Triple

T18090266
Position Surface form Disambiguated ID Type / Status
Subject Zimmerberg region E432944 entity
Predicate contains P35 FINISHED
Object Adliswil 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: Adliswil | Statement: [Zimmerberg region, contains, Adliswil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Adliswil
Context triple: [Zimmerberg region, contains, Adliswil]
  • A. Adliswil chosen
    Adliswil is a municipality in the canton of Zurich, Switzerland, situated in the Sihl Valley just south of the city of Zurich.
  • B. Hergiswil
    Hergiswil is a Swiss lakeside municipality known for its scenic setting on Lake Lucerne and its historic glassworks.
  • C. Wädenswil
    Wädenswil is a Swiss town in the canton of Zurich known for its lakeside location, wine-growing tradition, and research institutes.
  • D. Würenlingen
    Würenlingen is a municipality in the canton of Aargau in northern Switzerland, known for its residential character and proximity to the Aare River and regional transport links.
  • E. Walchwil
    Walchwil is a picturesque Swiss municipality in the canton of Zug, known for its scenic location on the eastern shore of Lake Zug and views of the surrounding Alps.
  • 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_69d8b907d05c819083cc3bd6021089e6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4dd17ba98819085a15e8593d98259 completed April 19, 2026, 1:48 p.m.
Created at: April 10, 2026, 10:27 a.m.