Triple

T21277475
Position Surface form Disambiguated ID Type / Status
Subject Lake Rosseau E524426 entity
Predicate locatedInRegion 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: [Lake Rosseau, locatedInRegion, Muskoka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Muskoka
Context triple: [Lake Rosseau, locatedInRegion, 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_69e0b516293c819089458ea2ec85f85e completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e736583c08819087a4726538e703e2 completed April 21, 2026, 8:33 a.m.
Created at: April 16, 2026, 4:02 p.m.