Triple

T13156229
Position Surface form Disambiguated ID Type / Status
Subject Paula Wagner E312597 entity
Predicate hasCollaborator P10645 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: [Paula Wagner, hasCollaborator, Sydney Pollack]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sydney Pollack
Context triple: [Paula Wagner, hasCollaborator, 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c06ccb881909390df18e1a6f7ed completed April 10, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f70a2a3f2881909af3e146ee24062d completed May 3, 2026, 8:41 a.m.
Created at: April 9, 2026, 9:12 p.m.