Triple

T21217584
Position Surface form Disambiguated ID Type / Status
Subject Winznau E522875 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Aarburg 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: Aarburg | Statement: [Winznau, neighboringMunicipality, Aarburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aarburg
Context triple: [Winznau, neighboringMunicipality, Aarburg]
  • A. Aarburg chosen
    Aarburg is a historic Swiss town in the canton of Aargau, known for its prominent riverside fortress overlooking the Aare River.
  • B. Attiswil
    Attiswil is a municipality in the canton of Bern in Switzerland, located in the Oberaargau region.
  • C. Bremgarten
    Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
  • D. Neuenegg
    Neuenegg is a Swiss municipality in the canton of Bern, known for its rural character and location near the city of Bern.
  • E. Kesswil
    Kesswil is a small Swiss village on the shores of Lake Constance, best known as the birthplace of the influential psychiatrist and psychoanalyst Carl Gustav Jung.
  • 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_69e0b511ed84819099b449b4a111085c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e734744dcc81908b3065adc93b4b98 completed April 21, 2026, 8:25 a.m.
Created at: April 16, 2026, 3:41 p.m.