Triple

T21886662
Position Surface form Disambiguated ID Type / Status
Subject Reitz E540422 entity
Predicate hasNotableBearer P458 FINISHED
Object Giselher Reitz
Giselher Reitz is a German former sprint canoeist who competed internationally in the 1960s.
 E1517575 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: Giselher Reitz | Statement: [Reitz, hasNotableBearer, Giselher Reitz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Giselher Reitz
Context triple: [Reitz, hasNotableBearer, Giselher Reitz]
  • A. Giselher Klebe
    Giselher Klebe was a 20th-century German composer best known for his operas and orchestral works, often inspired by literary sources.
  • B. Reinhard Klooss
    Reinhard Klooss is a German film director, screenwriter, and producer best known for his work on animated features such as the 2013 adaptation of Tarzan.
  • C. Bruno Loerzer
    Bruno Loerzer was a prominent German First World War fighter ace who later became a high-ranking Luftwaffe general during the Nazi era.
  • D. Herbert Viola
    Herbert Viola is a quirky, well-meaning junior detective and comic relief character from the 1980s television series "Moonlighting."
  • E. Lothar Popp
    Lothar Popp was a German socialist and sailor who emerged as a leading revolutionary figure during the Kiel mutiny of 1918, helping to spark the German Revolution at the end of World War I.
  • 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: Giselher Reitz
Triple: [Reitz, hasNotableBearer, Giselher Reitz]
Generated description
Giselher Reitz is a German former sprint canoeist who competed internationally in the 1960s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Giselher Reitz
Target entity description: Giselher Reitz is a German former sprint canoeist who competed internationally in the 1960s.
  • A. Giselher Klebe
    Giselher Klebe was a 20th-century German composer best known for his operas and orchestral works, often inspired by literary sources.
  • B. Reinhard Klooss
    Reinhard Klooss is a German film director, screenwriter, and producer best known for his work on animated features such as the 2013 adaptation of Tarzan.
  • C. Bruno Loerzer
    Bruno Loerzer was a prominent German First World War fighter ace who later became a high-ranking Luftwaffe general during the Nazi era.
  • D. Herbert Viola
    Herbert Viola is a quirky, well-meaning junior detective and comic relief character from the 1980s television series "Moonlighting."
  • E. Lothar Popp
    Lothar Popp was a German socialist and sailor who emerged as a leading revolutionary figure during the Kiel mutiny of 1918, helping to spark the German Revolution at the end of World War I.
  • 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_69e0c47a95908190ae3e19b716accb3d completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f118ed35948190bbffba2c40029eee completed April 28, 2026, 8:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a80969340819099fd82e8ebd5719c completed May 18, 2026, 2:59 a.m.
NEDg Description generation batch_6a0a849039a88190a47d14dfd8c43748 completed May 18, 2026, 3:16 a.m.
NED2 Entity disambiguation (via description) batch_6a0a852ded908190826fb128889791a6 completed May 18, 2026, 3:19 a.m.
Created at: April 16, 2026, 7:05 p.m.