Triple

T8969500
Position Surface form Disambiguated ID Type / Status
Subject Marianne Beauséjour E214226 entity
Predicate filmMusicBy P37392 FINISHED
Object Alan Silvestri E18968 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: Alan Silvestri | Statement: [Marianne Beauséjour, filmMusicBy, Alan Silvestri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alan Silvestri
Context triple: [Marianne Beauséjour, filmMusicBy, Alan Silvestri]
  • A. Alan Silvestri chosen
    Alan Silvestri is an American composer best known for his prolific film scores, including iconic work on movies such as the Back to the Future trilogy and numerous Marvel Cinematic Universe films.
  • B. Dave Silvestri
    Dave Silvestri is a former professional baseball infielder who played in Major League Baseball during the 1990s.
  • C. John Debney
    John Debney is an American film composer known for scoring a wide range of movies and television shows, including major studio productions and acclaimed dramas.
  • D. John Williams
    John Williams was a British actor known for his character roles in mid-20th-century films and television, including classic courtroom dramas and comedies.
  • E. John Williams
    John Williams is an acclaimed American composer and conductor best known for his iconic film scores for franchises such as Star Wars, Indiana Jones, Harry Potter, and many others.
  • 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_69ca839dbf608190a2f5990477115d29 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6765babc8190a4a3b79aa21047c8 completed April 1, 2026, 12:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc96006e48190978e4ccdedc48b41 completed April 3, 2026, 2:06 p.m.
Created at: March 30, 2026, 7:01 p.m.