Triple

T5515007
Position Surface form Disambiguated ID Type / Status
Subject The Little Foxes E144659 entity
Predicate editor P1954 FINISHED
Object Daniel Mandell E295857 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: Daniel Mandell | Statement: [The Little Foxes, editor, Daniel Mandell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Mandell
Context triple: [The Little Foxes, editor, Daniel Mandell]
  • A. Daniel Mandell chosen
    Daniel Mandell was an American film editor renowned for his work on numerous classic Hollywood films and for winning multiple Academy Awards for Best Film Editing.
  • B. Steven Baigelman
    Steven Baigelman is an American screenwriter and producer known for his work on biographical and crime dramas in film and television.
  • C. Dan Mindel
    Dan Mindel is a British cinematographer known for his work on major blockbuster films, including entries in the Star Trek and Star Wars franchises.
  • D. Daniel Melnick
    Daniel Melnick was an American film and television producer known for overseeing influential movies such as “Network,” “All That Jazz,” and “Altered States.”
  • E. Johnny Gandelsman
    Johnny Gandelsman is a Grammy-winning violinist and producer known for his work with ensembles like Brooklyn Rider and the Silk Road Ensemble, as well as for his innovative solo projects.
  • 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_69c008f77ff88190b0cd50ca207295d1 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f5b4e988190b590b4157cf089c1 completed March 22, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04cc0735881909b7ea6909570a750 completed March 22, 2026, 8:10 p.m.
Created at: March 22, 2026, 3:33 p.m.