Triple

T18213705
Position Surface form Disambiguated ID Type / Status
Subject Fraubrunnen E436096 entity
Predicate hasMunicipalityMerger P80558 FINISHED
Object Zauggenried
Zauggenried was a former Swiss municipality in the canton of Bern that has been incorporated into the larger municipality of Fraubrunnen.
E1318629 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: Zauggenried | Statement: [Fraubrunnen, hasMunicipalityMerger, Zauggenried]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zauggenried
Context triple: [Fraubrunnen, hasMunicipalityMerger, Zauggenried]
  • A. Waldegg
    Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
  • B. Bollschweil
    Bollschweil is a small municipality in southwestern Germany’s Baden-Württemberg region, situated near Freiburg im Breisgau in the scenic Breisgau area at the edge of the Black Forest.
  • C. Niederbühl
    Niederbühl is a district of the town of Rastatt in the state of Baden-Württemberg in southwestern Germany.
  • D. Küsnacht
    Küsnacht is a picturesque Swiss municipality on the shores of Lake Zurich, known for its affluent residential character and scenic lakeside setting.
  • E. Eggenwil
    Eggenwil is a small municipality in the canton of Aargau in northern Switzerland, situated near the Reuss River and characterized by its rural, village-like setting.
  • 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: Zauggenried
Triple: [Fraubrunnen, hasMunicipalityMerger, Zauggenried]
Generated description
Zauggenried was a former Swiss municipality in the canton of Bern that has been incorporated into the larger municipality of Fraubrunnen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Zauggenried
Target entity description: Zauggenried was a former Swiss municipality in the canton of Bern that has been incorporated into the larger municipality of Fraubrunnen.
  • A. Waldegg
    Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
  • B. Bollschweil
    Bollschweil is a small municipality in southwestern Germany’s Baden-Württemberg region, situated near Freiburg im Breisgau in the scenic Breisgau area at the edge of the Black Forest.
  • C. Niederbühl
    Niederbühl is a district of the town of Rastatt in the state of Baden-Württemberg in southwestern Germany.
  • D. Küsnacht
    Küsnacht is a picturesque Swiss municipality on the shores of Lake Zurich, known for its affluent residential character and scenic lakeside setting.
  • E. Eggenwil
    Eggenwil is a small municipality in the canton of Aargau in northern Switzerland, situated near the Reuss River and characterized by its rural, village-like setting.
  • 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_69d8b90dba6481908e119eb9aa4ca0cb completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4e475953c81909f792793ded2057e completed April 19, 2026, 2:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03c4b2915c819080678dbcd0558e65 completed May 13, 2026, 12:24 a.m.
NEDg Description generation batch_6a03c582c9fc8190a656bb9e5544b5cf completed May 13, 2026, 12:27 a.m.
NED2 Entity disambiguation (via description) batch_6a03c64c02288190903c7e9123ca5a79 completed May 13, 2026, 12:31 a.m.
Created at: April 10, 2026, 10:32 a.m.