Triple

T8415400
Position Surface form Disambiguated ID Type / Status
Subject Blade Runner E198718 entity
Predicate musicBy P1952 FINISHED
Object Vangelis E6338 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: Vangelis | Statement: [Blade Runner, musicBy, Vangelis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vangelis
Context triple: [Blade Runner, musicBy, Vangelis]
  • A. Vangelis chosen
    Vangelis was a Greek composer and pioneer of electronic and ambient music, renowned for his evocative synthesizer-based film scores such as those for "Chariots of Fire" and "Blade Runner."
  • B. Jon and Vangelis
    Jon and Vangelis was a musical collaboration between Yes vocalist Jon Anderson and Greek composer Vangelis, known for their melodic, synth-driven progressive pop songs in the late 1970s and 1980s.
  • C. Basil Poledouris
    Basil Poledouris was an American composer best known for his powerful, symphonic film scores for movies such as Conan the Barbarian, RoboCop, and The Hunt for Red October.
  • D. 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.
  • E. Maurice Jarre
    Maurice Jarre was a French composer renowned for his sweeping, Oscar-winning film scores, particularly for epic movies such as "Lawrence of Arabia," "Doctor Zhivago," and "A Passage to India."
  • 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_69ca831201b481909e137936ef99ff11 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb83e443a08190983d9a0a61e0f781 completed March 31, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce0333a3488190ba30d03b1d7bacb1 completed April 2, 2026, 5:48 a.m.
Created at: March 30, 2026, 6:06 p.m.