Triple
T21068539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huntsville, Ontario |
E519039
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Muskoka |
—
|
NE NERFINISHED |
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: Muskoka | Statement: [Huntsville, Ontario, region, Muskoka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Muskoka Context triple: [Huntsville, Ontario, region, Muskoka]
-
A.
Muskoka
chosen
Muskoka is a popular cottage and vacation region in Ontario, Canada, known for its scenic lakes, forests, and upscale resorts.
-
B.
Beloozero
Beloozero is a historic town in northwestern Russia, known as one of the oldest Russian settlements and an early center of medieval Rus.
-
C.
Lieksa
Lieksa is a small town and municipality in eastern Finland known for its forests, lakes, and proximity to Koli National Park.
-
D.
Onega Peninsula
The Onega Peninsula is a large, sparsely populated landmass in northwestern Russia that juts into the White Sea and is known for its rugged coastline and northern taiga landscapes.
-
E.
Onega
Onega is a small town in Arkhangelsk Oblast, northwestern Russia, situated near the mouth of the Onega River on the White Sea coast.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b505ef108190b25dd4033e2ff7eb |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6feb6d3a081909d6a6b181786deff |
completed | April 21, 2026, 4:36 a.m. |
Created at: April 16, 2026, 2:45 p.m.