Triple

T19786550
Position Surface form Disambiguated ID Type / Status
Subject Sarganserland region E475284 entity
Predicate contains P35 FINISHED
Object Walenstadt 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: Walenstadt | Statement: [Sarganserland region, contains, Walenstadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Walenstadt
Context triple: [Sarganserland region, contains, Walenstadt]
  • A. Walenstadt chosen
    Walenstadt is a Swiss town on the shores of Lake Walen in the canton of St. Gallen, known for its scenic alpine surroundings and outdoor recreation opportunities.
  • B. Herisau
    Herisau is a Swiss town that serves as the administrative and economic center of the canton of Appenzell Ausserrhoden.
  • C. Reichenau Island
    Reichenau Island is a UNESCO World Heritage island in Lake Constance, Germany, renowned for its medieval monastic heritage and well-preserved churches.
  • D. Schorisse
    Schorisse is a village in East Flanders, Belgium, that now forms part of the municipality of Maarkedal.
  • E. Eysins
    Eysins is a small municipality in the canton of Vaud in western Switzerland, situated near the town of Nyon and close to Lake Geneva.
  • 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.