Triple

T12424914
Position Surface form Disambiguated ID Type / Status
Subject True Confessions E296871 entity
Predicate castMember P1668 FINISHED
Object Cyril Cusack E243809 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: Cyril Cusack | Statement: [True Confessions, castMember, Cyril Cusack]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cyril Cusack
Context triple: [True Confessions, castMember, Cyril Cusack]
  • A. Cyril Cusack chosen
    Cyril Cusack was an acclaimed Irish stage and screen actor known for his prolific career in British and Irish cinema and theatre throughout the mid-20th century.
  • B. Ned Dennehy
    Ned Dennehy is an Irish character actor known for his distinctive supporting roles in film and television, including appearances in projects like "Peaky Blinders," "Good Omens," and "An Klondike."
  • C. Barry Fitzgerald
    Barry Fitzgerald was an Irish character actor best known for his prolific Hollywood career in the 1940s, including his Academy Award–winning performance in "Going My Way."
  • D. Reggie Brown
    Reggie Brown is an American entrepreneur best known as a co-founder of Snapchat, the multimedia messaging app developed by Snap Inc.
  • E. Donald Sinden
    Donald Sinden was a distinguished English actor known for his work in film, theatre, and television, particularly from the mid-20th century onward.
  • 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_69d6ada0640c81908c061d7fb3d47786 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d7b6bd08190b30beba393a5b1e7 completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6349716fc8190997b54a50d29827a completed May 2, 2026, 5:29 p.m.
Created at: April 8, 2026, 9:55 p.m.