Triple
T6376595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kitchener campus |
E143481
|
entity |
| Predicate | city |
P40
|
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: [Kitchener campus, city, Kitchener]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kitchener Context triple: [Kitchener campus, city, 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_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_69c65383e7148190817bd25840212cc6 |
completed | March 27, 2026, 9:53 a.m. |
Created at: March 22, 2026, 4:33 p.m.