Triple

T11009729
Position Surface form Disambiguated ID Type / Status
Subject Help! (film) E260215 entity
Predicate writer P1360 FINISHED
Object Marc Behm E399160 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: Marc Behm | Statement: [Help! (film), writer, Marc Behm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marc Behm
Context triple: [Help! (film), writer, Marc Behm]
  • A. Marc Behm chosen
    Marc Behm was an American novelist and screenwriter best known for his work on suspenseful, offbeat stories, including the screenplay for the classic film "Charade."
  • B. Christian Specht
    Christian Specht is a German politician who serves as the mayor of the city of Mannheim.
  • C. Richard Lohse
    Richard Lohse was a Swiss painter and graphic designer known for his influential role in concrete art and systematic, geometric abstraction in the 20th century.
  • D. Michael Beckmann
    Michael Beckmann is a composer and musician known for creating film scores, including the soundtrack for the romantic comedy "Love, Rosie."
  • E. Daniel von Bargen
    Daniel von Bargen was an American character actor known for his authoritative and often villainous roles in film and television, including appearances in projects like "The General’s Daughter," "Seinfeld," and "Malcolm in the Middle."
  • 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_69d6aa9687448190b28d353b1b6a610e completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79788d44c819084f35693ed96f422 completed April 9, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4419a91b08190a55c7f874a3df0fe completed April 19, 2026, 2:44 a.m.
Created at: April 8, 2026, 9:25 p.m.