Triple

T22383688
Position Surface form Disambiguated ID Type / Status
Subject Museum Mile Bonn E553338 entity
Predicate cityDistrictsCovered P143741 FINISHED
Object Gronau
Gronau is a district of Bonn, Germany, known for its concentration of cultural institutions, government buildings, and modern architecture along the Rhine.
 E1534791 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: Gronau | Statement: [Museum Mile Bonn, cityDistrictsCovered, Gronau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gronau
Context triple: [Museum Mile Bonn, cityDistrictsCovered, Gronau]
  • A. Gronau
    Gronau is a town in Germany historically noted as the site of a battle during the Seven Years' War.
  • B. Grotenberge
    Grotenberge is a village in East Flanders, Belgium, that forms part of the municipality of Zottegem.
  • C. Grafenberg
    Grafenberg is a small municipality in the German state of Baden-Württemberg, located within the Esslingen district near Stuttgart.
  • D. Neudorf
    Neudorf is a residential district of Strasbourg, France, known for its dense urban fabric, local commerce, and proximity to the city center.
  • E. Neudorf
    Neudorf is a village-level subdivision of the Tyrolean municipality of Umhausen in western Austria.
  • 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: Gronau
Triple: [Museum Mile Bonn, cityDistrictsCovered, Gronau]
Generated description
Gronau is a district of Bonn, Germany, known for its concentration of cultural institutions, government buildings, and modern architecture along the Rhine.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gronau
Target entity description: Gronau is a district of Bonn, Germany, known for its concentration of cultural institutions, government buildings, and modern architecture along the Rhine.
  • A. Gronau
    Gronau is a town in Germany historically noted as the site of a battle during the Seven Years' War.
  • B. Grotenberge
    Grotenberge is a village in East Flanders, Belgium, that forms part of the municipality of Zottegem.
  • C. Grafenberg
    Grafenberg is a small municipality in the German state of Baden-Württemberg, located within the Esslingen district near Stuttgart.
  • D. Neudorf
    Neudorf is a residential district of Strasbourg, France, known for its dense urban fabric, local commerce, and proximity to the city center.
  • E. Neudorf
    Neudorf is a village-level subdivision of the Tyrolean municipality of Umhausen in western Austria.
  • 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_69e11e4cf87c8190a1ff474daec326b7 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1582d8e548190a7330de49d519675 completed April 29, 2026, 1 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0ae9bc28fc81908967105a7a34903e completed May 18, 2026, 10:28 a.m.
NEDg Description generation batch_6a0aedd061408190a25b6b1773e6610a completed May 18, 2026, 10:45 a.m.
NED2 Entity disambiguation (via description) batch_6a0aee8497b881909019717c6b9b4888 completed May 18, 2026, 10:48 a.m.
Created at: April 16, 2026, 8:45 p.m.