Triple

T12682402
Position Surface form Disambiguated ID Type / Status
Subject Kerzers E302978 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Murten E315007 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: Murten | Statement: [Kerzers, hasNeighboringMunicipality, Murten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Murten
Context triple: [Kerzers, hasNeighboringMunicipality, Murten]
  • A. Murten chosen
    Murten is a historic bilingual town in the canton of Fribourg, Switzerland, known for its well-preserved medieval old town and lakeside setting on Lake Murten.
  • B. Grenchen
    Grenchen is a Swiss town in the canton of Solothurn known for its watchmaking industry and location at the foot of the Jura Mountains.
  • C. Regensdorf
    Regensdorf is a municipality in the canton of Zürich in northern Switzerland, known as a suburban residential and industrial area near the city of Zürich.
  • D. Richterswil
    Richterswil is a picturesque municipality on the shores of Lake Zurich in the canton of Zurich, Switzerland.
  • E. Landquart
    Landquart is a river in eastern Switzerland that flows through the canton of Graubünden before joining the Alpine Rhine.
  • 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_69d7bdee64a08190801c6d470aefd723 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961d68358819095bdaab8adf1dcf0 completed April 10, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f72658fa6c81909b9785d710c418e0 completed May 3, 2026, 10:41 a.m.
Created at: April 9, 2026, 5:21 p.m.