Triple

T6463639
Position Surface form Disambiguated ID Type / Status
Subject Exit Wounds E142179 entity
Predicate starring P1507 FINISHED
Object Jill Hennessy E77179 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: Jill Hennessy | Statement: [Exit Wounds, starring, Jill Hennessy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jill Hennessy
Context triple: [Exit Wounds, starring, Jill Hennessy]
  • A. Jill Hennessy chosen
    Jill Hennessy is a Canadian actress and musician best known for her leading roles on the television series Law & Order and Crossing Jordan.
  • B. Kristy McNichol
    Kristy McNichol is an American actress best known for her Emmy-winning role on the TV drama "Family" and her work in films like "Little Darlings" and "Only When I Laugh."
  • C. Tyne Daly
    Tyne Daly is an American actress acclaimed for her powerful performances in television dramas, film, and theater, including her iconic role in the series "Cagney & Lacey."
  • D. Tamara Tunie
    Tamara Tunie is an American actress and director best known for her long-running role as medical examiner Melinda Warner on the television series "Law & Order: Special Victims Unit."
  • E. Jami Gertz
    Jami Gertz is an American actress known for her roles in 1980s films and television series, including standout performances in movies like "The Lost Boys" and "Quicksilver."
  • 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_69c008d3bf4c8190bcf798c5ba9d6fb3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c069f9b58081909412b9da753b9285 completed March 22, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6e40c193c8190b4d7acd4530121f0 completed March 27, 2026, 8:09 p.m.
Created at: March 22, 2026, 4:49 p.m.