Triple

T7849136
Position Surface form Disambiguated ID Type / Status
Subject The Nanny E181999 entity
Predicate starring P1507 FINISHED
Object Fran Drescher E200749 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: Fran Drescher | Statement: [The Nanny, starring, Fran Drescher]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fran Drescher
Context triple: [The Nanny, starring, Fran Drescher]
  • A. Fran Drescher chosen
    Fran Drescher is an American actress and comedian best known for starring in the 1990s sitcom "The Nanny" and her distinctive nasal voice and comedic style.
  • B. Kirstie Alley
    Kirstie Alley was an American actress best known for her Emmy-winning role as Rebecca Howe on the hit sitcom "Cheers" and for her work in films like "Look Who's Talking."
  • C. Ginny Newhart
    Ginny Newhart was an American homemaker and the longtime wife of comedian and actor Bob Newhart, known for her behind-the-scenes influence on his career and for inspiring key ideas in his television work.
  • D. Laraine Newman
    Laraine Newman is an American comedian and actress best known as one of the original cast members of Saturday Night Live in the 1970s.
  • E. Mary Steenburgen
    Mary Steenburgen is an American actress known for her versatile performances in film and television, including acclaimed roles in movies such as "Melvin and Howard," "Back to the Future Part III," and numerous character-driven dramas and comedies.
  • 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_69ca82869ee08190b8f9040dbc2c0467 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb18e989ac819090e459b77d8932d3 completed March 31, 2026, 12:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbdf1834b08190ab9fd79387e496a7 completed March 31, 2026, 2:50 p.m.
Created at: March 30, 2026, 4:50 p.m.