Triple

T5972430
Position Surface form Disambiguated ID Type / Status
Subject Steve Zahn E132905 entity
Predicate notableWork P4 FINISHED
Object Daddy Day Care E318386 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: Daddy Day Care | Statement: [Steve Zahn, notableWork, Daddy Day Care]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daddy Day Care
Context triple: [Steve Zahn, notableWork, Daddy Day Care]
  • A. Daddy Day Care chosen
    Daddy Day Care is a 2003 family comedy film about two unemployed fathers who start an improvised daycare center, leading to chaotic and humorous situations.
  • B. 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."
  • C. The Babysitters
    The Babysitters is a poem by Sylvia Plath that reflects her characteristic blend of domestic imagery and psychological intensity.
  • D. Kiddyland
    Kiddyland is a children’s amusement area within Playland Park featuring kid-friendly rides and attractions.
  • E. Make Room for Daddy
    Make Room for Daddy is a classic American television sitcom starring Danny Thomas that originally aired in the 1950s and early 1960s, depicting the comedic family life of a nightclub entertainer.
  • 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_69c0086deab081908550159ca23eec9b completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04a00c3588190b335d7d3341b6d68 completed March 22, 2026, 7:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e40fa2488190b82d604d51b73090 completed March 23, 2026, 6:56 a.m.
Created at: March 22, 2026, 4:03 p.m.