Triple

T5704348
Position Surface form Disambiguated ID Type / Status
Subject YKF E125748 entity
Predicate serves P98 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: [YKF, serves, Kitchener]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kitchener
Context triple: [YKF, serves, Kitchener]
  • A. Kitchener chosen
    Kitchener is a mid-sized city in southwestern Ontario, Canada, known for its manufacturing history and annual Oktoberfest celebration.
  • B. Guelph
    Guelph is a mid-sized Canadian city known for its strong manufacturing base, historic architecture, and the University of Guelph.
  • C. 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.
  • D. Oshawa
    Oshawa is a city in southern Ontario, Canada, known historically as a major automotive manufacturing center and part of the Greater Toronto Area.
  • E. 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.
  • 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_69c0082c96988190b3a6a201edce472a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c024585d14819098ec34fd5a858836 completed March 22, 2026, 5:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a638f2881908a7eb9274f000138 completed March 22, 2026, 9:08 p.m.
Created at: March 22, 2026, 3:45 p.m.