Triple

T13537491
Position Surface form Disambiguated ID Type / Status
Subject Army Wives E323298 entity
Predicate executiveProducer P7225 FINISHED
Object Deborah Spera E1085314 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: Deborah Spera | Statement: [Army Wives, executiveProducer, Deborah Spera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Deborah Spera
Context triple: [Army Wives, executiveProducer, Deborah Spera]
  • A. Deborah Spera chosen
    Deborah Spera is a television producer and executive known for her work on series such as "Reaper" and other scripted dramas.
  • B. Deborah Pines
    Deborah Pines is an American physician and writer best known as the wife of journalist and author Tony Schwartz.
  • C. Deborah Kaplan
    Deborah Kaplan is an American screenwriter and film director best known for co-writing and co-directing teen comedies such as "Can't Hardly Wait."
  • D. Deborah Korman
    Deborah Korman is the wife of the late American comedic actor Harvey Korman, known for his work on The Carol Burnett Show and in Mel Brooks films.
  • E. Deborah Oppenheimer
    Deborah Oppenheimer is an American television producer best known for her work on popular sitcoms and for winning an Academy Award for the documentary "Into the Arms of Strangers: Stories of the Kindertransport."
  • 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_69d8076776248190bdf0d4fa1f85a5fc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafbe39948190808062d4eff91841 completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6471ba348190a0cd1745daff6114 completed May 8, 2026, 4:20 a.m.
Created at: April 9, 2026, 9:45 p.m.