Triple

T3356693
Position Surface form Disambiguated ID Type / Status
Subject Zurich Airport E70621 entity
Predicate locatedIn P40 FINISHED
Object Kloten
Kloten is a town in the canton of Zurich in northern Switzerland, best known as the home of Zurich Airport.
 E425440 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: Kloten | Statement: [Zurich Airport, locatedIn, Kloten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kloten
Context triple: [Zurich Airport, locatedIn, Kloten]
  • A. 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.
  • B. Rapperswil-Jona
    Rapperswil-Jona is a Swiss town in the canton of St. Gallen known for its historic old town, lakeside location, and prominent medieval castle.
  • C. Schaffhausen
    Schaffhausen is a historic town and capital of the canton of the same name in northern Switzerland, known for its well-preserved medieval old town and proximity to the Rhine Falls.
  • D. Liestal
    Liestal is a historic Swiss town in northwestern Switzerland that serves as the administrative and cultural center of the canton of Basel-Landschaft.
  • E. Olten
    Olten is a town in the canton of Solothurn in northwestern Switzerland, known as an important railway junction and regional economic center.
  • 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: Kloten
Triple: [Zurich Airport, locatedIn, Kloten]
Generated description
Kloten is a town in the canton of Zurich in northern Switzerland, best known as the home of Zurich Airport.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kloten
Target entity description: Kloten is a town in the canton of Zurich in northern Switzerland, best known as the home of Zurich Airport.
  • A. 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.
  • B. Rapperswil-Jona
    Rapperswil-Jona is a Swiss town in the canton of St. Gallen known for its historic old town, lakeside location, and prominent medieval castle.
  • C. Schaffhausen
    Schaffhausen is a historic town and capital of the canton of the same name in northern Switzerland, known for its well-preserved medieval old town and proximity to the Rhine Falls.
  • D. Liestal
    Liestal is a historic Swiss town in northwestern Switzerland that serves as the administrative and cultural center of the canton of Basel-Landschaft.
  • E. Olten
    Olten is a town in the canton of Solothurn in northwestern Switzerland, known as an important railway junction and regional economic center.
  • 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_69ad85a660c48190998489309a3b4869 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb242d4988190bbac993df587936d completed March 8, 2026, 5:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b73c409081909c583019d7ec1d4a completed March 14, 2026, 7:30 p.m.
NEDg Description generation batch_69b5b7e7f48881908ebb773499aebd5e completed March 14, 2026, 7:32 p.m.
NED2 Entity disambiguation (via description) batch_69b5b881c80081909af084ff4b43b01e completed March 14, 2026, 7:35 p.m.
Created at: March 8, 2026, 3:13 p.m.