Triple

T19877348
Position Surface form Disambiguated ID Type / Status
Subject Glatt E477672 entity
Predicate passesThrough P225 FINISHED
Object Opfikon NE NERFINISHED

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: Opfikon | Statement: [Glatt, passesThrough, Opfikon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Opfikon
Context triple: [Glatt, passesThrough, Opfikon]
  • A. Opfikon chosen
    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.
  • B. Landiswil
    Landiswil is a small rural municipality in the canton of Bern, Switzerland, characterized by its agricultural landscape and location in the Emmental region.
  • C. Rüschlikon
    Rüschlikon is a wealthy lakeside municipality on the western shore of Lake Zurich in the canton of Zurich, Switzerland.
  • D. Hinwil
    Hinwil is a municipality and regional center in the Swiss canton of Zürich, known for its rural surroundings and as the home base of the Sauber Formula One team.
  • E. Kloten
    Kloten is a town in the canton of Zurich in northern Switzerland, best known as the home of Zurich Airport.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51f32b08190b3687f4f60353250 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e658dbdb648190b423865e7994a8fe completed April 20, 2026, 4:48 p.m.
Created at: April 10, 2026, 1:52 p.m.