Triple
T4395245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clarington |
E99470
|
entity |
| Predicate | hasMajorCommunity |
P2321
|
FINISHED |
| Object | Bowmanville |
E436676
|
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: Bowmanville | Statement: [Clarington, hasMajorCommunity, Bowmanville]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bowmanville Context triple: [Clarington, hasMajorCommunity, Bowmanville]
-
A.
Bowmanville
chosen
Bowmanville is a community in Ontario, Canada, serving as the main urban and administrative centre of the municipality of Clarington in the Durham Region.
-
B.
Welland
Welland is a city in the Niagara Region of southern Ontario, Canada, known for the Welland Canal that connects Lake Ontario and Lake Erie.
-
C.
Orillia
Orillia is a small city in central Ontario, Canada, known for its lakeside setting on Lake Couchiching and Lake Simcoe and its popular waterfront and cultural festivals.
-
D.
Bloomfield, Ontario
Bloomfield, Ontario is a small village in Prince Edward County known for its historic charm, local shops, and proximity to the region’s wineries and scenic countryside.
-
E.
Wallaceburg
Wallaceburg is a small community in southwestern Ontario, Canada, known historically for its glass, sugar, and manufacturing industries along the Sydenham River.
- 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_69b345506b408190b0e3dee616738a7d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b352ab928c81909f4406d5df3e081b |
completed | March 12, 2026, 11:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5f5ec77d081909b07ebd004be136f |
completed | March 14, 2026, 11:57 p.m. |
Created at: March 12, 2026, 11:20 p.m.