Triple

T11214409
Position Surface form Disambiguated ID Type / Status
Subject John Uhler Lemmon III E265395 entity
Predicate spouse P13 FINISHED
Object Cynthia Stone E306644 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: Cynthia Stone | Statement: [John Uhler Lemmon III, spouse, Cynthia Stone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cynthia Stone
Context triple: [John Uhler Lemmon III, spouse, Cynthia Stone]
  • A. Cynthia Stone chosen
    Cynthia Stone was an American actress best known for her work in early television and for her marriage to actor Jack Lemmon.
  • B. Cynthia Stevenson
    Cynthia Stevenson is an American actress known for her work in film and television, including roles in projects like "Home for the Holidays" and the series "Dead Like Me."
  • C. Cynthia Blaise
    Cynthia Blaise is an American dialect coach and actress known for her work on films such as "Bad Teacher" and "The Tiger Hunter."
  • D. Cynthia Potter
    Cynthia Potter is a fictional character appearing in the classic 1938 Mickey Rooney film "Love Finds Andy Hardy."
  • E. Cynthia Solomon
    Cynthia Solomon is a pioneering computer scientist and educator best known for her foundational work in the development of educational programming languages for children, including co-creating Logo.
  • 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_69d6aac59460819089b9848b27f57848 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8d7f47c8190b78c640ff1a01943 completed April 9, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3cf630a8819094455fc45a815b83 completed May 8, 2026, 1:31 a.m.
Created at: April 8, 2026, 9:30 p.m.