Triple

T10311511
Position Surface form Disambiguated ID Type / Status
Subject Kathy Najimy E241899 entity
Predicate appearedIn P795 FINISHED
Object Younger E284568 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: Younger | Statement: [Kathy Najimy, appearedIn, Younger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Younger
Context triple: [Kathy Najimy, appearedIn, Younger]
  • A. Younger chosen
    Younger is a television comedy-drama series about a 40-year-old woman who pretends to be in her twenties to reenter the competitive publishing industry.
  • B. Junger
    Junger is the surname of Sebastian Junger, an American author, journalist, and documentary filmmaker known for works like "The Perfect Storm" and "Restrepo."
  • C. Young
    Young is a common English surname borne by numerous notable individuals across diverse fields such as politics, civil rights, science, and the arts.
  • D. Young
    Young is a regional town in New South Wales, Australia, historically known for its gold rush heritage and cherry production.
  • E. Youth
    "Youth" is a section of Peter Kropotkin’s autobiographical work *Memoirs of a Revolutionist*, recounting his early life and formative experiences.
  • 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_69d381ac38808190a8ca7457c85b625b completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d32ac6c08190b23eb042b3ec284a completed April 7, 2026, 9:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7502f7b308190aaefd62f2f8a0ac3 completed April 9, 2026, 7:07 a.m.
Created at: April 6, 2026, 11:47 a.m.