Triple

T21115301
Position Surface form Disambiguated ID Type / Status
Subject Verna Bloom E520279 entity
Predicate workedWithDirector P19638 FINISHED
Object Haskell Wexler 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: Haskell Wexler | Statement: [Verna Bloom, workedWithDirector, Haskell Wexler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haskell Wexler
Context triple: [Verna Bloom, workedWithDirector, Haskell Wexler]
  • A. Haskell Wexler chosen
    Haskell Wexler was an acclaimed American cinematographer and filmmaker known for his innovative visual style and influential work on both narrative features and political documentaries.
  • B. Boris Kaufman
    Boris Kaufman was an Academy Award–winning cinematographer known for his influential work on classic films such as "On the Waterfront."
  • C. Michael Wadleigh
    Michael Wadleigh is an American filmmaker best known for directing the landmark concert documentary film "Woodstock" (1970).
  • D. Ethan Winogrand
    Ethan Winogrand is known primarily as a son of the influential American street photographer Garry Winogrand.
  • E. Gordon Willis
    Gordon Willis was an influential American cinematographer, often called the "Prince of Darkness," renowned for his innovative use of shadow and light in films such as The Godfather series and Annie Hall.
  • 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_69e0b509a318819092fbbcb21d1fe603 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e72105bd648190beecc636284397bd completed April 21, 2026, 7:02 a.m.
Created at: April 16, 2026, 2:54 p.m.