Triple

T20183508
Position Surface form Disambiguated ID Type / Status
Subject Anaconda (1997 film) E492792 entity
Predicate musicBy P1952 FINISHED
Object Randy Edelman 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: Randy Edelman | Statement: [Anaconda (1997 film), musicBy, Randy Edelman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Randy Edelman
Context triple: [Anaconda (1997 film), musicBy, 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 (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_69da6268a034819081cbd9ea5a1c9475 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e668f068748190a0941e98ef5afd59 completed April 20, 2026, 5:57 p.m.
Created at: April 11, 2026, 11:36 p.m.