Triple

T19786554
Position Surface form Disambiguated ID Type / Status
Subject Sarganserland region E475284 entity
Predicate contains P35 FINISHED
Object Quarten 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: Quarten | Statement: [Sarganserland region, contains, Quarten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Quarten
Context triple: [Sarganserland region, contains, Quarten]
  • A. Quarten chosen
    Quarten is a Swiss municipality in the canton of St. Gallen, known for its location on the shores of Lake Walen and its proximity to the Flumserberg ski and hiking area.
  • B. Viertel
    Viertel is a German-language surname borne by various notable individuals in the arts and literature.
  • C. Fürth
    Fürth is a historic city in northern Bavaria, Germany, known for its well-preserved old town and proximity to Nuremberg within the Franconian metropolitan region.
  • D. La Quar
    La Quar is a small rural municipality in the Berguedà comarca of Catalonia, Spain, known for its mountainous landscape and traditional Catalan character.
  • E. Ruit
    Ruit is a locality or district that forms part of the town of Bretten in the state of Baden-Württemberg, Germany.
  • 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_69d8e51b014081908b263e167370529a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65387d3348190a31f9c2f9bc1c6d9 completed April 20, 2026, 4:25 p.m.
Created at: April 10, 2026, 1:49 p.m.