Triple

T12391349
Position Surface form Disambiguated ID Type / Status
Subject Kitchener line E295999 entity
Predicate connectsCity P4245 FINISHED
Object Guelph E34046 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: Guelph | Statement: [Kitchener line, connectsCity, Guelph]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guelph
Context triple: [Kitchener line, connectsCity, Guelph]
  • A. Guelph chosen
    Guelph is a mid-sized Canadian city known for its strong manufacturing base, historic architecture, and the University of Guelph.
  • B. Brantford
    Brantford is a city in southwestern Ontario, Canada, known as the hometown of hockey legend Wayne Gretzky and for its historic role in the development of telephone technology.
  • C. Oshawa
    Oshawa is a city in southern Ontario, Canada, known historically as a major automotive manufacturing center and part of the Greater Toronto Area.
  • D. 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.
  • E. St. Catharines
    St. Catharines is a city in southern Ontario, Canada, known for its location near Niagara Falls and its role as a regional commercial and manufacturing center.
  • 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fd0bcc48190bb1a59a3aaa6bfdf completed April 10, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a533a2788190b885c000c29f4e87 completed May 3, 2026, 1:30 a.m.
Created at: April 8, 2026, 9:54 p.m.