Triple

T9914027
Position Surface form Disambiguated ID Type / Status
Subject The Last Boy Scout E185821 entity
Predicate composer P1361 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: [The Last Boy Scout, composer, Michael Kamen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Kamen
Context triple: [The Last Boy Scout, composer, 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_69ca829b45f481909040f7b99a1976ed completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb53ba1ac8190ba655133b81596d7 completed April 2, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20dd82edc8190b405a3969864af77 completed April 5, 2026, 7:23 a.m.
Created at: March 30, 2026, 8:41 p.m.