Triple

T10080868
Position Surface form Disambiguated ID Type / Status
Subject Lucerne University of Applied Sciences and Arts E213896 entity
Predicate cityCampus P5417 FINISHED
Object Horw
Horw is a municipality in the canton of Lucerne in central Switzerland, located on the shores of Lake Lucerne and known for its proximity to the city of Lucerne and its educational institutions.
 E840484 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: Horw | Statement: [Lucerne University of Applied Sciences and Arts, cityCampus, Horw]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Horw
Context triple: [Lucerne University of Applied Sciences and Arts, cityCampus, Horw]
  • A. Hof
    Hof is a town in northeastern Bavaria, Germany, known for its location near the Czech border and its regional cultural and economic significance.
  • B. Horrem
    Horrem is a district of the town of Kerpen in North Rhine-Westphalia, Germany.
  • C. Wilhering
    Wilhering is a municipality in Upper Austria, known for the historic Wilhering Abbey and its location near the city of Linz.
  • D. Haslach
    Haslach is a district or locality that forms part of the town of Oberkirch in the German state of Baden-Württemberg.
  • E. Haslach
    Haslach is a town in southern Germany historically noted as the site of the Battle of Haslach-Jungingen during the Napoleonic Wars.
  • 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: Horw
Triple: [Lucerne University of Applied Sciences and Arts, cityCampus, Horw]
Generated description
Horw is a municipality in the canton of Lucerne in central Switzerland, located on the shores of Lake Lucerne and known for its proximity to the city of Lucerne and its educational institutions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Horw
Target entity description: Horw is a municipality in the canton of Lucerne in central Switzerland, located on the shores of Lake Lucerne and known for its proximity to the city of Lucerne and its educational institutions.
  • A. Hof
    Hof is a town in northeastern Bavaria, Germany, known for its location near the Czech border and its regional cultural and economic significance.
  • B. Horrem
    Horrem is a district of the town of Kerpen in North Rhine-Westphalia, Germany.
  • C. Wilhering
    Wilhering is a municipality in Upper Austria, known for the historic Wilhering Abbey and its location near the city of Linz.
  • D. Haslach
    Haslach is a district or locality that forms part of the town of Oberkirch in the German state of Baden-Württemberg.
  • E. Haslach
    Haslach is a town in southern Germany historically noted as the site of the Battle of Haslach-Jungingen during the Napoleonic Wars.
  • 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_69ca839bf730819086900c323c9b8c95 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd032ef288190a961d266d9ecafbc completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b660987c8190a6a29d9e56acbff7 completed April 5, 2026, 7:22 p.m.
NEDg Description generation batch_69d2b78f3c248190b104937e2d669882 completed April 5, 2026, 7:27 p.m.
NED2 Entity disambiguation (via description) batch_69d2b84a26a481908ab2705d5883cfce completed April 5, 2026, 7:30 p.m.
Created at: March 30, 2026, 9 p.m.