Triple

T15947404
Position Surface form Disambiguated ID Type / Status
Subject William Steinkamp E386719 entity
Predicate hasCollaboratedWith P8554 FINISHED
Object Sydney Pollack E152438 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: Sydney Pollack | Statement: [William Steinkamp, hasCollaboratedWith, Sydney Pollack]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sydney Pollack
Context triple: [William Steinkamp, hasCollaboratedWith, Sydney Pollack]
  • A. Sydney Pollack chosen
    Sydney Pollack was an American film director, producer, and actor known for acclaimed movies such as "Out of Africa," "Tootsie," and "The Firm."
  • B. Arthur Hiller
    Arthur Hiller was a Canadian-born film director best known for popular Hollywood movies such as "Love Story" and "The In-Laws."
  • C. Michael Cimino
    Michael Cimino is an American actor best known for starring as Victor Salazar in the Hulu/Disney+ teen drama series "Love, Victor."
  • D. Michael Cimino
    Michael Cimino was an American film director and screenwriter best known for his ambitious, visually striking dramas and his Oscar-winning work on the Vietnam War epic "The Deer Hunter."
  • E. Barry Levinson
    Barry Levinson is an American filmmaker and screenwriter best known for directing acclaimed films such as "Rain Man," "Diner," and "Good Morning, Vietnam."
  • 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_69d86da882448190a82ea962fe343b79 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156d2fda8819085279d2a0f8a02ab completed April 16, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffbe76df6481909f8246099faa377a completed May 9, 2026, 11:08 p.m.
Created at: April 10, 2026, 4:53 a.m.