Triple

T18813021
Position Surface form Disambiguated ID Type / Status
Subject Francis Lederer E460063 entity
Predicate spouse P13 FINISHED
Object Margo Lederer NE NERFINISHED

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: Margo Lederer | Statement: [Francis Lederer, spouse, Margo Lederer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margo Lederer
Context triple: [Francis Lederer, spouse, Margo Lederer]
  • A. Margo Lederer chosen
    Margo Lederer is an individual whose primary public identity is under the name Margo, with limited widely known biographical or professional information available.
  • B. Margo Klewans
    Margo Klewans is a film producer best known for her work on the comedy-drama movie "The Great Buck Howard."
  • C. Edie Wasserman
    Edie Wasserman was a prominent Hollywood philanthropist and influential figure in the entertainment community, known for her extensive charitable work and social leadership.
  • D. Margo Albert
    Margo Albert is an individual whose primary public reference is by the name Margo Albert, though further widely known biographical or professional details are not clearly established.
  • E. Marla Frumkin
    Marla Frumkin is an American voice actress best known for portraying Velma Dinkley in the Scooby-Doo animated franchise.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d398c7d4819091cb2f7e48948aeb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5a3de2f6881908a9da4d5abd7ee61 completed April 20, 2026, 3:56 a.m.
Created at: April 10, 2026, 11:53 a.m.