Triple

T20427193
Position Surface form Disambiguated ID Type / Status
Subject The White Countess E501035 entity
Predicate costumeDesigner P184 FINISHED
Object James Acheson 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: James Acheson | Statement: [The White Countess, costumeDesigner, James Acheson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: James Acheson
Context triple: [The White Countess, costumeDesigner, James Acheson]
  • A. James Acheson
    James Acheson is a film and television producer best known for his executive production work on the crime drama series "Godfather of Harlem."
  • B. James Acheson chosen
    James Acheson is an acclaimed British costume designer best known for his Oscar-winning work on films such as "The Last Emperor" and "Dangerous Liaisons."
  • C. Archibald Gillespie
    Archibald Gillespie was a U.S. Marine Corps officer notable for his role in the Mexican–American War, particularly in early California campaigns.
  • D. John Kelso
    John Kelso is a real-life Savannah journalist and social columnist who appears as a sharp-tongued, observant character in John Berendt’s nonfiction book "Midnight in the Garden of Good and Evil."
  • E. Hugh Baird
    Hugh Baird was a Scottish civil engineer best known for his major role in early 19th-century canal design and construction.
  • 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_69e0b4aa68fc8190b1a14c55575ef04a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67ba9700481909fa23493f98095d1 completed April 20, 2026, 7:16 p.m.
Created at: April 16, 2026, 11:30 a.m.