Triple

T12055362
Position Surface form Disambiguated ID Type / Status
Subject district of Toggenburg E287026 entity
Predicate contains P35 FINISHED
Object Brunnadern
Brunnadern is a village in the Toggenburg region of the Swiss canton of St. Gallen, known for its rural character and scenic surroundings.
E961251 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: Brunnadern | Statement: [district of Toggenburg, contains, Brunnadern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brunnadern
Context triple: [district of Toggenburg, contains, Brunnadern]
  • A. Kleine Brenz
    Kleine Brenz is a small river in southern Germany that serves as a tributary of the Brenz.
  • B. Seebruck
    Seebruck is a Bavarian lakeside village and popular holiday resort on the northern shore of Lake Chiemsee in southern Germany.
  • C. Radenthein
    Radenthein is a small town in the Austrian state of Carinthia, known for its alpine setting and history of magnesite mining.
  • D. Burggen
    Burggen is a small rural municipality in the Bavarian region of Upper Bavaria in southern Germany.
  • E. Morhet
    Morhet is a village in the Walloon region of Belgium, located within the municipality of Vaux-sur-Sûre in the province of Luxembourg.
  • 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: Brunnadern
Triple: [district of Toggenburg, contains, Brunnadern]
Generated description
Brunnadern is a village in the Toggenburg region of the Swiss canton of St. Gallen, known for its rural character and scenic surroundings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Brunnadern
Target entity description: Brunnadern is a village in the Toggenburg region of the Swiss canton of St. Gallen, known for its rural character and scenic surroundings.
  • A. Kleine Brenz
    Kleine Brenz is a small river in southern Germany that serves as a tributary of the Brenz.
  • B. Seebruck
    Seebruck is a Bavarian lakeside village and popular holiday resort on the northern shore of Lake Chiemsee in southern Germany.
  • C. Radenthein
    Radenthein is a small town in the Austrian state of Carinthia, known for its alpine setting and history of magnesite mining.
  • D. Burggen
    Burggen is a small rural municipality in the Bavarian region of Upper Bavaria in southern Germany.
  • E. Morhet
    Morhet is a village in the Walloon region of Belgium, located within the municipality of Vaux-sur-Sûre in the province of Luxembourg.
  • 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_69d6ab4780948190bdb9f7620c2ac27e completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90425258c8190ba7b3b837c439253 completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49dea043c8190a74ffb448bbae5d0 completed May 1, 2026, 12:34 p.m.
NEDg Description generation batch_69f53d95d4fc8190b5f4e460646bec2a completed May 1, 2026, 11:56 p.m.
NED2 Entity disambiguation (via description) batch_69f56495830c8190ad5e1767f251b4c5 completed May 2, 2026, 2:42 a.m.
Created at: April 8, 2026, 9:47 p.m.