Triple

T10201173
Position Surface form Disambiguated ID Type / Status
Subject Crimes of the Future (2022 film) E238882 entity
Predicate character P662 FINISHED
Object Saul Tenser E847399 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: Saul Tenser | Statement: [Crimes of the Future (2022 film), character, Saul Tenser]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saul Tenser
Context triple: [Crimes of the Future (2022 film), character, Saul Tenser]
  • A. Saul Tenser chosen
    Saul Tenser is the performance-artist protagonist of David Cronenberg’s 2022 body-horror film "Crimes of the Future," known for publicly showcasing the surgical removal of his continually mutating internal organs.
  • B. Qohen Leth
    Qohen Leth is a reclusive, existentially tormented computer genius who serves as the protagonist of Terry Gilliam’s dystopian science fiction film "The Zero Theorem."
  • C. Ranon Ufgood
    Ranon Ufgood is a character from the fantasy film "Willow," known as one of Willow Ufgood's children in the Nelwyn village.
  • D. Herb Tarlek
    Herb Tarlek is a loud, tacky-suited, and comically inept advertising salesman character from the WKRP in Cincinnati television franchise.
  • E. Samuel Lord
    Samuel Lord was a 19th-century English-born American merchant best known for establishing the iconic New York department store Lord & Taylor.
  • 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_69ca84e1ea088190b38162e43d4cfa8f completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdee40cb7481908a1bf4d5636eb8ef completed April 2, 2026, 4:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69d32afa75ec8190bbaf2e69b4ee24f1 completed April 6, 2026, 3:39 a.m.
Created at: March 30, 2026, 9:14 p.m.