Triple

T17802617
Position Surface form Disambiguated ID Type / Status
Subject Francesca Gardner Margulies E444470 entity
Predicate spouse P13 FINISHED
Object Paul Margulies E347434 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: Paul Margulies | Statement: [Francesca Gardner Margulies, spouse, Paul Margulies]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul Margulies
Context triple: [Francesca Gardner Margulies, spouse, Paul Margulies]
  • A. Paul Margulies chosen
    Paul Margulies was an American advertising executive and writer, best known as the father of actress Julianna Margulies.
  • B. David Margulies
    David Margulies was an American character actor known for his roles in films such as Ghostbusters and numerous appearances on stage and television.
  • C. Stan Margulies
    Stan Margulies was an American film and television producer known for his work on projects such as the classic 1971 musical fantasy film "Willy Wonka & the Chocolate Factory."
  • D. Phillip Margulies
    Phillip Margulies is a film and television producer and screenwriter known for his work on projects such as the movie "The Siege."
  • E. Alfred Margulies
    Alfred Margulies is an American psychiatrist and author known for his work on the narrative and ethical dimensions of clinical practice.
  • 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_69d8b9efe370819095cd219b143ae727 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4880171608190be2088c7a387bfb7 completed April 19, 2026, 7:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a030c5557788190bfd7b9af6d8d3035 completed May 12, 2026, 11:17 a.m.
Created at: April 10, 2026, 10:13 a.m.