Triple

T13486378
Position Surface form Disambiguated ID Type / Status
Subject The Whole Nine Yards E318514 entity
Predicate composer P1361 FINISHED
Object Randy Edelman E359056 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: Randy Edelman | Statement: [The Whole Nine Yards, composer, Randy Edelman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Randy Edelman
Context triple: [The Whole Nine Yards, composer, Randy Edelman]
  • A. Randy Edelman chosen
    Randy Edelman is an American composer best known for his prolific work on film and television scores, including numerous Hollywood action and drama movies.
  • B. Don Grusin
    Don Grusin is an American jazz and fusion keyboardist, composer, and producer known for his solo work and collaborations within contemporary jazz, including projects with his brother Dave Grusin.
  • C. Albert Weinert
    Albert Weinert was a German-American sculptor and monument designer known for his public memorials in the United States.
  • D. Dave Grusin
    Dave Grusin is an American composer, arranger, and jazz pianist best known for his prolific film and television scores and for co-founding GRP Records.
  • E. Ron Goodwin
    Ron Goodwin was a British composer and conductor best known for his rousing film scores for war and adventure movies in the mid-20th century.
  • 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_69d806b6bfec819089222715b2e86c8e completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf3a15b48190b63fb59e926a97ae completed April 12, 2026, 2:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f74638e2088190a126791f60b541c7 completed May 3, 2026, 12:57 p.m.
Created at: April 9, 2026, 9:42 p.m.