Triple

T2919880
Position Surface form Disambiguated ID Type / Status
Subject Tokyo Vice E78692 entity
Predicate director P255 FINISHED
Object Michael Mann E57782 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 Mann | Statement: [Tokyo Vice, director, Michael Mann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Mann
Context triple: [Tokyo Vice, director, Michael Mann]
  • A. Michael Mann chosen
    Michael Mann is an American filmmaker renowned for his stylish, atmospheric crime dramas and thrillers such as "Heat," "Collateral," and "Manhunter."
  • B. Michael Mann
    Michael Mann was a German sociologist and political scientist, son of writer Thomas Mann, known for his work on the sociology of power and social structures.
  • C. Michael Cimino
    Michael Cimino was an American film director and screenwriter best known for his ambitious, visually striking dramas and his Oscar-winning work on the Vietnam War epic "The Deer Hunter."
  • D. Robert Stevens
    Robert Stevens was an American television and film director best known for his work on classic anthology series such as Alfred Hitchcock Presents.
  • E. Richard LaGravenese
    Richard LaGravenese is an American screenwriter and director known for his character-driven dramas and adaptations, including films like "The Fisher King," "The Bridges of Madison County," and "P.S. I Love You."
  • 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_69ad8b0c2ad081909ff87050ae542bb9 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad96a53f8c8190b188d549f1161e84 completed March 8, 2026, 3:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0562fc5f081909c9130f71f379a24 completed March 10, 2026, 5:34 p.m.
Created at: March 8, 2026, 2:54 p.m.