Triple

T15193018
Position Surface form Disambiguated ID Type / Status
Subject Dean Torrence E363067 entity
Predicate familyName P18 FINISHED
Object Torrence E666647 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: Torrence | Statement: [Dean Torrence, familyName, Torrence]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Torrence
Context triple: [Dean Torrence, familyName, Torrence]
  • A. Torrence chosen
    Torrence is a Scottish surname most notably associated with silent film and early Hollywood character actor Ernest Torrence.
  • B. Torry
    Torry is a surname most notably associated with American comedian and actor Joe Torry.
  • C. Tucker
    Tucker is the criminal defendant whose custodial interrogation and subsequent appeal led to the U.S. Supreme Court decision in Michigan v. Tucker, which clarified the scope of Miranda-related protections.
  • D. Tucker
    Tucker is a surname most notably associated with Albert W. Tucker, a Canadian-American mathematician and game theorist known for his contributions to topology and the formalization of the prisoner's dilemma.
  • E. Tucker
    Tucker is a paranormal investigator character from the Insidious horror film series, known for his tech-based ghost-hunting work alongside his partner Specs.
  • 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_69d85a09a39c81908759f23268e2d408 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0067eb710819085211fd05d5fa5f0 completed April 15, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec8995bb08190bd7f0be0a0fcf1e7 completed May 9, 2026, 5:39 a.m.
Created at: April 10, 2026, 3:10 a.m.