Triple

T21627632
Position Surface form Disambiguated ID Type / Status
Subject Borden Chase E533742 entity
Predicate collaboratedWith P435 FINISHED
Object Anthony Mann 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: Anthony Mann | Statement: [Borden Chase, collaboratedWith, Anthony Mann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anthony Mann
Context triple: [Borden Chase, collaboratedWith, Anthony Mann]
  • A. Anthony Mann chosen
    Anthony Mann was an American film director best known for his psychologically complex film noirs and influential 1950s Westerns.
  • B. Budd Boetticher
    Budd Boetticher was an American film director best known for his influential 1950s Westerns, particularly a series of minimalist, psychologically driven films starring Randolph Scott.
  • C. Don Siegel
    Don Siegel was an American film director best known for his taut, hard-edged action and crime dramas, including classics like "Dirty Harry" and "Invasion of the Body Snatchers."
  • D. James Nava
    James Nava is a character in the crime drama series "Shades of Blue," involved in the show's complex world of law enforcement and corruption.
  • E. Robert Benton
    Robert Benton is an American film director and screenwriter best known for his Academy Award–winning work on dramas such as "Kramer vs. Kramer."
  • 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_69e0c464fba881908d0ff2ac80511ce1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef52141e1c8190a861f4bc7cfcb490 completed April 27, 2026, 12:09 p.m.
Created at: April 16, 2026, 6:34 p.m.