Triple

T22550067
Position Surface form Disambiguated ID Type / Status
Subject Lebern electoral district E557534 entity
Predicate hasMunicipality P847 FINISHED
Object Lüsslingen-Nennigkofen 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: Lüsslingen-Nennigkofen | Statement: [Lebern electoral district, hasMunicipality, Lüsslingen-Nennigkofen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lüsslingen-Nennigkofen
Context triple: [Lebern electoral district, hasMunicipality, Lüsslingen-Nennigkofen]
  • A. Lüsslingen chosen
    Lüsslingen is a village and former municipality in the canton of Solothurn in Switzerland.
  • B. Nenzlingen
    Nenzlingen is a small municipality in the canton of Basel-Landschaft in northwestern Switzerland, known for its rural character and scenic surroundings.
  • C. Neidlingen
    Neidlingen is a small municipality in the German state of Baden-Württemberg, situated on the edge of the Swabian Jura.
  • D. Läufelfingen
    Läufelfingen is a municipality in the canton of Basel-Landschaft in Switzerland, situated in a rural, hilly region near the Hauenstein Pass.
  • E. Andelfingen
    Andelfingen is a municipality and regional center in the canton of Zürich in northern Switzerland, known for its rural character and vineyards along the Thur River.
  • 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_69e11e59db848190b4272ecd2b690ffd completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15f74512c8190b5369e19a4bc6325 completed April 29, 2026, 1:31 a.m.
Created at: April 16, 2026, 8:52 p.m.