Triple

T23477565
Position Surface form Disambiguated ID Type / Status
Subject Dear John E570306 entity
Predicate executiveProducer P7225 FINISHED
Object Ed. Weinberger 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: Ed. Weinberger | Statement: [Dear John, executiveProducer, Ed. Weinberger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ed. Weinberger
Context triple: [Dear John, executiveProducer, Ed. Weinberger]
  • A. Ed. Weinberger chosen
    Ed. Weinberger is an American television producer and writer best known for his work on influential sitcoms such as The Mary Tyler Moore Show, Taxi, and The Cosby Show.
  • B. Josef Weinberger
    Josef Weinberger is a music publishing company known for issuing operettas and other theatrical works, particularly in the Central European tradition.
  • C. Weinberger
    Weinberger is a music publishing company known for issuing classical works, including compositions by major Romantic-era composers.
  • D. Weinberger
    Weinberger is a German-origin surname most notably associated with Caspar Weinberger, a former U.S. Secretary of Defense.
  • E. Bob Kurland
    Bob Kurland was a pioneering American basketball center, renowned as one of the first great 7-footers and a two-time NCAA champion and Olympic gold medalist in the 1940s.
  • 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_69e245af8a88819084f2704f6d265a92 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a74dbea8819085ca84391039e7f7 completed April 29, 2026, 6:38 a.m.
Created at: April 17, 2026, 6:02 p.m.