Triple

T18587798
Position Surface form Disambiguated ID Type / Status
Subject 29th Academy Awards E454282 entity
Predicate bestActorWinner P8115 FINISHED
Object Yul Brynner 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: Yul Brynner | Statement: [29th Academy Awards, bestActorWinner, Yul Brynner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yul Brynner
Context triple: [29th Academy Awards, bestActorWinner, Yul Brynner]
  • A. Yul Brynner chosen
    Yul Brynner was a Russian-born American actor best known for his charismatic, bald-headed performances in classic films and stage productions such as "The King and I."
  • B. Richard Powell
    Richard Powell is an architect best known as one of the founding partners of the acclaimed architecture firm Bohlin Cywinski Jackson.
  • C. Dan Hedaya
    Dan Hedaya is an American character actor known for his frequent portrayals of tough, often villainous or hard-edged supporting roles in film and television, including movies like "Clueless," "Blood Simple," and "The Hurricane."
  • D. Omar Sharif
    Omar Sharif was an acclaimed Egyptian actor known internationally for his roles in classic films such as "Lawrence of Arabia" and "Doctor Zhivago."
  • E. Herbert Lom
    Herbert Lom was a Czech-born British actor best known for his versatile character roles in films such as "The Pink Panther" series, "Spartacus," and numerous classic British and Hollywood productions.
  • 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_69d8d38ae7e081908a98df1251842402 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e545b2f20481908da74447cd08d5bd completed April 19, 2026, 9:14 p.m.
Created at: April 10, 2026, 11:44 a.m.