Triple

T190901
Position Surface form Disambiguated ID Type / Status
Subject Omar Sharif E3718 entity
Predicate fullName P16 FINISHED
Object Omar Sharif E3718 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: Omar Sharif | Statement: [Omar Sharif, fullName, Omar Sharif]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Omar Sharif
Context triple: [Omar Sharif, fullName, Omar Sharif]
  • A. Omar Sharif chosen
    Omar Sharif was an acclaimed Egyptian actor known internationally for his roles in classic films such as "Lawrence of Arabia" and "Doctor Zhivago."
  • B. Laurence Olivier
    Laurence Olivier was a renowned 20th-century English actor and director, widely regarded as one of the greatest performers in the history of stage and screen.
  • C. Robert Shaw
    Robert Shaw was a British actor and writer best known for his intense, commanding performances in films such as "Jaws," "From Russia with Love," and "The Sting."
  • D. Gregory Peck
    Gregory Peck was an acclaimed American actor renowned for his dignified, morally upright roles in classic films such as "To Kill a Mockingbird."
  • E. Tyrone Power
    Tyrone Power was a popular American film and stage actor of the 1930s–1950s, best known for his swashbuckling and romantic leading roles in Hollywood classics such as "The Mark of Zorro" and "Blood and Sand."
  • 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_69a2548debd48190ae3a06d6e65b53c6 completed Feb. 28, 2026, 2:35 a.m.
NER Named-entity recognition batch_69a25964fc5c8190bd3e37daaf695ecf completed Feb. 28, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69a305e64a9081908f147299826d5ae9 completed Feb. 28, 2026, 3:12 p.m.
Created at: Feb. 28, 2026, 2:41 a.m.