Triple

T22480737
Position Surface form Disambiguated ID Type / Status
Subject Gus Kahn E555756 entity
Predicate name P16 FINISHED
Object Gus Kahn 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: Gus Kahn | Statement: [Gus Kahn, name, Gus Kahn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gus Kahn
Context triple: [Gus Kahn, name, Gus Kahn]
  • A. Gus Kahn chosen
    Gus Kahn was a prominent early 20th-century American lyricist known for writing enduring popular standards for Tin Pan Alley and Hollywood films.
  • B. Jimmy Dorsey
    Jimmy Dorsey was an American jazz clarinetist, saxophonist, composer, and big band leader who became one of the most popular bandleaders of the Swing Era.
  • C. Mitch Miller
    Mitch Miller was an American conductor, record producer, and television host best known for his influential work at Columbia Records and his popular sing-along music programs in the 1950s and 1960s.
  • D. Joe Williams
    Joe Williams was a renowned American jazz and blues singer best known for his powerful baritone voice and celebrated recordings with the Count Basie Orchestra.
  • E. Joe Williams
    Joe Williams is a fictional character in John Dos Passos's novel "The 42nd Parallel," representing the experiences and struggles of ordinary Americans in the early 20th century.
  • 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_69e11e53897c819088863779f8c50bb0 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15c3836a08190b6f0d88b94cb80a3 completed April 29, 2026, 1:17 a.m.
Created at: April 16, 2026, 8:49 p.m.