Triple
T10153113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kempenfelt Bay |
E232700
|
entity |
| Predicate | hasCityOnShore |
P969
|
FINISHED |
| Object | Barrie |
E35529
|
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: Barrie | Statement: [Kempenfelt Bay, hasCityOnShore, Barrie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barrie Context triple: [Kempenfelt Bay, hasCityOnShore, Barrie]
-
A.
Barrie
chosen
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.
-
B.
Cobourg
Cobourg is a small town in Ontario, Canada, known for its historic downtown, sandy beach, and picturesque waterfront along Lake Ontario.
-
C.
Oshawa
Oshawa is a city in southern Ontario, Canada, known historically as a major automotive manufacturing center and part of the Greater Toronto Area.
-
D.
Guelph
Guelph is a mid-sized Canadian city known for its strong manufacturing base, historic architecture, and the University of Guelph.
-
E.
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.
- 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_69ca84885e48819088a31b127cf44904 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec376cd48190990862c56c3a4dce |
completed | April 2, 2026, 4:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d300a40638819082e575d957711377 |
completed | April 6, 2026, 12:39 a.m. |
Created at: March 30, 2026, 9:08 p.m.