Triple

T7567317
Position Surface form Disambiguated ID Type / Status
Subject Walter Wanger E178949 entity
Predicate spouse P13 FINISHED
Object Joan Bennett E342141 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: Joan Bennett | Statement: [Walter Wanger, spouse, Joan Bennett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joan Bennett
Context triple: [Walter Wanger, spouse, Joan Bennett]
  • A. Joan Bennett chosen
    Joan Bennett was a prominent American film actress of the 1930s and 1940s, known for her transition from blonde ingenue roles to sultry film noir femme fatales under director Fritz Lang.
  • B. Dina Merrill
    Dina Merrill was an American actress, heiress, and philanthropist known for her elegant screen presence in mid-20th-century Hollywood films and television.
  • C. Evelyn Keyes
    Evelyn Keyes was an American film actress best known for her role as Suellen O'Hara in the classic 1939 film "Gone with the Wind."
  • D. Eileen Heckart
    Eileen Heckart was an American character actress known for her versatile work on stage, film, and television, including an Academy Award–winning performance in "Butterflies Are Free."
  • E. Phyllis Kirk
    Phyllis Kirk was an American actress best known for her roles in 1950s film noir and horror, including the classic 3D film "House of Wax."
  • 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_69c69f2f80288190b95cceb4da92ab2b completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f91c717881909c88901cc3b101c7 completed March 27, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c98f54f0908190afec4f26e96d8173 completed March 29, 2026, 8:45 p.m.
Created at: March 27, 2026, 3:51 p.m.