Triple

T19412095
Position Surface form Disambiguated ID Type / Status
Subject Francis Sheeran E485610 entity
Predicate hasSpouse P13 FINISHED
Object Mary Leddy 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: Mary Leddy | Statement: [Francis Sheeran, hasSpouse, Mary Leddy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary Leddy
Context triple: [Francis Sheeran, hasSpouse, Mary Leddy]
  • A. Mary Leddy chosen
    Mary Leddy was the wife of American labor union official and alleged mob hitman Frank Sheeran, whose life inspired the film "The Irishman."
  • B. Mary Grace Slattery
    Mary Grace Slattery was the first wife of American playwright Arthur Miller, whom he married before achieving his major theatrical success.
  • C. Mary Beth Johnson
    Mary Beth Johnson is known as the wife of American Western film actor Charles Starrett.
  • D. Mary Beth Hughes
    Mary Beth Hughes was an American film and television actress best known for her roles in 1940s Hollywood dramas and crime films.
  • E. Kathleen Treado
    Kathleen Treado is the longtime wife of actor Jeff Daniels, known for her low-profile life and support of his career and their shared community and theater work in Michigan.
  • 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_69d8e8d5162481909db12435d9535c1a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e62af681288190ba2ec52d5adb6a22 completed April 20, 2026, 1:32 p.m.
Created at: April 10, 2026, 1:37 p.m.