Triple

T21368937
Position Surface form Disambiguated ID Type / Status
Subject canton of Zug E526997 entity
Predicate hasMunicipality P847 FINISHED
Object Oberägeri 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: Oberägeri | Statement: [canton of Zug, hasMunicipality, Oberägeri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oberägeri
Context triple: [canton of Zug, hasMunicipality, Oberägeri]
  • A. Oberägeri chosen
    Oberägeri is a Swiss municipality in the canton of Zug, known for its scenic location by Lake Ägeri and surrounding pre-Alpine landscapes.
  • B. Oberkriech
    Oberkriech is a locality within the municipality of Thalgau in the Austrian state of Salzburg.
  • C. Oberönz
    Oberönz is a village in the Oberaargau region of the canton of Bern in Switzerland.
  • D. Ueberstorf
    Ueberstorf is a municipality in the canton of Fribourg in western Switzerland, known for its rural character and location near the linguistic border between German- and French-speaking regions.
  • E. Obertal
    Obertal is a village and district of the Black Forest municipality of Baiersbronn in Baden-Württemberg, Germany, known for its scenic landscapes and tourism.
  • 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_69e0b51e80808190ba5cb05667af02a9 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69ee5baf5fb4819093f8d8afdd83ffdb completed April 26, 2026, 6:38 p.m.
Created at: April 16, 2026, 5:09 p.m.