Triple

T22689794
Position Surface form Disambiguated ID Type / Status
Subject Laura Devon E561019 entity
Predicate spouse P13 FINISHED
Object Maurice Jarre NE NERFINISHED

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: [Laura Devon, spouse, Maurice Jarre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maurice Jarre
Context triple: [Laura Devon, spouse, 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 (2 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_69e2454d71b48190a1f80af9f82b6fcf completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1789a1fd08190bce5fa0babe695d3 completed April 29, 2026, 3:18 a.m.
Created at: April 17, 2026, 3:13 p.m.