Triple

T10737371
Position Surface form Disambiguated ID Type / Status
Subject Love, Rosie E253227 entity
Predicate musicBy P1952 FINISHED
Object Ralf Wengenmayr
Ralf Wengenmayr is a German film composer known for scoring a variety of feature films and international productions.
E899173 NE FINISHED

How this triple was built (4 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: Ralf Wengenmayr | Statement: [Love, Rosie, musicBy, Ralf Wengenmayr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ralf Wengenmayr
Context triple: [Love, Rosie, musicBy, Ralf Wengenmayr]
  • A. Karl Rammelt
    Karl Rammelt was a German Luftwaffe fighter ace of World War II, credited with numerous aerial victories on the Eastern Front.
  • B. Joachim Haspinger
    Joachim Haspinger was a Capuchin priest and military leader who became a prominent figure in the Tyrolean uprising against Napoleonic and Bavarian rule in 1809.
  • C. Harald Kainz
    Harald Kainz is an Austrian civil engineer and academic who has served as a leading figure in higher education, notably heading Graz University of Technology.
  • D. Ewald Stadler
    Ewald Stadler is an Austrian politician and former member of the European Parliament known for his right-wing, nationalist positions.
  • E. Rainer Schmid
    Rainer Schmid is a German local politician who serves as the mayor of the municipality of Gailingen am Hochrhein in Baden-Württemberg.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ralf Wengenmayr
Triple: [Love, Rosie, musicBy, Ralf Wengenmayr]
Generated description
Ralf Wengenmayr is a German film composer known for scoring a variety of feature films and international productions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ralf Wengenmayr
Target entity description: Ralf Wengenmayr is a German film composer known for scoring a variety of feature films and international productions.
  • A. Karl Rammelt
    Karl Rammelt was a German Luftwaffe fighter ace of World War II, credited with numerous aerial victories on the Eastern Front.
  • B. Joachim Haspinger
    Joachim Haspinger was a Capuchin priest and military leader who became a prominent figure in the Tyrolean uprising against Napoleonic and Bavarian rule in 1809.
  • C. Harald Kainz
    Harald Kainz is an Austrian civil engineer and academic who has served as a leading figure in higher education, notably heading Graz University of Technology.
  • D. Ewald Stadler
    Ewald Stadler is an Austrian politician and former member of the European Parliament known for his right-wing, nationalist positions.
  • E. Rainer Schmid
    Rainer Schmid is a German local politician who serves as the mayor of the municipality of Gailingen am Hochrhein in Baden-Württemberg.
  • F. None of above. chosen

Provenance (5 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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d710410a04819090036597ac0d271c completed April 9, 2026, 2:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69e373af06588190879cd11cce11c7bb completed April 18, 2026, 12:06 p.m.
NEDg Description generation batch_69e378dcc92c8190952d4acfee2a309c completed April 18, 2026, 12:28 p.m.
NED2 Entity disambiguation (via description) batch_69e37be75a588190abb9569ef1e87279 completed April 18, 2026, 12:41 p.m.
Created at: April 8, 2026, 9:14 p.m.