Triple

T22280871
Position Surface form Disambiguated ID Type / Status
Subject Marathon, Ontario E550726 entity
Predicate locatedBetween P1262 FINISHED
Object Thunder Bay, Ontario 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: Thunder Bay, Ontario | Statement: [Marathon, Ontario, locatedBetween, Thunder Bay, Ontario]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thunder Bay, Ontario
Context triple: [Marathon, Ontario, locatedBetween, Thunder Bay, Ontario]
  • A. Thunder Bay
    Thunder Bay is a bay on Lake Huron in Michigan known for its numerous shipwrecks and the Thunder Bay National Marine Sanctuary.
  • B. Thunder Bay chosen
    Thunder Bay is a Canadian city in northwestern Ontario that serves as a key transportation, shipping, and commercial hub on the north shore of Lake Superior.
  • C. Owen Sound
    Owen Sound is a small port city on Georgian Bay in southwestern Ontario, Canada, known for its waterfront, regional services, and surrounding natural attractions.
  • D. Fort Frances
    Fort Frances is a small Canadian town in northwestern Ontario located on the Rainy River along the U.S. border opposite International Falls, Minnesota.
  • E. Thunder Bay—Atikokan
    Thunder Bay—Atikokan is a provincial electoral district in northwestern Ontario, Canada, represented in the Legislative Assembly of Ontario.
  • 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_69e11e44d538819097c6b8f333af3352 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f14eab4f848190b1a8ba70f9fb0581 completed April 29, 2026, 12:19 a.m.
Created at: April 16, 2026, 8:40 p.m.