Triple

T15961862
Position Surface form Disambiguated ID Type / Status
Subject Paulie Bleeker E387080 entity
Predicate creator P184 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: [Paulie Bleeker, creator, Diablo Cody]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diablo Cody
Context triple: [Paulie Bleeker, creator, 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_69d86da882448190a82ea962fe343b79 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e15700651c819091c1cc4f60894c35 completed April 16, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffc3c3aae081909366c01b3fec4d47 completed May 9, 2026, 11:31 p.m.
Created at: April 10, 2026, 4:53 a.m.