Triple

T16256830
Position Surface form Disambiguated ID Type / Status
Subject Betty Joan Perske E394650 entity
Predicate father P120 FINISHED
Object William Perske E422747 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: William Perske | Statement: [Betty Joan Perske, father, William Perske]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: William Perske
Context triple: [Betty Joan Perske, father, William Perske]
  • A. William Perske chosen
    William Perske was the father of acclaimed American actress Lauren Bacall, born Betty Joan Perske.
  • B. William Perlberg
    William Perlberg was a prominent American film producer active during Hollywood's studio era, known for overseeing a range of successful comedies and dramas.
  • C. Michael Peyser
    Michael Peyser is an American film and television producer known for his work on a variety of studio and independent projects.
  • D. Joseph Weishaar
    Joseph Weishaar is an American architect and designer best known for winning the competition to create the National World War I Memorial in Washington, D.C.
  • E. Lester Persky
    Lester Persky was an American film and television producer known for backing notable projects in Hollywood and independent cinema.
  • 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_69d87f221d8081909b0b2063e7528ba2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2459b1624819086bf681075097235 completed April 17, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012ec5c99c819082f154267c246e92 completed May 11, 2026, 1:20 a.m.
Created at: April 10, 2026, 5:04 a.m.