Triple

T23295717
Position Surface form Disambiguated ID Type / Status
Subject Malibu Country E590162 entity
Predicate executiveProducer P7225 FINISHED
Object Michael Hanel 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: Michael Hanel | Statement: [Malibu Country, executiveProducer, Michael Hanel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Hanel
Context triple: [Malibu Country, executiveProducer, Michael Hanel]
  • A. Michael Hanel chosen
    Michael Hanel is a television producer best known for his executive production work on the sitcom "The War at Home."
  • B. Michael Healey
    Michael Healey is a Canadian playwright and actor best known for his acclaimed play "The Drawer Boy" and his contributions to contemporary Canadian theatre.
  • C. Michael Haney
    Michael Haney is a fictional character who serves as the main protagonist in the 1960 comedy film "Who Was That Lady?".
  • D. Michael Elkins
    Michael Elkins was a screenwriter known for his work on the 1960 biblical epic film "Esther and the King."
  • E. Michael Bille
    Michael Bille was a notable member of the Danish Bille noble family, recognized for his role and status within this historically influential lineage.
  • 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_69e25d1af9d88190a0b9b5e8fa608618 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f196cec9e88190b83cfd53a6455e0f completed April 29, 2026, 5:27 a.m.
Created at: April 17, 2026, 5:03 p.m.