Triple

T21368935
Position Surface form Disambiguated ID Type / Status
Subject canton of Zug E526997 entity
Predicate hasMunicipality P847 FINISHED
Object Menzingen 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: Menzingen | Statement: [canton of Zug, hasMunicipality, Menzingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Menzingen
Context triple: [canton of Zug, hasMunicipality, Menzingen]
  • A. Menzingen chosen
    Menzingen is a municipality in the canton of Zug in central Switzerland, known for its rural landscape and location in the pre-Alpine region.
  • B. Memmingen
    Memmingen is a historic town in the Bavarian region of Germany, known for its well-preserved medieval old town and role as a regional transport hub.
  • C. Münsingen
    Münsingen is a Swiss municipality in the canton of Bern, known for its scenic location in the Aare valley between Bern and Thun.
  • D. Mötzingen
    Mötzingen is a small municipality in the German state of Baden-Württemberg, located in the Böblingen region of southwestern Germany.
  • E. Bermatingen
    Bermatingen is a small municipality in the Bodenseekreis district of Baden-Württemberg in southern Germany, situated near Lake Constance.
  • 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.