Triple

T11121620
Position Surface form Disambiguated ID Type / Status
Subject Lenny (1974 film) E263029 entity
Predicate producer P490 FINISHED
Object Marvin Worth E294798 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: Marvin Worth | Statement: [Lenny (1974 film), producer, Marvin Worth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marvin Worth
Context triple: [Lenny (1974 film), producer, Marvin Worth]
  • A. Marvin Worth chosen
    Marvin Worth was an American film and television producer and screenwriter best known for biographical projects such as the Muhammad Ali film "The Greatest" and the Lenny Bruce biopic "Lenny."
  • B. Henry Minsky
    Henry Minsky is the son of artificial intelligence pioneer Marvin Minsky and is known as a software engineer and technologist.
  • C. Ralph Guggenheim
    Ralph Guggenheim is an American film producer best known for his work at Pixar, where he helped pioneer computer-animated feature filmmaking.
  • D. Nathan Straus
    Nathan Straus was a German-born American merchant and philanthropist best known as a co-owner of Macy’s and for pioneering public milk pasteurization programs to combat disease.
  • E. Arthur Richman
    Arthur Richman was an American playwright and screenwriter best known for his stage works that were adapted into successful films during the early 20th century.
  • 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_69d6aa9b46cc8190b19f9f0cc45bf322 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79afa0ab88190ab6d61df8cf485ec completed April 9, 2026, 12:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69e42d8406988190837a16d7ad8048d1 completed April 19, 2026, 1:19 a.m.
Created at: April 8, 2026, 9:28 p.m.