Triple

T20341373
Position Surface form Disambiguated ID Type / Status
Subject Wolhusen E495747 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Ruswil 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: Ruswil | Statement: [Wolhusen, neighboringMunicipality, Ruswil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ruswil
Context triple: [Wolhusen, neighboringMunicipality, Ruswil]
  • A. Ruswil chosen
    Ruswil is a municipality in the canton of Lucerne in central Switzerland, known for its rural character and agricultural landscape.
  • B. Richterswil
    Richterswil is a picturesque municipality on the shores of Lake Zurich in the canton of Zurich, Switzerland.
  • C. Liestal
    Liestal is a historic Swiss town in northwestern Switzerland that serves as the administrative and cultural center of the canton of Basel-Landschaft.
  • D. Giswil
    Giswil is a Swiss municipality in the canton of Obwalden, known for its scenic alpine landscape and location along key routes through central Switzerland.
  • E. 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.
  • 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_69e0b4a3320881909495ae8bc30bc2dc completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67835f6e881908834dda06cf66c50 completed April 20, 2026, 7:02 p.m.
Created at: April 16, 2026, 11:23 a.m.