Triple
T8834934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ridgebacks |
E210242
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Oshawa, Ontario |
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, Ontario | Statement: [Ridgebacks, locatedIn, Oshawa, Ontario]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oshawa, Ontario Context triple: [Ridgebacks, locatedIn, Oshawa, Ontario]
-
A.
Oshawa, Ontario, Canada
Oshawa, Ontario, Canada is an industrial city in the Greater Toronto Area best known as a major automotive manufacturing hub and home to several educational and cultural institutions.
-
B.
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.
-
C.
Anderson, Ontario
Anderson, Ontario is a small rural community in Canada best known as the birthplace of former Prime Minister Arthur Meighen.
-
D.
Tillsonburg, Ontario
Tillsonburg, Ontario is a small town in southwestern Ontario known historically for its tobacco farming and agricultural roots.
-
E.
Mississauga, Ontario, Canada
Mississauga, Ontario, Canada is a large suburban city west of Toronto known for its diverse population, major corporate headquarters, and proximity to Toronto Pearson International Airport.
- 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_69ca8388549c819095fd94eadefbb007 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60686cac8190b3138db40b6fe058 |
completed | April 1, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d100a931988190aaff56f16057ea90 |
completed | April 4, 2026, 12:14 p.m. |
Created at: March 30, 2026, 6:47 p.m.