Triple

T10682339
Position Surface form Disambiguated ID Type / Status
Subject Ricki and the Flash E251787 entity
Predicate notableWorkOf P4 FINISHED
Object Diablo Cody E241147 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: Diablo Cody | Statement: [Ricki and the Flash, notableWorkOf, Diablo Cody]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diablo Cody
Context triple: [Ricki and the Flash, notableWorkOf, Diablo Cody]
  • A. Diablo Cody chosen
    Diablo Cody is an Academy Award–winning American screenwriter and author best known for her sharp, character-driven scripts in films such as "Juno" and "Young Adult."
  • B. Anna Kaufman
    Anna Kaufman is the daughter of acclaimed American screenwriter and director Charlie Kaufman.
  • C. Charlotte Wells
    Charlotte Wells is a central courtesan character in the British period drama series "Harlots," known for navigating the power struggles and personal conflicts within 18th-century London's sex trade.
  • D. Leslye Headland
    Leslye Headland is an American playwright, screenwriter, and director best known for co-creating the Netflix series "Russian Doll" and for her sharp, darkly comedic storytelling.
  • E. Lake Bell
    Lake Bell is an American actress, writer, and director known for her work in film and television comedies and dramas, including roles in projects like "In a World..." and "Boston Legal."
  • 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_69d6aa5bd7c08190a816e733b4045c23 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fcc30be481909922844b539b622d completed April 9, 2026, 1:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69dbacf1a43c8190869f4a64f9d6a26c completed April 12, 2026, 2:32 p.m.
Created at: April 8, 2026, 9:10 p.m.