Triple

T9393491
Position Surface form Disambiguated ID Type / Status
Subject Michael Kitchen E226083 entity
Predicate portrayed P1668 FINISHED
Object Christopher Foyle E349162 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: Christopher Foyle | Statement: [Michael Kitchen, portrayed, Christopher Foyle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christopher Foyle
Context triple: [Michael Kitchen, portrayed, Christopher Foyle]
  • A. Christopher Foyle chosen
    Christopher Foyle is the principled, quietly determined British detective at the heart of the World War II-era crime drama series "Foyle's War."
  • B. Peter Robinson
    Peter Robinson is a Northern Irish politician who served as leader of the Democratic Unionist Party and First Minister of Northern Ireland.
  • C. Philip Kerr
    Philip Kerr was a British author best known for his Bernie Gunther series of historical crime novels set in Nazi and post-war Germany.
  • D. John Robie
    John Robie is a retired jewel thief known as "The Cat" who becomes embroiled in a new string of robberies on the French Riviera in Alfred Hitchcock's film "To Catch a Thief."
  • E. Robert Grace
    Robert Grace was an early American civic leader and philanthropist known for his role in colonial Philadelphia’s public institutions and community organizations.
  • 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_69ca842f7e3481908bf5bcf52e032dbd completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd510fec6481908b51c497744068c8 completed April 1, 2026, 5:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69d10108cd0c8190a38ee2325d3475ce completed April 4, 2026, 12:16 p.m.
Created at: March 30, 2026, 7:45 p.m.