Triple

T6202136
Position Surface form Disambiguated ID Type / Status
Subject The City E138658 entity
Predicate creator P184 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: [The City, creator, Vangelis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vangelis
Context triple: [The City, creator, 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_69c008acbea48190991c6b834bb45d65 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0626a32908190a3332008aee2e4a9 completed March 22, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20d4499dc8190943486cf1af83f0a completed March 24, 2026, 4:04 a.m.
Created at: March 22, 2026, 4:20 p.m.