Triple

T11172152
Position Surface form Disambiguated ID Type / Status
Subject The Wolverine E264300 entity
Predicate editedBy P1954 FINISHED
Object Michael McCusker E223312 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: Michael McCusker | Statement: [The Wolverine, editedBy, Michael McCusker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael McCusker
Context triple: [The Wolverine, editedBy, Michael McCusker]
  • A. Michael McCusker chosen
    Michael McCusker is an American film editor known for his work on major Hollywood productions, including the thriller "The Girl on the Train" (2016).
  • B. Kevin McLaughlin
    Kevin McLaughlin is a literary scholar and translator known for his English translation of Walter Benjamin’s "The Arcades Project."
  • C. Michael Maloney
    Michael Maloney is a British actor known for his work in film, television, and theatre, including prominent roles in Shakespearean adaptations.
  • D. Brian Kavanagh
    Brian Kavanagh is a film editor best known for his work on notable Australian and international films, including the drama "The Devil's Playground."
  • E. Brian Duggan
    Brian Duggan is a relatively obscure individual whose name is shared with multiple people, making it difficult to identify a single widely recognized public figure by that name.
  • 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_69d6aa9dafac8190bd90d2c74f661aa7 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e89660208190b1d9e91529f5d246 completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671788ec88190852df74698bc4518 completed May 2, 2026, 9:49 p.m.
Created at: April 8, 2026, 9:29 p.m.