Triple

T680044
Position Surface form Disambiguated ID Type / Status
Subject Prévessin-Moëns E13160 entity
Predicate hasTwinTown P919 FINISHED
Object Schlieren
Schlieren is a municipality in the canton of Zurich in northern Switzerland, known as a suburban town within the Zurich metropolitan area.
 E82313 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: Schlieren | Statement: [Prévessin-Moëns, hasTwinTown, Schlieren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Schlieren
Context triple: [Prévessin-Moëns, hasTwinTown, Schlieren]
  • A. Crombach
    Crombach is a village in the municipality of St. Vith in the German-speaking region of eastern Belgium.
  • B. Lichtenberg
    Lichtenberg is a borough in eastern Berlin, Germany, known for its mix of residential areas, historical sites, and former Soviet administrative and military facilities.
  • C. Leven
    Leven is a coastal town in eastern Scotland, situated on the Firth of Forth in the council area of Fife.
  • D. Nischel
    Nischel is the local colloquial nickname for the large Karl Marx Monument in Chemnitz, Germany.
  • E. Gera
    Gera is a city in the German state of Thuringia, known for its industrial heritage and historic architecture along the White Elster river.
  • 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: Schlieren
Triple: [Prévessin-Moëns, hasTwinTown, Schlieren]
Generated description
Schlieren is a municipality in the canton of Zurich in northern Switzerland, known as a suburban town within the Zurich metropolitan area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Schlieren
Target entity description: Schlieren is a municipality in the canton of Zurich in northern Switzerland, known as a suburban town within the Zurich metropolitan area.
  • A. Crombach
    Crombach is a village in the municipality of St. Vith in the German-speaking region of eastern Belgium.
  • B. Lichtenberg
    Lichtenberg is a borough in eastern Berlin, Germany, known for its mix of residential areas, historical sites, and former Soviet administrative and military facilities.
  • C. Leven
    Leven is a coastal town in eastern Scotland, situated on the Firth of Forth in the council area of Fife.
  • D. Nischel
    Nischel is the local colloquial nickname for the large Karl Marx Monument in Chemnitz, Germany.
  • E. Gera
    Gera is a city in the German state of Thuringia, known for its industrial heritage and historic architecture along the White Elster river.
  • 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_69a4933d3bf88190972041cd8cf143b9 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a04f4efc819082767a7517fa760a completed March 1, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5c3a5701c8190810e5e52bc2b61f7 completed March 2, 2026, 5:06 p.m.
NEDg Description generation batch_69a5cd8acc888190b9bb80198bce5d00 completed March 2, 2026, 5:48 p.m.
NED2 Entity disambiguation (via description) batch_69a5ce6232e08190a8dba769f173f431 completed March 2, 2026, 5:52 p.m.
Created at: March 1, 2026, 7:36 p.m.