Triple

T4445746
Position Surface form Disambiguated ID Type / Status
Subject Wadern E96280 entity
Predicate mayor P185 FINISHED
Object Jochen Kuttler
Jochen Kuttler is a German local politician who serves as the mayor of the town of Wadern in Saarland.
E450553 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: Jochen Kuttler | Statement: [Wadern, mayor, Jochen Kuttler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jochen Kuttler
Context triple: [Wadern, mayor, Jochen Kuttler]
  • A. Andreas Hügerich
    Andreas Hügerich is a German local politician who serves as the mayor of the town of Lichtenfels in Bavaria.
  • B. Sven Budelmann
    Sven Budelmann is a German film editor known for his work on major productions including the 2022 adaptation of "All Quiet on the Western Front."
  • C. Jochen Nickel
    Jochen Nickel is a German actor known for his character roles in films and television, including appearances in notable World War II dramas.
  • D. Jörg Streitparth
    Jörg Streitparth is a German architect best known for his role in designing Berlin’s iconic Fernsehturm (TV Tower), one of the city’s most recognizable landmarks.
  • E. Johannes Popitz
    Johannes Popitz was a German lawyer, conservative politician, and high-ranking finance official who served as Prussian finance minister and later became involved in resistance circles against the Nazi regime.
  • 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: Jochen Kuttler
Triple: [Wadern, mayor, Jochen Kuttler]
Generated description
Jochen Kuttler is a German local politician who serves as the mayor of the town of Wadern in Saarland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jochen Kuttler
Target entity description: Jochen Kuttler is a German local politician who serves as the mayor of the town of Wadern in Saarland.
  • A. Andreas Hügerich
    Andreas Hügerich is a German local politician who serves as the mayor of the town of Lichtenfels in Bavaria.
  • B. Sven Budelmann
    Sven Budelmann is a German film editor known for his work on major productions including the 2022 adaptation of "All Quiet on the Western Front."
  • C. Jochen Nickel
    Jochen Nickel is a German actor known for his character roles in films and television, including appearances in notable World War II dramas.
  • D. Jörg Streitparth
    Jörg Streitparth is a German architect best known for his role in designing Berlin’s iconic Fernsehturm (TV Tower), one of the city’s most recognizable landmarks.
  • E. Johannes Popitz
    Johannes Popitz was a German lawyer, conservative politician, and high-ranking finance official who served as Prussian finance minister and later became involved in resistance circles against the Nazi regime.
  • 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_69b345415ba481908df738e7174448ba completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b355d1eba08190899d0a3c1684ce4e completed March 13, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69bdacc9ef8c81909ff2a16cf68844d0 completed March 20, 2026, 8:23 p.m.
NEDg Description generation batch_69bdad757394819091d334c12b660b95 completed March 20, 2026, 8:26 p.m.
NED2 Entity disambiguation (via description) batch_69bdadd612a48190b088fe6ac894dbb5 completed March 20, 2026, 8:28 p.m.
Created at: March 12, 2026, 11:32 p.m.