Triple

T11994648
Position Surface form Disambiguated ID Type / Status
Subject Jerry Lewis E285497 entity
Predicate spouse P13 FINISHED
Object SanDee Pitnick E285506 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: SanDee Pitnick | Statement: [Jerry Lewis, spouse, SanDee Pitnick]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SanDee Pitnick
Context triple: [Jerry Lewis, spouse, SanDee Pitnick]
  • A. SanDee Pitnick chosen
    SanDee Pitnick is an American former dancer and actress best known as the second wife of comedian and filmmaker Jerry Lewis.
  • B. Dana DeMuth
    Dana DeMuth is a longtime Major League Baseball umpire who has officiated numerous postseason games, including multiple World Series.
  • C. Tempe Pigott
    Tempe Pigott was an English character actress known for her supporting roles in early 20th-century stage and film productions, including numerous Hollywood films of the 1930s and 1940s.
  • D. Danelle Morton
    Danelle Morton is an American journalist and author known for co-writing celebrity memoirs and nonfiction books, including collaborating with Lynne Spears.
  • E. Cindy Pickett
    Cindy Pickett is an American actress best known for her role as Ferris Bueller’s mother in the classic 1986 teen comedy film "Ferris Bueller’s Day Off."
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903b211688190bfe6dd15c3f96d2f completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f47273e1088190b899071baff1375a completed May 1, 2026, 9:29 a.m.
Created at: April 8, 2026, 9:46 p.m.