Triple

T10026832
Position Surface form Disambiguated ID Type / Status
Subject Fran Drescher E200749 entity
Predicate coCreated P1858 FINISHED
Object The Nanny E181999 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: The Nanny | Statement: [Fran Drescher, coCreated, The Nanny]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Nanny
Context triple: [Fran Drescher, coCreated, The Nanny]
  • A. The Nanny chosen
    The Nanny is a popular 1990s American sitcom starring Fran Drescher as a flashy Queens nanny working for a wealthy Manhattan family.
  • B. The Nanny Diaries
    The Nanny Diaries is a 2007 comedy-drama film, based on the bestselling novel, that follows a college student working as a nanny for a wealthy New York family and stars Scarlett Johansson and Laura Linney.
  • C. Nanny
    Nanny is the kind-hearted, loyal housekeeper who helps care for Pongo and Perdita’s puppies in Disney’s "One Hundred and One Dalmatians."
  • D. Mr. Nanny
    Mr. Nanny is a 1993 family comedy film starring Hulk Hogan as a tough ex-wrestler who becomes the bodyguard and caretaker for two mischievous children.
  • E. Dayanhe, My Nanny
    "Dayanhe, My Nanny" is a well-known poem by Chinese poet Ai Qing that affectionately commemorates the life and kindness of the nanny who raised him.
  • 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_69ca831c45f08190ac1505cc15076608 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cdcde3c1b88190924e6158f406b453 completed April 2, 2026, 2:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2822bca308190ad2fad82653c6e74 completed April 5, 2026, 3:39 p.m.
Created at: March 30, 2026, 8:54 p.m.