Triple

T5554212
Position Surface form Disambiguated ID Type / Status
Subject Kerry Bishé E145597 entity
Predicate name P16 FINISHED
Object Kerry Bishé E145597 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: Kerry Bishé | Statement: [Kerry Bishé, name, Kerry Bishé]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kerry Bishé
Context triple: [Kerry Bishé, name, Kerry Bishé]
  • A. Kerry Bishé chosen
    Kerry Bishé is a New Zealand–born American actress best known for her roles in the film "Argo" and the television series "Halt and Catch Fire."
  • B. Claire Jackman
    Claire Jackman is a fictional character portrayed by actress Gina Bellman, known from her work in British television and film.
  • C. Robyn Nevin
    Robyn Nevin is a prominent Australian actress and theatre director known for her extensive work on stage, film, and television, as well as her leadership roles in major Australian theatre companies.
  • D. Suzanne Mackie
    Suzanne Mackie is a British television and film producer known for her work on acclaimed projects such as "The Crown" and other high-profile UK dramas.
  • E. Leah Purcell
    Leah Purcell is an acclaimed Australian actor, writer, and director known for her powerful performances and contributions to Indigenous storytelling in film, television, and theatre.
  • 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_69c008fcaf788190bafa02a1917ee73b completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01ff9c9c48190b5e587d58c6515d8 completed March 22, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69c059e7636c819082cc18b1913c08c9 completed March 22, 2026, 9:06 p.m.
Created at: March 22, 2026, 3:36 p.m.