Triple

T8040666
Position Surface form Disambiguated ID Type / Status
Subject Kölsch E187426 entity
Predicate closelyRelatedTo P37 FINISHED
Object Bönnsch
Bönnsch is a regional German beer style and dialect variant from Bonn, closely associated with and similar to the Kölsch tradition of nearby Cologne.
E715000 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: Bönnsch | Statement: [Kölsch, closelyRelatedTo, Bönnsch]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bönnsch
Context triple: [Kölsch, closelyRelatedTo, Bönnsch]
  • A. Röthlein
    Röthlein is a small municipality in the Schweinfurt district of Bavaria, Germany.
  • B. Bardenbach
    Bardenbach is a village and district of the town of Wadern in the Saarland region of western Germany.
  • C. Bramsche
    Bramsche is a town in Lower Saxony, Germany, known for its location near Osnabrück and its historical textile industry.
  • D. Haslach
    Haslach is a district or locality that forms part of the town of Oberkirch in the German state of Baden-Württemberg.
  • E. Erkelenz
    Erkelenz is a historic town in western Germany, known for its medieval origins and role as a regional administrative and cultural center.
  • 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: Bönnsch
Triple: [Kölsch, closelyRelatedTo, Bönnsch]
Generated description
Bönnsch is a regional German beer style and dialect variant from Bonn, closely associated with and similar to the Kölsch tradition of nearby Cologne.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bönnsch
Target entity description: Bönnsch is a regional German beer style and dialect variant from Bonn, closely associated with and similar to the Kölsch tradition of nearby Cologne.
  • A. Röthlein
    Röthlein is a small municipality in the Schweinfurt district of Bavaria, Germany.
  • B. Bardenbach
    Bardenbach is a village and district of the town of Wadern in the Saarland region of western Germany.
  • C. Bramsche
    Bramsche is a town in Lower Saxony, Germany, known for its location near Osnabrück and its historical textile industry.
  • D. Haslach
    Haslach is a district or locality that forms part of the town of Oberkirch in the German state of Baden-Württemberg.
  • E. Erkelenz
    Erkelenz is a historic town in western Germany, known for its medieval origins and role as a regional administrative and cultural center.
  • 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_69ca82b00cb48190b59a300f70e97bd7 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3f1d62c48190bf4a6cd17517c5dc completed March 31, 2026, 3:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbe4ca4cc8190a664968334225087 completed April 1, 2026, 6:42 a.m.
NEDg Description generation batch_69ccc24a39f88190995f076d1a7ec3e7 completed April 1, 2026, 6:59 a.m.
NED2 Entity disambiguation (via description) batch_69ccc37f0ca88190b4e077f23dbbe6f8 completed April 1, 2026, 7:04 a.m.
Created at: March 30, 2026, 5:23 p.m.