Triple

T18934132
Position Surface form Disambiguated ID Type / Status
Subject Michael Benaroya E463194 entity
Predicate employer P7 FINISHED
Object Benaroya Pictures 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: Benaroya Pictures | Statement: [Michael Benaroya, employer, Benaroya Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Benaroya Pictures
Context triple: [Michael Benaroya, employer, Benaroya Pictures]
  • A. Benaroya Pictures chosen
    Benaroya Pictures is an independent film production company known for financing and producing a range of critically acclaimed and commercially successful feature films.
  • B. Sycamore Pictures
    Sycamore Pictures is an American film production company known for financing and producing independent and mid-budget feature films.
  • C. Annapurna Pictures
    Annapurna Pictures is an American film production company known for backing critically acclaimed, auteur-driven movies such as "Her," "Zero Dark Thirty," and "American Hustle."
  • D. Magnolia Pictures
    Magnolia Pictures is an American independent film distribution company known for releasing a wide range of arthouse, documentary, and foreign films.
  • E. Boardwalk Pictures
    Boardwalk Pictures is a documentary-focused film and television production company known for creating acclaimed non-fiction series and features for major streaming platforms.
  • 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_69d8dcfec90481909e926be9767e5779 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d3e57e648190aa4d3b09e84d4d38 completed April 20, 2026, 7:21 a.m.
Created at: April 10, 2026, 11:59 a.m.