Triple

T11588918
Position Surface form Disambiguated ID Type / Status
Subject Linus Roache E274827 entity
Predicate playedCharacter P1507 FINISHED
Object Michael Cutter E653948 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 Cutter | Statement: [Linus Roache, playedCharacter, Michael Cutter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Cutter
Context triple: [Linus Roache, playedCharacter, Michael Cutter]
  • A. Michael Cutter chosen
    Michael Cutter is a fictional executive assistant district attorney known for his aggressive, hard-driving prosecution style on the television series "Law & Order."
  • B. Jeff Cutter
    Jeff Cutter is an American cinematographer known for his work on genre films such as the thriller "10 Cloverfield Lane."
  • C. James Cutler
    James Cutler is an architect best known for designing the Salem Witch Trials Memorial in Salem, Massachusetts.
  • D. Charles Keefe
    Charles Keefe is a fictional high-profile political figure whose life becomes the focus of an assassination plot in the thriller film "Red Eye."
  • E. Grant Cutler
    Grant Cutler is a musician best known as a member of the indie supergroup Gayngs, contributing to its atmospheric, genre-blending sound.
  • 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_69d6aae6b14c81908dc5a74bad7591f9 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d89463360c8190b91228c46bfe2e5f completed April 10, 2026, 6:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69e71451f1388190b72d7b755d198999 completed April 21, 2026, 6:08 a.m.
Created at: April 8, 2026, 9:38 p.m.