Triple

T6887083
Position Surface form Disambiguated ID Type / Status
Subject Marjorie Main E158948 entity
Predicate name P16 FINISHED
Object Marjorie Main E152794 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: Marjorie Main | Statement: [Marjorie Main, name, Marjorie Main]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marjorie Main
Context triple: [Marjorie Main, name, Marjorie Main]
  • A. Marjorie Main chosen
    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.
  • B. 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."
  • C. 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."
  • D. Marion Grodin
    Marion Grodin is an American stand-up comedian, writer, and actress known for her sharp wit and for being the daughter of actor and comedian Charles Grodin.
  • 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_69c688342f6c8190ad7eea6ba262db99 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d90e92488190b738676342ac6393 completed March 27, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c86822add88190909a82b9c263bb6f completed March 28, 2026, 11:45 p.m.
Created at: March 27, 2026, 2:23 p.m.