Triple

T13696032
Position Surface form Disambiguated ID Type / Status
Subject Cats & Dogs E328386 entity
Predicate producer P490 FINISHED
Object Andrew Lazar E582331 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: Andrew Lazar | Statement: [Cats & Dogs, producer, Andrew Lazar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Andrew Lazar
Context triple: [Cats & Dogs, producer, Andrew Lazar]
  • A. Andrew Lazar chosen
    Andrew Lazar is an American film producer known for his work on movies such as "Get Smart" and other major studio comedies and dramas.
  • B. Edward Zorinsky
    Edward Zorinsky was a U.S. Senator from Nebraska and former mayor of Omaha known for his moderate Democratic politics and service in the late 20th century.
  • C. George Kozmetsky
    George Kozmetsky was an American technology entrepreneur, investor, and educator best known as a co-founder of Teledyne and a major figure in fostering innovation and high-tech industry growth.
  • D. Alexander Beilinson
    Alexander Beilinson is a prominent mathematician known for his foundational contributions to algebraic geometry, representation theory, and the theory of motives, including the formulation of the Beilinson conjectures.
  • E. Lazar Wolf
    Lazar Wolf is the wealthy village butcher and would-be suitor to Tevye’s daughter in the musical and film "Fiddler on the Roof."
  • 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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc8773f388190b2413b1e05fd5fd7 completed April 12, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7b063661481908da569084c20f37c completed May 3, 2026, 8:30 p.m.
Created at: April 9, 2026, 9:54 p.m.