Triple

T21210754
Position Surface form Disambiguated ID Type / Status
Subject Nancy Thompson E522711 entity
Predicate fullName P16 FINISHED
Object Nancy Thompson 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: Nancy Thompson | Statement: [Nancy Thompson, fullName, Nancy Thompson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nancy Thompson
Context triple: [Nancy Thompson, fullName, Nancy Thompson]
  • A. Nancy Thompson chosen
    Nancy Thompson is the resourceful teenage heroine of the original "A Nightmare on Elm Street" film, known for battling the dream-stalking killer Freddy Krueger.
  • B. Jacqueline Voorhees
    Jacqueline Voorhees is a wealthy, image-obsessed Manhattan socialite and main character on the comedy series "Unbreakable Kimmy Schmidt."
  • C. Tanee McCall
    Tanee McCall is an American actress and professional dancer known for her roles in film and television, including action and dance-focused projects.
  • D. Nancy Blake
    Nancy Blake is a musician known for her frequent collaborations and performances with American acoustic guitarist and folk artist Norman Blake.
  • E. Marla Gibbs
    Marla Gibbs is an American actress and comedian best known for her Emmy-nominated role as the sharp-tongued maid Florence Johnston on the classic sitcom "The Jeffersons."
  • 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_69e0b5112d8881909510b2dcdc93106d completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7346eb20c8190aeb3c0cc0a24aaf9 completed April 21, 2026, 8:25 a.m.
Created at: April 16, 2026, 3:35 p.m.