Triple

T22899570
Position Surface form Disambiguated ID Type / Status
Subject The Giver (2014 film) E568271 entity
Predicate cinematographyBy P1953 FINISHED
Object Ross Emery 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: Ross Emery | Statement: [The Giver (2014 film), cinematographyBy, Ross Emery]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ross Emery
Context triple: [The Giver (2014 film), cinematographyBy, Ross Emery]
  • A. Ross Emery chosen
    Ross Emery is an Australian cinematographer known for his work on genre films and large-scale visual productions, including the movie "I, Frankenstein."
  • B. Richard Emery
    Richard Emery is a bishop who has served as the ecclesiastical leader of the Episcopal Diocese of North Dakota.
  • C. Richard Emery
    Richard Emery is an American civil rights attorney and litigator known for his work on police misconduct and government accountability cases.
  • D. Michael Emery
    Michael Emery is a British archaeologist and the brother of filmmaker Martha Fiennes and actor Ralph Fiennes.
  • E. Ken Emerson
    Ken Emerson is an American music journalist and cultural historian known for his writings on popular music and its social context.
  • 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_69e2458c23ec81908fa2570692c6614f completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f180155b1c8190a83eb6ec45387a1a completed April 29, 2026, 3:50 a.m.
Created at: April 17, 2026, 3:41 p.m.