Triple

T11170731
Position Surface form Disambiguated ID Type / Status
Subject Lutzenberg E264265 entity
Predicate hasSettlement P1068 FINISHED
Object Tobel
Tobel is a small settlement within the municipality of Lutzenberg in the canton of Appenzell Ausserrhoden, Switzerland.
E909888 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: Tobel | Statement: [Lutzenberg, hasSettlement, Tobel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tobel
Context triple: [Lutzenberg, hasSettlement, Tobel]
  • 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. Selzach
    Selzach is a Swiss municipality located in the canton of Solothurn, known for its rural character and proximity to the Jura Mountains.
  • C. 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.
  • D. Oberegg
    Oberegg is a Swiss municipality in the canton of Appenzell Innerrhoden, known for its rural landscape and location in the Appenzell region.
  • E. Buochs
    Buochs is a Swiss lakeside municipality known for its scenic setting on Lake Lucerne and proximity to the Alps in central Switzerland.
  • 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: Tobel
Triple: [Lutzenberg, hasSettlement, Tobel]
Generated description
Tobel is a small settlement within the municipality of Lutzenberg in the canton of Appenzell Ausserrhoden, Switzerland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tobel
Target entity description: Tobel is a small settlement within the municipality of Lutzenberg in the canton of Appenzell Ausserrhoden, Switzerland.
  • 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. Selzach
    Selzach is a Swiss municipality located in the canton of Solothurn, known for its rural character and proximity to the Jura Mountains.
  • C. 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.
  • D. Oberegg
    Oberegg is a Swiss municipality in the canton of Appenzell Innerrhoden, known for its rural landscape and location in the Appenzell region.
  • E. Buochs
    Buochs is a Swiss lakeside municipality known for its scenic setting on Lake Lucerne and proximity to the Alps in central Switzerland.
  • 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_69d6aa9dafac8190bd90d2c74f661aa7 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8952e248190b0751669e8c960b7 completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69e483816af08190877f86ee52846581 completed April 19, 2026, 7:25 a.m.
NEDg Description generation batch_69e48715bd2081908774d325db2b6dd5 completed April 19, 2026, 7:41 a.m.
NED2 Entity disambiguation (via description) batch_69e4886c0da881909105b3a45e786ce9 completed April 19, 2026, 7:46 a.m.
Created at: April 8, 2026, 9:29 p.m.