Triple

T8660262
Position Surface form Disambiguated ID Type / Status
Subject Swissair E205529 entity
Predicate headquartersLocation P62 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: [Swissair, headquartersLocation, Kloten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kloten
Context triple: [Swissair, headquartersLocation, 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. Opfikon
    Opfikon is a municipality in the canton of Zürich in Switzerland, known for its proximity to Zurich Airport and its role as a residential and commercial suburb of the city of Zürich.
  • D. 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.
  • E. 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.
  • 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_69ca8350897c819086cde7596fbe5fe7 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc48701c748190a5f7bd9e2da0e5e9 completed March 31, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfc91d31d48190bfd8a8254f6f518e completed April 3, 2026, 2:05 p.m.
Created at: March 30, 2026, 6:30 p.m.