Triple

T13635350
Position Surface form Disambiguated ID Type / Status
Subject Greater Zürich Area E325833 entity
Predicate includesMunicipality P14658 FINISHED
Object Adliswil E429058 NE FINISHED

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: [Greater Zürich Area, includesMunicipality, Adliswil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Adliswil
Context triple: [Greater Zürich Area, includesMunicipality, 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 (3 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_69d8076beddc8190a53156f5bea77f5e completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc5a616dc81908b8c1213e1d4beed completed April 12, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd466ac0f08190b99dd4cdcef339c6 completed May 8, 2026, 2:11 a.m.
Created at: April 9, 2026, 9:51 p.m.