Triple

T11272687
Position Surface form Disambiguated ID Type / Status
Subject Aegidienberg E266851 entity
Predicate hasSubdistrict P747 FINISHED
Object Wülscheid
Wülscheid is a small locality within the Aegidienberg district of Bad Honnef in North Rhine-Westphalia, Germany.
E935666 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: Wülscheid | Statement: [Aegidienberg, hasSubdistrict, Wülscheid]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wülscheid
Context triple: [Aegidienberg, hasSubdistrict, Wülscheid]
  • A. Radevormwald
    Radevormwald is a small historic town in North Rhine-Westphalia, western Germany, known for its hilly Bergisches Land landscape and traditional textile and metalworking industries.
  • B. Rheydt
    Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
  • C. Monschau
    Monschau is a historic small town in western Germany’s Eifel region, known for its well-preserved half-timbered houses, medieval center, and scenic setting along the Rur River.
  • D. Waldbröl
    Waldbröl is a small town in North Rhine-Westphalia, Germany, known for its rural setting in the Bergisches Land region.
  • E. Gummersbach
    Gummersbach is a town in North Rhine-Westphalia, Germany, known as a regional center in the Bergisches Land and a location for higher education and industry.
  • 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: Wülscheid
Triple: [Aegidienberg, hasSubdistrict, Wülscheid]
Generated description
Wülscheid is a small locality within the Aegidienberg district of Bad Honnef in North Rhine-Westphalia, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Wülscheid
Target entity description: Wülscheid is a small locality within the Aegidienberg district of Bad Honnef in North Rhine-Westphalia, Germany.
  • A. Radevormwald
    Radevormwald is a small historic town in North Rhine-Westphalia, western Germany, known for its hilly Bergisches Land landscape and traditional textile and metalworking industries.
  • B. Rheydt
    Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
  • C. Monschau
    Monschau is a historic small town in western Germany’s Eifel region, known for its well-preserved half-timbered houses, medieval center, and scenic setting along the Rur River.
  • D. Waldbröl
    Waldbröl is a small town in North Rhine-Westphalia, Germany, known for its rural setting in the Bergisches Land region.
  • E. Gummersbach
    Gummersbach is a town in North Rhine-Westphalia, Germany, known as a regional center in the Bergisches Land and a location for higher education and industry.
  • 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_69d6aac8c2f48190ad0596f1f89f0470 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e965c9048190804ebb48f0a4817b completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e8a6df121c8190a8522ce0e366013c completed April 22, 2026, 10:45 a.m.
NEDg Description generation batch_69e8aa378edc8190807451b1855a4502 completed April 22, 2026, 11 a.m.
NED2 Entity disambiguation (via description) batch_69e8b05117988190aa029efa250053db completed April 22, 2026, 11:26 a.m.
Created at: April 8, 2026, 9:31 p.m.