Triple

T10752071
Position Surface form Disambiguated ID Type / Status
Subject Nurse Betty E253594 entity
Predicate producer P490 FINISHED
Object Gail Mutrux E287173 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: Gail Mutrux | Statement: [Nurse Betty, producer, Gail Mutrux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gail Mutrux
Context triple: [Nurse Betty, producer, Gail Mutrux]
  • A. Gail Mutrux chosen
    Gail Mutrux is an American film producer known for her work on acclaimed dramas such as "News of the World" and "Donnie Brasco."
  • B. Alison Schapker
    Alison Schapker is an American television writer and producer known for her work on series such as Alias, Lost, Fringe, and The Flash.
  • C. Dr. Susan Lewis
    Dr. Susan Lewis is a central emergency physician character on the long-running medical drama series "ER," known for her compassionate care and complex personal storylines.
  • D. Marcia Strassman
    Marcia Strassman was an American actress best known for her roles in the sitcom "Welcome Back, Kotter" and the "Honey, I Shrunk the Kids" film series.
  • E. Peggy Eisenhauer
    Peggy Eisenhauer is a renowned American lighting designer known for her acclaimed work on Broadway productions and collaborations with top theater artists.
  • 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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d71dc184d0819085f8bc4edb034377 completed April 9, 2026, 3:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb0a03a1481908edb933b1613a027 completed April 14, 2026, 9:24 p.m.
Created at: April 8, 2026, 9:15 p.m.