Triple

T18927310
Position Surface form Disambiguated ID Type / Status
Subject Klausen E463007 entity
Predicate officialName P66 FINISHED
Object Klausen 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: Klausen | Statement: [Klausen, officialName, Klausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Klausen
Context triple: [Klausen, officialName, Klausen]
  • A. Klausen chosen
    Klausen is a small historic town in South Tyrol, northern Italy, known for its picturesque Alpine setting and medieval charm.
  • B. Wyssachen
    Wyssachen is a small rural municipality and village located in the Emmental region of the canton of Bern, Switzerland.
  • C. Bollingen
    Bollingen is a small Swiss locality on the shores of Lake Zurich, known for its rural character and scenic lakeside setting.
  • D. Meinwald
    Meinwald is a surname most notably associated with individuals such as J. Meinwald, an American chemist recognized for his contributions to organic chemistry.
  • E. Kiental
    Kiental is a picturesque alpine valley and village in the Bernese Oberland region of Switzerland, known for its dramatic mountain scenery and hiking opportunities.
  • 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_69d8dcfdbbb881909964fa5a75bd0b48 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c9bc36588190ae9cc3b8abf8afd4 completed April 20, 2026, 6:37 a.m.
Created at: April 10, 2026, 11:59 a.m.