Triple

T13340085
Position Surface form Disambiguated ID Type / Status
Subject Limmat region E317800 entity
Predicate hasMainCity P3940 FINISHED
Object Dietikon E392055 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: Dietikon | Statement: [Limmat region, hasMainCity, Dietikon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dietikon
Context triple: [Limmat region, hasMainCity, Dietikon]
  • A. Dietikon chosen
    Dietikon is a town and municipality in the canton of Zurich in Switzerland, known as an important regional center in the Limmat Valley.
  • B. Zurich Wiedikon
    Zurich Wiedikon is a residential and commercial district in the city of Zurich, Switzerland, known for its urban character, good public transport connections, and proximity to the Sihl River.
  • C. 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.
  • D. Kloten
    Kloten is a town in the canton of Zurich in northern Switzerland, best known as the home of Zurich Airport.
  • 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 (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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99d01bf8481908cd3a99e5557b972 completed April 11, 2026, 12:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b058bc688190b3549d1cac6f4576 completed May 3, 2026, 8:30 p.m.
Created at: April 9, 2026, 9:31 p.m.