Triple

T9539993
Position Surface form Disambiguated ID Type / Status
Subject Mad Love E230126 entity
Predicate musicBy P1952 FINISHED
Object Dimitri Tiomkin E218087 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: Dimitri Tiomkin | Statement: [Mad Love, musicBy, Dimitri Tiomkin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dimitri Tiomkin
Context triple: [Mad Love, musicBy, Dimitri Tiomkin]
  • A. Dimitri Tiomkin chosen
    Dimitri Tiomkin was a renowned Russian-American film composer best known for his dramatic, Oscar-winning scores for classic Hollywood movies such as "High Noon" and "The High and the Mighty."
  • 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. Franz Waxman
    Franz Waxman was a German-American composer renowned for his influential and Oscar-winning film scores during Hollywood's Golden Age.
  • D. 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."
  • E. David Raksin
    David Raksin was an American film composer best known for his influential scores in classic Hollywood cinema, including the iconic music for the film "Laura."
  • 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_69ca847b1b3081908f72bc932c17cc41 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd98e4df6c8190a4d1160c42daa45f completed April 1, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69d15278efd4819091e707aabd9a59d7 completed April 4, 2026, 6:03 p.m.
Created at: March 30, 2026, 8:01 p.m.