Triple

T21149431
Position Surface form Disambiguated ID Type / Status
Subject Strip Polka E521145 entity
Predicate associatedWith P37 FINISHED
Object Jimmy Dorsey 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: Jimmy Dorsey | Statement: [Strip Polka, associatedWith, Jimmy Dorsey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jimmy Dorsey
Context triple: [Strip Polka, associatedWith, Jimmy Dorsey]
  • A. Jimmy Dorsey chosen
    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.
  • B. Tony Dorsey
    Tony Dorsey is a trombonist best known for his work as a touring and session musician, including performing with Paul McCartney and Wings in the 1970s.
  • C. Tommy Dorsey
    Tommy Dorsey was a prominent American jazz trombonist and big band leader, famed for his smooth tone and influential swing-era recordings.
  • D. Gus Kahn
    Gus Kahn was a prominent early 20th-century American lyricist known for writing enduring popular standards for Tin Pan Alley and Hollywood films.
  • E. Don Dorsey
    Don Dorsey is an American audio producer and entertainment designer best known for creating and directing groundbreaking nighttime spectaculars for Disney theme parks.
  • 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_69e0b50c6a848190a4e525a77a319b8a completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e72400911c8190978e88138a9bfaff completed April 21, 2026, 7:15 a.m.
Created at: April 16, 2026, 2:58 p.m.