Triple
T8939229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Downtown Oshawa campus |
E212854
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Oshawa |
E34994
|
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: Oshawa | Statement: [Downtown Oshawa campus, city, Oshawa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oshawa Context triple: [Downtown Oshawa campus, city, Oshawa]
-
A.
Oshawa
chosen
Oshawa is a city in southern Ontario, Canada, known historically as a major automotive manufacturing center and part of the Greater Toronto Area.
-
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.
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.
-
D.
Sarnia
Sarnia is an industrial city in southwestern Ontario, Canada, located on the shores of Lake Huron near the U.S. border, known for its petrochemical industry and busy port.
-
E.
Brampton
Brampton is a large suburban city in the Greater Toronto Area known for its diverse population and rapidly growing economy.
- 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_69ca839694c88190b324ffeb43d23b08 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc66b7484481909e0d7610552f5386 |
completed | April 1, 2026, 12:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d19f50f1c4819099a9c511f58e9873 |
completed | April 4, 2026, 11:31 p.m. |
Created at: March 30, 2026, 6:58 p.m.