Triple

T7001752
Position Surface form Disambiguated ID Type / Status
Subject Lake Lucerne E162352 entity
Predicate hasTownOnShore P969 FINISHED
Object Vitznau
Vitznau is a picturesque Swiss lakeside village in the canton of Lucerne, known as a gateway to Mount Rigi and a popular destination for scenic tourism on Lake Lucerne.
 E636375 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: Vitznau | Statement: [Lake Lucerne, hasTownOnShore, Vitznau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vitznau
Context triple: [Lake Lucerne, hasTownOnShore, Vitznau]
  • A. Sursee
    Sursee is a historic Swiss town in the canton of Lucerne, known for its well-preserved medieval old town and scenic setting near Lake Sempach.
  • B. Bettlach
    Bettlach is a Swiss municipality located in the canton of Solothurn.
  • C. Kiental
    Kiental is a picturesque alpine valley and village in the Bernese Oberland region of Switzerland, known for its dramatic mountain scenery and hiking opportunities.
  • D. Breggia
    Breggia is a river in the Lombardy region of northern Italy that flows through the province of Como before entering Switzerland.
  • E. Selzach
    Selzach is a Swiss municipality located in the canton of Solothurn, known for its rural character and proximity to the Jura Mountains.
  • 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: Vitznau
Triple: [Lake Lucerne, hasTownOnShore, Vitznau]
Generated description
Vitznau is a picturesque Swiss lakeside village in the canton of Lucerne, known as a gateway to Mount Rigi and a popular destination for scenic tourism on Lake Lucerne.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vitznau
Target entity description: Vitznau is a picturesque Swiss lakeside village in the canton of Lucerne, known as a gateway to Mount Rigi and a popular destination for scenic tourism on Lake Lucerne.
  • A. Sursee
    Sursee is a historic Swiss town in the canton of Lucerne, known for its well-preserved medieval old town and scenic setting near Lake Sempach.
  • B. Bettlach
    Bettlach is a Swiss municipality located in the canton of Solothurn.
  • C. Kiental
    Kiental is a picturesque alpine valley and village in the Bernese Oberland region of Switzerland, known for its dramatic mountain scenery and hiking opportunities.
  • D. Breggia
    Breggia is a river in the Lombardy region of northern Italy that flows through the province of Como before entering Switzerland.
  • E. Selzach
    Selzach is a Swiss municipality located in the canton of Solothurn, known for its rural character and proximity to the Jura Mountains.
  • 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_69c68857ffc08190857dc62cd5253777 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dc0f8830819091f4356296234713 completed March 27, 2026, 7:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c775573c84819081f34ab2b14b700a completed March 28, 2026, 6:29 a.m.
NEDg Description generation batch_69c777b443e88190a4f7c9e069d2a7a4 completed March 28, 2026, 6:39 a.m.
NED2 Entity disambiguation (via description) batch_69c7789d07c08190b6b6479ffbbc9f3e completed March 28, 2026, 6:43 a.m.
Created at: March 27, 2026, 2:33 p.m.