Triple

T2650021
Position Surface form Disambiguated ID Type / Status
Subject Wildhaus E53874 entity
Predicate locatedIn P40 FINISHED
Object Toggenburg
Toggenburg is a mountainous region in the canton of St. Gallen in northeastern Switzerland, known for its alpine landscapes, traditional villages, and outdoor recreation.
 E287025 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: Toggenburg | Statement: [Wildhaus, locatedIn, Toggenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Toggenburg
Context triple: [Wildhaus, locatedIn, Toggenburg]
  • A. Berner
    A Berner is a resident or native of the Swiss city of Bern.
  • B. Salmo svizzero
    Salmo svizzero è il titolo italiano dell’inno nazionale della Svizzera, noto per il suo carattere solenne e patriottico.
  • C. Bega
    Bega is a rural town in New South Wales, Australia, best known as a major dairy and cheese-producing centre.
  • 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. San Bernardo
    San Bernardo is a commune and city in Chile that forms part of the Greater Santiago urban area and serves as an important residential and industrial hub.
  • 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: Toggenburg
Triple: [Wildhaus, locatedIn, Toggenburg]
Generated description
Toggenburg is a mountainous region in the canton of St. Gallen in northeastern Switzerland, known for its alpine landscapes, traditional villages, and outdoor recreation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Toggenburg
Target entity description: Toggenburg is a mountainous region in the canton of St. Gallen in northeastern Switzerland, known for its alpine landscapes, traditional villages, and outdoor recreation.
  • A. Berner
    A Berner is a resident or native of the Swiss city of Bern.
  • B. Salmo svizzero
    Salmo svizzero è il titolo italiano dell’inno nazionale della Svizzera, noto per il suo carattere solenne e patriottico.
  • C. Bega
    Bega is a rural town in New South Wales, Australia, best known as a major dairy and cheese-producing centre.
  • 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. San Bernardo
    San Bernardo is a commune and city in Chile that forms part of the Greater Santiago urban area and serves as an important residential and industrial hub.
  • 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_69ab495e192081909c77b622e8e7e15a completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd91ca1288190ba302b04bac4c153 completed March 7, 2026, 7:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98cc2d9881908556b915a1870c02 completed March 10, 2026, 4:06 a.m.
NEDg Description generation batch_69af9a0966a88190b76c50ac801438e2 completed March 10, 2026, 4:11 a.m.
NED2 Entity disambiguation (via description) batch_69af9dfac8048190be715b844eedf064 completed March 10, 2026, 4:28 a.m.
Created at: March 6, 2026, 9:53 p.m.