeley, for whom the university’s chemical engineering building, Tan Hall, is named.
  • D. Alfred Chuang
    Alfred Chuang is a Chinese-American technology entrepreneur best known as the co-founder and former CEO of enterprise software company BEA Systems.
  • E. Tony Wu
    Tony Wu is a member of the technical team at xAI, the artificial intelligence company founded by Elon Musk.
  • 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_69a8891201bc8190aca837be6de41579 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb8efbe148190901d3650aa60408a completed March 7, 2026, 5:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fe88e8881909f2e64ebe23b6d1f completed March 9, 2026, 1:18 a.m.
Created at: March 4, 2026, 7:38 p.m.