Triple
T21156371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ontario |
E521321
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Kitchener |
—
|
NE NERFINISHED |
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: [Ontario, containsCity, Kitchener]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kitchener Context triple: [Ontario, containsCity, Kitchener]
-
A.
Kitchener
chosen
Kitchener is a mid-sized city in southwestern Ontario, Canada, known for its manufacturing history and annual Oktoberfest celebration.
-
B.
Kitchener
Kitchener is a small town in the Hunter Region of New South Wales, Australia, known for its coal mining heritage and rural character.
-
C.
Cobourg
Cobourg is a small town in Ontario, Canada, known for its historic downtown, sandy beach, and picturesque waterfront along Lake Ontario.
-
D.
Guelph
Guelph is a mid-sized Canadian city known for its strong manufacturing base, historic architecture, and the University of Guelph.
-
E.
Alliston
Alliston is a community in New Tecumseth, Ontario, Canada, known historically as the birthplace of insulin co-discoverer Sir Frederick Banting.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b50d1ea481909c07e63c3ead9316 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7252c6db08190bcdffc3f2cfc6138 |
completed | April 21, 2026, 7:20 a.m. |
Created at: April 16, 2026, 2:59 p.m.