Triple

T19589526
Position Surface form Disambiguated ID Type / Status
Subject Frutigen-Niedersimmental E470193 entity
Predicate containsMunicipality P852 FINISHED
Object Kandergrund 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: Kandergrund | Statement: [Frutigen-Niedersimmental, containsMunicipality, Kandergrund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kandergrund
Context triple: [Frutigen-Niedersimmental, containsMunicipality, Kandergrund]
  • A. Kandergrund chosen
    Kandergrund is a small Swiss municipality in the Bernese Oberland region, known for its alpine scenery and location in the Kandertal valley.
  • B. Krattigen
    Krattigen is a Swiss municipality in the canton of Bern, known for its scenic location above Lake Thun in the Bernese Oberland.
  • C. Damkina
    Damkina is a Mesopotamian earth and mother goddess, best known as the consort of the god Enki (Ea) and mother of the Babylonian chief god Marduk.
  • D. Schindellegi
    Schindellegi is a village in the municipality of Feusisberg in the canton of Schwyz, Switzerland, known as a residential community in the greater Zurich area.
  • E. Godden
    Godden is a surname most notably associated with British author Rumer Godden, known for her novels often set in India and exploring complex emotional and cultural themes.
  • 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_69d8e510024481908415c0d616fa6186 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e64054299481908d83c85cefdab075 completed April 20, 2026, 3:03 p.m.
Created at: April 10, 2026, 1:43 p.m.