Triple

T7915292
Position Surface form Disambiguated ID Type / Status
Subject Klaus Badelt E183808 entity
Predicate workedWith P398 FINISHED
Object Hans Zimmer E13255 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: Hans Zimmer | Statement: [Klaus Badelt, workedWith, Hans Zimmer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hans Zimmer
Context triple: [Klaus Badelt, workedWith, Hans Zimmer]
  • A. Hans Zimmer chosen
    Hans Zimmer is a renowned German film composer celebrated for his influential, award-winning scores for major Hollywood blockbusters such as The Lion King, Gladiator, Inception, and The Dark Knight trilogy.
  • B. James Newton Howard
    James Newton Howard is an acclaimed American composer best known for his prolific film and television scores across a wide range of genres.
  • C. Ramin Djawadi
    Ramin Djawadi is a German-Iranian composer best known for his powerful, cinematic scores for film and television, including Game of Thrones, Westworld, and major blockbuster movies.
  • D. Clint Mansell
    Clint Mansell is a British composer best known for his atmospheric and often haunting film scores, including work on movies like Requiem for a Dream, The Fountain, and Black Swan.
  • E. 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.
  • 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_69ca828efbe48190bd48482650182e79 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a759b548190af2e2aa0705d7051 completed March 31, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5be54fdc81909a988114a6f30a13 completed March 31, 2026, 5:30 a.m.
Created at: March 30, 2026, 5:05 p.m.