Triple

T16634050
Position Surface form Disambiguated ID Type / Status
Subject Who Wants to Live Forever E404151 entity
Predicate orchestrationBy P4735 FINISHED
Object Michael Kamen E291037 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: Michael Kamen | Statement: [Who Wants to Live Forever, orchestrationBy, Michael Kamen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Kamen
Context triple: [Who Wants to Live Forever, orchestrationBy, Michael Kamen]
  • A. Michael Kamen chosen
    Michael Kamen was an American composer and conductor renowned for his film and television scores, including major works in action cinema and acclaimed historical dramas.
  • B. 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.
  • C. Albert Weinert
    Albert Weinert was a German-American sculptor and monument designer known for his public memorials in the United States.
  • D. Christophe Beck
    Christophe Beck is a Canadian composer best known for his film and television scores, including work on projects like "Buffy the Vampire Slayer" and various major Hollywood films.
  • E. Elliot Goldenthal
    Elliot Goldenthal is an American composer known for his innovative, often experimental film scores for movies such as "Interview with the Vampire," "Batman Forever," and "Frida."
  • 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_69d8838a41f08190b0c3f79c47df5078 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e378e8a76c8190bf08e6f6dec63c50 completed April 18, 2026, 12:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c79657ec8190b1b3500b7a99df0a completed May 10, 2026, 5:59 p.m.
Created at: April 10, 2026, 5:17 a.m.