Triple

T19877192
Position Surface form Disambiguated ID Type / Status
Subject Wallisellen E477668 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Wangen-Brüttisellen 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: Wangen-Brüttisellen | Statement: [Wallisellen, neighboringMunicipality, Wangen-Brüttisellen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wangen-Brüttisellen
Context triple: [Wallisellen, neighboringMunicipality, Wangen-Brüttisellen]
  • A. Wangen-Brüttisellen chosen
    Wangen-Brüttisellen is a municipality in the canton of Zurich, Switzerland, known for its residential character and proximity to major transport routes and urban centers.
  • B. Wüllen
    Wüllen is a district of the town of Ahaus in North Rhine-Westphalia, Germany, known for its rural character within the Münsterland region.
  • C. Wiesenbronn
    Wiesenbronn is a small municipality in the Franconian region of northern Bavaria, Germany, known for its winegrowing tradition and rural character.
  • D. Brüntorf
    Brüntorf is a village-level district that forms part of the town of Lemgo in the Lippe region of North Rhine-Westphalia, Germany.
  • E. Wallenbrück
    Wallenbrück is a district or locality within the town of Spenge in North Rhine-Westphalia, Germany.
  • 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.