Triple

T18676528
Position Surface form Disambiguated ID Type / Status
Subject The Good Fairy E456615 entity
Predicate hasMusicBy P1952 FINISHED
Object Heinz Roemheld 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: Heinz Roemheld | Statement: [The Good Fairy, hasMusicBy, Heinz Roemheld]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heinz Roemheld
Context triple: [The Good Fairy, hasMusicBy, Heinz Roemheld]
  • A. Heinz Roemheld chosen
    Heinz Roemheld was an American composer and pianist best known for his prolific work scoring Hollywood films during the 1930s and 1940s.
  • B. Hans-Jürgen von Cramon-Taubadel
    Hans-Jürgen von Cramon-Taubadel was a German Luftwaffe officer and fighter wing commander during World War II.
  • C. Geert W. Schmid-Schönbein
    Geert W. Schmid-Schönbein is a biomedical engineer and physiologist known for his research on microcirculation, inflammation, and the biomechanics of the cardiovascular system.
  • D. Rolf Dieter Brinkmann
    Rolf Dieter Brinkmann was a German poet and writer known for his experimental, avant-garde style and for introducing elements of American pop culture and Beat literature into postwar German poetry.
  • E. Dr. Peter Lüttmann
    Dr. Peter Lüttmann is a German local politician who serves as the mayor of the city of Rheine in North Rhine-Westphalia.
  • 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_69d8d38f72b4819090a935175d9ca8af completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e556b5a52c81908a71ac86544fb6aa completed April 19, 2026, 10:27 p.m.
Created at: April 10, 2026, 11:48 a.m.