Triple

T21416414
Position Surface form Disambiguated ID Type / Status
Subject The Smiling Lieutenant E528307 entity
Predicate musicBy P1952 FINISHED
Object W. Franke Harling 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: W. Franke Harling | Statement: [The Smiling Lieutenant, musicBy, W. Franke Harling]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: W. Franke Harling
Context triple: [The Smiling Lieutenant, musicBy, W. Franke Harling]
  • A. W. Franke Harling chosen
    W. Franke Harling was an American composer best known for his film scores during the early sound era of Hollywood.
  • B. William Wendt
    William Wendt was a prominent American landscape painter celebrated as a leading figure of the California Impressionist movement.
  • C. Harold Huth
    Harold Huth was a British film director, producer, and occasional actor active in the mid-20th century, known for his work in the British studio system.
  • D. George Hildebrand
    George Hildebrand was an American Major League Baseball umpire active in the early 20th century.
  • E. Harold Wenstrom
    Harold Wenstrom was an American cinematographer active during the early 20th century, known for his work on numerous silent and early sound films.
  • 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_69e0c454c248819093425d1099101c09 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e8b205d17c8190b9b6b5708658f9be completed April 22, 2026, 11:33 a.m.
Created at: April 16, 2026, 5:46 p.m.