Triple

T14731253
Position Surface form Disambiguated ID Type / Status
Subject canton of Solothurn E346078 entity
Predicate contains P35 FINISHED
Object Kappel SO
Kappel SO is a municipality in the Swiss canton of Solothurn, known for its rural character and location in the northwestern part of Switzerland.
 E1117873 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: Kappel SO | Statement: [canton of Solothurn, contains, Kappel SO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kappel SO
Context triple: [canton of Solothurn, contains, Kappel SO]
  • A. Kappelen
    Kappelen is a small municipality in the canton of Bern in Switzerland.
  • B. Kapellen
    Kapellen is a municipality in the Belgian province of Antwerp, known for its residential character and green surroundings.
  • C. Kapelle
    Kapelle is a small municipality and town in the Dutch province of Zeeland, known for its agricultural landscape and historic village character.
  • D. Kappeln
    Kappeln is a small town in northern Germany known for its picturesque harbor on the Schlei inlet and its traditional herring fishery.
  • E. Kappel am Albis
    Kappel am Albis is a municipality in the canton of Zurich, Switzerland, historically known as the site of the 1531 Battle of Kappel where reformer Huldrych Zwingli was killed.
  • 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: Kappel SO
Triple: [canton of Solothurn, contains, Kappel SO]
Generated description
Kappel SO is a municipality in the Swiss canton of Solothurn, known for its rural character and location in the northwestern part of Switzerland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kappel SO
Target entity description: Kappel SO is a municipality in the Swiss canton of Solothurn, known for its rural character and location in the northwestern part of Switzerland.
  • A. Kappelen
    Kappelen is a small municipality in the canton of Bern in Switzerland.
  • B. Kapellen
    Kapellen is a municipality in the Belgian province of Antwerp, known for its residential character and green surroundings.
  • C. Kapelle
    Kapelle is a small municipality and town in the Dutch province of Zeeland, known for its agricultural landscape and historic village character.
  • D. Kappeln
    Kappeln is a small town in northern Germany known for its picturesque harbor on the Schlei inlet and its traditional herring fishery.
  • E. Kappel am Albis
    Kappel am Albis is a municipality in the canton of Zurich, Switzerland, historically known as the site of the 1531 Battle of Kappel where reformer Huldrych Zwingli was killed.
  • 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_69d822e5911c8190ba589f957dbd9ba7 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec26311c8819093a81ff0fa43b33b completed April 14, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb89ea388190b356df74e36023f7 completed May 8, 2026, 3:04 p.m.
NEDg Description generation batch_69fdfdd73dcc8190bd0340b2f2a2c54a completed May 8, 2026, 3:14 p.m.
NED2 Entity disambiguation (via description) batch_69fdfe70e03481909eb9a9bf863f826b completed May 8, 2026, 3:17 p.m.
Created at: April 10, 2026, 1:29 a.m.