Triple

T4888875
Position Surface form Disambiguated ID Type / Status
Subject Canton of Zürich E109508 entity
Predicate contains P35 FINISHED
Object Uster
Uster is a Swiss town and municipality in the canton of Zürich, known as a regional center near Lake Greifen with a mix of urban amenities and surrounding natural landscapes.
 E483927 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: Uster | Statement: [Canton of Zürich, contains, Uster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Uster
Context triple: [Canton of Zürich, contains, Uster]
  • A. Olten
    Olten is a town in the canton of Solothurn in northwestern Switzerland, known as an important railway junction and regional economic center.
  • B. Liestal
    Liestal is a historic Swiss town in northwestern Switzerland that serves as the administrative and cultural center of the canton of Basel-Landschaft.
  • C. Grenchen
    Grenchen is a Swiss town in the canton of Solothurn known for its watchmaking industry and location at the foot of the Jura Mountains.
  • D. Schafhausen
    Schafhausen is a village and district of the town Weil der Stadt in the German state of Baden-Württemberg.
  • E. St. Gallen
    St. Gallen is a historic city in northeastern Switzerland renowned for its UNESCO-listed Abbey of Saint Gall and rich textile heritage.
  • 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: Uster
Triple: [Canton of Zürich, contains, Uster]
Generated description
Uster is a Swiss town and municipality in the canton of Zürich, known as a regional center near Lake Greifen with a mix of urban amenities and surrounding natural landscapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Uster
Target entity description: Uster is a Swiss town and municipality in the canton of Zürich, known as a regional center near Lake Greifen with a mix of urban amenities and surrounding natural landscapes.
  • A. Olten
    Olten is a town in the canton of Solothurn in northwestern Switzerland, known as an important railway junction and regional economic center.
  • B. Liestal
    Liestal is a historic Swiss town in northwestern Switzerland that serves as the administrative and cultural center of the canton of Basel-Landschaft.
  • C. Grenchen
    Grenchen is a Swiss town in the canton of Solothurn known for its watchmaking industry and location at the foot of the Jura Mountains.
  • D. Schafhausen
    Schafhausen is a village and district of the town Weil der Stadt in the German state of Baden-Württemberg.
  • E. St. Gallen
    St. Gallen is a historic city in northeastern Switzerland renowned for its UNESCO-listed Abbey of Saint Gall and rich textile heritage.
  • 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_69be89de55c48190a280ae0719b5a8b6 completed March 21, 2026, 12:06 p.m.
NEDg Description generation batch_69be8a5682888190a335742fab9a4649 completed March 21, 2026, 12:08 p.m.
NED2 Entity disambiguation (via description) batch_69be8aed0d58819092243e7bdf872069 completed March 21, 2026, 12:11 p.m.
Created at: March 20, 2026, 1:28 p.m.