Triple

T16148110
Position Surface form Disambiguated ID Type / Status
Subject Why Women Kill E391838 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: [Why Women Kill, executiveProducer, Michael Hanel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Hanel
Context triple: [Why Women Kill, 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. Tony Hoffer
    Tony Hoffer is an American record producer and mixer known for his work with artists such as Beck, M83, and The Kooks, shaping distinctive indie and alternative rock sounds.
  • D. Eric Marienthal
    Eric Marienthal is an American contemporary jazz saxophonist known for his work in jazz fusion and smooth jazz, including prominent collaborations with leading artists and bands.
  • E. Michael Haussman
    Michael Haussman is an American director and filmmaker best known for his work on high-profile music videos and commercials.
  • 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_69d87f1c65e48190aa2b4c472e9bafc4 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21d9551e081908391061b092ff31b completed April 17, 2026, 11:46 a.m.
Created at: April 10, 2026, 5:01 a.m.