Triple

T4888884
Position Surface form Disambiguated ID Type / Status
Subject Canton of Zürich E109508 entity
Predicate contains P35 FINISHED
Object Andelfingen
Andelfingen is a municipality and regional center in the canton of Zürich in northern Switzerland, known for its rural character and vineyards along the Thur River.
 E479770 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: Andelfingen | Statement: [Canton of Zürich, contains, Andelfingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Andelfingen
Context triple: [Canton of Zürich, contains, Andelfingen]
  • A. Niederbühl
    Niederbühl is a district of the town of Rastatt in the state of Baden-Württemberg in southwestern Germany.
  • B. Göschenen
    Göschenen is a Swiss mountain village and railway junction in the canton of Uri, known as a gateway to the Gotthard region.
  • C. Volketswil
    Volketswil is a municipality in the canton of Zurich in Switzerland, known for its residential character and proximity to the city of Zurich.
  • D. Bönigen
    Bönigen is a Swiss village in the canton of Bern, known for its scenic location on the shore of Lake Brienz near Interlaken.
  • E. Küsnacht
    Küsnacht is a picturesque Swiss municipality on the shores of Lake Zurich, known for its affluent residential character and scenic lakeside setting.
  • 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: Andelfingen
Triple: [Canton of Zürich, contains, Andelfingen]
Generated description
Andelfingen is a municipality and regional center in the canton of Zürich in northern Switzerland, known for its rural character and vineyards along the Thur River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Andelfingen
Target entity description: Andelfingen is a municipality and regional center in the canton of Zürich in northern Switzerland, known for its rural character and vineyards along the Thur River.
  • A. Niederbühl
    Niederbühl is a district of the town of Rastatt in the state of Baden-Württemberg in southwestern Germany.
  • B. Göschenen
    Göschenen is a Swiss mountain village and railway junction in the canton of Uri, known as a gateway to the Gotthard region.
  • C. Volketswil
    Volketswil is a municipality in the canton of Zurich in Switzerland, known for its residential character and proximity to the city of Zurich.
  • D. Bönigen
    Bönigen is a Swiss village in the canton of Bern, known for its scenic location on the shore of Lake Brienz near Interlaken.
  • E. Küsnacht
    Küsnacht is a picturesque Swiss municipality on the shores of Lake Zurich, known for its affluent residential character and scenic lakeside setting.
  • 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_69bd440f71348190b99938e59fb7f9a1 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6e06a81881908734dbdc350a2039 completed March 20, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6fbf3e74819099910475bbd18734 completed March 21, 2026, 10:15 a.m.
NEDg Description generation batch_69be735ea2cc819085c221b7230db63d completed March 21, 2026, 10:30 a.m.
NED2 Entity disambiguation (via description) batch_69be73b237388190b3502e64e185a26e completed March 21, 2026, 10:32 a.m.
Created at: March 20, 2026, 1:28 p.m.