Triple
T12467346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barrie line |
E297959
|
entity |
| Predicate | locale |
P387
|
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: [Barrie line, locale, Barrie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barrie Context triple: [Barrie line, locale, 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.
Barrie
Barrie is the given name of American dancer and actress Barrie Chase, known for her work with Fred Astaire and in classic Hollywood films.
-
C.
Cobourg
Cobourg is a small town in Ontario, Canada, known for its historic downtown, sandy beach, and picturesque waterfront along Lake Ontario.
-
D.
Oshawa
Oshawa is a city in southern Ontario, Canada, known historically as a major automotive manufacturing center and part of the Greater Toronto Area.
-
E.
Guelph
Guelph is a mid-sized Canadian city known for its strong manufacturing base, historic architecture, and the University of Guelph.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94db979c481908778188794b2c08e |
completed | April 10, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64ba3983c8190aef5e3b6a6d2e41e |
completed | May 2, 2026, 7:08 p.m. |
Created at: April 8, 2026, 9:56 p.m.