Triple

T22831140
Position Surface form Disambiguated ID Type / Status
Subject Bussnang E565802 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Weinfelden 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: Weinfelden | Statement: [Bussnang, neighboringMunicipality, Weinfelden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Weinfelden
Context triple: [Bussnang, neighboringMunicipality, Weinfelden]
  • A. Weinfelden chosen
    Weinfelden is a town and municipality in northeastern Switzerland that serves as an important regional center in the canton of Thurgau.
  • B. Reigoldswil
    Reigoldswil is a municipality in the canton of Basel-Landschaft in northwestern Switzerland, known as a gateway to the Jura hills and local hiking areas.
  • C. Rüderswil
    Rüderswil is a municipality in the Emmental region of the canton of Bern in Switzerland, known for its rural character and agricultural landscape.
  • D. Walperswil
    Walperswil is a small municipality in the canton of Bern in Switzerland.
  • E. Bäretswil
    Bäretswil is a rural municipality in the canton of Zurich in Switzerland, known for its scenic pre-Alpine landscape and small-village character.
  • 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_69e24585ab1c81909b2b5065d15805d5 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17e2bcad8819091f237fd2273a20c completed April 29, 2026, 3:42 a.m.
Created at: April 17, 2026, 3:34 p.m.