Triple

T16253526
Position Surface form Disambiguated ID Type / Status
Subject Gorillas in the Mist E394572 entity
Predicate musicBy P1952 FINISHED
Object Maurice Jarre E133300 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: Maurice Jarre | Statement: [Gorillas in the Mist, musicBy, Maurice Jarre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maurice Jarre
Context triple: [Gorillas in the Mist, musicBy, Maurice Jarre]
  • A. Maurice Jarre chosen
    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."
  • B. Richard Addinsell
    Richard Addinsell was a British composer best known for his film scores and the popular orchestral piece "Warsaw Concerto."
  • C. Miklós Rózsa
    Miklós Rózsa was a Hungarian-American composer renowned for his influential and Oscar-winning film scores during Hollywood’s Golden Age, including classics like Ben-Hur and Double Indemnity.
  • D. Ernest Gold
    Ernest Gold was an Austrian-born American composer best known for his acclaimed film scores, including the Oscar-winning music for "Exodus."
  • E. Franz Waxman
    Franz Waxman was a German-American composer renowned for his influential and Oscar-winning film scores during Hollywood's Golden Age.
  • 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_69d87f2171208190951025e526947816 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e24598c9488190a92df7d8b1824724 completed April 17, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0017b1e22c8190bddca67661121c2d completed May 10, 2026, 5:29 a.m.
Created at: April 10, 2026, 5:04 a.m.