Triple

T17331989
Position Surface form Disambiguated ID Type / Status
Subject Death Wish E420837 entity
Predicate cinematographyBy P1953 FINISHED
Object Arthur Ornitz 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: Arthur Ornitz | Statement: [Death Wish, cinematographyBy, Arthur Ornitz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arthur Ornitz
Context triple: [Death Wish, cinematographyBy, Arthur Ornitz]
  • A. Arthur Ornitz chosen
    Arthur Ornitz was an American cinematographer known for his work on numerous films from the 1960s through the 1980s.
  • B. Andrew Shulkind
    Andrew Shulkind is a cinematographer known for his atmospheric and visually immersive work in genre films and television.
  • C. Roger Birnbaum
    Roger Birnbaum is an American film producer and studio executive known for co-founding Spyglass Entertainment and producing numerous mainstream Hollywood films.
  • D. Douglas Shulman
    Douglas Shulman is an American public official who served as the head of the U.S. Internal Revenue Service (IRS) during the late 2000s and early 2010s.
  • E. Frank Sachs
    Frank Sachs is a minor supporting character in the 1997 romantic comedy-drama film "As Good as It Gets."
  • 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_69d889d3adc881909319f1edb8d2a956 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e439d6870c8190989897aa6beba8ff completed April 19, 2026, 2:11 a.m.
Created at: April 10, 2026, 5:43 a.m.