Triple

T5713295
Position Surface form Disambiguated ID Type / Status
Subject The Mirror Has Two Faces E125960 entity
Predicate producedBy 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: [The Mirror Has Two Faces, producedBy, Marvin Worth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marvin Worth
Context triple: [The Mirror Has Two Faces, producedBy, 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. John Merchant
    John Merchant is a music producer known for his work on the project "In the Now."
  • 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_69c0082d6fe48190b777fb383769e5c8 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c024b5205c8190aaab291a6e485ec1 completed March 22, 2026, 5:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a74b350819099d8881ef248e1e7 completed March 22, 2026, 9:09 p.m.
Created at: March 22, 2026, 3:46 p.m.