Triple

T22806608
Position Surface form Disambiguated ID Type / Status
Subject Forchbahn E564552 entity
Predicate servesMunicipality P3936 FINISHED
Object Zumikon 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: Zumikon | Statement: [Forchbahn, servesMunicipality, Zumikon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zumikon
Context triple: [Forchbahn, servesMunicipality, Zumikon]
  • A. Zumikon chosen
    Zumikon is a small, affluent municipality in the Zürich metropolitan area of Switzerland, known for its residential character and proximity to the city of Zürich.
  • B. Zollikon
    Zollikon is an affluent suburban municipality on the shores of Lake Zurich, known for its residential character and proximity to the city of Zurich in Switzerland.
  • C. Ottikon
    Ottikon is a small village in the municipality of Illnau-Effretikon in the canton of Zurich, Switzerland.
  • D. Ramiswil
    Ramiswil is a small rural municipality in the canton of Solothurn in northwestern Switzerland, known for its scenic Jura landscape and agricultural character.
  • E. Rüschlikon
    Rüschlikon is a wealthy lakeside municipality on the western shore of Lake Zurich in the canton of Zurich, Switzerland.
  • 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_69e245823f4c8190ade442cdcc2c224a completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17d5c193481908550993e2547515d completed April 29, 2026, 3:39 a.m.
Created at: April 17, 2026, 3:32 p.m.