Triple

T18375837
Position Surface form Disambiguated ID Type / Status
Subject The Snapper E446309 entity
Predicate portrayedBy P1507 FINISHED
Object Ruth McCabe 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: Ruth McCabe | Statement: [The Snapper, portrayedBy, Ruth McCabe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ruth McCabe
Context triple: [The Snapper, portrayedBy, Ruth McCabe]
  • A. Ruth McCabe chosen
    Ruth McCabe is an Irish actress known for her work in film, television, and theatre, including roles in acclaimed dramas such as "Philomena."
  • B. Ruth Kearney
    Ruth Kearney is an Irish actress known for her television roles, including a starring part in the Netflix series "Flaked."
  • C. Elizabeth McLaughlin
    Elizabeth McLaughlin is an American actress known for her roles in television series such as the psychological drama "Hand of God."
  • D. Joan O’Callaghan
    Joan O’Callaghan, better known by her stage name Anna Kashfi, was a British-Indian actress who appeared in several Hollywood films in the 1950s and was briefly married to actor Marlon Brando.
  • E. Anne Duggan
    Anne Duggan is a scholar and academic known for her contributions to the study of medieval history and canon law.
  • 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_69d8b9f370b88190b1e5081c2c238e7f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e51759353481908aa2de599fd2cf3b completed April 19, 2026, 5:56 p.m.
Created at: April 10, 2026, 10:45 a.m.