Triple

T22916493
Position Surface form Disambiguated ID Type / Status
Subject Farewell to the King E568745 entity
Predicate cinematographyBy P1953 FINISHED
Object Dean Semler 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: Dean Semler | Statement: [Farewell to the King, cinematographyBy, Dean Semler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dean Semler
Context triple: [Farewell to the King, cinematographyBy, Dean Semler]
  • A. Dean Semler chosen
    Dean Semler is an Australian cinematographer renowned for his work on major Hollywood films, including the comedy sequel "Nutty Professor II: The Klumps."
  • B. Dean Grinsfelder
    Dean Grinsfelder is a television and film composer best known for his work on animated series such as "Wolverine and the X-Men."
  • C. Michael Leiters
    Michael Leiters is an automotive executive known for senior leadership roles at high-performance sports car manufacturers, including serving as CEO of McLaren Automotive.
  • D. Jeff Seckendorf
    Jeff Seckendorf is an American cinematographer and filmmaker known for his work on feature films, television, and commercials, including the teen comedy "The Girl Next Door."
  • E. Donald Baechler
    Donald Baechler was an American contemporary artist known for his bold, graphic paintings and collages that combined childlike imagery with sophisticated art-historical references.
  • 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_69e2458d90c88190a58cead4e781ca6a completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1807a14648190b5d5f7d926f19320 completed April 29, 2026, 3:52 a.m.
Created at: April 17, 2026, 3:42 p.m.