Triple

T21665036
Position Surface form Disambiguated ID Type / Status
Subject Josie Lawrence E534691 entity
Predicate name P16 FINISHED
Object Josie Lawrence NE NERFINISHED

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: Josie Lawrence | Statement: [Josie Lawrence, name, Josie Lawrence]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Josie Lawrence
Context triple: [Josie Lawrence, name, Josie Lawrence]
  • A. Josie Lawrence chosen
    Josie Lawrence is an English actress and comedian best known for her improvisational work on the TV show "Whose Line Is It Anyway?" and numerous stage and screen roles.
  • B. Nat Jaffe
    Nat Jaffe is a central character in Michael Chabon’s novel "Telegraph Avenue," depicted as one of the intertwined figures navigating family, culture, and community in contemporary Oakland and Berkeley.
  • C. Josephine Lawrence
    Josephine Lawrence was an American author and screenwriter known for her popular novels and contributions to early 20th-century film adaptations.
  • D. Bitsie Tulloch
    Bitsie Tulloch is an American actress best known for her role as Juliette Silverton/Eve on the television series "Grimm."
  • E. Lysette Anthony
    Lysette Anthony is a British actress and model known for her work in film and television, including prominent roles in comedies and genre movies.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c467e1f48190af2650b19175abc4 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef6c0b26c8819092c13e59dcc3c25c completed April 27, 2026, 2 p.m.
Created at: April 16, 2026, 6:36 p.m.