Triple

T4267899
Position Surface form Disambiguated ID Type / Status
Subject Malcolm X (1992 film) E96869 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: [Malcolm X (1992 film), producer, Marvin Worth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marvin Worth
Context triple: [Malcolm X (1992 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. Charles Stillman
    Charles Stillman was an American labor leader and educator best known for helping to establish the American Federation of Teachers as a national teachers’ union.
  • E. Frederick Winsor
    Frederick Winsor was a pioneering British physician and medical officer known for his contributions to public health and military medicine in the 19th 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_69b34543f06c8190915ebb1a4574ffa9 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34fce710481909d90ed4a3d150fde completed March 12, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b79fe8c08190b4a9e4812babc78e completed March 14, 2026, 7:31 p.m.
Created at: March 12, 2026, 11:07 p.m.