Triple

T20178314
Position Surface form Disambiguated ID Type / Status
Subject Goosebumps (TV series) E492656 entity
Predicate executiveProducer P7225 FINISHED
Object Debra Forte 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: Debra Forte | Statement: [Goosebumps (TV series), executiveProducer, Debra Forte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Debra Forte
Context triple: [Goosebumps (TV series), executiveProducer, Debra Forte]
  • A. Deborah Forte chosen
    Deborah Forte is an American film and television producer best known for developing and producing family and fantasy franchises such as Goosebumps and The Golden Compass.
  • B. Debra Humphries
    Debra Humphries is the mother of former NBA player Kris Humphries.
  • C. Debra Frisch
    Debra Frisch is an American former psychology professor and blogger best known for a high-profile online harassment case involving a political commentator.
  • D. Debra Newell
    Debra Newell is an interior designer whose real-life relationship with conman John Meehan inspired the true-crime podcast and TV series "Dirty John."
  • E. Debra Christofferson
    Debra Christofferson is an American actress best known for her role as the bearded lady Lila in the HBO television series "Carnivàle."
  • 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_69da6268a034819081cbd9ea5a1c9475 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e668ed07c8819091bd9ffda237a91c completed April 20, 2026, 5:57 p.m.
Created at: April 11, 2026, 11:36 p.m.