Triple

T7915916
Position Surface form Disambiguated ID Type / Status
Subject canton of Nidwalden E183826 entity
Predicate hasMunicipality P847 FINISHED
Object Ennetbürgen
Ennetbürgen is a Swiss lakeside municipality known for its scenic location on Lake Lucerne and proximity to Mount Bürgenstock in central Switzerland.
 E712083 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: Ennetbürgen | Statement: [canton of Nidwalden, hasMunicipality, Ennetbürgen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ennetbürgen
Context triple: [canton of Nidwalden, hasMunicipality, Ennetbürgen]
  • A. Bürglen
    Bürglen is a Swiss municipality in the alpine canton of Uri, known for its mountainous landscape and traditional rural character.
  • B. Neuenegg
    Neuenegg is a Swiss municipality in the canton of Bern, known for its rural character and location near the city of Bern.
  • C. Bremgarten
    Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
  • D. Waldegg
    Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
  • E. Attiswil
    Attiswil is a municipality in the canton of Bern in Switzerland, located in the Oberaargau region.
  • 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: Ennetbürgen
Triple: [canton of Nidwalden, hasMunicipality, Ennetbürgen]
Generated description
Ennetbürgen is a Swiss lakeside municipality known for its scenic location on Lake Lucerne and proximity to Mount Bürgenstock in central Switzerland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ennetbürgen
Target entity description: Ennetbürgen is a Swiss lakeside municipality known for its scenic location on Lake Lucerne and proximity to Mount Bürgenstock in central Switzerland.
  • A. Bürglen
    Bürglen is a Swiss municipality in the alpine canton of Uri, known for its mountainous landscape and traditional rural character.
  • B. Neuenegg
    Neuenegg is a Swiss municipality in the canton of Bern, known for its rural character and location near the city of Bern.
  • C. Bremgarten
    Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
  • D. Waldegg
    Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
  • E. Attiswil
    Attiswil is a municipality in the canton of Bern in Switzerland, located in the Oberaargau region.
  • 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_69ca828efbe48190bd48482650182e79 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a76ae688190b068e4c92603a16d completed March 31, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc936b4d088190bfcfd3bc6c05f7e8 completed April 1, 2026, 3:39 a.m.
NEDg Description generation batch_69cc955542fc8190a84be60f4efea915 completed April 1, 2026, 3:47 a.m.
NED2 Entity disambiguation (via description) batch_69cc964c6b308190ae121072b1180268 completed April 1, 2026, 3:51 a.m.
Created at: March 30, 2026, 5:05 p.m.