Triple

T4888887
Position Surface form Disambiguated ID Type / Status
Subject Canton of Zürich E109508 entity
Predicate contains P35 FINISHED
Object Kloten E425440 NE FINISHED

How this triple was built (2 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: [Canton of Zürich, contains, Kloten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kloten
Context triple: [Canton of Zürich, contains, Kloten]
  • A. Kloten chosen
    Kloten is a town in the canton of Zurich in northern Switzerland, best known as the home of Zurich Airport.
  • B. 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.
  • C. Bülach
    Bülach is a town in northern Switzerland that serves as a regional center near Zurich, known for its residential character and proximity to Zurich Airport.
  • D. 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.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69bed90355a88190bc1aafed3ad74625 completed March 21, 2026, 5:44 p.m.
Created at: March 20, 2026, 1:28 p.m.