Triple

T6376586
Position Surface form Disambiguated ID Type / Status
Subject Kitchener campus E143481 entity
Predicate locatedIn P40 FINISHED
Object Kitchener, Ontario E32080 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: Kitchener, Ontario | Statement: [Kitchener campus, locatedIn, Kitchener, Ontario]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kitchener, Ontario
Context triple: [Kitchener campus, locatedIn, Kitchener, Ontario]
  • A. Kitchener chosen
    Kitchener is a mid-sized city in southwestern Ontario, Canada, known for its manufacturing history and annual Oktoberfest celebration.
  • B. Waterloo, Ontario
    Waterloo, Ontario is a Canadian city in the Regional Municipality of Waterloo best known as a major tech and innovation hub and home to the University of Waterloo and Wilfrid Laurier University.
  • C. Kingston, Ontario
    Kingston, Ontario is a historic Canadian city on the northeastern shore of Lake Ontario, known for its 19th-century limestone architecture, military and political heritage, and as home to Queen’s University.
  • D. Guelph
    Guelph is a mid-sized Canadian city known for its strong manufacturing base, historic architecture, and the University of Guelph.
  • E. Markham, Ontario
    Markham, Ontario is a rapidly growing city in the Greater Toronto Area known for its diverse population, high-tech industry hub, and blend of urban and suburban communities.
  • 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_69c008d9f4348190ab598a2913259a1c completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0683bfc7081908b15c3c9a3c72e7b completed March 22, 2026, 10:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64badc3c481908199bf32069cc1c7 completed March 27, 2026, 9:19 a.m.
Created at: March 22, 2026, 4:33 p.m.