Triple

T6331871
Position Surface form Disambiguated ID Type / Status
Subject Niederbipp E142398 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Oensingen E138514 NE FINISHED

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: Oensingen | Statement: [Niederbipp, hasNeighboringMunicipality, Oensingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oensingen
Context triple: [Niederbipp, hasNeighboringMunicipality, Oensingen]
  • A. Oensingen chosen
    Oensingen is a Swiss municipality located in the canton of Solothurn, known as a regional transport hub near the Jura mountains.
  • B. Weiningen
    Weiningen is a small Swiss municipality in the canton of Zurich, located in the Limmat Valley near the city of Zurich.
  • C. Orsingen-Nenzingen
    Orsingen-Nenzingen is a small municipality in the state of Baden-Württemberg in southern Germany.
  • D. Schönaich
    Schönaich is a municipality in the German state of Baden-Württemberg, known for its local community life and international town twinning partnerships.
  • E. Gernsbach
    Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c008d4d8e88190ad301c05b08722ac completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0651634b08190b54860ba0a70f5c4 completed March 22, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6041f713c8190b27ba54181049377 completed March 27, 2026, 4:14 a.m.
Created at: March 22, 2026, 4:30 p.m.