Triple

T13394333
Position Surface form Disambiguated ID Type / Status
Subject Warren Stevens E319659 entity
Predicate name P16 FINISHED
Object Warren Stevens E319659 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: Warren Stevens | Statement: [Warren Stevens, name, Warren Stevens]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warren Stevens
Context triple: [Warren Stevens, name, Warren Stevens]
  • A. Warren Stevens chosen
    Warren Stevens was an American character actor best known for his roles in mid-20th-century film and television, including notable appearances in science fiction and crime dramas.
  • B. David Stevens
    David Stevens was an Australian screenwriter and director best known for co-writing the acclaimed film "Breaker Morant" and his work in film, television, and theatre.
  • C. Don Stevens
    Don Stevens is a notable individual recognized for achievements significant enough to be distinguished from others sharing the surname Stevens.
  • D. Gowan Stevens
    Gowan Stevens is a central character in William Faulkner’s novel "Sanctuary," known for his role in the story’s tragic and morally complex events.
  • E. Roger Stevens
    Roger Stevens was a prominent British civil servant and diplomat who notably served as the first Vice-Chancellor of the University of Leeds.
  • 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_69d806b943cc8190b6af624d385d7e12 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dba0d892d08190b1b192b93fe3d72d completed April 12, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7306fb8348190a325a07a1ac858fd completed May 3, 2026, 11:24 a.m.
Created at: April 9, 2026, 9:34 p.m.