Triple

T8241301
Position Surface form Disambiguated ID Type / Status
Subject Waterloo E192540 entity
Predicate adjacentTo P224 FINISHED
Object Kitchener 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 | Statement: [Waterloo, adjacentTo, Kitchener]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kitchener
Context triple: [Waterloo, adjacentTo, Kitchener]
  • A. Kitchener chosen
    Kitchener is a mid-sized city in southwestern Ontario, Canada, known for its manufacturing history and annual Oktoberfest celebration.
  • B. Cobourg
    Cobourg is a small town in Ontario, Canada, known for its historic downtown, sandy beach, and picturesque waterfront along Lake Ontario.
  • C. Guelph
    Guelph is a mid-sized Canadian city known for its strong manufacturing base, historic architecture, and the University of Guelph.
  • D. Alliston
    Alliston is a community in New Tecumseth, Ontario, Canada, known historically as the birthplace of insulin co-discoverer Sir Frederick Banting.
  • E. Barrie
    Barrie is a mid-sized city in central Ontario, Canada, located on the western shore of Lake Simcoe and known as a growing regional hub for commuters, industry, and recreation.
  • 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_69ca82dc8f148190a2c75a98501a7b91 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb783e13648190abf34eb8c244ea17 completed March 31, 2026, 7:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf5120159881908361bf9cb81e3932 completed April 3, 2026, 5:33 a.m.
Created at: March 30, 2026, 5:47 p.m.