Triple

T19877352
Position Surface form Disambiguated ID Type / Status
Subject Glatt E477672 entity
Predicate passesThrough P225 FINISHED
Object Niederglatt 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: Niederglatt | Statement: [Glatt, passesThrough, Niederglatt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Niederglatt
Context triple: [Glatt, passesThrough, Niederglatt]
  • A. Niederglatt chosen
    Niederglatt is a municipality in the canton of Zurich in northern Switzerland, situated in the Glatt Valley and integrated into the greater Zurich metropolitan area.
  • B. Neulengbach
    Neulengbach is a small town in Lower Austria known for its historic center and its location within the Vienna Woods region.
  • C. Reichstett
    Reichstett is a small commune in northeastern France, situated near Strasbourg in the Grand Est region.
  • D. Gneixendorf
    Gneixendorf is a village and cadastral community that forms part of the city of Krems an der Donau in Lower Austria.
  • E. Glattfelden
    Glattfelden is a municipality in the canton of Zurich in northern Switzerland, known for its scenic setting along the Glatt River and its well-preserved historic village center.
  • 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.