Triple

T18193021
Position Surface form Disambiguated ID Type / Status
Subject Dübendorf E435587 entity
Predicate hasNeighbour P5707 FINISHED
Object Wallisellen 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: Wallisellen | Statement: [Dübendorf, hasNeighbour, Wallisellen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wallisellen
Context triple: [Dübendorf, hasNeighbour, Wallisellen]
  • A. Wallisellen chosen
    Wallisellen is a municipality in the canton of Zürich, Switzerland, known as a residential and commercial suburb on the outskirts of the city of Zürich.
  • B. Wallis
    Wallis is a given name and surname used in English-speaking countries, often considered a variant of Wallace.
  • C. Wallas
    Wallas is a surname most notably associated with Graham Wallas, the British social psychologist and political scientist known for his work on democratic theory and the psychology of thought.
  • D. Mayne
    Mayne is the surname of Thom Mayne, the influential American architect and founder of the firm Morphosis, known for his bold, unconventional designs.
  • E. Hartley
    Hartley is a small census-designated community located in Solano County, California.
  • 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_69d8b90c7ec081909b4694ccecb449c6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4e0d12b688190842375dcc5d5537c completed April 19, 2026, 2:04 p.m.
Created at: April 10, 2026, 10:31 a.m.