Triple

T14509313
Position Surface form Disambiguated ID Type / Status
Subject Totally Under Control E340353 entity
Predicate screenwriter P2831 FINISHED
Object Suzanne Hillinger E1124303 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: Suzanne Hillinger | Statement: [Totally Under Control, screenwriter, Suzanne Hillinger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suzanne Hillinger
Context triple: [Totally Under Control, screenwriter, Suzanne Hillinger]
  • A. Suzanne Hillinger chosen
    Suzanne Hillinger is a documentary filmmaker best known for co-directing the political documentary "Totally Under Control" about the U.S. response to the COVID-19 pandemic.
  • B. Suzanne Zimmer
    Suzanne Zimmer is the wife of renowned film composer Hans Zimmer and the mother of several of his children.
  • C. Suzanne Verdal
    Suzanne Verdal is a Canadian woman best known as the real-life muse who inspired Leonard Cohen’s song “Suzanne.”
  • D. Suzanne Hahn
    Suzanne Hahn is known as the first wife of American actor John Astin, with whom she was married in the mid-20th century.
  • E. Suzanne Mulkern
    Suzanne Mulkern is known for being the first wife of Apple co-founder Steve Wozniak.
  • 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_69d822d9c0408190b9a2b3643e58bb4d completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69de94e5b7b48190878be271840c265b completed April 14, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f21a97c819082b59b343ef337ec completed May 9, 2026, 4:21 p.m.
Created at: April 10, 2026, 1:21 a.m.