Triple

T6712001
Position Surface form Disambiguated ID Type / Status
Subject Franz Waxman E153166 entity
Predicate name P16 FINISHED
Object Franz Waxman E153166 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: Franz Waxman | Statement: [Franz Waxman, name, Franz Waxman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Franz Waxman
Context triple: [Franz Waxman, name, Franz Waxman]
  • A. Franz Waxman chosen
    Franz Waxman was a German-American composer renowned for his influential and Oscar-winning film scores during Hollywood's Golden Age.
  • B. 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.
  • C. Max Steiner
    Max Steiner was an Austrian-American composer and conductor renowned as one of the founding fathers of film music, scoring classics such as Gone with the Wind and Casablanca.
  • D. Bernard Herrmann
    Bernard Herrmann was an influential American composer best known for his innovative and dramatic film scores, including his landmark collaborations with directors Orson Welles and Alfred Hitchcock.
  • E. Elmer Bernstein
    Elmer Bernstein was an American composer renowned for his prolific and influential film scores across genres, including classics like "The Ten Commandments," "The Magnificent Seven," and "To Kill a Mockingbird."
  • 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_69c68808d8d8819087369015270788fe completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d108acc08190b38b43161d8912b9 completed March 27, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7880545c4819091979008c84b3325 completed March 28, 2026, 7:49 a.m.
Created at: March 27, 2026, 2:07 p.m.