Triple

T4082889
Position Surface form Disambiguated ID Type / Status
Subject Mr. Bernstein E87518 entity
Predicate portrayedBy P1507 FINISHED
Object Everett Sloane E152539 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: Everett Sloane | Statement: [Mr. Bernstein, portrayedBy, Everett Sloane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Everett Sloane
Context triple: [Mr. Bernstein, portrayedBy, Everett Sloane]
  • A. Everett Sloane chosen
    Everett Sloane was an American character actor of stage, film, radio, and television, best known for his collaborations with Orson Welles and roles in classic films of the 1940s and 1950s.
  • B. Leonard Franklin Slye
    Leonard Franklin Slye, better known as Roy Rogers, was a hugely popular American singing cowboy actor and musician who became a Western film and television icon in the mid-20th century.
  • C. Clifford Garvin
    Clifford Garvin was an American business executive best known as a former chairman and CEO of Exxon who helped shape U.S. corporate policy through his role in founding the Business Roundtable.
  • D. Gene Milford
    Gene Milford was an American film editor known for his work on numerous classic Hollywood films across several decades.
  • E. Ellsworth Hoagland
    Ellsworth Hoagland was an American film editor known for his work on numerous Hollywood productions in the mid-20th century.
  • 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_69aed9435cf48190ad1da737c962d19d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefc7933b481909bb3e02c6c04c8ee completed March 9, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b757a4c48190bf72c6852b00777f completed March 14, 2026, 7:30 p.m.
Created at: March 9, 2026, 3:39 p.m.