Triple

T10467247
Position Surface form Disambiguated ID Type / Status
Subject Kate & Leopold E246828 entity
Predicate musicBy P1952 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: [Kate & Leopold, musicBy, Randy Edelman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Randy Edelman
Context triple: [Kate & Leopold, 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 (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_69d381c16c248190a2fe5b471e584e9c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5092e3230819098ab444f73c9bd40 completed April 7, 2026, 1:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8dc5c26a88190aab4a590c20191a3 completed April 10, 2026, 11:17 a.m.
Created at: April 6, 2026, 12:20 p.m.