Triple

T7731752
Position Surface form Disambiguated ID Type / Status
Subject George Barnes E175275 entity
Predicate spouse P13 FINISHED
Object Evelyn Keyes E322735 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: Evelyn Keyes | Statement: [George Barnes, spouse, Evelyn Keyes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Evelyn Keyes
Context triple: [George Barnes, spouse, Evelyn Keyes]
  • A. Evelyn Keyes chosen
    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."
  • B. Linda Harrison
    Linda Harrison is an American actress best known for her role as Nova in the original "Planet of the Apes" films.
  • C. Marjorie Main
    Marjorie Main was an American character actress best known for her comedic, no-nonsense roles in classic Hollywood films, particularly as Ma Kettle in the "Ma and Pa Kettle" series.
  • D. 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.
  • E. Joan Bennett
    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.
  • 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_69c6995e912c81909a49a2657103f786 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c70336aafc819099a060950ab8922f completed March 27, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9bcbe7f488190aee034a51e8a281b completed March 29, 2026, 11:58 p.m.
Created at: March 27, 2026, 4:06 p.m.