Triple

T7851111
Position Surface form Disambiguated ID Type / Status
Subject canton of Uri E182054 entity
Predicate hasMunicipalities P747 FINISHED
Object Bürglen
Bürglen is a Swiss municipality in the alpine canton of Uri, known for its mountainous landscape and traditional rural character.
 E705854 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: Bürglen | Statement: [canton of Uri, hasMunicipalities, Bürglen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bürglen
Context triple: [canton of Uri, hasMunicipalities, Bürglen]
  • A. Besseggen
    Besseggen is a famous mountain ridge and hiking route in Norway known for its dramatic views between the lakes Gjende and Bessvatnet.
  • B. Bremgarten
    Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
  • C. Bürmoos
    Bürmoos is a small Austrian municipality located in the state of Salzburg, known for its residential character and proximity to the city of Salzburg.
  • D. Zugerberg
    Zugerberg is a scenic mountain and recreational area in the Swiss canton of Zug, known for its panoramic views over Lake Zug and the surrounding Alps.
  • E. Bönigen
    Bönigen is a Swiss village in the canton of Bern, known for its scenic location on the shore of Lake Brienz near Interlaken.
  • 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: Bürglen
Triple: [canton of Uri, hasMunicipalities, Bürglen]
Generated description
Bürglen is a Swiss municipality in the alpine canton of Uri, known for its mountainous landscape and traditional rural character.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bürglen
Target entity description: Bürglen is a Swiss municipality in the alpine canton of Uri, known for its mountainous landscape and traditional rural character.
  • A. Besseggen
    Besseggen is a famous mountain ridge and hiking route in Norway known for its dramatic views between the lakes Gjende and Bessvatnet.
  • B. Bremgarten
    Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
  • C. Bürmoos
    Bürmoos is a small Austrian municipality located in the state of Salzburg, known for its residential character and proximity to the city of Salzburg.
  • D. Zugerberg
    Zugerberg is a scenic mountain and recreational area in the Swiss canton of Zug, known for its panoramic views over Lake Zug and the surrounding Alps.
  • E. Bönigen
    Bönigen is a Swiss village in the canton of Bern, known for its scenic location on the shore of Lake Brienz near Interlaken.
  • 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_69ca82869ee08190b8f9040dbc2c0467 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb18eaac508190bf373b1d50b52e1e completed March 31, 2026, 12:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc5606caa08190b68ff051bb8ef64d completed March 31, 2026, 11:17 p.m.
NEDg Description generation batch_69cc5822581481908a143376bee599ec completed March 31, 2026, 11:26 p.m.
NED2 Entity disambiguation (via description) batch_69cc58f549388190ba6c8b41c0820cd6 completed March 31, 2026, 11:29 p.m.
Created at: March 30, 2026, 4:50 p.m.